Malibu

This reverts commit fa9234212b.

cereal/car.capnp

@@ -532,11 +532,12 @@ struct CarParams {
     useSteeringAngle @0 :Bool;
     kp @1 :Float32;
     ki @2 :Float32;
+    kd @8 : Float32;
     friction @3 :Float32;
-    kf @4 :Float32;
     steeringAngleDeadzoneDeg @5 :Float32;
     latAccelFactor @6 :Float32;
     latAccelOffset @7 :Float32;
+    kfDEPRECATED @4 :Float32;
   }
 
   struct LongitudinalPIDTuning {
@@ -544,7 +545,7 @@ struct CarParams {
     kpV @1 :List(Float32);
     kiBP @2 :List(Float32);
     kiV @3 :List(Float32);
-    kf @6 :Float32;
+    kfDEPRECATED @6 :Float32;
     deadzoneBP @4 :List(Float32);
     deadzoneV @5 :List(Float32);
   }

cereal/custom.capnp

@@ -105,11 +105,7 @@ struct FrogPilotCarParams @0xf35cc4560bbf6ec2 {
   isHDA2 @3 :Bool;
   openpilotLongitudinalControlDisabled @4 :Bool;
   safetyConfigs @5 :List(SafetyConfig);
-
-  lateralTuning :union {
-    pid @6 :Car.CarParams.LateralPIDTuning;
-    torque @7 :Car.CarParams.LateralTorqueTuning;
-  }
+  canUseSASCM @6 :Bool;
 
   struct SafetyConfig {
     safetyParam @0 :UInt16;
@@ -193,34 +189,35 @@ struct FrogPilotPlan @0xa1680744031fdb2d {
   cscTraining @4 :Bool;
   dangerJerk @5 :Float32;
   desiredFollowDistance @6 :Int64;
-  experimentalMode @7 :Bool;
-  forcingStop @8 :Bool;
-  forcingStopLength @9 :Float32;
-  frogpilotEvents @10 :List(FrogPilotCarEvent);
-  increasedStoppedDistance @11 :Float32;
-  lateralCheck @12 :Bool;
-  laneWidthLeft @13 :Float32;
-  laneWidthRight @14 :Float32;
-  maxAcceleration @15 :Float32;
-  minAcceleration @16 :Float32;
-  redLight @17 :Bool;
-  roadCurvature @18 :Float32;
-  slcMapSpeedLimit @19 :Float32;
-  slcMapboxSpeedLimit @20 :Float32;
-  slcNextSpeedLimit @21 :Float32;
-  slcOverriddenSpeed @22 :Float32;
-  slcSpeedLimit @23 :Float32;
-  slcSpeedLimitOffset @24 :Float32;
-  slcSpeedLimitSource @25 :Text;
-  speedJerk @26 :Float32;
-  speedJerkStock @27 :Float32;
-  speedLimitChanged @28 :Bool;
-  tFollow @29 :Float32;
-  themeUpdated @30 :Bool;
-  togglesUpdated @31 :Bool;
-  trackingLead @32 :Bool;
-  unconfirmedSlcSpeedLimit @33 :Float32;
-  vCruise @34 :Float32;
+  disableThrottle @7 :Bool;
+  experimentalMode @8 :Bool;
+  forcingStop @9 :Bool;
+  forcingStopLength @10 :Float32;
+  frogpilotEvents @11 :List(FrogPilotCarEvent);
+  increasedStoppedDistance @12 :Float32;
+  lateralCheck @13 :Bool;
+  laneWidthLeft @14 :Float32;
+  laneWidthRight @15 :Float32;
+  maxAcceleration @16 :Float32;
+  minAcceleration @17 :Float32;
+  redLight @18 :Bool;
+  roadCurvature @19 :Float32;
+  slcMapSpeedLimit @20 :Float32;
+  slcMapboxSpeedLimit @21 :Float32;
+  slcNextSpeedLimit @22 :Float32;
+  slcOverriddenSpeed @23 :Float32;
+  slcSpeedLimit @24 :Float32;
+  slcSpeedLimitOffset @25 :Float32;
+  slcSpeedLimitSource @26 :Text;
+  speedJerk @27 :Float32;
+  speedJerkStock @28 :Float32;
+  speedLimitChanged @29 :Bool;
+  tFollow @30 :Float32;
+  themeUpdated @31 :Bool;
+  togglesUpdated @32 :Bool;
+  trackingLead @33 :Bool;
+  unconfirmedSlcSpeedLimit @34 :Float32;
+  vCruise @35 :Float32;
 }
 
 struct FrogPilotRadarState @0xcb9fd56c7057593a {

cereal/gen/cpp/car.capnp.c++

@@ -5262,17 +5262,17 @@ const ::capnp::_::RawSchema s_9622723fcbd14c2e = {
   0, 5, i_9622723fcbd14c2e, nullptr, nullptr, { &s_9622723fcbd14c2e, nullptr, nullptr, 0, 0, nullptr }, false
 };
 #endif  // !CAPNP_LITE
-static const ::capnp::_::AlignedData<147> b_80366e0e804ecc1d = {
+static const ::capnp::_::AlignedData<163> b_80366e0e804ecc1d = {
   {   0,   0,   0,   0,   5,   0,   6,   0,
      29, 204,  78, 128,  14, 110,  54, 128,
-     20,   0,   0,   0,   1,   0,   4,   0,
+     20,   0,   0,   0,   1,   0,   5,   0,
     218, 169, 170, 144,  36,  55, 105, 140,
       0,   0,   7,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
      21,   0,   0,   0,  66,   1,   0,   0,
      37,   0,   0,   0,   7,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-     33,   0,   0,   0, 199,   1,   0,   0,
+     33,   0,   0,   0, 255,   1,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
      99,  97, 114,  46,  99,  97, 112, 110,
@@ -5281,63 +5281,70 @@ static const ::capnp::_::AlignedData<147> b_80366e0e804ecc1d = {
     114,  97, 108,  84, 111, 114, 113, 117,
     101,  84, 117, 110, 105, 110, 103,   0,
       0,   0,   0,   0,   1,   0,   1,   0,
-     32,   0,   0,   0,   3,   0,   4,   0,
+     36,   0,   0,   0,   3,   0,   4,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   1,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    209,   0,   0,   0, 138,   0,   0,   0,
+    237,   0,   0,   0, 138,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    212,   0,   0,   0,   3,   0,   1,   0,
-    224,   0,   0,   0,   2,   0,   1,   0,
+    240,   0,   0,   0,   3,   0,   1,   0,
+    252,   0,   0,   0,   2,   0,   1,   0,
       1,   0,   0,   0,   1,   0,   0,   0,
       0,   0,   1,   0,   1,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    221,   0,   0,   0,  26,   0,   0,   0,
+    249,   0,   0,   0,  26,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    216,   0,   0,   0,   3,   0,   1,   0,
-    228,   0,   0,   0,   2,   0,   1,   0,
+    244,   0,   0,   0,   3,   0,   1,   0,
+      0,   1,   0,   0,   2,   0,   1,   0,
       2,   0,   0,   0,   2,   0,   0,   0,
       0,   0,   1,   0,   2,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    225,   0,   0,   0,  26,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-    220,   0,   0,   0,   3,   0,   1,   0,
-    232,   0,   0,   0,   2,   0,   1,   0,
-      3,   0,   0,   0,   3,   0,   0,   0,
-      0,   0,   1,   0,   3,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-    229,   0,   0,   0,  74,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-    228,   0,   0,   0,   3,   0,   1,   0,
-    240,   0,   0,   0,   2,   0,   1,   0,
-      4,   0,   0,   0,   4,   0,   0,   0,
-      0,   0,   1,   0,   4,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-    237,   0,   0,   0,  26,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-    232,   0,   0,   0,   3,   0,   1,   0,
-    244,   0,   0,   0,   2,   0,   1,   0,
-      5,   0,   0,   0,   5,   0,   0,   0,
-      0,   0,   1,   0,   5,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-    241,   0,   0,   0, 202,   0,   0,   0,
+    253,   0,   0,   0,  26,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
     248,   0,   0,   0,   3,   0,   1,   0,
       4,   1,   0,   0,   2,   0,   1,   0,
-      6,   0,   0,   0,   6,   0,   0,   0,
-      0,   0,   1,   0,   6,   0,   0,   0,
+      4,   0,   0,   0,   3,   0,   0,   0,
+      0,   0,   1,   0,   3,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-      1,   1,   0,   0, 122,   0,   0,   0,
+      1,   1,   0,   0,  74,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
       0,   1,   0,   0,   3,   0,   1,   0,
      12,   1,   0,   0,   2,   0,   1,   0,
-      7,   0,   0,   0,   7,   0,   0,   0,
-      0,   0,   1,   0,   7,   0,   0,   0,
+      8,   0,   0,   0,   4,   0,   0,   0,
+      0,   0,   1,   0,   4,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-      9,   1,   0,   0, 122,   0,   0,   0,
+      9,   1,   0,   0, 106,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
       8,   1,   0,   0,   3,   0,   1,   0,
      20,   1,   0,   0,   2,   0,   1,   0,
+      5,   0,   0,   0,   5,   0,   0,   0,
+      0,   0,   1,   0,   5,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     17,   1,   0,   0, 202,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     24,   1,   0,   0,   3,   0,   1,   0,
+     36,   1,   0,   0,   2,   0,   1,   0,
+      6,   0,   0,   0,   6,   0,   0,   0,
+      0,   0,   1,   0,   6,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     33,   1,   0,   0, 122,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     32,   1,   0,   0,   3,   0,   1,   0,
+     44,   1,   0,   0,   2,   0,   1,   0,
+      7,   0,   0,   0,   7,   0,   0,   0,
+      0,   0,   1,   0,   7,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     41,   1,   0,   0, 122,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     40,   1,   0,   0,   3,   0,   1,   0,
+     52,   1,   0,   0,   2,   0,   1,   0,
+      3,   0,   0,   0,   8,   0,   0,   0,
+      0,   0,   1,   0,   8,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     49,   1,   0,   0,  26,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     44,   1,   0,   0,   3,   0,   1,   0,
+     56,   1,   0,   0,   2,   0,   1,   0,
     117, 115, 101,  83, 116, 101, 101, 114,
     105, 110, 103,  65, 110, 103, 108, 101,
       0,   0,   0,   0,   0,   0,   0,   0,
@@ -5373,7 +5380,8 @@ static const ::capnp::_::AlignedData<147> b_80366e0e804ecc1d = {
      10,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    107, 102,   0,   0,   0,   0,   0,   0,
+    107, 102,  68,  69,  80,  82,  69,  67,
+     65,  84,  69,  68,   0,   0,   0,   0,
      10,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
@@ -5403,6 +5411,14 @@ static const ::capnp::_::AlignedData<147> b_80366e0e804ecc1d = {
       0,   0,   0,   0,   0,   0,   0,   0,
     108,  97, 116,  65,  99,  99, 101, 108,
      79, 102, 102, 115, 101, 116,   0,   0,
+     10,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     10,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    107, 100,   0,   0,   0,   0,   0,   0,
      10,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
@@ -5413,14 +5429,14 @@ static const ::capnp::_::AlignedData<147> b_80366e0e804ecc1d = {
 };
 ::capnp::word const* const bp_80366e0e804ecc1d = b_80366e0e804ecc1d.words;
 #if !CAPNP_LITE
-static const uint16_t m_80366e0e804ecc1d[] = {3, 4, 2, 1, 6, 7, 5, 0};
-static const uint16_t i_80366e0e804ecc1d[] = {0, 1, 2, 3, 4, 5, 6, 7};
+static const uint16_t m_80366e0e804ecc1d[] = {3, 8, 4, 2, 1, 6, 7, 5, 0};
+static const uint16_t i_80366e0e804ecc1d[] = {0, 1, 2, 3, 4, 5, 6, 7, 8};
 const ::capnp::_::RawSchema s_80366e0e804ecc1d = {
-  0x80366e0e804ecc1d, b_80366e0e804ecc1d.words, 147, nullptr, m_80366e0e804ecc1d,
-  0, 8, i_80366e0e804ecc1d, nullptr, nullptr, { &s_80366e0e804ecc1d, nullptr, nullptr, 0, 0, nullptr }, false
+  0x80366e0e804ecc1d, b_80366e0e804ecc1d.words, 163, nullptr, m_80366e0e804ecc1d,
+  0, 9, i_80366e0e804ecc1d, nullptr, nullptr, { &s_80366e0e804ecc1d, nullptr, nullptr, 0, 0, nullptr }, false
 };
 #endif  // !CAPNP_LITE
-static const ::capnp::_::AlignedData<151> b_c342cefc303e9b8e = {
+static const ::capnp::_::AlignedData<152> b_c342cefc303e9b8e = {
   {   0,   0,   0,   0,   5,   0,   6,   0,
     142, 155,  62,  48, 252, 206,  66, 195,
      20,   0,   0,   0,   1,   0,   1,   0,
@@ -5486,10 +5502,10 @@ static const ::capnp::_::AlignedData<151> b_c342cefc303e9b8e = {
       4,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   1,   0,   6,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-     53,   1,   0,   0,  26,   0,   0,   0,
+     53,   1,   0,   0, 106,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-     48,   1,   0,   0,   3,   0,   1,   0,
-     60,   1,   0,   0,   2,   0,   1,   0,
+     52,   1,   0,   0,   3,   0,   1,   0,
+     64,   1,   0,   0,   2,   0,   1,   0,
     107, 112,  66,  80,   0,   0,   0,   0,
      14,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
@@ -5564,7 +5580,8 @@ static const ::capnp::_::AlignedData<151> b_c342cefc303e9b8e = {
      14,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    107, 102,   0,   0,   0,   0,   0,   0,
+    107, 102,  68,  69,  80,  82,  69,  67,
+     65,  84,  69,  68,   0,   0,   0,   0,
      10,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
@@ -5578,7 +5595,7 @@ static const ::capnp::_::AlignedData<151> b_c342cefc303e9b8e = {
 static const uint16_t m_c342cefc303e9b8e[] = {4, 5, 6, 2, 3, 0, 1};
 static const uint16_t i_c342cefc303e9b8e[] = {0, 1, 2, 3, 4, 5, 6};
 const ::capnp::_::RawSchema s_c342cefc303e9b8e = {
-  0xc342cefc303e9b8e, b_c342cefc303e9b8e.words, 151, nullptr, m_c342cefc303e9b8e,
+  0xc342cefc303e9b8e, b_c342cefc303e9b8e.words, 152, nullptr, m_c342cefc303e9b8e,
   0, 7, i_c342cefc303e9b8e, nullptr, nullptr, { &s_c342cefc303e9b8e, nullptr, nullptr, 0, 0, nullptr }, false
 };
 #endif  // !CAPNP_LITE

cereal/gen/cpp/car.capnp.h

@@ -626,7 +626,7 @@ struct CarParams::LateralTorqueTuning {
   class Pipeline;
 
   struct _capnpPrivate {
-    CAPNP_DECLARE_STRUCT_HEADER(80366e0e804ecc1d, 4, 0)
+    CAPNP_DECLARE_STRUCT_HEADER(80366e0e804ecc1d, 5, 0)
     #if !CAPNP_LITE
     static constexpr ::capnp::_::RawBrandedSchema const* brand() { return &schema->defaultBrand; }
     #endif  // !CAPNP_LITE
@@ -3140,7 +3140,7 @@ public:
 
   inline float getFriction() const;
 
-  inline float getKf() const;
+  inline float getKfDEPRECATED() const;
 
   inline float getSteeringAngleDeadzoneDeg() const;
 
@@ -3148,6 +3148,8 @@ public:
 
   inline float getLatAccelOffset() const;
 
+  inline float getKd() const;
+
 private:
   ::capnp::_::StructReader _reader;
   template <typename, ::capnp::Kind>
@@ -3188,8 +3190,8 @@ public:
   inline float getFriction();
   inline void setFriction(float value);
 
-  inline float getKf();
-  inline void setKf(float value);
+  inline float getKfDEPRECATED();
+  inline void setKfDEPRECATED(float value);
 
   inline float getSteeringAngleDeadzoneDeg();
   inline void setSteeringAngleDeadzoneDeg(float value);
@@ -3200,6 +3202,9 @@ public:
   inline float getLatAccelOffset();
   inline void setLatAccelOffset(float value);
 
+  inline float getKd();
+  inline void setKd(float value);
+
 private:
   ::capnp::_::StructBuilder _builder;
   template <typename, ::capnp::Kind>
@@ -3261,7 +3266,7 @@ public:
   inline bool hasDeadzoneV() const;
   inline  ::capnp::List<float,  ::capnp::Kind::PRIMITIVE>::Reader getDeadzoneV() const;
 
-  inline float getKf() const;
+  inline float getKfDEPRECATED() const;
 
 private:
   ::capnp::_::StructReader _reader;
@@ -3339,8 +3344,8 @@ public:
   inline void adoptDeadzoneV(::capnp::Orphan< ::capnp::List<float,  ::capnp::Kind::PRIMITIVE>>&& value);
   inline ::capnp::Orphan< ::capnp::List<float,  ::capnp::Kind::PRIMITIVE>> disownDeadzoneV();
 
-  inline float getKf();
-  inline void setKf(float value);
+  inline float getKfDEPRECATED();
+  inline void setKfDEPRECATED(float value);
 
 private:
   ::capnp::_::StructBuilder _builder;
@@ -7791,16 +7796,16 @@ inline void CarParams::LateralTorqueTuning::Builder::setFriction(float value) {
       ::capnp::bounded<3>() * ::capnp::ELEMENTS, value);
 }
 
-inline float CarParams::LateralTorqueTuning::Reader::getKf() const {
+inline float CarParams::LateralTorqueTuning::Reader::getKfDEPRECATED() const {
   return _reader.getDataField<float>(
       ::capnp::bounded<4>() * ::capnp::ELEMENTS);
 }
 
-inline float CarParams::LateralTorqueTuning::Builder::getKf() {
+inline float CarParams::LateralTorqueTuning::Builder::getKfDEPRECATED() {
   return _builder.getDataField<float>(
       ::capnp::bounded<4>() * ::capnp::ELEMENTS);
 }
-inline void CarParams::LateralTorqueTuning::Builder::setKf(float value) {
+inline void CarParams::LateralTorqueTuning::Builder::setKfDEPRECATED(float value) {
   _builder.setDataField<float>(
       ::capnp::bounded<4>() * ::capnp::ELEMENTS, value);
 }
@@ -7847,6 +7852,20 @@ inline void CarParams::LateralTorqueTuning::Builder::setLatAccelOffset(float val
       ::capnp::bounded<7>() * ::capnp::ELEMENTS, value);
 }
 
+inline float CarParams::LateralTorqueTuning::Reader::getKd() const {
+  return _reader.getDataField<float>(
+      ::capnp::bounded<8>() * ::capnp::ELEMENTS);
+}
+
+inline float CarParams::LateralTorqueTuning::Builder::getKd() {
+  return _builder.getDataField<float>(
+      ::capnp::bounded<8>() * ::capnp::ELEMENTS);
+}
+inline void CarParams::LateralTorqueTuning::Builder::setKd(float value) {
+  _builder.setDataField<float>(
+      ::capnp::bounded<8>() * ::capnp::ELEMENTS, value);
+}
+
 inline bool CarParams::LongitudinalPIDTuning::Reader::hasKpBP() const {
   return !_reader.getPointerField(
       ::capnp::bounded<0>() * ::capnp::POINTERS).isNull();
@@ -8075,16 +8094,16 @@ inline ::capnp::Orphan< ::capnp::List<float,  ::capnp::Kind::PRIMITIVE>> CarPara
       ::capnp::bounded<5>() * ::capnp::POINTERS));
 }
 
-inline float CarParams::LongitudinalPIDTuning::Reader::getKf() const {
+inline float CarParams::LongitudinalPIDTuning::Reader::getKfDEPRECATED() const {
   return _reader.getDataField<float>(
       ::capnp::bounded<0>() * ::capnp::ELEMENTS);
 }
 
-inline float CarParams::LongitudinalPIDTuning::Builder::getKf() {
+inline float CarParams::LongitudinalPIDTuning::Builder::getKfDEPRECATED() {
   return _builder.getDataField<float>(
       ::capnp::bounded<0>() * ::capnp::ELEMENTS);
 }
-inline void CarParams::LongitudinalPIDTuning::Builder::setKf(float value) {
+inline void CarParams::LongitudinalPIDTuning::Builder::setKfDEPRECATED(float value) {
   _builder.setDataField<float>(
       ::capnp::bounded<0>() * ::capnp::ELEMENTS, value);
 }

cereal/gen/cpp/custom.capnp.c++

@@ -642,12 +642,12 @@ const ::capnp::_::RawSchema s_aedffd8f31e7b55d = {
 };
 #endif  // !CAPNP_LITE
 CAPNP_DEFINE_ENUM(EventName_aedffd8f31e7b55d, aedffd8f31e7b55d);
-static const ::capnp::_::AlignedData<132> b_f35cc4560bbf6ec2 = {
+static const ::capnp::_::AlignedData<139> b_f35cc4560bbf6ec2 = {
   {   0,   0,   0,   0,   5,   0,   6,   0,
     194, 110, 191,  11,  86, 196,  92, 243,
      13,   0,   0,   0,   1,   0,   1,   0,
      89,  10,  85,  29, 102, 186,  38, 181,
-      2,   0,   7,   0,   0,   0,   0,   0,
+      1,   0,   7,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
      21,   0,   0,   0,   2,   1,   0,   0,
      33,   0,   0,   0,  23,   0,   0,   0,
@@ -707,13 +707,13 @@ static const ::capnp::_::AlignedData<132> b_f35cc4560bbf6ec2 = {
       0,   0,   0,   0,   0,   0,   0,   0,
     224,   0,   0,   0,   3,   0,   1,   0,
     252,   0,   0,   0,   2,   0,   1,   0,
-      6,   0,   0,   0,   0,   0,   0,   0,
-      1,   0,   0,   0,   0,   0,   0,   0,
-     73, 118, 234, 203, 210,  73, 201, 252,
-    249,   0,   0,   0, 114,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
+      6,   0,   0,   0,   4,   0,   0,   0,
+      0,   0,   1,   0,   6,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
+    249,   0,   0,   0,  98,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
+    248,   0,   0,   0,   3,   0,   1,   0,
+      4,   1,   0,   0,   2,   0,   1,   0,
      99,  97, 110,  85, 115, 101,  80, 101,
     100,  97, 108,   0,   0,   0,   0,   0,
       1,   0,   0,   0,   0,   0,   0,   0,
@@ -773,20 +773,26 @@ static const ::capnp::_::AlignedData<132> b_f35cc4560bbf6ec2 = {
      14,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    108,  97, 116, 101, 114,  97, 108,  84,
-    117, 110, 105, 110, 103,   0,   0,   0, }
+     99,  97, 110,  85, 115, 101,  83,  65,
+     83,  67,  77,   0,   0,   0,   0,   0,
+      1,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+      1,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0, }
 };
 ::capnp::word const* const bp_f35cc4560bbf6ec2 = b_f35cc4560bbf6ec2.words;
 #if !CAPNP_LITE
 static const ::capnp::_::RawSchema* const d_f35cc4560bbf6ec2[] = {
   &s_8d65dd40bad40951,
-  &s_fcc949d2cbea7649,
 };
-static const uint16_t m_f35cc4560bbf6ec2[] = {0, 1, 2, 3, 6, 4, 5};
+static const uint16_t m_f35cc4560bbf6ec2[] = {0, 6, 1, 2, 3, 4, 5};
 static const uint16_t i_f35cc4560bbf6ec2[] = {0, 1, 2, 3, 4, 5, 6};
 const ::capnp::_::RawSchema s_f35cc4560bbf6ec2 = {
-  0xf35cc4560bbf6ec2, b_f35cc4560bbf6ec2.words, 132, d_f35cc4560bbf6ec2, m_f35cc4560bbf6ec2,
-  2, 7, i_f35cc4560bbf6ec2, nullptr, nullptr, { &s_f35cc4560bbf6ec2, nullptr, nullptr, 0, 0, nullptr }, false
+  0xf35cc4560bbf6ec2, b_f35cc4560bbf6ec2.words, 139, d_f35cc4560bbf6ec2, m_f35cc4560bbf6ec2,
+  1, 7, i_f35cc4560bbf6ec2, nullptr, nullptr, { &s_f35cc4560bbf6ec2, nullptr, nullptr, 0, 0, nullptr }, false
 };
 #endif  // !CAPNP_LITE
 static const ::capnp::_::AlignedData<36> b_8d65dd40bad40951 = {
@@ -836,71 +842,6 @@ const ::capnp::_::RawSchema s_8d65dd40bad40951 = {
   0, 1, i_8d65dd40bad40951, nullptr, nullptr, { &s_8d65dd40bad40951, nullptr, nullptr, 0, 0, nullptr }, false
 };
 #endif  // !CAPNP_LITE
-static const ::capnp::_::AlignedData<49> b_fcc949d2cbea7649 = {
-  {   0,   0,   0,   0,   5,   0,   6,   0,
-     73, 118, 234, 203, 210,  73, 201, 252,
-     32,   0,   0,   0,   1,   0,   1,   0,
-    194, 110, 191,  11,  86, 196,  92, 243,
-      2,   0,   7,   0,   1,   0,   2,   0,
-      1,   0,   0,   0,   0,   0,   0,   0,
-     21,   0,   0,   0, 114,   1,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     33,   0,   0,   0, 119,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     99, 117, 115, 116, 111, 109,  46,  99,
-     97, 112, 110, 112,  58,  70, 114, 111,
-    103,  80, 105, 108, 111, 116,  67,  97,
-    114,  80,  97, 114,  97, 109, 115,  46,
-    108,  97, 116, 101, 114,  97, 108,  84,
-    117, 110, 105, 110, 103,   0,   0,   0,
-      8,   0,   0,   0,   3,   0,   4,   0,
-      0,   0, 255, 255,   1,   0,   0,   0,
-      0,   0,   1,   0,   6,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     41,   0,   0,   0,  34,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     36,   0,   0,   0,   3,   0,   1,   0,
-     48,   0,   0,   0,   2,   0,   1,   0,
-      1,   0, 254, 255,   1,   0,   0,   0,
-      0,   0,   1,   0,   7,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     45,   0,   0,   0,  58,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     40,   0,   0,   0,   3,   0,   1,   0,
-     52,   0,   0,   0,   2,   0,   1,   0,
-    112, 105, 100,   0,   0,   0,   0,   0,
-     16,   0,   0,   0,   0,   0,   0,   0,
-     46,  76, 209, 203,  63, 114,  34, 150,
-      0,   0,   0,   0,   0,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     16,   0,   0,   0,   0,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-    116, 111, 114, 113, 117, 101,   0,   0,
-     16,   0,   0,   0,   0,   0,   0,   0,
-     29, 204,  78, 128,  14, 110,  54, 128,
-      0,   0,   0,   0,   0,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     16,   0,   0,   0,   0,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0, }
-};
-::capnp::word const* const bp_fcc949d2cbea7649 = b_fcc949d2cbea7649.words;
-#if !CAPNP_LITE
-static const ::capnp::_::RawSchema* const d_fcc949d2cbea7649[] = {
-  &s_80366e0e804ecc1d,
-  &s_9622723fcbd14c2e,
-  &s_f35cc4560bbf6ec2,
-};
-static const uint16_t m_fcc949d2cbea7649[] = {0, 1};
-static const uint16_t i_fcc949d2cbea7649[] = {0, 1};
-const ::capnp::_::RawSchema s_fcc949d2cbea7649 = {
-  0xfcc949d2cbea7649, b_fcc949d2cbea7649.words, 49, d_fcc949d2cbea7649, m_fcc949d2cbea7649,
-  3, 2, i_fcc949d2cbea7649, nullptr, nullptr, { &s_fcc949d2cbea7649, nullptr, nullptr, 0, 0, nullptr }, false
-};
-#endif  // !CAPNP_LITE
 static const ::capnp::_::AlignedData<268> b_da96579883444c35 = {
   {   0,   0,   0,   0,   5,   0,   6,   0,
      53,  76,  68, 131, 152,  87, 150, 218,
@@ -1739,7 +1680,7 @@ const ::capnp::_::RawSchema s_f416ec09499d9d19 = {
   0, 3, i_f416ec09499d9d19, nullptr, nullptr, { &s_f416ec09499d9d19, nullptr, nullptr, 0, 0, nullptr }, false
 };
 #endif  // !CAPNP_LITE
-static const ::capnp::_::AlignedData<597> b_a1680744031fdb2d = {
+static const ::capnp::_::AlignedData<613> b_a1680744031fdb2d = {
   {   0,   0,   0,   0,   5,   0,   6,   0,
      45, 219,  31,   3,  68,   7, 104, 161,
      13,   0,   0,   0,   1,   0,  13,   0,
@@ -1749,7 +1690,7 @@ static const ::capnp::_::AlignedData<597> b_a1680744031fdb2d = {
      21,   0,   0,   0, 218,   0,   0,   0,
      33,   0,   0,   0,   7,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-     29,   0,   0,   0, 175,   7,   0,   0,
+     29,   0,   0,   0, 231,   7,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
      99, 117, 115, 116, 111, 109,  46,  99,
@@ -1757,252 +1698,259 @@ static const ::capnp::_::AlignedData<597> b_a1680744031fdb2d = {
     103,  80, 105, 108, 111, 116,  80, 108,
      97, 110,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   1,   0,   1,   0,
-    140,   0,   0,   0,   3,   0,   4,   0,
+    144,   0,   0,   0,   3,   0,   4,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   1,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    197,   3,   0,   0, 138,   0,   0,   0,
+    225,   3,   0,   0, 138,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    200,   3,   0,   0,   3,   0,   1,   0,
-    212,   3,   0,   0,   2,   0,   1,   0,
+    228,   3,   0,   0,   3,   0,   1,   0,
+    240,   3,   0,   0,   2,   0,   1,   0,
       1,   0,   0,   0,   1,   0,   0,   0,
       0,   0,   1,   0,   1,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    209,   3,   0,   0, 178,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-    212,   3,   0,   0,   3,   0,   1,   0,
-    224,   3,   0,   0,   2,   0,   1,   0,
-      2,   0,   0,   0,  64,   0,   0,   0,
-      0,   0,   1,   0,   2,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-    221,   3,   0,   0, 162,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-    224,   3,   0,   0,   3,   0,   1,   0,
-    236,   3,   0,   0,   2,   0,   1,   0,
-      3,   0,   0,   0,   3,   0,   0,   0,
-      0,   0,   1,   0,   3,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-    233,   3,   0,   0,  74,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-    232,   3,   0,   0,   3,   0,   1,   0,
-    244,   3,   0,   0,   2,   0,   1,   0,
-      4,   0,   0,   0,  65,   0,   0,   0,
-      0,   0,   1,   0,   4,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-    241,   3,   0,   0,  98,   0,   0,   0,
+    237,   3,   0,   0, 178,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
     240,   3,   0,   0,   3,   0,   1,   0,
     252,   3,   0,   0,   2,   0,   1,   0,
-      5,   0,   0,   0,   4,   0,   0,   0,
-      0,   0,   1,   0,   5,   0,   0,   0,
+      2,   0,   0,   0,  64,   0,   0,   0,
+      0,   0,   1,   0,   2,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    249,   3,   0,   0,  90,   0,   0,   0,
+    249,   3,   0,   0, 162,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    248,   3,   0,   0,   3,   0,   1,   0,
-      4,   4,   0,   0,   2,   0,   1,   0,
-      6,   0,   0,   0,   3,   0,   0,   0,
-      0,   0,   1,   0,   6,   0,   0,   0,
+    252,   3,   0,   0,   3,   0,   1,   0,
+      8,   4,   0,   0,   2,   0,   1,   0,
+      3,   0,   0,   0,   3,   0,   0,   0,
+      0,   0,   1,   0,   3,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-      1,   4,   0,   0, 178,   0,   0,   0,
+      5,   4,   0,   0,  74,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
       4,   4,   0,   0,   3,   0,   1,   0,
      16,   4,   0,   0,   2,   0,   1,   0,
+      4,   0,   0,   0,  65,   0,   0,   0,
+      0,   0,   1,   0,   4,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     13,   4,   0,   0,  98,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     12,   4,   0,   0,   3,   0,   1,   0,
+     24,   4,   0,   0,   2,   0,   1,   0,
+      5,   0,   0,   0,   4,   0,   0,   0,
+      0,   0,   1,   0,   5,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     21,   4,   0,   0,  90,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     20,   4,   0,   0,   3,   0,   1,   0,
+     32,   4,   0,   0,   2,   0,   1,   0,
+      6,   0,   0,   0,   3,   0,   0,   0,
+      0,   0,   1,   0,   6,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     29,   4,   0,   0, 178,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     32,   4,   0,   0,   3,   0,   1,   0,
+     44,   4,   0,   0,   2,   0,   1,   0,
       7,   0,   0,   0,  66,   0,   0,   0,
       0,   0,   1,   0,   7,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-     13,   4,   0,   0, 138,   0,   0,   0,
+     41,   4,   0,   0, 130,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-     16,   4,   0,   0,   3,   0,   1,   0,
-     28,   4,   0,   0,   2,   0,   1,   0,
+     40,   4,   0,   0,   3,   0,   1,   0,
+     52,   4,   0,   0,   2,   0,   1,   0,
       8,   0,   0,   0,  67,   0,   0,   0,
       0,   0,   1,   0,   8,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-     25,   4,   0,   0,  98,   0,   0,   0,
+     49,   4,   0,   0, 138,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-     24,   4,   0,   0,   3,   0,   1,   0,
-     36,   4,   0,   0,   2,   0,   1,   0,
-      9,   0,   0,   0,   5,   0,   0,   0,
+     52,   4,   0,   0,   3,   0,   1,   0,
+     64,   4,   0,   0,   2,   0,   1,   0,
+      9,   0,   0,   0,  68,   0,   0,   0,
       0,   0,   1,   0,   9,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-     33,   4,   0,   0, 146,   0,   0,   0,
+     61,   4,   0,   0,  98,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-     36,   4,   0,   0,   3,   0,   1,   0,
-     48,   4,   0,   0,   2,   0,   1,   0,
-     10,   0,   0,   0,   0,   0,   0,   0,
+     60,   4,   0,   0,   3,   0,   1,   0,
+     72,   4,   0,   0,   2,   0,   1,   0,
+     10,   0,   0,   0,   5,   0,   0,   0,
       0,   0,   1,   0,  10,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-     45,   4,   0,   0, 130,   0,   0,   0,
+     69,   4,   0,   0, 146,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-     44,   4,   0,   0,   3,   0,   1,   0,
-     72,   4,   0,   0,   2,   0,   1,   0,
-     11,   0,   0,   0,   8,   0,   0,   0,
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       0,   0,   1,   0,  11,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
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       0,   0,   0,   0,   0,   0,   0,   0,
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       0,   0,   0,   0,   0,   0,   0,   0,
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       0,   0,   0,   0,   0,   0,   0,   0,
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       0,   0,   0,   0,   0,   0,   0,   0,
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       0,   0,   0,   0,   0,   0,   0,   0,
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       0,   0,   0,   0,   0,   0,   0,   0,
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       0,   0,   0,   0,   0,   0,   0,   0,
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       0,   0,   0,   0,   0,   0,   0,   0,
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       0,   0,   0,   0,   0,   0,   0,   0,
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-    120,   4,   0,   0,   2,   0,   1,   0,
-     16,   0,   0,   0,  12,   0,   0,   0,
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       0,   0,   1,   0,  16,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    117,   4,   0,   0, 130,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-    116,   4,   0,   0,   3,   0,   1,   0,
-    128,   4,   0,   0,   2,   0,   1,   0,
-     17,   0,   0,   0,  69,   0,   0,   0,
-      0,   0,   1,   0,  17,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-    125,   4,   0,   0,  74,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-    124,   4,   0,   0,   3,   0,   1,   0,
-    136,   4,   0,   0,   2,   0,   1,   0,
-     18,   0,   0,   0,  13,   0,   0,   0,
-      0,   0,   1,   0,  18,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-    133,   4,   0,   0, 114,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-    132,   4,   0,   0,   3,   0,   1,   0,
-    144,   4,   0,   0,   2,   0,   1,   0,
-     19,   0,   0,   0,  14,   0,   0,   0,
-      0,   0,   1,   0,  19,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-    141,   4,   0,   0, 138,   0,   0,   0,
+    145,   4,   0,   0, 130,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
     144,   4,   0,   0,   3,   0,   1,   0,
     156,   4,   0,   0,   2,   0,   1,   0,
-     20,   0,   0,   0,  15,   0,   0,   0,
-      0,   0,   1,   0,  20,   0,   0,   0,
+     17,   0,   0,   0,  12,   0,   0,   0,
+      0,   0,   1,   0,  17,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    153,   4,   0,   0, 162,   0,   0,   0,
+    153,   4,   0,   0, 130,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    156,   4,   0,   0,   3,   0,   1,   0,
-    168,   4,   0,   0,   2,   0,   1,   0,
-     21,   0,   0,   0,  16,   0,   0,   0,
-      0,   0,   1,   0,  21,   0,   0,   0,
+    152,   4,   0,   0,   3,   0,   1,   0,
+    164,   4,   0,   0,   2,   0,   1,   0,
+     18,   0,   0,   0,  70,   0,   0,   0,
+      0,   0,   1,   0,  18,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    165,   4,   0,   0, 146,   0,   0,   0,
+    161,   4,   0,   0,  74,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    160,   4,   0,   0,   3,   0,   1,   0,
+    172,   4,   0,   0,   2,   0,   1,   0,
+     19,   0,   0,   0,  13,   0,   0,   0,
+      0,   0,   1,   0,  19,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    169,   4,   0,   0, 114,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
     168,   4,   0,   0,   3,   0,   1,   0,
     180,   4,   0,   0,   2,   0,   1,   0,
-     22,   0,   0,   0,  17,   0,   0,   0,
-      0,   0,   1,   0,  22,   0,   0,   0,
+     20,   0,   0,   0,  14,   0,   0,   0,
+      0,   0,   1,   0,  20,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    177,   4,   0,   0, 154,   0,   0,   0,
+    177,   4,   0,   0, 138,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
     180,   4,   0,   0,   3,   0,   1,   0,
     192,   4,   0,   0,   2,   0,   1,   0,
-     23,   0,   0,   0,  18,   0,   0,   0,
+     21,   0,   0,   0,  15,   0,   0,   0,
+      0,   0,   1,   0,  21,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    189,   4,   0,   0, 162,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    192,   4,   0,   0,   3,   0,   1,   0,
+    204,   4,   0,   0,   2,   0,   1,   0,
+     22,   0,   0,   0,  16,   0,   0,   0,
+      0,   0,   1,   0,  22,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    201,   4,   0,   0, 146,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    204,   4,   0,   0,   3,   0,   1,   0,
+    216,   4,   0,   0,   2,   0,   1,   0,
+     23,   0,   0,   0,  17,   0,   0,   0,
       0,   0,   1,   0,  23,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    189,   4,   0,   0, 114,   0,   0,   0,
+    213,   4,   0,   0, 154,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    188,   4,   0,   0,   3,   0,   1,   0,
-    200,   4,   0,   0,   2,   0,   1,   0,
-     24,   0,   0,   0,  19,   0,   0,   0,
+    216,   4,   0,   0,   3,   0,   1,   0,
+    228,   4,   0,   0,   2,   0,   1,   0,
+     24,   0,   0,   0,  18,   0,   0,   0,
       0,   0,   1,   0,  24,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    197,   4,   0,   0, 162,   0,   0,   0,
+    225,   4,   0,   0, 114,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    200,   4,   0,   0,   3,   0,   1,   0,
-    212,   4,   0,   0,   2,   0,   1,   0,
-     25,   0,   0,   0,   1,   0,   0,   0,
+    224,   4,   0,   0,   3,   0,   1,   0,
+    236,   4,   0,   0,   2,   0,   1,   0,
+     25,   0,   0,   0,  19,   0,   0,   0,
       0,   0,   1,   0,  25,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    209,   4,   0,   0, 162,   0,   0,   0,
+    233,   4,   0,   0, 162,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    212,   4,   0,   0,   3,   0,   1,   0,
-    224,   4,   0,   0,   2,   0,   1,   0,
-     26,   0,   0,   0,  20,   0,   0,   0,
+    236,   4,   0,   0,   3,   0,   1,   0,
+    248,   4,   0,   0,   2,   0,   1,   0,
+     26,   0,   0,   0,   1,   0,   0,   0,
       0,   0,   1,   0,  26,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    221,   4,   0,   0,  82,   0,   0,   0,
+    245,   4,   0,   0, 162,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    220,   4,   0,   0,   3,   0,   1,   0,
-    232,   4,   0,   0,   2,   0,   1,   0,
-     27,   0,   0,   0,  21,   0,   0,   0,
+    248,   4,   0,   0,   3,   0,   1,   0,
+      4,   5,   0,   0,   2,   0,   1,   0,
+     27,   0,   0,   0,  20,   0,   0,   0,
       0,   0,   1,   0,  27,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    229,   4,   0,   0, 122,   0,   0,   0,
+      1,   5,   0,   0,  82,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    228,   4,   0,   0,   3,   0,   1,   0,
-    240,   4,   0,   0,   2,   0,   1,   0,
-     28,   0,   0,   0,  70,   0,   0,   0,
+      0,   5,   0,   0,   3,   0,   1,   0,
+     12,   5,   0,   0,   2,   0,   1,   0,
+     28,   0,   0,   0,  21,   0,   0,   0,
       0,   0,   1,   0,  28,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    237,   4,   0,   0, 146,   0,   0,   0,
+      9,   5,   0,   0, 122,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    240,   4,   0,   0,   3,   0,   1,   0,
-    252,   4,   0,   0,   2,   0,   1,   0,
-     29,   0,   0,   0,  22,   0,   0,   0,
+      8,   5,   0,   0,   3,   0,   1,   0,
+     20,   5,   0,   0,   2,   0,   1,   0,
+     29,   0,   0,   0,  71,   0,   0,   0,
       0,   0,   1,   0,  29,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    249,   4,   0,   0,  66,   0,   0,   0,
+     17,   5,   0,   0, 146,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    244,   4,   0,   0,   3,   0,   1,   0,
-      0,   5,   0,   0,   2,   0,   1,   0,
-     30,   0,   0,   0,  71,   0,   0,   0,
+     20,   5,   0,   0,   3,   0,   1,   0,
+     32,   5,   0,   0,   2,   0,   1,   0,
+     30,   0,   0,   0,  22,   0,   0,   0,
       0,   0,   1,   0,  30,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    253,   4,   0,   0, 106,   0,   0,   0,
+     29,   5,   0,   0,  66,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-    252,   4,   0,   0,   3,   0,   1,   0,
-      8,   5,   0,   0,   2,   0,   1,   0,
+     24,   5,   0,   0,   3,   0,   1,   0,
+     36,   5,   0,   0,   2,   0,   1,   0,
      31,   0,   0,   0,  72,   0,   0,   0,
       0,   0,   1,   0,  31,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-      5,   5,   0,   0, 122,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-      4,   5,   0,   0,   3,   0,   1,   0,
-     16,   5,   0,   0,   2,   0,   1,   0,
-     32,   0,   0,   0,  73,   0,   0,   0,
-      0,   0,   1,   0,  32,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     13,   5,   0,   0, 106,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     12,   5,   0,   0,   3,   0,   1,   0,
-     24,   5,   0,   0,   2,   0,   1,   0,
-     33,   0,   0,   0,  23,   0,   0,   0,
-      0,   0,   1,   0,  33,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     21,   5,   0,   0, 202,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     28,   5,   0,   0,   3,   0,   1,   0,
-     40,   5,   0,   0,   2,   0,   1,   0,
-     34,   0,   0,   0,  24,   0,   0,   0,
-      0,   0,   1,   0,  34,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     37,   5,   0,   0,  66,   0,   0,   0,
+     33,   5,   0,   0, 106,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
      32,   5,   0,   0,   3,   0,   1,   0,
      44,   5,   0,   0,   2,   0,   1,   0,
+     32,   0,   0,   0,  73,   0,   0,   0,
+      0,   0,   1,   0,  32,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     41,   5,   0,   0, 122,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     40,   5,   0,   0,   3,   0,   1,   0,
+     52,   5,   0,   0,   2,   0,   1,   0,
+     33,   0,   0,   0,  74,   0,   0,   0,
+      0,   0,   1,   0,  33,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     49,   5,   0,   0, 106,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     48,   5,   0,   0,   3,   0,   1,   0,
+     60,   5,   0,   0,   2,   0,   1,   0,
+     34,   0,   0,   0,  23,   0,   0,   0,
+      0,   0,   1,   0,  34,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     57,   5,   0,   0, 202,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     64,   5,   0,   0,   3,   0,   1,   0,
+     76,   5,   0,   0,   2,   0,   1,   0,
+     35,   0,   0,   0,  24,   0,   0,   0,
+      0,   0,   1,   0,  35,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     73,   5,   0,   0,  66,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     68,   5,   0,   0,   3,   0,   1,   0,
+     80,   5,   0,   0,   2,   0,   1,   0,
      97,  99,  99, 101, 108, 101, 114,  97,
     116, 105, 111, 110,  74, 101, 114, 107,
       0,   0,   0,   0,   0,   0,   0,   0,
@@ -2070,6 +2018,15 @@ static const ::capnp::_::AlignedData<597> b_a1680744031fdb2d = {
       5,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
+    100, 105, 115,  97,  98, 108, 101,  84,
+    104, 114, 111, 116, 116, 108, 101,   0,
+      1,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+      1,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
     101, 120, 112, 101, 114, 105, 109, 101,
     110, 116,  97, 108,  77, 111, 100, 101,
       0,   0,   0,   0,   0,   0,   0,   0,
@@ -2343,11 +2300,11 @@ static const ::capnp::_::AlignedData<597> b_a1680744031fdb2d = {
 static const ::capnp::_::RawSchema* const d_a1680744031fdb2d[] = {
   &s_81c2f05a394cf4af,
 };
-static const uint16_t m_a1680744031fdb2d[] = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 12, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34};
-static const uint16_t i_a1680744031fdb2d[] = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34};
+static const uint16_t m_a1680744031fdb2d[] = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 13, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35};
+static const uint16_t i_a1680744031fdb2d[] = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35};
 const ::capnp::_::RawSchema s_a1680744031fdb2d = {
-  0xa1680744031fdb2d, b_a1680744031fdb2d.words, 597, d_a1680744031fdb2d, m_a1680744031fdb2d,
-  1, 35, i_a1680744031fdb2d, nullptr, nullptr, { &s_a1680744031fdb2d, nullptr, nullptr, 0, 0, nullptr }, false
+  0xa1680744031fdb2d, b_a1680744031fdb2d.words, 613, d_a1680744031fdb2d, m_a1680744031fdb2d,
+  1, 36, i_a1680744031fdb2d, nullptr, nullptr, { &s_a1680744031fdb2d, nullptr, nullptr, 0, 0, nullptr }, false
 };
 #endif  // !CAPNP_LITE
 static const ::capnp::_::AlignedData<55> b_cb9fd56c7057593a = {
@@ -2761,18 +2718,6 @@ constexpr ::capnp::_::RawSchema const* FrogPilotCarParams::SafetyConfig::_capnpP
 #endif  // !CAPNP_NEED_REDUNDANT_CONSTEXPR_DECL
 #endif  // !CAPNP_LITE
 
-// FrogPilotCarParams::LateralTuning
-#if CAPNP_NEED_REDUNDANT_CONSTEXPR_DECL
-constexpr uint16_t FrogPilotCarParams::LateralTuning::_capnpPrivate::dataWordSize;
-constexpr uint16_t FrogPilotCarParams::LateralTuning::_capnpPrivate::pointerCount;
-#endif  // !CAPNP_NEED_REDUNDANT_CONSTEXPR_DECL
-#if !CAPNP_LITE
-#if CAPNP_NEED_REDUNDANT_CONSTEXPR_DECL
-constexpr ::capnp::Kind FrogPilotCarParams::LateralTuning::_capnpPrivate::kind;
-constexpr ::capnp::_::RawSchema const* FrogPilotCarParams::LateralTuning::_capnpPrivate::schema;
-#endif  // !CAPNP_NEED_REDUNDANT_CONSTEXPR_DECL
-#endif  // !CAPNP_LITE
-
 // FrogPilotCarState
 #if CAPNP_NEED_REDUNDANT_CONSTEXPR_DECL
 constexpr uint16_t FrogPilotCarState::_capnpPrivate::dataWordSize;

cereal/gen/cpp/custom.capnp.h

@@ -84,7 +84,6 @@ enum class EventName_aedffd8f31e7b55d: uint16_t {
 CAPNP_DECLARE_ENUM(EventName, aedffd8f31e7b55d);
 CAPNP_DECLARE_SCHEMA(f35cc4560bbf6ec2);
 CAPNP_DECLARE_SCHEMA(8d65dd40bad40951);
-CAPNP_DECLARE_SCHEMA(fcc949d2cbea7649);
 CAPNP_DECLARE_SCHEMA(da96579883444c35);
 CAPNP_DECLARE_SCHEMA(ccb4d6b0dc102d40);
 CAPNP_DECLARE_SCHEMA(8033e8e60d6a0edb);
@@ -185,10 +184,9 @@ struct FrogPilotCarParams {
   class Builder;
   class Pipeline;
   struct SafetyConfig;
-  struct LateralTuning;
 
   struct _capnpPrivate {
-    CAPNP_DECLARE_STRUCT_HEADER(f35cc4560bbf6ec2, 1, 2)
+    CAPNP_DECLARE_STRUCT_HEADER(f35cc4560bbf6ec2, 1, 1)
     #if !CAPNP_LITE
     static constexpr ::capnp::_::RawBrandedSchema const* brand() { return &schema->defaultBrand; }
     #endif  // !CAPNP_LITE
@@ -210,25 +208,6 @@ struct FrogPilotCarParams::SafetyConfig {
   };
 };
 
-struct FrogPilotCarParams::LateralTuning {
-  LateralTuning() = delete;
-
-  class Reader;
-  class Builder;
-  class Pipeline;
-  enum Which: uint16_t {
-    PID,
-    TORQUE,
-  };
-
-  struct _capnpPrivate {
-    CAPNP_DECLARE_STRUCT_HEADER(fcc949d2cbea7649, 1, 2)
-    #if !CAPNP_LITE
-    static constexpr ::capnp::_::RawBrandedSchema const* brand() { return &schema->defaultBrand; }
-    #endif  // !CAPNP_LITE
-  };
-};
-
 struct FrogPilotCarState {
   FrogPilotCarState() = delete;
 
@@ -690,7 +669,7 @@ public:
   inline bool hasSafetyConfigs() const;
   inline  ::capnp::List< ::cereal::FrogPilotCarParams::SafetyConfig,  ::capnp::Kind::STRUCT>::Reader getSafetyConfigs() const;
 
-  inline typename LateralTuning::Reader getLateralTuning() const;
+  inline bool getCanUseSASCM() const;
 
 private:
   ::capnp::_::StructReader _reader;
@@ -742,8 +721,8 @@ public:
   inline void adoptSafetyConfigs(::capnp::Orphan< ::capnp::List< ::cereal::FrogPilotCarParams::SafetyConfig,  ::capnp::Kind::STRUCT>>&& value);
   inline ::capnp::Orphan< ::capnp::List< ::cereal::FrogPilotCarParams::SafetyConfig,  ::capnp::Kind::STRUCT>> disownSafetyConfigs();
 
-  inline typename LateralTuning::Builder getLateralTuning();
-  inline typename LateralTuning::Builder initLateralTuning();
+  inline bool getCanUseSASCM();
+  inline void setCanUseSASCM(bool value);
 
 private:
   ::capnp::_::StructBuilder _builder;
@@ -763,7 +742,6 @@ public:
   inline explicit Pipeline(::capnp::AnyPointer::Pipeline&& typeless)
       : _typeless(kj::mv(typeless)) {}
 
-  inline typename LateralTuning::Pipeline getLateralTuning();
 private:
   ::capnp::AnyPointer::Pipeline _typeless;
   friend class ::capnp::PipelineHook;
@@ -848,103 +826,6 @@ private:
 };
 #endif  // !CAPNP_LITE
 
-class FrogPilotCarParams::LateralTuning::Reader {
-public:
-  typedef LateralTuning Reads;
-
-  Reader() = default;
-  inline explicit Reader(::capnp::_::StructReader base): _reader(base) {}
-
-  inline ::capnp::MessageSize totalSize() const {
-    return _reader.totalSize().asPublic();
-  }
-
-#if !CAPNP_LITE
-  inline ::kj::StringTree toString() const {
-    return ::capnp::_::structString(_reader, *_capnpPrivate::brand());
-  }
-#endif  // !CAPNP_LITE
-
-  inline Which which() const;
-  inline bool isPid() const;
-  inline bool hasPid() const;
-  inline  ::cereal::CarParams::LateralPIDTuning::Reader getPid() const;
-
-  inline bool isTorque() const;
-  inline bool hasTorque() const;
-  inline  ::cereal::CarParams::LateralTorqueTuning::Reader getTorque() const;
-
-private:
-  ::capnp::_::StructReader _reader;
-  template <typename, ::capnp::Kind>
-  friend struct ::capnp::ToDynamic_;
-  template <typename, ::capnp::Kind>
-  friend struct ::capnp::_::PointerHelpers;
-  template <typename, ::capnp::Kind>
-  friend struct ::capnp::List;
-  friend class ::capnp::MessageBuilder;
-  friend class ::capnp::Orphanage;
-};
-
-class FrogPilotCarParams::LateralTuning::Builder {
-public:
-  typedef LateralTuning Builds;
-
-  Builder() = delete;  // Deleted to discourage incorrect usage.
-                       // You can explicitly initialize to nullptr instead.
-  inline Builder(decltype(nullptr)) {}
-  inline explicit Builder(::capnp::_::StructBuilder base): _builder(base) {}
-  inline operator Reader() const { return Reader(_builder.asReader()); }
-  inline Reader asReader() const { return *this; }
-
-  inline ::capnp::MessageSize totalSize() const { return asReader().totalSize(); }
-#if !CAPNP_LITE
-  inline ::kj::StringTree toString() const { return asReader().toString(); }
-#endif  // !CAPNP_LITE
-
-  inline Which which();
-  inline bool isPid();
-  inline bool hasPid();
-  inline  ::cereal::CarParams::LateralPIDTuning::Builder getPid();
-  inline void setPid( ::cereal::CarParams::LateralPIDTuning::Reader value);
-  inline  ::cereal::CarParams::LateralPIDTuning::Builder initPid();
-  inline void adoptPid(::capnp::Orphan< ::cereal::CarParams::LateralPIDTuning>&& value);
-  inline ::capnp::Orphan< ::cereal::CarParams::LateralPIDTuning> disownPid();
-
-  inline bool isTorque();
-  inline bool hasTorque();
-  inline  ::cereal::CarParams::LateralTorqueTuning::Builder getTorque();
-  inline void setTorque( ::cereal::CarParams::LateralTorqueTuning::Reader value);
-  inline  ::cereal::CarParams::LateralTorqueTuning::Builder initTorque();
-  inline void adoptTorque(::capnp::Orphan< ::cereal::CarParams::LateralTorqueTuning>&& value);
-  inline ::capnp::Orphan< ::cereal::CarParams::LateralTorqueTuning> disownTorque();
-
-private:
-  ::capnp::_::StructBuilder _builder;
-  template <typename, ::capnp::Kind>
-  friend struct ::capnp::ToDynamic_;
-  friend class ::capnp::Orphanage;
-  template <typename, ::capnp::Kind>
-  friend struct ::capnp::_::PointerHelpers;
-};
-
-#if !CAPNP_LITE
-class FrogPilotCarParams::LateralTuning::Pipeline {
-public:
-  typedef LateralTuning Pipelines;
-
-  inline Pipeline(decltype(nullptr)): _typeless(nullptr) {}
-  inline explicit Pipeline(::capnp::AnyPointer::Pipeline&& typeless)
-      : _typeless(kj::mv(typeless)) {}
-
-private:
-  ::capnp::AnyPointer::Pipeline _typeless;
-  friend class ::capnp::PipelineHook;
-  template <typename, ::capnp::Kind>
-  friend struct ::capnp::ToDynamic_;
-};
-#endif  // !CAPNP_LITE
-
 class FrogPilotCarState::Reader {
 public:
   typedef FrogPilotCarState Reads;
@@ -1557,6 +1438,8 @@ public:
 
   inline  ::int64_t getDesiredFollowDistance() const;
 
+  inline bool getDisableThrottle() const;
+
   inline bool getExperimentalMode() const;
 
   inline bool getForcingStop() const;
@@ -1664,6 +1547,9 @@ public:
   inline  ::int64_t getDesiredFollowDistance();
   inline void setDesiredFollowDistance( ::int64_t value);
 
+  inline bool getDisableThrottle();
+  inline void setDisableThrottle(bool value);
+
   inline bool getExperimentalMode();
   inline void setExperimentalMode(bool value);
 
@@ -2339,22 +2225,20 @@ inline ::capnp::Orphan< ::capnp::List< ::cereal::FrogPilotCarParams::SafetyConfi
       ::capnp::bounded<0>() * ::capnp::POINTERS));
 }
 
-inline typename FrogPilotCarParams::LateralTuning::Reader FrogPilotCarParams::Reader::getLateralTuning() const {
-  return typename FrogPilotCarParams::LateralTuning::Reader(_reader);
+inline bool FrogPilotCarParams::Reader::getCanUseSASCM() const {
+  return _reader.getDataField<bool>(
+      ::capnp::bounded<4>() * ::capnp::ELEMENTS);
 }
-inline typename FrogPilotCarParams::LateralTuning::Builder FrogPilotCarParams::Builder::getLateralTuning() {
-  return typename FrogPilotCarParams::LateralTuning::Builder(_builder);
+
+inline bool FrogPilotCarParams::Builder::getCanUseSASCM() {
+  return _builder.getDataField<bool>(
+      ::capnp::bounded<4>() * ::capnp::ELEMENTS);
 }
-#if !CAPNP_LITE
-inline typename FrogPilotCarParams::LateralTuning::Pipeline FrogPilotCarParams::Pipeline::getLateralTuning() {
-  return typename FrogPilotCarParams::LateralTuning::Pipeline(_typeless.noop());
-}
-#endif  // !CAPNP_LITE
-inline typename FrogPilotCarParams::LateralTuning::Builder FrogPilotCarParams::Builder::initLateralTuning() {
-  _builder.setDataField< ::uint16_t>(::capnp::bounded<1>() * ::capnp::ELEMENTS, 0);
-  _builder.getPointerField(::capnp::bounded<1>() * ::capnp::POINTERS).clear();
-  return typename FrogPilotCarParams::LateralTuning::Builder(_builder);
+inline void FrogPilotCarParams::Builder::setCanUseSASCM(bool value) {
+  _builder.setDataField<bool>(
+      ::capnp::bounded<4>() * ::capnp::ELEMENTS, value);
 }
+
 inline  ::uint16_t FrogPilotCarParams::SafetyConfig::Reader::getSafetyParam() const {
   return _reader.getDataField< ::uint16_t>(
       ::capnp::bounded<0>() * ::capnp::ELEMENTS);
@@ -2369,123 +2253,6 @@ inline void FrogPilotCarParams::SafetyConfig::Builder::setSafetyParam( ::uint16_
       ::capnp::bounded<0>() * ::capnp::ELEMENTS, value);
 }
 
-inline  ::cereal::FrogPilotCarParams::LateralTuning::Which FrogPilotCarParams::LateralTuning::Reader::which() const {
-  return _reader.getDataField<Which>(
-      ::capnp::bounded<1>() * ::capnp::ELEMENTS);
-}
-inline  ::cereal::FrogPilotCarParams::LateralTuning::Which FrogPilotCarParams::LateralTuning::Builder::which() {
-  return _builder.getDataField<Which>(
-      ::capnp::bounded<1>() * ::capnp::ELEMENTS);
-}
-
-inline bool FrogPilotCarParams::LateralTuning::Reader::isPid() const {
-  return which() == FrogPilotCarParams::LateralTuning::PID;
-}
-inline bool FrogPilotCarParams::LateralTuning::Builder::isPid() {
-  return which() == FrogPilotCarParams::LateralTuning::PID;
-}
-inline bool FrogPilotCarParams::LateralTuning::Reader::hasPid() const {
-  if (which() != FrogPilotCarParams::LateralTuning::PID) return false;
-  return !_reader.getPointerField(
-      ::capnp::bounded<1>() * ::capnp::POINTERS).isNull();
-}
-inline bool FrogPilotCarParams::LateralTuning::Builder::hasPid() {
-  if (which() != FrogPilotCarParams::LateralTuning::PID) return false;
-  return !_builder.getPointerField(
-      ::capnp::bounded<1>() * ::capnp::POINTERS).isNull();
-}
-inline  ::cereal::CarParams::LateralPIDTuning::Reader FrogPilotCarParams::LateralTuning::Reader::getPid() const {
-  KJ_IREQUIRE((which() == FrogPilotCarParams::LateralTuning::PID),
-              "Must check which() before get()ing a union member.");
-  return ::capnp::_::PointerHelpers< ::cereal::CarParams::LateralPIDTuning>::get(_reader.getPointerField(
-      ::capnp::bounded<1>() * ::capnp::POINTERS));
-}
-inline  ::cereal::CarParams::LateralPIDTuning::Builder FrogPilotCarParams::LateralTuning::Builder::getPid() {
-  KJ_IREQUIRE((which() == FrogPilotCarParams::LateralTuning::PID),
-              "Must check which() before get()ing a union member.");
-  return ::capnp::_::PointerHelpers< ::cereal::CarParams::LateralPIDTuning>::get(_builder.getPointerField(
-      ::capnp::bounded<1>() * ::capnp::POINTERS));
-}
-inline void FrogPilotCarParams::LateralTuning::Builder::setPid( ::cereal::CarParams::LateralPIDTuning::Reader value) {
-  _builder.setDataField<FrogPilotCarParams::LateralTuning::Which>(
-      ::capnp::bounded<1>() * ::capnp::ELEMENTS, FrogPilotCarParams::LateralTuning::PID);
-  ::capnp::_::PointerHelpers< ::cereal::CarParams::LateralPIDTuning>::set(_builder.getPointerField(
-      ::capnp::bounded<1>() * ::capnp::POINTERS), value);
-}
-inline  ::cereal::CarParams::LateralPIDTuning::Builder FrogPilotCarParams::LateralTuning::Builder::initPid() {
-  _builder.setDataField<FrogPilotCarParams::LateralTuning::Which>(
-      ::capnp::bounded<1>() * ::capnp::ELEMENTS, FrogPilotCarParams::LateralTuning::PID);
-  return ::capnp::_::PointerHelpers< ::cereal::CarParams::LateralPIDTuning>::init(_builder.getPointerField(
-      ::capnp::bounded<1>() * ::capnp::POINTERS));
-}
-inline void FrogPilotCarParams::LateralTuning::Builder::adoptPid(
-    ::capnp::Orphan< ::cereal::CarParams::LateralPIDTuning>&& value) {
-  _builder.setDataField<FrogPilotCarParams::LateralTuning::Which>(
-      ::capnp::bounded<1>() * ::capnp::ELEMENTS, FrogPilotCarParams::LateralTuning::PID);
-  ::capnp::_::PointerHelpers< ::cereal::CarParams::LateralPIDTuning>::adopt(_builder.getPointerField(
-      ::capnp::bounded<1>() * ::capnp::POINTERS), kj::mv(value));
-}
-inline ::capnp::Orphan< ::cereal::CarParams::LateralPIDTuning> FrogPilotCarParams::LateralTuning::Builder::disownPid() {
-  KJ_IREQUIRE((which() == FrogPilotCarParams::LateralTuning::PID),
-              "Must check which() before get()ing a union member.");
-  return ::capnp::_::PointerHelpers< ::cereal::CarParams::LateralPIDTuning>::disown(_builder.getPointerField(
-      ::capnp::bounded<1>() * ::capnp::POINTERS));
-}
-
-inline bool FrogPilotCarParams::LateralTuning::Reader::isTorque() const {
-  return which() == FrogPilotCarParams::LateralTuning::TORQUE;
-}
-inline bool FrogPilotCarParams::LateralTuning::Builder::isTorque() {
-  return which() == FrogPilotCarParams::LateralTuning::TORQUE;
-}
-inline bool FrogPilotCarParams::LateralTuning::Reader::hasTorque() const {
-  if (which() != FrogPilotCarParams::LateralTuning::TORQUE) return false;
-  return !_reader.getPointerField(
-      ::capnp::bounded<1>() * ::capnp::POINTERS).isNull();
-}
-inline bool FrogPilotCarParams::LateralTuning::Builder::hasTorque() {
-  if (which() != FrogPilotCarParams::LateralTuning::TORQUE) return false;
-  return !_builder.getPointerField(
-      ::capnp::bounded<1>() * ::capnp::POINTERS).isNull();
-}
-inline  ::cereal::CarParams::LateralTorqueTuning::Reader FrogPilotCarParams::LateralTuning::Reader::getTorque() const {
-  KJ_IREQUIRE((which() == FrogPilotCarParams::LateralTuning::TORQUE),
-              "Must check which() before get()ing a union member.");
-  return ::capnp::_::PointerHelpers< ::cereal::CarParams::LateralTorqueTuning>::get(_reader.getPointerField(
-      ::capnp::bounded<1>() * ::capnp::POINTERS));
-}
-inline  ::cereal::CarParams::LateralTorqueTuning::Builder FrogPilotCarParams::LateralTuning::Builder::getTorque() {
-  KJ_IREQUIRE((which() == FrogPilotCarParams::LateralTuning::TORQUE),
-              "Must check which() before get()ing a union member.");
-  return ::capnp::_::PointerHelpers< ::cereal::CarParams::LateralTorqueTuning>::get(_builder.getPointerField(
-      ::capnp::bounded<1>() * ::capnp::POINTERS));
-}
-inline void FrogPilotCarParams::LateralTuning::Builder::setTorque( ::cereal::CarParams::LateralTorqueTuning::Reader value) {
-  _builder.setDataField<FrogPilotCarParams::LateralTuning::Which>(
-      ::capnp::bounded<1>() * ::capnp::ELEMENTS, FrogPilotCarParams::LateralTuning::TORQUE);
-  ::capnp::_::PointerHelpers< ::cereal::CarParams::LateralTorqueTuning>::set(_builder.getPointerField(
-      ::capnp::bounded<1>() * ::capnp::POINTERS), value);
-}
-inline  ::cereal::CarParams::LateralTorqueTuning::Builder FrogPilotCarParams::LateralTuning::Builder::initTorque() {
-  _builder.setDataField<FrogPilotCarParams::LateralTuning::Which>(
-      ::capnp::bounded<1>() * ::capnp::ELEMENTS, FrogPilotCarParams::LateralTuning::TORQUE);
-  return ::capnp::_::PointerHelpers< ::cereal::CarParams::LateralTorqueTuning>::init(_builder.getPointerField(
-      ::capnp::bounded<1>() * ::capnp::POINTERS));
-}
-inline void FrogPilotCarParams::LateralTuning::Builder::adoptTorque(
-    ::capnp::Orphan< ::cereal::CarParams::LateralTorqueTuning>&& value) {
-  _builder.setDataField<FrogPilotCarParams::LateralTuning::Which>(
-      ::capnp::bounded<1>() * ::capnp::ELEMENTS, FrogPilotCarParams::LateralTuning::TORQUE);
-  ::capnp::_::PointerHelpers< ::cereal::CarParams::LateralTorqueTuning>::adopt(_builder.getPointerField(
-      ::capnp::bounded<1>() * ::capnp::POINTERS), kj::mv(value));
-}
-inline ::capnp::Orphan< ::cereal::CarParams::LateralTorqueTuning> FrogPilotCarParams::LateralTuning::Builder::disownTorque() {
-  KJ_IREQUIRE((which() == FrogPilotCarParams::LateralTuning::TORQUE),
-              "Must check which() before get()ing a union member.");
-  return ::capnp::_::PointerHelpers< ::cereal::CarParams::LateralTorqueTuning>::disown(_builder.getPointerField(
-      ::capnp::bounded<1>() * ::capnp::POINTERS));
-}
-
 inline bool FrogPilotCarState::Reader::getAccelPressed() const {
   return _reader.getDataField<bool>(
       ::capnp::bounded<0>() * ::capnp::ELEMENTS);
@@ -3036,34 +2803,48 @@ inline void FrogPilotPlan::Builder::setDesiredFollowDistance( ::int64_t value) {
       ::capnp::bounded<3>() * ::capnp::ELEMENTS, value);
 }
 
-inline bool FrogPilotPlan::Reader::getExperimentalMode() const {
+inline bool FrogPilotPlan::Reader::getDisableThrottle() const {
   return _reader.getDataField<bool>(
       ::capnp::bounded<66>() * ::capnp::ELEMENTS);
 }
 
-inline bool FrogPilotPlan::Builder::getExperimentalMode() {
+inline bool FrogPilotPlan::Builder::getDisableThrottle() {
   return _builder.getDataField<bool>(
       ::capnp::bounded<66>() * ::capnp::ELEMENTS);
 }
-inline void FrogPilotPlan::Builder::setExperimentalMode(bool value) {
+inline void FrogPilotPlan::Builder::setDisableThrottle(bool value) {
   _builder.setDataField<bool>(
       ::capnp::bounded<66>() * ::capnp::ELEMENTS, value);
 }
 
-inline bool FrogPilotPlan::Reader::getForcingStop() const {
+inline bool FrogPilotPlan::Reader::getExperimentalMode() const {
   return _reader.getDataField<bool>(
       ::capnp::bounded<67>() * ::capnp::ELEMENTS);
 }
 
-inline bool FrogPilotPlan::Builder::getForcingStop() {
+inline bool FrogPilotPlan::Builder::getExperimentalMode() {
   return _builder.getDataField<bool>(
       ::capnp::bounded<67>() * ::capnp::ELEMENTS);
 }
-inline void FrogPilotPlan::Builder::setForcingStop(bool value) {
+inline void FrogPilotPlan::Builder::setExperimentalMode(bool value) {
   _builder.setDataField<bool>(
       ::capnp::bounded<67>() * ::capnp::ELEMENTS, value);
 }
 
+inline bool FrogPilotPlan::Reader::getForcingStop() const {
+  return _reader.getDataField<bool>(
+      ::capnp::bounded<68>() * ::capnp::ELEMENTS);
+}
+
+inline bool FrogPilotPlan::Builder::getForcingStop() {
+  return _builder.getDataField<bool>(
+      ::capnp::bounded<68>() * ::capnp::ELEMENTS);
+}
+inline void FrogPilotPlan::Builder::setForcingStop(bool value) {
+  _builder.setDataField<bool>(
+      ::capnp::bounded<68>() * ::capnp::ELEMENTS, value);
+}
+
 inline float FrogPilotPlan::Reader::getForcingStopLength() const {
   return _reader.getDataField<float>(
       ::capnp::bounded<5>() * ::capnp::ELEMENTS);
@@ -3128,16 +2909,16 @@ inline void FrogPilotPlan::Builder::setIncreasedStoppedDistance(float value) {
 
 inline bool FrogPilotPlan::Reader::getLateralCheck() const {
   return _reader.getDataField<bool>(
-      ::capnp::bounded<68>() * ::capnp::ELEMENTS);
+      ::capnp::bounded<69>() * ::capnp::ELEMENTS);
 }
 
 inline bool FrogPilotPlan::Builder::getLateralCheck() {
   return _builder.getDataField<bool>(
-      ::capnp::bounded<68>() * ::capnp::ELEMENTS);
+      ::capnp::bounded<69>() * ::capnp::ELEMENTS);
 }
 inline void FrogPilotPlan::Builder::setLateralCheck(bool value) {
   _builder.setDataField<bool>(
-      ::capnp::bounded<68>() * ::capnp::ELEMENTS, value);
+      ::capnp::bounded<69>() * ::capnp::ELEMENTS, value);
 }
 
 inline float FrogPilotPlan::Reader::getLaneWidthLeft() const {
@@ -3198,16 +2979,16 @@ inline void FrogPilotPlan::Builder::setMinAcceleration(float value) {
 
 inline bool FrogPilotPlan::Reader::getRedLight() const {
   return _reader.getDataField<bool>(
-      ::capnp::bounded<69>() * ::capnp::ELEMENTS);
+      ::capnp::bounded<70>() * ::capnp::ELEMENTS);
 }
 
 inline bool FrogPilotPlan::Builder::getRedLight() {
   return _builder.getDataField<bool>(
-      ::capnp::bounded<69>() * ::capnp::ELEMENTS);
+      ::capnp::bounded<70>() * ::capnp::ELEMENTS);
 }
 inline void FrogPilotPlan::Builder::setRedLight(bool value) {
   _builder.setDataField<bool>(
-      ::capnp::bounded<69>() * ::capnp::ELEMENTS, value);
+      ::capnp::bounded<70>() * ::capnp::ELEMENTS, value);
 }
 
 inline float FrogPilotPlan::Reader::getRoadCurvature() const {
@@ -3372,16 +3153,16 @@ inline void FrogPilotPlan::Builder::setSpeedJerkStock(float value) {
 
 inline bool FrogPilotPlan::Reader::getSpeedLimitChanged() const {
   return _reader.getDataField<bool>(
-      ::capnp::bounded<70>() * ::capnp::ELEMENTS);
+      ::capnp::bounded<71>() * ::capnp::ELEMENTS);
 }
 
 inline bool FrogPilotPlan::Builder::getSpeedLimitChanged() {
   return _builder.getDataField<bool>(
-      ::capnp::bounded<70>() * ::capnp::ELEMENTS);
+      ::capnp::bounded<71>() * ::capnp::ELEMENTS);
 }
 inline void FrogPilotPlan::Builder::setSpeedLimitChanged(bool value) {
   _builder.setDataField<bool>(
-      ::capnp::bounded<70>() * ::capnp::ELEMENTS, value);
+      ::capnp::bounded<71>() * ::capnp::ELEMENTS, value);
 }
 
 inline float FrogPilotPlan::Reader::getTFollow() const {
@@ -3400,46 +3181,46 @@ inline void FrogPilotPlan::Builder::setTFollow(float value) {
 
 inline bool FrogPilotPlan::Reader::getThemeUpdated() const {
   return _reader.getDataField<bool>(
-      ::capnp::bounded<71>() * ::capnp::ELEMENTS);
+      ::capnp::bounded<72>() * ::capnp::ELEMENTS);
 }
 
 inline bool FrogPilotPlan::Builder::getThemeUpdated() {
   return _builder.getDataField<bool>(
-      ::capnp::bounded<71>() * ::capnp::ELEMENTS);
+      ::capnp::bounded<72>() * ::capnp::ELEMENTS);
 }
 inline void FrogPilotPlan::Builder::setThemeUpdated(bool value) {
-  _builder.setDataField<bool>(
-      ::capnp::bounded<71>() * ::capnp::ELEMENTS, value);
-}
-
-inline bool FrogPilotPlan::Reader::getTogglesUpdated() const {
-  return _reader.getDataField<bool>(
-      ::capnp::bounded<72>() * ::capnp::ELEMENTS);
-}
-
-inline bool FrogPilotPlan::Builder::getTogglesUpdated() {
-  return _builder.getDataField<bool>(
-      ::capnp::bounded<72>() * ::capnp::ELEMENTS);
-}
-inline void FrogPilotPlan::Builder::setTogglesUpdated(bool value) {
   _builder.setDataField<bool>(
       ::capnp::bounded<72>() * ::capnp::ELEMENTS, value);
 }
 
-inline bool FrogPilotPlan::Reader::getTrackingLead() const {
+inline bool FrogPilotPlan::Reader::getTogglesUpdated() const {
   return _reader.getDataField<bool>(
       ::capnp::bounded<73>() * ::capnp::ELEMENTS);
 }
 
-inline bool FrogPilotPlan::Builder::getTrackingLead() {
+inline bool FrogPilotPlan::Builder::getTogglesUpdated() {
   return _builder.getDataField<bool>(
       ::capnp::bounded<73>() * ::capnp::ELEMENTS);
 }
-inline void FrogPilotPlan::Builder::setTrackingLead(bool value) {
+inline void FrogPilotPlan::Builder::setTogglesUpdated(bool value) {
   _builder.setDataField<bool>(
       ::capnp::bounded<73>() * ::capnp::ELEMENTS, value);
 }
 
+inline bool FrogPilotPlan::Reader::getTrackingLead() const {
+  return _reader.getDataField<bool>(
+      ::capnp::bounded<74>() * ::capnp::ELEMENTS);
+}
+
+inline bool FrogPilotPlan::Builder::getTrackingLead() {
+  return _builder.getDataField<bool>(
+      ::capnp::bounded<74>() * ::capnp::ELEMENTS);
+}
+inline void FrogPilotPlan::Builder::setTrackingLead(bool value) {
+  _builder.setDataField<bool>(
+      ::capnp::bounded<74>() * ::capnp::ELEMENTS, value);
+}
+
 inline float FrogPilotPlan::Reader::getUnconfirmedSlcSpeedLimit() const {
   return _reader.getDataField<float>(
       ::capnp::bounded<23>() * ::capnp::ELEMENTS);

cereal/gen/cpp/log.capnp.c++

@@ -9336,17 +9336,17 @@ const ::capnp::_::RawSchema s_f28c5dc9e09375e3 = {
   0, 10, i_f28c5dc9e09375e3, nullptr, nullptr, { &s_f28c5dc9e09375e3, nullptr, nullptr, 0, 0, nullptr }, false
 };
 #endif  // !CAPNP_LITE
-static const ::capnp::_::AlignedData<191> b_e774a050cbf689a4 = {
+static const ::capnp::_::AlignedData<223> b_e774a050cbf689a4 = {
   {   0,   0,   0,   0,   5,   0,   6,   0,
     164, 137, 246, 203,  80, 160, 116, 231,
-     24,   0,   0,   0,   1,   0,   5,   0,
+     24,   0,   0,   0,   1,   0,   6,   0,
     241, 171,   1,  54, 197, 105, 255, 151,
       0,   0,   7,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
      21,   0,   0,   0,  90,   1,   0,   0,
      41,   0,   0,   0,   7,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-     37,   0,   0,   0, 111,   2,   0,   0,
+     37,   0,   0,   0, 223,   2,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
     108, 111, 103,  46,  99,  97, 112, 110,
@@ -9356,84 +9356,98 @@ static const ::capnp::_::AlignedData<191> b_e774a050cbf689a4 = {
     111, 114, 113, 117, 101,  83, 116,  97,
     116, 101,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   1,   0,   1,   0,
-     44,   0,   0,   0,   3,   0,   4,   0,
+     52,   0,   0,   0,   3,   0,   4,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   1,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-     37,   1,   0,   0,  58,   0,   0,   0,
+     93,   1,   0,   0,  58,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-     32,   1,   0,   0,   3,   0,   1,   0,
-     44,   1,   0,   0,   2,   0,   1,   0,
+     88,   1,   0,   0,   3,   0,   1,   0,
+    100,   1,   0,   0,   2,   0,   1,   0,
       1,   0,   0,   0,   1,   0,   0,   0,
       0,   0,   1,   0,   1,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-     41,   1,   0,   0,  50,   0,   0,   0,
+     97,   1,   0,   0,  50,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-     36,   1,   0,   0,   3,   0,   1,   0,
-     48,   1,   0,   0,   2,   0,   1,   0,
+     92,   1,   0,   0,   3,   0,   1,   0,
+    104,   1,   0,   0,   2,   0,   1,   0,
       3,   0,   0,   0,   2,   0,   0,   0,
       0,   0,   1,   0,   2,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
-     45,   1,   0,   0,  18,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     40,   1,   0,   0,   3,   0,   1,   0,
-     52,   1,   0,   0,   2,   0,   1,   0,
-      4,   0,   0,   0,   3,   0,   0,   0,
-      0,   0,   1,   0,   3,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     49,   1,   0,   0,  18,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     44,   1,   0,   0,   3,   0,   1,   0,
-     56,   1,   0,   0,   2,   0,   1,   0,
-      5,   0,   0,   0,   4,   0,   0,   0,
-      0,   0,   1,   0,   4,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     53,   1,   0,   0,  18,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     48,   1,   0,   0,   3,   0,   1,   0,
-     60,   1,   0,   0,   2,   0,   1,   0,
-      6,   0,   0,   0,   5,   0,   0,   0,
-      0,   0,   1,   0,   5,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     57,   1,   0,   0,  18,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     52,   1,   0,   0,   3,   0,   1,   0,
-     64,   1,   0,   0,   2,   0,   1,   0,
-      7,   0,   0,   0,   6,   0,   0,   0,
-      0,   0,   1,   0,   6,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     61,   1,   0,   0,  58,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     56,   1,   0,   0,   3,   0,   1,   0,
-     68,   1,   0,   0,   2,   0,   1,   0,
-      8,   0,   0,   0,   1,   0,   0,   0,
-      0,   0,   1,   0,   7,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     65,   1,   0,   0,  82,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     64,   1,   0,   0,   3,   0,   1,   0,
-     76,   1,   0,   0,   2,   0,   1,   0,
-      2,   0,   0,   0,   7,   0,   0,   0,
-      0,   0,   1,   0,   8,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     73,   1,   0,   0,  82,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     72,   1,   0,   0,   3,   0,   1,   0,
-     84,   1,   0,   0,   2,   0,   1,   0,
-      9,   0,   0,   0,   8,   0,   0,   0,
-      0,   0,   1,   0,   9,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     81,   1,   0,   0, 154,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     84,   1,   0,   0,   3,   0,   1,   0,
-     96,   1,   0,   0,   2,   0,   1,   0,
-     10,   0,   0,   0,   9,   0,   0,   0,
-      0,   0,   1,   0,  10,   0,   0,   0,
-      0,   0,   0,   0,   0,   0,   0,   0,
-     93,   1,   0,   0, 162,   0,   0,   0,
+    101,   1,   0,   0,  18,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
      96,   1,   0,   0,   3,   0,   1,   0,
     108,   1,   0,   0,   2,   0,   1,   0,
+      4,   0,   0,   0,   3,   0,   0,   0,
+      0,   0,   1,   0,   3,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    105,   1,   0,   0,  18,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    100,   1,   0,   0,   3,   0,   1,   0,
+    112,   1,   0,   0,   2,   0,   1,   0,
+      5,   0,   0,   0,   4,   0,   0,   0,
+      0,   0,   1,   0,   4,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    109,   1,   0,   0,  18,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    104,   1,   0,   0,   3,   0,   1,   0,
+    116,   1,   0,   0,   2,   0,   1,   0,
+      6,   0,   0,   0,   5,   0,   0,   0,
+      0,   0,   1,   0,   5,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    113,   1,   0,   0,  18,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    108,   1,   0,   0,   3,   0,   1,   0,
+    120,   1,   0,   0,   2,   0,   1,   0,
+      7,   0,   0,   0,   6,   0,   0,   0,
+      0,   0,   1,   0,   6,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    117,   1,   0,   0,  58,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    112,   1,   0,   0,   3,   0,   1,   0,
+    124,   1,   0,   0,   2,   0,   1,   0,
+      8,   0,   0,   0,   1,   0,   0,   0,
+      0,   0,   1,   0,   7,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    121,   1,   0,   0,  82,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    120,   1,   0,   0,   3,   0,   1,   0,
+    132,   1,   0,   0,   2,   0,   1,   0,
+      2,   0,   0,   0,   7,   0,   0,   0,
+      0,   0,   1,   0,   8,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    129,   1,   0,   0,  82,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    128,   1,   0,   0,   3,   0,   1,   0,
+    140,   1,   0,   0,   2,   0,   1,   0,
+      9,   0,   0,   0,   8,   0,   0,   0,
+      0,   0,   1,   0,   9,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    137,   1,   0,   0, 154,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    140,   1,   0,   0,   3,   0,   1,   0,
+    152,   1,   0,   0,   2,   0,   1,   0,
+     10,   0,   0,   0,   9,   0,   0,   0,
+      0,   0,   1,   0,  10,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    149,   1,   0,   0, 162,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    152,   1,   0,   0,   3,   0,   1,   0,
+    164,   1,   0,   0,   2,   0,   1,   0,
+     11,   0,   0,   0,  10,   0,   0,   0,
+      0,   0,   1,   0,  11,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    161,   1,   0,   0, 154,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    164,   1,   0,   0,   3,   0,   1,   0,
+    176,   1,   0,   0,   2,   0,   1,   0,
+     12,   0,   0,   0,  11,   0,   0,   0,
+      0,   0,   1,   0,  12,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    173,   1,   0,   0,  66,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    168,   1,   0,   0,   3,   0,   1,   0,
+    180,   1,   0,   0,   2,   0,   1,   0,
      97,  99, 116, 105, 118, 101,   0,   0,
       1,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
@@ -9526,16 +9540,34 @@ static const ::capnp::_::AlignedData<191> b_e774a050cbf689a4 = {
       0,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
      10,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    100, 101, 115, 105, 114, 101, 100,  76,
+     97, 116, 101, 114,  97, 108,  74, 101,
+    114, 107,   0,   0,   0,   0,   0,   0,
+     10,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+     10,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+    118, 101, 114, 115, 105, 111, 110,   0,
+      4,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+      0,   0,   0,   0,   0,   0,   0,   0,
+      4,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0,
       0,   0,   0,   0,   0,   0,   0,   0, }
 };
 ::capnp::word const* const bp_e774a050cbf689a4 = b_e774a050cbf689a4.words;
 #if !CAPNP_LITE
-static const uint16_t m_e774a050cbf689a4[] = {0, 9, 4, 10, 1, 8, 5, 3, 6, 2, 7};
-static const uint16_t i_e774a050cbf689a4[] = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10};
+static const uint16_t m_e774a050cbf689a4[] = {0, 9, 4, 10, 11, 1, 8, 5, 3, 6, 2, 7, 12};
+static const uint16_t i_e774a050cbf689a4[] = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12};
 const ::capnp::_::RawSchema s_e774a050cbf689a4 = {
-  0xe774a050cbf689a4, b_e774a050cbf689a4.words, 191, nullptr, m_e774a050cbf689a4,
-  0, 11, i_e774a050cbf689a4, nullptr, nullptr, { &s_e774a050cbf689a4, nullptr, nullptr, 0, 0, nullptr }, false
+  0xe774a050cbf689a4, b_e774a050cbf689a4.words, 223, nullptr, m_e774a050cbf689a4,
+  0, 13, i_e774a050cbf689a4, nullptr, nullptr, { &s_e774a050cbf689a4, nullptr, nullptr, 0, 0, nullptr }, false
 };
 #endif  // !CAPNP_LITE
 static const ::capnp::_::AlignedData<130> b_9024e2d790c82ade = {

cereal/gen/cpp/log.capnp.h

@@ -1076,7 +1076,7 @@ struct ControlsState::LateralTorqueState {
   class Pipeline;
 
   struct _capnpPrivate {
-    CAPNP_DECLARE_STRUCT_HEADER(e774a050cbf689a4, 5, 0)
+    CAPNP_DECLARE_STRUCT_HEADER(e774a050cbf689a4, 6, 0)
     #if !CAPNP_LITE
     static constexpr ::capnp::_::RawBrandedSchema const* brand() { return &schema->defaultBrand; }
     #endif  // !CAPNP_LITE
@@ -7531,6 +7531,10 @@ public:
 
   inline float getDesiredLateralAccel() const;
 
+  inline float getDesiredLateralJerk() const;
+
+  inline  ::int32_t getVersion() const;
+
 private:
   ::capnp::_::StructReader _reader;
   template <typename, ::capnp::Kind>
@@ -7592,6 +7596,12 @@ public:
   inline float getDesiredLateralAccel();
   inline void setDesiredLateralAccel(float value);
 
+  inline float getDesiredLateralJerk();
+  inline void setDesiredLateralJerk(float value);
+
+  inline  ::int32_t getVersion();
+  inline void setVersion( ::int32_t value);
+
 private:
   ::capnp::_::StructBuilder _builder;
   template <typename, ::capnp::Kind>
@@ -30064,6 +30074,34 @@ inline void ControlsState::LateralTorqueState::Builder::setDesiredLateralAccel(f
       ::capnp::bounded<9>() * ::capnp::ELEMENTS, value);
 }
 
+inline float ControlsState::LateralTorqueState::Reader::getDesiredLateralJerk() const {
+  return _reader.getDataField<float>(
+      ::capnp::bounded<10>() * ::capnp::ELEMENTS);
+}
+
+inline float ControlsState::LateralTorqueState::Builder::getDesiredLateralJerk() {
+  return _builder.getDataField<float>(
+      ::capnp::bounded<10>() * ::capnp::ELEMENTS);
+}
+inline void ControlsState::LateralTorqueState::Builder::setDesiredLateralJerk(float value) {
+  _builder.setDataField<float>(
+      ::capnp::bounded<10>() * ::capnp::ELEMENTS, value);
+}
+
+inline  ::int32_t ControlsState::LateralTorqueState::Reader::getVersion() const {
+  return _reader.getDataField< ::int32_t>(
+      ::capnp::bounded<11>() * ::capnp::ELEMENTS);
+}
+
+inline  ::int32_t ControlsState::LateralTorqueState::Builder::getVersion() {
+  return _builder.getDataField< ::int32_t>(
+      ::capnp::bounded<11>() * ::capnp::ELEMENTS);
+}
+inline void ControlsState::LateralTorqueState::Builder::setVersion( ::int32_t value) {
+  _builder.setDataField< ::int32_t>(
+      ::capnp::bounded<11>() * ::capnp::ELEMENTS, value);
+}
+
 inline bool ControlsState::LateralLQRState::Reader::getActive() const {
   return _reader.getDataField<bool>(
       ::capnp::bounded<0>() * ::capnp::ELEMENTS);

cereal/log.capnp

@@ -795,6 +795,8 @@ struct ControlsState @0x97ff69c53601abf1 {
     saturated @7 :Bool;
     actualLateralAccel @9 :Float32;
     desiredLateralAccel @10 :Float32;
+    desiredLateralJerk @11 :Float32;
+    version @12 :Int32;
    }
 
   struct LateralLQRState {

common/params.cc

@@ -224,6 +224,7 @@ std::unordered_map<std::string, uint32_t> keys = {
     {"AdvancedLateralTune", PERSISTENT},
     {"AdvancedLongitudinalTune", PERSISTENT},
     {"AggressiveFollow", PERSISTENT},
+    {"AggressiveFollowHigh", PERSISTENT},
     {"AggressiveJerkAcceleration", PERSISTENT},
     {"AggressiveJerkDanger", PERSISTENT},
     {"AggressiveJerkDeceleration", PERSISTENT},
@@ -240,6 +241,7 @@ std::unordered_map<std::string, uint32_t> keys = {
     {"AutomaticallyDownloadModels", PERSISTENT},
     {"AutomaticUpdates", PERSISTENT},
     {"AvailableModelNames", PERSISTENT},
+    {"AvailableModelSeries", PERSISTENT},
     {"AvailableModels", PERSISTENT},
     {"BigMap", PERSISTENT},
     {"BlacklistedModels", PERSISTENT},
@@ -320,6 +322,7 @@ std::unordered_map<std::string, uint32_t> keys = {
     {"DynamicPedalsOnUI", PERSISTENT},
     {"EngageVolume", PERSISTENT},
     {"ExperimentalGMTune", PERSISTENT},
+    {"EVTuning", PERSISTENT},
     {"Fahrenheit", PERSISTENT},
     {"FavoriteDestinations", PERSISTENT | DONT_LOG},
     {"FlashPanda", CLEAR_ON_MANAGER_START},
@@ -345,6 +348,7 @@ std::unordered_map<std::string, uint32_t> keys = {
     {"FrogsGoMoosTweak", PERSISTENT},
     {"FullMap", PERSISTENT},
     {"GasRegenCmd", PERSISTENT},
+    {"GMPedalLongitudinal", PERSISTENT},
     {"GoatScream", PERSISTENT},
     {"GreenLightAlert", PERSISTENT},
     {"HideAlerts", PERSISTENT},
@@ -398,12 +402,17 @@ std::unordered_map<std::string, uint32_t> keys = {
     {"MinimumBackupSize", PERSISTENT},
     {"MinimumLaneChangeSpeed", PERSISTENT},
     {"Model", PERSISTENT},
+    {"ModelVersion", PERSISTENT},
     {"ModelDownloadProgress", CLEAR_ON_MANAGER_START},
     {"ModelDrivesAndScores", PERSISTENT},
     {"ModelRandomizer", PERSISTENT},
     {"ModelToDownload", CLEAR_ON_MANAGER_START},
     {"ModelUI", PERSISTENT},
     {"ModelVersions", PERSISTENT},
+    {"ModelReleasedDates", PERSISTENT},
+    {"CommunityFavorites", PERSISTENT},
+    {"UserFavorites", PERSISTENT},
+    {"SortModelsByDate", PERSISTENT},
     {"NavigationUI", PERSISTENT},
     {"NextMapSpeedLimit", CLEAR_ON_MANAGER_START},
     {"NewLongAPI", PERSISTENT},
@@ -449,6 +458,7 @@ std::unordered_map<std::string, uint32_t> keys = {
     {"RandomThemes", PERSISTENT},
     {"RefuseVolume", PERSISTENT},
     {"RelaxedFollow", PERSISTENT},
+    {"RelaxedFollowHigh", PERSISTENT},
     {"RelaxedJerkAcceleration", PERSISTENT},
     {"RelaxedJerkDanger", PERSISTENT},
     {"RelaxedJerkDeceleration", PERSISTENT},
@@ -508,6 +518,7 @@ std::unordered_map<std::string, uint32_t> keys = {
     {"SpeedLimitsFiltered", PERSISTENT | DONT_LOG},
     {"SpeedLimitSources", PERSISTENT},
     {"StandardFollow", PERSISTENT},
+    {"StandardFollowHigh", PERSISTENT},
     {"StandardJerkAcceleration", PERSISTENT},
     {"StandardJerkDanger", PERSISTENT},
     {"StandardJerkDeceleration", PERSISTENT},
@@ -524,6 +535,8 @@ std::unordered_map<std::string, uint32_t> keys = {
     {"SteerDelayStock", PERSISTENT},
     {"SteerFriction", PERSISTENT},
     {"SteerFrictionStock", PERSISTENT},
+    {"SteerOffset", PERSISTENT},
+    {"SteerOffsetStock", PERSISTENT},
     {"SteerLatAccel", PERSISTENT},
     {"SteerLatAccelStock", PERSISTENT},
     {"SteerKP", PERSISTENT},
@@ -538,6 +551,7 @@ std::unordered_map<std::string, uint32_t> keys = {
     {"StoppedTimer", PERSISTENT},
     {"TacoTune", PERSISTENT},
     {"TacoTuneHacks", PERSISTENT},
+    {"TrailerLoad", PERSISTENT},
     {"TestAlert", CLEAR_ON_MANAGER_START},
     {"TetheringEnabled", PERSISTENT},
     {"ThemeDownloadProgress", CLEAR_ON_MANAGER_START},
@@ -576,6 +590,8 @@ std::unordered_map<std::string, uint32_t> keys = {
     {"WarningSoftVolume", PERSISTENT},
     {"WheelIcon", PERSISTENT},
     {"WheelSpeed", PERSISTENT},
+    {"StopDistance", PERSISTENT},
+    {"RecoveryPower", PERSISTENT},
     {"WheelToDownload", CLEAR_ON_MANAGER_START},
 };
 

common/realtime.py

@@ -6,6 +6,7 @@ from collections import deque
 
 from setproctitle import getproctitle
 
+from openpilot.common.swaglog import cloudlog
 from openpilot.system.hardware import PC
 
 
@@ -34,7 +35,17 @@ def set_realtime_priority(level: int) -> None:
 
 def set_core_affinity(cores: list[int]) -> None:
   if not PC:
-    os.sched_setaffinity(0, cores)
+    for attempt in range(3):  # Retry up to 3 times
+      try:
+        os.sched_setaffinity(0, cores)
+        return
+      except OSError as e:
+        if e.errno == 22:  # EINVAL
+          time.sleep(0.1)  # Brief delay before retry
+        else:
+          raise  # Re-raise other errors
+    # If all retries fail, log and continue without affinity
+    cloudlog.error(f"Failed to set core affinity after retries: {cores}")
 
 
 def config_realtime_process(cores: int | list[int], priority: int) -> None:

frogpilot/assets/download_functions.py

@@ -6,14 +6,13 @@ from datetime import datetime
 from pathlib import Path
 
 from openpilot.frogpilot.common.frogpilot_utilities import delete_file, is_url_pingable
-from openpilot.frogpilot.common.frogpilot_variables import RESOURCES_REPO, params_memory
 
-GITHUB_URL = f"https://raw.githubusercontent.com/{RESOURCES_REPO}"
-GITLAB_URL = f"https://gitlab.com/{RESOURCES_REPO}/-/raw"
+GITHUB_URL = "https://raw.githubusercontent.com/firestar5683/StarPilot-Resources"
+GITLAB_URL = "https://gitlab.com/firestar5683/FrogPilot-Resources/-/raw"
 
-def check_github_rate_limit(session):
+def check_github_rate_limit():
   try:
-    response = session.get("https://api.github.com/rate_limit", timeout=10)
+    response = requests.get("https://api.github.com/rate_limit")
     response.raise_for_status()
     rate_limit_info = response.json()
 
@@ -26,91 +25,87 @@ def check_github_rate_limit(session):
     print("GitHub rate limit reached")
     print(f"GitHub Rate Limit Resets At (UTC): {reset_time}")
     return False
-  except requests.exceptions.RequestException as exception:
-    print(f"Error checking GitHub rate limit: {exception}")
+  except requests.exceptions.RequestException as error:
+    print(f"Error checking GitHub rate limit: {error}")
     return False
 
-def download_file(cancel_param, destination, progress_param, url, download_param, session, offset_bytes=0, total_bytes=0):
+def download_file(cancel_param, destination, progress_param, url, download_param, params_memory):
   try:
     destination.parent.mkdir(parents=True, exist_ok=True)
 
-    total_size = get_remote_file_size(url, session)
+    total_size = get_remote_file_size(url)
     if total_size == 0:
       if not url.endswith(".gif"):
-        handle_error(None, "Download invalid...", "Download invalid...", download_param, progress_param)
+        handle_error(None, "Download invalid...", "Download invalid...", download_param, progress_param, params_memory)
       return
 
-    with session.get(url, stream=True, timeout=10) as response:
+    with requests.get(url, stream=True, timeout=10) as response:
       response.raise_for_status()
 
-      with tempfile.NamedTemporaryFile(delete=False, dir=destination.parent) as temp_file:
+      with tempfile.NamedTemporaryFile(dir=destination.parent, delete=False) as temp_file:
         temp_file_path = Path(temp_file.name)
 
         downloaded_size = 0
         for chunk in response.iter_content(chunk_size=16384):
           if params_memory.get_bool(cancel_param):
             temp_file_path.unlink(missing_ok=True)
-            handle_error(None, "Download cancelled...", "Download cancelled...", download_param, progress_param)
+            handle_error(None, "Download cancelled...", "Download cancelled...", download_param, progress_param, params_memory)
             return
 
           if chunk:
             temp_file.write(chunk)
             downloaded_size += len(chunk)
 
-            if total_bytes:
-              overall_progress = (offset_bytes + downloaded_size) / total_bytes * 100
-            else:
-              overall_progress = downloaded_size / total_size * 100
-
-            if overall_progress != 100:
-              params_memory.put(progress_param, f"{overall_progress:.0f}%")
+            progress = (downloaded_size / total_size) * 100
+            if progress != 100:
+              params_memory.put(progress_param, f"{progress:.0f}%")
             else:
               params_memory.put(progress_param, "Verifying authenticity...")
 
         temp_file_path.rename(destination)
 
-  except Exception as exception:
-    handle_request_error(exception, destination, download_param, progress_param)
+  except Exception as error:
+    handle_request_error(error, destination, download_param, progress_param, params_memory)
 
-def get_remote_file_size(url, session):
+def get_remote_file_size(url):
   try:
-    response = session.head(url, headers={"Accept-Encoding": "identity"}, timeout=10)
+    response = requests.head(url, headers={"Accept-Encoding": "identity"}, timeout=10)
     response.raise_for_status()
     return int(response.headers.get("Content-Length", 0))
-  except Exception as exception:
-    handle_request_error(exception, None, None, None)
+  except Exception as error:
+    handle_request_error(error, None, None, None, None)
     return 0
 
-def get_repository_url(session):
+def get_repository_url():
   if is_url_pingable("https://github.com"):
-    if check_github_rate_limit(session):
+    if check_github_rate_limit():
       return GITHUB_URL
   if is_url_pingable("https://gitlab.com"):
     return GITLAB_URL
   return None
 
-def handle_error(destination, error_message, error, download_param, progress_param):
+def handle_error(destination, error_message, error, download_param, progress_param, params_memory):
   if destination:
     delete_file(destination)
 
-  if progress_param and "404" not in error_message:
+  if params_memory and progress_param and "404" not in error_message:
     print(f"Error occurred: {error}")
     params_memory.put(progress_param, error_message)
     params_memory.remove(download_param)
 
-def handle_request_error(error, destination, download_param, progress_param):
+def handle_request_error(error, destination, download_param, progress_param, params_memory):
   error_map = {
-    requests.exceptions.ConnectionError: "Connection dropped",
-    requests.exceptions.HTTPError: lambda error: f"Server error ({error.response.status_code})" if error and getattr(error, "response", None) else "Server error",
-    requests.exceptions.RequestException: "Network request error. Check connection",
-    requests.exceptions.Timeout: "Download timed out",
+    requests.ConnectionError: "Connection dropped",
+    requests.HTTPError: lambda error: f"Server error ({error.response.status_code})" if error.response else "Server error",
+    requests.RequestException: "Network request error. Check connection",
+    requests.Timeout: "Download timed out"
   }
 
   error_message = error_map.get(type(error), "Unexpected error")
-  handle_error(destination, f"Failed: {error_message}", error, download_param, progress_param)
+  handle_error(destination, f"Failed: {error_message}", error, download_param, progress_param, params_memory)
 
-def verify_download(file_path, url, session):
-  remote_file_size = get_remote_file_size(url, session)
+def verify_download(file_path, url):
+  remote_file_size = get_remote_file_size(url)
 
   if remote_file_size == 0:
     print(f"Error fetching remote size for {file_path}")

frogpilot/assets/model_manager.py

@@ -5,59 +5,240 @@ import requests
 import shutil
 import time
 import urllib.parse
+import urllib.request
 
 from pathlib import Path
-from urllib.parse import quote_plus
 
-from openpilot.common.basedir import BASEDIR
-from openpilot.frogpilot.assets.download_functions import GITLAB_URL, download_file, get_remote_file_size, get_repository_url, handle_error, handle_request_error, verify_download
-from openpilot.frogpilot.common.frogpilot_utilities import delete_file, extract_tar, load_json_file, update_json_file
-from openpilot.frogpilot.common.frogpilot_variables import DEFAULT_MODEL, MODELS_PATH, RESOURCES_REPO, TINYGRAD_FILES, params, params_default, params_memory, update_frogpilot_toggles
+from openpilot.frogpilot.assets.download_functions import GITLAB_URL, download_file, get_repository_url, handle_error, handle_request_error, verify_download
+from openpilot.frogpilot.common.frogpilot_utilities import delete_file
+from openpilot.frogpilot.common.frogpilot_variables import DEFAULT_MODEL, MODELS_PATH, params, params_default, params_memory
 
-VERSION = "v16"
-VERSION_PATH = MODELS_PATH / "model_version"
+VERSION = "v20"
 
 CANCEL_DOWNLOAD_PARAM = "CancelModelDownload"
 DOWNLOAD_PROGRESS_PARAM = "ModelDownloadProgress"
 MODEL_DOWNLOAD_PARAM = "ModelToDownload"
 MODEL_DOWNLOAD_ALL_PARAM = "DownloadAllModels"
-UPDATE_TINYGRAD_PARAM = "UpdateTinygrad"
-
-DEFAULT_TINYGRAD_SIZE = 87746736
-TAR_FILE_NAME = f"Tinygrad_{VERSION}.tar.gz"
-
-TINYGRAD_MODELD_PATH = Path(BASEDIR) / "frogpilot/tinygrad_modeld"
-TINYGRAD_REPO_PATH = Path(BASEDIR) / "tinygrad_repo"
 
 class ModelManager:
-  def __init__(self, boot_run=False):
+  def __init__(self):
+    self.available_models = (params.get("AvailableModels", encoding="utf-8") or "").split(",")
+    self.model_versions = (params.get("ModelVersions", encoding="utf-8") or "").split(",")
+    self.model_series = (params.get("AvailableModelSeries", encoding="utf-8") or "").split(",")
+
+
     self.downloading_model = False
 
-    self.available_models = (params.get("AvailableModels", encoding="utf-8") or "").split(",")
-    self.available_model_names = (params.get("AvailableModelNames", encoding="utf-8") or "").split(",")
-    self.model_versions = (params.get("ModelVersions", encoding="utf-8") or "").split(",")
+  @staticmethod
+  def fetch_models(url):
+    try:
+      with urllib.request.urlopen(url, timeout=10) as response:
+        return json.loads(response.read().decode("utf-8"))["models"]
+    except Exception as error:
+      handle_request_error(error, None, None, None, None)
+      return []
 
-    self.model_sizes_path = MODELS_PATH / "model_sizes.json"
-    self.tinygrad_sizes_path = MODELS_PATH / "tinygrad_sizes.json"
+  @staticmethod
+  def fetch_all_model_sizes(repo_url):
+    project_path = "firestar5683/StarPilot-Resources"
+    branch = "Models"
 
-    self.model_sizes = load_json_file(self.model_sizes_path)
-    self.tinygrad_sizes = load_json_file(self.tinygrad_sizes_path)
+    if "github" in repo_url:
+      api_url = f"https://api.github.com/repos/{project_path}/contents?ref={branch}"
+    elif "gitlab" in repo_url:
+      api_url = f"https://gitlab.com/api/v4/projects/{urllib.parse.quote_plus(project_path)}/repository/tree?ref={branch}"
+    else:
+      return {}
 
-    self.session = requests.Session()
-    self.session.headers.update({"Accept-Language": "en"})
-    self.session.headers.update({"User-Agent": "frogpilot-model-downloader/1.0 (https://github.com/FrogAi/FrogPilot)"})
+    try:
+      response = requests.get(api_url)
+      response.raise_for_status()
+      model_files = [file for file in response.json() if "." in file["name"]]
 
-    if boot_run:
-      self.copy_default_model()
-      self.validate_models()
+      if "gitlab" in repo_url:
+        model_sizes = {}
+        for file in model_files:
+          file_path = file["path"]
+          metadata_url = f"https://gitlab.com/api/v4/projects/{urllib.parse.quote_plus(project_path)}/repository/files/{urllib.parse.quote_plus(file_path)}/raw?ref={branch}"
+          metadata_response = requests.head(metadata_url)
+          metadata_response.raise_for_status()
+          model_sizes[file["name"].rsplit(".", 1)[0]] = int(metadata_response.headers.get("content-length", 0))
+        return model_sizes
+      else:
+        return {file["name"].rsplit(".", 1)[0]: file["size"] for file in model_files if "size" in file}
+
+    except Exception as error:
+      handle_request_error(f"Failed to fetch model sizes from {'GitHub' if 'github' in repo_url else 'GitLab'}: {error}", None, None, None, None)
+      return {}
+
+  def handle_verification_failure(self, model, model_path, file_extension):
+    print(f"Verification failed for model {model}. Retrying from GitLab...")
+    model_url = f"{GITLAB_URL}/Models/{model}.{file_extension}"
+    download_file(CANCEL_DOWNLOAD_PARAM, model_path, DOWNLOAD_PROGRESS_PARAM, model_url, MODEL_DOWNLOAD_PARAM, params_memory)
+
+    if params_memory.get_bool(CANCEL_DOWNLOAD_PARAM):
+      handle_error(None, "Download cancelled...", "Download cancelled...", MODEL_DOWNLOAD_PARAM, DOWNLOAD_PROGRESS_PARAM, params_memory)
+      self.downloading_model = False
+      return
+
+    if verify_download(model_path, model_url):
+      print(f"Model {model} downloaded and verified successfully!")
+      params_memory.put(DOWNLOAD_PROGRESS_PARAM, "Downloaded!")
+      params_memory.remove(MODEL_DOWNLOAD_PARAM)
+      self.downloading_model = False
+    else:
+      handle_error(model_path, "Verification failed...", "GitLab verification failed", MODEL_DOWNLOAD_PARAM, DOWNLOAD_PROGRESS_PARAM, params_memory)
+      self.downloading_model = False
+
+  def download_model(self, model_to_download):
+    self.downloading_model = True
+
+    repo_url = get_repository_url()
+    if not repo_url:
+      handle_error(None, "GitHub and GitLab are offline...", "Repository unavailable", MODEL_DOWNLOAD_PARAM, DOWNLOAD_PROGRESS_PARAM, params_memory)
+      self.downloading_model = False
+      return
+
+    try:
+      model_index = self.available_models.index(model_to_download)
+      model_version = self.model_versions[model_index]
+    except Exception:
+      handle_error(None, f"Unknown model version for {model_to_download}! Download aborted.", "Model download failed", MODEL_DOWNLOAD_PARAM, DOWNLOAD_PROGRESS_PARAM, params_memory)
+      self.downloading_model = False
+      return
+
+    if model_version in ("v8", "v9", "v10", "v11", "v12"):
+      # Download all PKL and metadata files for multi-file tinygrad models (v8 and v9)
+      filenames = [
+          f"{model_to_download}_driving_policy_tinygrad.pkl",
+          f"{model_to_download}_driving_vision_tinygrad.pkl",
+          f"{model_to_download}_driving_policy_metadata.pkl",
+          f"{model_to_download}_driving_vision_metadata.pkl",
+      ]
+      if model_version == "v12":
+        filenames += [
+          f"{model_to_download}_driving_off_policy_tinygrad.pkl",
+          f"{model_to_download}_driving_off_policy_metadata.pkl",
+        ]
+      for filename in filenames:
+        model_path = MODELS_PATH / filename
+        model_url = f"{repo_url}/Models/{filename}"
+        print(f"Downloading model file: {filename}")
+        download_file(CANCEL_DOWNLOAD_PARAM, model_path, DOWNLOAD_PROGRESS_PARAM, model_url, MODEL_DOWNLOAD_PARAM, params_memory)
+
+        if params_memory.get_bool(CANCEL_DOWNLOAD_PARAM):
+          handle_error(None, "Download cancelled...", "Download cancelled...", MODEL_DOWNLOAD_PARAM, DOWNLOAD_PROGRESS_PARAM, params_memory)
+          self.downloading_model = False
+          return
+
+        if verify_download(model_path, model_url):
+          print(f"File {filename} downloaded and verified successfully!")
+          params_memory.put(DOWNLOAD_PROGRESS_PARAM, f"Downloaded {filename}!")
+        else:
+          self.handle_verification_failure(filename[:-4], model_path, "pkl")
+          self.downloading_model = False
+          return
+      # After all files are downloaded and verified
+      params_memory.put(DOWNLOAD_PROGRESS_PARAM, "Downloaded!")
+      params_memory.remove(MODEL_DOWNLOAD_PARAM)
+
+    elif model_version == "v7":
+      # Download both PKL and metadata for OG tinygrad models
+      v7_filenames = [
+        f"{model_to_download}.pkl",
+        f"{model_to_download}_metadata.pkl"
+      ]
+      for filename in v7_filenames:
+        model_path = MODELS_PATH / filename
+        model_url = f"{repo_url}/Models/{filename}"
+        print(f"Downloading v7 model file: {filename}")
+        download_file(CANCEL_DOWNLOAD_PARAM, model_path, DOWNLOAD_PROGRESS_PARAM, model_url, MODEL_DOWNLOAD_PARAM, params_memory)
+
+        if params_memory.get_bool(CANCEL_DOWNLOAD_PARAM):
+          handle_error(None, "Download cancelled...", "Download cancelled...", MODEL_DOWNLOAD_PARAM, DOWNLOAD_PROGRESS_PARAM, params_memory)
+          self.downloading_model = False
+          return
+
+        if verify_download(model_path, model_url):
+          print(f"File {filename} downloaded and verified successfully!")
+          params_memory.put(DOWNLOAD_PROGRESS_PARAM, f"Downloaded {filename}!")
+        else:
+          self.handle_verification_failure(filename.rsplit('.',1)[0], model_path, "pkl")
+          self.downloading_model = False
+          return
+
+      # Once both files are fetched
+      params_memory.put(DOWNLOAD_PROGRESS_PARAM, "Downloaded!")
+      params_memory.remove(MODEL_DOWNLOAD_PARAM)
+
+    else:
+      # Classic model: download only the .thneed file
+      file_extension = "thneed"
+      model_path = MODELS_PATH / f"{model_to_download}.{file_extension}"
+      model_url = f"{repo_url}/Models/{model_to_download}.{file_extension}"
+      print(f"Downloading classic model: {model_to_download}")
+      download_file(CANCEL_DOWNLOAD_PARAM, model_path, DOWNLOAD_PROGRESS_PARAM, model_url, MODEL_DOWNLOAD_PARAM, params_memory)
+
+      if params_memory.get_bool(CANCEL_DOWNLOAD_PARAM):
+        handle_error(None, "Download cancelled...", "Download cancelled...", MODEL_DOWNLOAD_PARAM, DOWNLOAD_PROGRESS_PARAM, params_memory)
+        self.downloading_model = False
+        return
+
+      if verify_download(model_path, model_url):
+        print(f"Model {model_to_download} downloaded and verified successfully!")
+        params_memory.put(DOWNLOAD_PROGRESS_PARAM, "Downloaded!")
+        params_memory.remove(MODEL_DOWNLOAD_PARAM)
+      else:
+        self.handle_verification_failure(model_to_download, model_path, file_extension)
+        self.downloading_model = False
+        return
+
+    self.downloading_model = False
+
+  @staticmethod
+  def copy_default_model():
+    default_model_path = MODELS_PATH / f"{DEFAULT_MODEL}.thneed"
+    source_path = Path(__file__).parents[2] / "selfdrive/modeld/models/supercombo.thneed"
+    if source_path.is_file() and not default_model_path.is_file():
+      shutil.copyfile(source_path, default_model_path)
+      print(f"Copied the default model from {source_path} to {default_model_path}")
 
   def check_models(self, boot_run, repo_url):
-    downloaded_models = [
-      model for model in MODELS_PATH.iterdir()
-      if (MODELS_PATH / f"{model}.thneed").is_file() or all((MODELS_PATH / f"{model}_{filename}").is_file() for filename, _ in TINYGRAD_FILES)
-    ]
-    for model_file in downloaded_models:
-      if not any(model in model_file.name for model in set(self.available_models)):
+    available_models = set(self.available_models) - {DEFAULT_MODEL}
+    downloaded_models = set()
+    for model in available_models:
+      try:
+        model_index = self.available_models.index(model)
+        model_version = self.model_versions[model_index]
+      except Exception:
+        model_version = None
+
+      if model_version in ("v8", "v9", "v10", "v11", "v12"):
+        v8_v9_files = [
+          f"{model}_driving_policy_tinygrad.pkl",
+          f"{model}_driving_vision_tinygrad.pkl",
+          f"{model}_driving_policy_metadata.pkl",
+          f"{model}_driving_vision_metadata.pkl",
+        ]
+        if model_version == "v12":
+          v8_v9_files += [
+            f"{model}_driving_off_policy_tinygrad.pkl",
+            f"{model}_driving_off_policy_metadata.pkl",
+          ]
+        if all((MODELS_PATH / f).is_file() for f in v8_v9_files):
+          downloaded_models.add(model)
+      elif model_version == "v7":
+        filename = f"{model}.pkl"
+        if (MODELS_PATH / filename).is_file():
+          downloaded_models.add(model)
+      else:
+        filename = f"{model}.thneed"
+        if (MODELS_PATH / filename).is_file():
+          downloaded_models.add(model)
+
+    outdated_models = downloaded_models - available_models
+    for model in outdated_models:
+      for model_file in MODELS_PATH.glob(f"{model}*"):
         print(f"Removing outdated model: {model_file}")
         delete_file(model_file)
 
@@ -65,466 +246,185 @@ class ModelManager:
       if tmp_file.is_file():
         delete_file(tmp_file)
 
-    if params.get("Model", encoding="utf-8").removesuffix("_default") not in self.available_models:
+    if params.get("Model", encoding="utf-8") not in self.available_models:
       params.put("Model", params_default.get("Model", encoding="utf-8"))
 
-    if not (not boot_run and params.get_bool("AutomaticallyDownloadModels")):
+    automatically_download_models = params.get_bool("AutomaticallyDownloadModels")
+    if not automatically_download_models:
       return
 
     model_sizes = self.fetch_all_model_sizes(repo_url)
     if not model_sizes:
-      print("No model size data available. Skipping model checks...")
-      return
+      print("No model size data available. Continuing downloads based on file existence")
+      # do not return; proceed to download missing files
 
-    need_to_update_models = False
-    for model in self.available_models:
-      if self.is_tinygrad_model(model):
-        model_file = MODELS_PATH / f"{model}.thneed"
-        if not model_file.is_file():
-          need_to_update_models = True
-          continue
+    needs_download = False
 
-        expected_size = model_sizes.get(model_file.name)
-        local_size = self.model_sizes.get(model_file.name)
+    # Enhanced model file validation per model version
+    for model in available_models:
+      model_version = None
+      try:
+        model_index = self.available_models.index(model)
+        model_version = self.model_versions[model_index]
+      except Exception:
+        model_version = None
 
-        if expected_size > 0 and local_size != expected_size:
-          print(f"Model {model} is outdated. Deleting {model_file}...")
-          delete_file(model_file)
-          need_to_update_models = True
-      else:
-        model_missing = False
-        model_outdated = False
-
-        for filename, _ in TINYGRAD_FILES:
-          expected_file = MODELS_PATH / f"{model}_{filename}"
-          if not expected_file.is_file():
-            model_missing = True
-            need_to_update_models = True
+      if model_version in ("v8", "v9", "v10", "v11", "v12"):
+        v8_v9_files = [
+          f"{model}_driving_policy_tinygrad.pkl",
+          f"{model}_driving_vision_tinygrad.pkl",
+          f"{model}_driving_policy_metadata.pkl",
+          f"{model}_driving_vision_metadata.pkl",
+        ]
+        if model_version == "v12":
+          v8_v9_files += [
+            f"{model}_driving_off_policy_tinygrad.pkl",
+            f"{model}_driving_off_policy_metadata.pkl",
+          ]
+        for filename in v8_v9_files:
+          path = MODELS_PATH / filename
+          expected_size = model_sizes.get(filename.rsplit(".", 1)[0])
+          if not path.is_file() or expected_size is None or path.stat().st_size != expected_size:
+            needs_download = True
             break
-
-        for filename, _ in TINYGRAD_FILES:
-          model_file = f"{model}_{filename}"
-
-          expected_size = model_sizes.get(model_file)
-          local_size = self.model_sizes.get(model_file)
-
-          if expected_size > 0 and local_size != expected_size:
-            model_outdated = True
-            need_to_update_models = True
-            break
-
-        if model_missing or model_outdated:
-          print(f"Model {model} is either missing required files or outdated. Deleting...")
-          for filename, _ in TINYGRAD_FILES:
-            delete_file(MODELS_PATH / f"{model}_{filename}")
-
-    if need_to_update_models:
-      params_memory.put_bool(MODEL_DOWNLOAD_ALL_PARAM, True)
-
-  def check_tinygrad(self, repo_url):
-    tinygrad_url = f"{repo_url}/Tinygrad/{TAR_FILE_NAME}"
-
-    expected_size = get_remote_file_size(tinygrad_url, self.session)
-    local_size = int(self.tinygrad_sizes.get(TAR_FILE_NAME, 0))
-
-    if expected_size > 0 and local_size != expected_size:
-      print(f"Tinygrad version {VERSION} is outdated, expected_size: {expected_size}, local_size: {local_size}, flagging for update...")
-      params.put_bool("TinygradUpdateAvailable", True)
-
-  def copy_default_model(self):
-    classic_default_model_path = MODELS_PATH / "wd-40.thneed"
-    source_path = Path(__file__).parents[1] / "classic_modeld/models/supercombo.thneed"
-    if source_path.is_file() and (not classic_default_model_path.is_file() or source_path.stat().st_size != classic_default_model_path.stat().st_size):
-      shutil.copyfile(source_path, classic_default_model_path)
-      print(f"Copied the classic default model from {source_path} to {classic_default_model_path}")
-      self.update_model_size(classic_default_model_path)
-
-    default_model_path = MODELS_PATH / "national-public-radio.thneed"
-    source_path = Path(__file__).parents[2] / "selfdrive/modeld/models/supercombo.thneed"
-    if source_path.is_file() and (not default_model_path.is_file() or source_path.stat().st_size != default_model_path.stat().st_size):
-      shutil.copyfile(source_path, default_model_path)
-      print(f"Copied the default model from {source_path} to {default_model_path}")
-      self.update_model_size(default_model_path)
-
-    for filename, description in TINYGRAD_FILES:
-      source = TINYGRAD_MODELD_PATH / "models" / filename
-      target = MODELS_PATH / f"{DEFAULT_MODEL}_{filename}"
-      if source.is_file() and (not target.is_file() or source.stat().st_size != target.stat().st_size):
-        shutil.copyfile(source, target)
-        print(f"Copied the tinygrad {description} from {source} to {target}")
-
-  def download_all_models(self):
-    repo_url = get_repository_url(self.session)
-    if not repo_url:
-      handle_error(None, "GitHub and GitLab are offline...", "Repository unavailable", MODEL_DOWNLOAD_PARAM, DOWNLOAD_PROGRESS_PARAM)
-      return
-
-    self.fetch_models(f"{repo_url}/Versions/model_names_{VERSION}.json", repo_url)
-
-    for model in self.available_models:
-      if params_memory.get_bool(CANCEL_DOWNLOAD_PARAM):
-        handle_error(None, "Download cancelled...", "Download cancelled...", MODEL_DOWNLOAD_ALL_PARAM, DOWNLOAD_PROGRESS_PARAM)
-        return
-
-      if self.is_tinygrad_model(model):
-        already_downloaded = (MODELS_PATH / f"{model}.thneed").is_file()
+      elif model_version == "v7":
+        filename = f"{model}.pkl"
+        path = MODELS_PATH / filename
+        expected_size = model_sizes.get(model)
+        if not path.is_file() or expected_size is None or path.stat().st_size != expected_size:
+          needs_download = True
       else:
-        already_downloaded = all((MODELS_PATH / f"{model}_{filename}").is_file() for filename, _ in TINYGRAD_FILES)
+        filename = f"{model}.thneed"
+        path = MODELS_PATH / filename
+        expected_size = model_sizes.get(model)
+        if not path.is_file() or expected_size is None or path.stat().st_size != expected_size:
+          needs_download = True
 
-      if already_downloaded:
-        continue
+    if needs_download:
+      self.download_all_models()
 
-      print(f"Model {model} is not downloaded. Preparing to download...")
-      params_memory.put(DOWNLOAD_PROGRESS_PARAM, f"Downloading \"{self.available_model_names[self.available_models.index(model)]}\"...")
-      self.download_model(model)
+  def update_model_params(self, model_info, repo_url):
+      self.available_models = [model["id"] for model in model_info]
+      self.model_versions = [model["version"] for model in model_info]
+      self.model_series = [model.get("series", "Dom Forgot To Label Me") for model in model_info]
 
-    params_memory.put(DOWNLOAD_PROGRESS_PARAM, "All models downloaded!")
-    params_memory.remove(MODEL_DOWNLOAD_ALL_PARAM)
+      params.put("AvailableModels", ",".join(self.available_models))
+      params.put("AvailableModelNames", ",".join([model["name"] for model in model_info]))
+      params.put("AvailableModelSeries", ",".join(self.model_series))
+      params.put("CommunityFavorites", ",".join([model["id"] for model in model_info if model.get("community_favorite", False)]))
+      params.put("ModelReleasedDates", ",".join([model.get("released", "2023-01-01") for model in model_info]))
+      params.put("ModelVersions", ",".join(self.model_versions))
+      params.put("CommunityFavorites", ",".join([model["id"] for model in model_info if model.get("community_favorite", False)]))
+      params.put("AvailableModelSeries", ",".join(self.model_series))
+      print("Models list updated successfully")
 
-  def download_model(self, model_to_download):
-    self.downloading_model = True
+      # --- Generate per-model version JSON for offline UI ---
+      try:
+          versions_file = MODELS_PATH / ".model_versions.json"
+          version_map = {model_id: version for model_id, version in zip(self.available_models, self.model_versions)}
+          with open(versions_file, "w") as vf:
+              json.dump(version_map, vf)
+      except Exception as e:
+          print(f"Failed to write .model_versions.json: {e}")
+      # --- end JSON generation ---
 
-    repo_url = get_repository_url(self.session)
-    if not repo_url:
-      handle_error(None, "GitHub and GitLab are offline...", "Repository unavailable", MODEL_DOWNLOAD_PARAM, DOWNLOAD_PROGRESS_PARAM)
-      self.downloading_model = False
-      return
+      # Immediately sync the active ModelVersion param
+      try:
+          current = params.get("Model", encoding="utf-8")
+          if current in version_map:
+              params.put("ModelVersion", version_map[current])
+              print(f"Successfully synced ModelVersion to {version_map[current]} for model {current}")
+          else:
+              print(f"Warning: Model {current} not found in version map")
+      except Exception as e:
+          print(f"Failed to sync ModelVersion for {current}: {e}")
 
-    if self.is_tinygrad_model(model_to_download):
-      model_path = MODELS_PATH / f"{model_to_download}.thneed"
-      model_url = f"{repo_url}/Models/{model_to_download}.thneed"
+      # Also ensure ModelVersion is set for the default model if not already set
+      try:
+          if not params.get("ModelVersion", encoding="utf-8"):
+              default_model = params.get("Model", encoding="utf-8") or DEFAULT_MODEL
+              if default_model in version_map:
+                  params.put("ModelVersion", version_map[default_model])
+                  print(f"Set default ModelVersion to {version_map[default_model]} for model {default_model}")
+      except Exception as e:
+          print(f"Failed to set default ModelVersion: {e}")
 
-      print(f"Downloading model: {model_to_download}")
-      download_file(CANCEL_DOWNLOAD_PARAM, model_path, DOWNLOAD_PROGRESS_PARAM, model_url, MODEL_DOWNLOAD_PARAM, self.session)
-
-      if params_memory.get_bool(CANCEL_DOWNLOAD_PARAM):
-        delete_file(model_path)
-
-        handle_error(None, "Download cancelled...", "Download cancelled...", MODEL_DOWNLOAD_PARAM, DOWNLOAD_PROGRESS_PARAM)
-        self.downloading_model = False
-        return
-
-      if verify_download(model_path, model_url, self.session):
-        print(f"Model {model_to_download} downloaded and verified successfully!")
-        self.update_model_size(model_path)
-
-        params_memory.put(DOWNLOAD_PROGRESS_PARAM, "Downloaded!")
-        params_memory.remove(MODEL_DOWNLOAD_PARAM)
-
-        self.downloading_model = False
-        return
-
-      print(f"Verification failed for model {model_to_download}. Retrying from GitLab...")
-      fallback_url = f"{GITLAB_URL}/Models/{model_to_download}.thneed"
-      download_file(CANCEL_DOWNLOAD_PARAM, model_path, DOWNLOAD_PROGRESS_PARAM, fallback_url, MODEL_DOWNLOAD_PARAM, self.session)
-
-      if params_memory.get_bool(CANCEL_DOWNLOAD_PARAM):
-        delete_file(model_path)
-
-        handle_error(None, "Download cancelled...", "Download cancelled...", MODEL_DOWNLOAD_PARAM, DOWNLOAD_PROGRESS_PARAM)
-        self.downloading_model = False
-        return
-
-      if verify_download(model_path, fallback_url, self.session):
-        print(f"Model {model_to_download} downloaded and verified successfully from GitLab!")
-        self.update_model_size(model_path)
-
-        params_memory.put(DOWNLOAD_PROGRESS_PARAM, "Downloaded!")
-        params_memory.remove(MODEL_DOWNLOAD_PARAM)
-
-        self.downloading_model = False
-      else:
-        handle_error(model_path, "Verification failed...", "GitLab verification failed", MODEL_DOWNLOAD_PARAM, DOWNLOAD_PROGRESS_PARAM)
-        self.downloading_model = False
-    else:
-      all_model_sizes = self.fetch_all_model_sizes(repo_url) or {}
-      tinygrad_filenames = [f"{model_to_download}_{file_key}" for file_key, _ in TINYGRAD_FILES]
-
-      file_sizes = []
-      file_sources = []
-
-      missing = [name for name in tinygrad_filenames if int(all_model_sizes.get(name, 0)) <= 0]
-      if missing:
-        handle_error(None, "Missing size metadata...", f"Sizes not found for: {', '.join(missing)}...", MODEL_DOWNLOAD_PARAM, DOWNLOAD_PROGRESS_PARAM)
-        self.downloading_model = False
-        return
-
-      for filename in tinygrad_filenames:
-        primary_url = f"{repo_url}/Models/compiled/{filename}"
-        file_size = int(all_model_sizes.get(filename, 0))
-        file_sizes.append(file_size)
-        file_sources.append((primary_url, None))
-
-      downloaded_offset_bytes = 0
-      known_file_sizes = [size for size in file_sizes if size > 0]
-      total_model_bytes = sum(known_file_sizes) if len(known_file_sizes) == len(file_sizes) else 0
-
-      for (file_key, description), part_bytes, (primary_url, fallback_url) in zip(TINYGRAD_FILES, file_sizes, file_sources):
-        filename = f"{model_to_download}_{file_key}"
-        model_path = MODELS_PATH / filename
-
-        print(f"Downloading {description} for model: {model_to_download}")
-        download_file(CANCEL_DOWNLOAD_PARAM, model_path, DOWNLOAD_PROGRESS_PARAM, primary_url, MODEL_DOWNLOAD_PARAM, self.session, offset_bytes=downloaded_offset_bytes, total_bytes=total_model_bytes)
-
-        if params_memory.get_bool(CANCEL_DOWNLOAD_PARAM):
-          delete_file(model_path)
-
-          handle_error(None, "Download cancelled...", "Download cancelled...", MODEL_DOWNLOAD_PARAM, DOWNLOAD_PROGRESS_PARAM)
-          self.downloading_model = False
-          return
-
-        if verify_download(model_path, primary_url, self.session):
-          print(f"{description.capitalize()} for {model_to_download} downloaded and verified successfully!")
-          if total_model_bytes:
-            downloaded_offset_bytes += part_bytes
-          continue
-
-        print(f"Verification failed for {filename}. Retrying from GitLab...")
-        fallback_url = f"{GITLAB_URL}/Models/compiled/{filename}"
-        download_file(CANCEL_DOWNLOAD_PARAM, model_path, DOWNLOAD_PROGRESS_PARAM, fallback_url, MODEL_DOWNLOAD_PARAM, self.session, offset_bytes=downloaded_offset_bytes, total_bytes=total_model_bytes)
-
-        if params_memory.get_bool(CANCEL_DOWNLOAD_PARAM):
-          delete_file(model_path)
-
-          handle_error(None, "Download cancelled...", "Download cancelled...", MODEL_DOWNLOAD_PARAM, DOWNLOAD_PROGRESS_PARAM)
-          self.downloading_model = False
-          return
-
-        if verify_download(model_path, fallback_url, self.session):
-          print(f"{description.capitalize()} for {model_to_download} downloaded and verified successfully from GitLab!")
-          if total_model_bytes:
-            downloaded_offset_bytes += part_bytes
-        else:
-          handle_error(model_path, "Verification failed...", f"GitLab verification failed for {filename}", MODEL_DOWNLOAD_PARAM, DOWNLOAD_PROGRESS_PARAM)
-          self.downloading_model = False
-          return
-
-      print(f"Updating model sizes for {model_to_download}...")
-      for filename, _ in TINYGRAD_FILES:
-        file_path = MODELS_PATH / f"{model_to_download}_{filename}"
-        self.update_model_size(file_path)
-
-      params_memory.put(DOWNLOAD_PROGRESS_PARAM, "Downloaded!")
-      params_memory.remove(MODEL_DOWNLOAD_PARAM)
-
-      self.downloading_model = False
-
-  def fetch_all_model_sizes(self, repo_url):
-    is_github = "github" in repo_url
-    is_gitlab = "gitlab" in repo_url
-    repo_encoded = quote_plus(RESOURCES_REPO)
-
-    model_sizes = {}
-    try:
-      def fetch_dir_sizes(api_url):
-        sizes = {}
-        print(f"Fetching model metadata: {api_url}")
-        response = self.session.get(api_url, timeout=10)
-        response.raise_for_status()
-        content = response.json()
-
-        model_files = [file for file in content if "." in file["name"]]
-
-        if is_github:
-          for file in model_files:
-            sizes[file["name"]] = file.get("size", 0)
-        else:
-          for file in model_files:
-            file_path = quote_plus(file["path"])
-            metadata_url = f"https://gitlab.com/api/v4/projects/{repo_encoded}/repository/files/{file_path}/raw?ref=Models"
-            head_response = self.session.head(metadata_url, timeout=10)
-            if head_response.ok:
-              sizes[file["name"]] = int(head_response.headers.get("content-length", 0))
-        return sizes
-
-      if is_github:
-        top_api_url = f"https://api.github.com/repos/{RESOURCES_REPO}/contents?ref=Models"
-        version_api_url = f"https://api.github.com/repos/{RESOURCES_REPO}/contents/compiled?ref=Models"
-      elif is_gitlab:
-        top_api_url = f"https://gitlab.com/api/v4/projects/{repo_encoded}/repository/tree?ref=Models"
-        version_api_url = f"https://gitlab.com/api/v4/projects/{repo_encoded}/repository/tree?path=compiled&ref=Models"
-      else:
-        print(f"Unsupported repository URL: {repo_url}")
-        return model_sizes
-
-      model_sizes.update(fetch_dir_sizes(top_api_url))
-      model_sizes.update(fetch_dir_sizes(version_api_url))
-
-      return model_sizes
-
-    except requests.exceptions.RequestException as e:
-      handle_request_error(f"Failed to fetch model sizes from {'GitHub' if is_github else 'GitLab'}: {e}", None, None, None)
-      return {}
-
-  def fetch_models(self, url, repo_url, boot_run=False):
-    try:
-      response = self.session.get(url, timeout=10)
-      response.raise_for_status()
-      model_info = response.json().get("models", [])
-
-      if model_info:
-        self.update_model_params(model_info)
-        self.check_models(boot_run, repo_url)
-        self.check_tinygrad(repo_url)
-    except Exception as exception:
-      handle_request_error(exception, None, None, None)
-      return []
-
-  def is_tinygrad_model(self, model):
-    return self.model_versions[self.available_models.index(model)] in {"v1", "v2", "v3", "v4", "v5", "v6"}
-
-  def update_model_params(self, model_info):
-    self.available_models = [model["id"] for model in model_info]
-    self.available_model_names = [model["name"] for model in model_info]
-    self.model_versions = [model["version"] for model in model_info]
-
-    params.put("AvailableModels", ",".join(self.available_models))
-    params.put("AvailableModelNames", ",".join(self.available_model_names))
-    params.put("ModelVersions", ",".join(self.model_versions))
-    print("Models list updated successfully!")
-
-  def update_models(self, boot_run):
+  def update_models(self, boot_run=False):
     if self.downloading_model:
       return
 
-    repo_url = get_repository_url(self.session)
+    repo_url = get_repository_url()
     if repo_url is None:
       print("GitHub and GitLab are offline...")
       return
 
-    self.fetch_models(f"{repo_url}/Versions/model_names_{VERSION}.json", repo_url, boot_run)
+    model_info = self.fetch_models(f"{repo_url}/Versions/model_names_{VERSION}.json")
+    if model_info:
+      self.update_model_params(model_info, repo_url)
+      self.check_models(boot_run, repo_url)
 
-  def update_model_size(self, file_path):
-    self.model_sizes[file_path.name] = file_path.stat().st_size
-    update_json_file(self.model_sizes_path, self.model_sizes)
-    print(f"Updated size for {file_path.name} in {self.model_sizes_path.name}")
+      # Ensure ModelVersion is set immediately after updating model params
+      if boot_run:
+        try:
+          current = params.get("Model", encoding="utf-8")
+          if current and current in [model["id"] for model in model_info]:
+            model_index = [model["id"] for model in model_info].index(current)
+            version = model_info[model_index]["version"]
+            params.put("ModelVersion", version)
+            print(f"Boot sync: Set ModelVersion to {version} for model {current}")
+        except Exception as e:
+          print(f"Boot sync failed: {e}")
 
-  def update_tinygrad_size(self, file_path):
-    self.tinygrad_sizes[TAR_FILE_NAME] = file_path.stat().st_size
-    update_json_file(self.tinygrad_sizes_path, self.tinygrad_sizes)
-    print(f"Updated size for {TAR_FILE_NAME} in {self.tinygrad_sizes_path.name}")
-
-  def update_tinygrad(self):
-    repo_url = get_repository_url(self.session)
+  def download_all_models(self):
+    repo_url = get_repository_url()
     if not repo_url:
-      handle_error(None, "GitHub and GitLab are offline...", "Repository unavailable", None, None)
+      handle_error(None, "GitHub and GitLab are offline...", "Repository unavailable", MODEL_DOWNLOAD_ALL_PARAM, DOWNLOAD_PROGRESS_PARAM, params_memory)
       return
 
-    primary_url = f"{repo_url}/Tinygrad/{TAR_FILE_NAME}"
-    fallback_url = f"https://gitlab.com/{RESOURCES_REPO}/-/raw/Tinygrad/{TAR_FILE_NAME}"
+    model_info = self.fetch_models(f"{repo_url}/Versions/model_names_{VERSION}.json")
+    if model_info:
+      available_models = [model["id"] for model in model_info]
+      available_model_names = [re.sub(r"[🗺️👀📡]", "", model["name"]).strip() for model in model_info]
+      model_versions = [model["version"] for model in model_info]
+      model_series = [model.get("series", "Dom Forgot To Label Me") for model in model_info]
 
-    tinygrad_tar_path = Path("/data/tmp/tinygrad.tar.gz")
-    try:
-      print(f"Attempting to download tinygrad from {primary_url}...")
-      download_file(CANCEL_DOWNLOAD_PARAM, tinygrad_tar_path, DOWNLOAD_PROGRESS_PARAM, primary_url, UPDATE_TINYGRAD_PARAM, self.session)
-
-      if params_memory.get_bool(CANCEL_DOWNLOAD_PARAM):
-        delete_file(tinygrad_tar_path)
-
-        handle_error(None, "Tinygrad update cancelled...", "Tinygrad update cancelled...", UPDATE_TINYGRAD_PARAM, DOWNLOAD_PROGRESS_PARAM)
-        params_memory.remove("CancelModelDownload")
-        return
-
-      if not verify_download(tinygrad_tar_path, primary_url, self.session):
-        print(f"Verification failed for {primary_url}. Retrying from GitLab...")
-        download_file(CANCEL_DOWNLOAD_PARAM, tinygrad_tar_path, DOWNLOAD_PROGRESS_PARAM, fallback_url, UPDATE_TINYGRAD_PARAM, self.session)
-
-      if params_memory.get_bool(CANCEL_DOWNLOAD_PARAM):
-        delete_file(tinygrad_tar_path)
-
-        handle_error(None, "Tinygrad update cancelled...", "Tinygrad update cancelled...", UPDATE_TINYGRAD_PARAM, DOWNLOAD_PROGRESS_PARAM)
-        params_memory.remove("CancelModelDownload")
-        return
-
-      if not verify_download(tinygrad_tar_path, fallback_url, self.session):
-        handle_error(tinygrad_tar_path, "Verification Failed", "Tinygrad verification failed", UPDATE_TINYGRAD_PARAM, DOWNLOAD_PROGRESS_PARAM)
-        return
-
-      print("Tinygrad downloaded successfully! Proceeding with installation...")
-      self.update_tinygrad_size(tinygrad_tar_path)
-
-      params_memory.put(DOWNLOAD_PROGRESS_PARAM, "Installing...")
-
-      print("Deleting old tinygrad directories...")
-      delete_file(TINYGRAD_MODELD_PATH)
-      print(f"Removed {TINYGRAD_MODELD_PATH}")
-      delete_file(TINYGRAD_REPO_PATH)
-      print(f"Removed {TINYGRAD_REPO_PATH}")
-
-      extract_tar(tinygrad_tar_path, Path(BASEDIR))
-
-      print("Tinygrad update completed successfully!")
-
-      params.put_bool("TinygradUpdateAvailable", False)
-
-      params_memory.put(DOWNLOAD_PROGRESS_PARAM, "Updated!")
-      params_memory.remove(UPDATE_TINYGRAD_PARAM)
-
-      self.update_tinygrad_models(repo_url)
-    except Exception as exception:
-      handle_error(tinygrad_tar_path, "Update Failed", f"An unexpected error occurred: {exception}", UPDATE_TINYGRAD_PARAM, DOWNLOAD_PROGRESS_PARAM)
-
-  def update_tinygrad_models(self, repo_url=None):
-    print("Updating old Tinygrad models...")
-
-    installed_tinygrad_models = set()
-    for filename, _ in TINYGRAD_FILES:
-      suffix = f"_{filename}"
-      for file_path in MODELS_PATH.glob(f"*{suffix}"):
-        model_name = file_path.name.rsplit(suffix, 1)[0]
-        if model_name in set(self.available_models):
-          installed_tinygrad_models.add(model_name)
-        delete_file(file_path)
-
-    self.copy_default_model()
-
-    update_frogpilot_toggles()
-
-    if repo_url is None:
-      return
-
-    current_model = params.get("Model", encoding="utf-8").removesuffix("_default")
-
-    models_to_redownload = [current_model]
-    models_to_redownload += [model for model in sorted(installed_tinygrad_models) if model != current_model]
-
-    if DEFAULT_MODEL in models_to_redownload:
-      models_to_redownload.remove(DEFAULT_MODEL)
-
-    if models_to_redownload:
-      print(f"Redownloading the following models: {', '.join(models_to_redownload)}")
-      self.fetch_models(f"{repo_url}/Versions/model_names_{VERSION}.json", repo_url, boot_run=True)
-
-      for model in models_to_redownload:
+      for model, model_name, model_version in zip(available_models, available_model_names, model_versions):
         if params_memory.get_bool(CANCEL_DOWNLOAD_PARAM):
-          handle_error(None, "Download cancelled...", "Download cancelled...", MODEL_DOWNLOAD_ALL_PARAM, DOWNLOAD_PROGRESS_PARAM)
+          handle_error(None, "Download cancelled...", "Download cancelled...", MODEL_DOWNLOAD_ALL_PARAM, DOWNLOAD_PROGRESS_PARAM, params_memory)
           return
 
-        params_memory.put(DOWNLOAD_PROGRESS_PARAM, f"Downloading \"{self.available_model_names[self.available_models.index(model)]}\"...")
-        self.download_model(model)
+        if model_version in ("v8", "v9", "v10", "v11", "v12"):
+          required_files = [
+              f"{model}_driving_policy_tinygrad.pkl",
+              f"{model}_driving_vision_tinygrad.pkl",
+              f"{model}_driving_policy_metadata.pkl",
+              f"{model}_driving_vision_metadata.pkl",
+          ]
+          if model_version == "v12":
+            required_files += [
+              f"{model}_driving_off_policy_tinygrad.pkl",
+              f"{model}_driving_off_policy_metadata.pkl",
+            ]
+          missing = [f for f in required_files if not (MODELS_PATH / f).is_file()]
+          if missing:
+            print(f"Tinygrad model {model} is missing files. Preparing to download...")
+            params_memory.put(DOWNLOAD_PROGRESS_PARAM, f"Downloading \"{model_name}\"...")
+            self.download_model(model)
+        elif model_version == "v7":
+          # OG tinygrad: only need PKL file
+          model_file = MODELS_PATH / f"{model}.pkl"
+          if not model_file.is_file():
+            print(f"PKL model {model} is missing. Preparing to download...")
+            params_memory.put(DOWNLOAD_PROGRESS_PARAM, f"Downloading \"{model_name}\"...")
+            self.download_model(model)
+        else:
+          # Classic: only need .thneed
+          model_file = MODELS_PATH / f"{model}.thneed"
+          if not model_file.is_file():
+            print(f"Classic model {model} is missing. Preparing to download...")
+            params_memory.put(DOWNLOAD_PROGRESS_PARAM, f"Downloading \"{model_name}\"...")
+            self.download_model(model)
+
+      params_memory.put(DOWNLOAD_PROGRESS_PARAM, "All models downloaded!")
     else:
-      print("No previously installed tinygrad models to redownload")
-
-    update_frogpilot_toggles()
-
-  def validate_models(self):
-    current = params.get("Model", encoding="utf-8")
-    default = params_default.get("Model", encoding="utf-8")
-
-    if current.endswith("_default") and current != default:
-      print(f"Model '{current}' does not match default '{default}', resetting...")
-      params.put("Model", default)
-
-    if VERSION_PATH.is_file():
-      version_name = VERSION_PATH.read_text().strip()
-      if version_name != VERSION or int(self.tinygrad_sizes.get(TAR_FILE_NAME, 0)) == 0:
-        self.update_tinygrad_models()
-
-        self.tinygrad_sizes[TAR_FILE_NAME] = DEFAULT_TINYGRAD_SIZE
-        update_json_file(self.tinygrad_sizes_path, self.tinygrad_sizes)
-        print(f"Updated size for {TAR_FILE_NAME} in {self.tinygrad_sizes_path.name}")
-
-        params.remove("TinygradUpdateAvailable")
-
-    VERSION_PATH.write_text(VERSION)
-    print(f"Updated {VERSION_PATH} to {VERSION}")
+      handle_error(None, "Unable to fetch models...", "Model list unavailable", MODEL_DOWNLOAD_ALL_PARAM, DOWNLOAD_PROGRESS_PARAM, params_memory)

frogpilot/assets/nnff_models/CHEVROLET_BOLT_EUV.json

@@ -0,0 +1 @@
+{"input_std":[[9.281861],[1.8477924],[0.7977224],[0.047467366],[1.7969038],[1.8168812],[1.8351218],[1.785757],[1.7335743],[1.6658221],[1.5893887],[0.047346078],[0.0473731],[0.047383286],[0.047291175],[0.047300573],[0.04712479],[0.046799928]],"model_test_loss":0.027355343103408813,"input_size":18,"current_date_and_time":"2023-08-05_05-11-44","input_mean":[[21.655252],[-0.07694559],[-0.006081294],[-0.007598456],[-0.07309746],[-0.075890236],[-0.07804942],[-0.076106496],[-0.07184982],[-0.06528668],[-0.060404416],[-0.0077262702],[-0.0077046235],[-0.0076850485],[-0.007687444],[-0.007708868],[-0.0077959923],[-0.008017422]],"input_vars":["v_ego","lateral_accel","lateral_jerk","roll","lateral_accel_m03","lateral_accel_m02","lateral_accel_m01","lateral_accel_p03","lateral_accel_p06","lateral_accel_p10","lateral_accel_p15","roll_m03","roll_m02","roll_m01","roll_p03","roll_p06","roll_p10","roll_p15"],"output_size":1,"layers":[{"dense_1_b":[[-0.35776415],[-0.126288],[0.007988413],[0.03850029],[-0.056796823],[0.0072075897],[0.17376427]],"dense_1_W":[[0.010538558,6.7293744,-0.007391298,-1.035045,-0.47446147,1.0940393,0.08225446,-0.5795131,0.573115,1.82923,-0.16999252,0.8818023,0.03560901,-0.9470653,-1.042151,1.1532398,1.9009485,-1.2265956],[0.009010456,-1.3618345,0.039026346,0.22943486,-0.6669799,-0.768271,-0.16828564,-0.13406865,0.19760236,-0.18953702,-0.019137766,0.1468623,0.26367718,0.4732375,0.73679143,0.62450147,0.30198866,-0.93340015],[-0.044318866,2.2138615,9.620889,-0.66480356,-0.06849887,-0.038568456,-0.30580127,-0.088089585,0.31187677,0.5968372,-1.1462088,0.13234706,0.29166338,-0.69978577,-0.01790655,-0.097928315,-0.56950736,0.7560642],[1.3758256,0.8700429,-0.24295154,0.20832618,-0.7735097,1.0379355,-0.60753095,-0.5457418,-1.0892137,-0.6708325,0.24982774,0.09251328,0.08596103,-0.58034134,-0.3046114,-0.19754426,0.006461508,0.5989185],[0.06314328,-2.492993,-0.28200585,0.49902886,0.8513198,-0.5704965,1.0960953,-0.08426956,-0.76074624,0.10669376,0.02775254,-0.42194095,-0.34657434,-0.10863868,0.17019278,0.0963825,-0.10169116,0.21243806],[0.007984091,-1.9276509,-0.0013926353,0.04057924,1.4438432,1.3440262,-2.506722,1.700801,0.72410774,0.13471895,-0.18753268,0.7303607,0.018133093,-0.71643597,0.07050904,-0.30161944,0.085108586,0.061202843],[0.9413167,-0.9954305,-0.19510143,-0.4711845,-0.12398665,-0.45175523,1.0616771,0.28550953,-0.55543137,-0.21576759,-0.2364377,-0.012782618,-0.050565187,0.257694,-0.20975965,0.00022543047,-0.08760746,0.4983852]],"activation":"σ"},{"dense_2_W":[[-0.71804935,0.017023304,-0.099854074,-0.3262651,-0.402829,-0.12073083,0.13537839],[-0.44002575,-0.1071093,-0.58886194,-0.17319413,-0.21134079,0.23135148,0.0006880979],[-0.55711204,-0.8693639,-0.6443761,-0.7382846,0.18980889,-0.6082511,-0.63103676],[0.11338112,-0.5327033,0.2856197,0.32239884,-0.72682667,0.5302305,-0.45094746],[-0.35197002,-0.14440043,-0.025249843,-0.48697743,0.3340018,-0.25992322,0.0050561456],[0.34757507,0.15670523,-0.14263277,0.50704384,-0.020171141,0.6408679,-0.3074123],[0.40258837,-0.59363264,0.35948923,-0.060853776,-0.0072541097,0.89743376,-0.49789146],[-0.63476,0.29580453,0.1689314,-0.5061521,0.24901053,-0.23218995,0.57968193],[-0.66173035,0.50861925,-0.5845035,-0.6602214,0.8341883,-0.31437424,0.8046359],[0.038493533,0.15464582,-0.04848341,-0.57820857,-0.25891733,-0.47527292,0.21441916],[-0.15464531,-0.07454202,-0.8215851,-0.12614948,-0.5924209,0.00017916794,0.24154592],[0.6091424,-0.112086505,0.1144111,-0.31035227,-0.9237534,0.041003596,-0.3542808],[0.2989792,-0.23780549,0.116059326,-0.6056522,0.5499526,-0.9001413,0.5200723]],"activation":"σ","dense_2_b":[[-0.2638964],[-0.24607328],[-0.15493082],[-0.0071187904],[-0.23515384],[-0.09098133],[-0.034066215],[0.03609036],[-0.03842933],[-0.042302527],[-0.2439947],[-0.16342077],[-0.01030317]]},{"dense_3_W":[[0.45771673,-0.2084603,0.3570187,0.35835707,0.13684571,-0.582958,0.29889587,0.43543494,0.11841301,-0.26185623,-0.4988437,0.5752996,-0.28057483],[-0.19594137,0.050280698,-0.29057446,-0.2829161,-0.16987291,-0.21278952,-0.59946907,0.21295123,0.7040468,0.53549695,-0.52553934,-0.19560973,0.6233473],[-0.19091003,0.08669418,-0.5792192,0.57799137,-0.36263424,0.6037143,0.27898273,-0.30951327,-0.3572644,0.46720102,-0.5403428,0.32415462,-0.60570025]],"activation":"identity","dense_3_b":[[-0.0047377176],[0.023170695],[-0.021546118]]},{"dense_4_W":[[-0.12453941,-1.006034,0.96776205]],"dense_4_b":[[-0.02351544]],"activation":"identity"}]}

frogpilot/assets/nnff_models/CHEVROLET_MALIBU_CC.json

@@ -0,0 +1 @@
+{"input_std":[[9.342214],[1.5915664],[0.60113484],[0.048193663],[1.5680411],[1.57577],[1.5836853],[1.5711677],[1.5445132],[1.5007596],[1.4529978],[0.047915205],[0.04800539],[0.04808892],[0.04822398],[0.04817677],[0.047881734],[0.047405947]],"model_test_loss":0.019342588260769844,"input_size":18,"current_date_and_time":"2023-08-05_06-09-11","input_mean":[[22.757933],[-0.016342578],[-0.001405228],[-0.014619173],[-0.018091483],[-0.018382493],[-0.019270267],[-0.018759886],[-0.019559544],[-0.017848592],[-0.020014366],[-0.014564899],[-0.01457757],[-0.014600966],[-0.014757987],[-0.014915743],[-0.015121007],[-0.015359475]],"input_vars":["v_ego","lateral_accel","lateral_jerk","roll","lateral_accel_m03","lateral_accel_m02","lateral_accel_m01","lateral_accel_p03","lateral_accel_p06","lateral_accel_p10","lateral_accel_p15","roll_m03","roll_m02","roll_m01","roll_p03","roll_p06","roll_p10","roll_p15"],"output_size":1,"layers":[{"dense_1_b":[[-0.045577038],[-2.8160777],[-0.21418032],[2.9552083],[-0.06852827],[0.029141279],[-0.053249933]],"dense_1_W":[[0.0010664682,1.3813498,-8.153277,-0.009101015,-0.1484779,1.0008405,-1.5930991,-1.195274,0.6136762,0.3560462,-0.30077773,0.93531257,0.14550218,-0.40074933,-0.21716364,0.13834935,-0.0658936,-0.49427196],[-0.7338253,-0.037501235,-0.49922377,-1.0526338,-0.46141604,-1.3649396,0.7309814,-0.91667104,0.044683233,-0.18628967,-0.20878822,-0.2678598,0.48446324,0.51164204,0.09547851,0.41491362,-0.4524314,0.16594785],[-0.0032175342,3.5451593,-0.11421584,-0.2511033,0.27893174,0.6384996,0.80790603,1.3835542,1.8000495,2.249461,1.4026878,0.7851167,-0.35052946,0.041820426,-0.39790183,0.45703772,-0.30459648,0.18287674],[0.72289664,-0.77138704,-0.5025135,-0.49323097,-0.39893976,-0.8779149,0.6848096,-0.58729875,-0.16643623,-0.14427555,-0.15013328,-0.11467142,-0.27280045,0.48508415,0.52080667,-0.0029569597,-0.28170735,0.06367212],[0.00014026981,-2.0353239,0.0060915067,0.4794941,1.1882906,-1.512865,0.80642134,-0.26044324,-0.56213886,-0.365122,0.55078083,-0.34897435,-0.32031298,0.46106994,0.37792024,-0.14116105,0.15597256,-0.32811671],[0.0011494387,1.9060265,8.3941965,-0.3078165,-0.9530427,0.6589645,-1.2487054,-0.541133,0.13451256,0.2805466,-0.33187166,0.9900705,0.2821258,-0.51270896,-0.5130031,-0.28222615,0.042734932,0.27233443],[-0.0014444552,-1.0933362,0.003359957,-0.15052961,0.37165833,1.7087307,-1.4971043,0.673802,-0.108465396,-0.088505454,0.21561684,0.6252258,-0.15019403,-0.34727478,0.08958758,-0.1723621,-0.25557828,0.29778987]],"activation":"σ"},{"dense_2_W":[[0.20810607,-0.13481373,-0.15003344,-0.6067625,-0.31937903,-0.37380016,0.4666911],[0.71834767,0.15669753,-0.11389502,0.27131546,-0.060118295,0.039282244,0.52961355],[-0.27200606,0.43380752,-0.106262706,-0.49363258,0.35659012,-0.01706296,-1.0807354],[-0.79583454,-0.66428274,-0.42157334,-0.52979547,-0.2803004,-0.57637554,0.084149174],[0.1230394,-0.57023287,0.28639448,-0.506744,-0.9920808,0.7510901,0.8584937],[-0.41256845,0.35423175,0.13009231,0.5198333,0.7576573,-0.7053181,-0.3390053],[-0.15090485,0.33375353,-0.64164793,0.57386595,0.25700107,-0.15245672,-0.49020413],[-0.50120676,0.5210849,-0.3282951,0.4276323,1.0257447,-1.0398436,-0.8911315],[0.11402861,-0.41491523,0.247507,-0.39776865,-0.6089287,0.20646147,0.6692102],[0.09411492,0.31819808,0.41330767,0.024243973,0.2314893,0.08529045,0.14911193],[0.5179265,0.20473345,-0.36762783,-0.009045922,-0.19436747,-0.548099,-0.08656279],[-0.69121784,-0.14201449,0.3887621,0.10787631,1.0371574,-0.64747447,-0.73437464],[-0.07860244,-0.597764,0.019551078,0.010199122,-0.7493642,0.66619915,0.121666186]],"activation":"σ","dense_2_b":[[-0.04259814],[-0.053309314],[-0.28045595],[-0.23801634],[0.00944943],[-0.109921046],[-0.037457183],[0.24627604],[-0.0069056284],[-0.04725389],[-0.03361769],[0.044101644],[-0.0009850285]]},{"dense_3_W":[[-0.19631335,-0.47722518,-0.019853225,-0.29363275,-0.625923,0.35145283,0.62401354,0.14337404,-0.25707108,-0.51310915,0.2565006,0.61742216,-0.07952821],[0.5868974,-0.36786363,-0.0177682,-0.45121866,0.68608487,-0.55178356,-0.35236016,-0.7226455,-0.015394288,-0.10650332,0.5391039,0.17791761,0.34196886],[0.16821232,-0.35580373,0.26906335,0.41736925,-0.6979869,0.41801625,0.34707317,0.7784011,-0.10002936,0.32485273,-0.3644285,0.49092358,-0.43872768]],"activation":"identity","dense_3_b":[[-0.019481273],[0.031026587],[-0.03595322]]},{"dense_4_W":[[-0.72340566,0.21244061,-0.67248434]],"dense_4_b":[[0.026229527]],"activation":"identity"}]}

frogpilot/assets/nnff_models/CHEVROLET_MALIBU_HYBRID_CC.json

@@ -0,0 +1 @@
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frogpilot/assets/nnff_models/CHEVROLET_VOLT_2019.json

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frogpilot/assets/nnff_models/CHEVROLET_VOLT_ASCM.json

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frogpilot/assets/nnff_models/CHEVROLET_VOLT_CAMERA.json

@@ -0,0 +1 @@
+{"input_std":[[9.342214],[1.5915664],[0.60113484],[0.048193663],[1.5680411],[1.57577],[1.5836853],[1.5711677],[1.5445132],[1.5007596],[1.4529978],[0.047915205],[0.04800539],[0.04808892],[0.04822398],[0.04817677],[0.047881734],[0.047405947]],"model_test_loss":0.019342588260769844,"input_size":18,"current_date_and_time":"2023-08-05_06-09-11","input_mean":[[22.757933],[-0.016342578],[-0.001405228],[-0.014619173],[-0.018091483],[-0.018382493],[-0.019270267],[-0.018759886],[-0.019559544],[-0.017848592],[-0.020014366],[-0.014564899],[-0.01457757],[-0.014600966],[-0.014757987],[-0.014915743],[-0.015121007],[-0.015359475]],"input_vars":["v_ego","lateral_accel","lateral_jerk","roll","lateral_accel_m03","lateral_accel_m02","lateral_accel_m01","lateral_accel_p03","lateral_accel_p06","lateral_accel_p10","lateral_accel_p15","roll_m03","roll_m02","roll_m01","roll_p03","roll_p06","roll_p10","roll_p15"],"output_size":1,"layers":[{"dense_1_b":[[-0.045577038],[-2.8160777],[-0.21418032],[2.9552083],[-0.06852827],[0.029141279],[-0.053249933]],"dense_1_W":[[0.0010664682,1.3813498,-8.153277,-0.009101015,-0.1484779,1.0008405,-1.5930991,-1.195274,0.6136762,0.3560462,-0.30077773,0.93531257,0.14550218,-0.40074933,-0.21716364,0.13834935,-0.0658936,-0.49427196],[-0.7338253,-0.037501235,-0.49922377,-1.0526338,-0.46141604,-1.3649396,0.7309814,-0.91667104,0.044683233,-0.18628967,-0.20878822,-0.2678598,0.48446324,0.51164204,0.09547851,0.41491362,-0.4524314,0.16594785],[-0.0032175342,3.5451593,-0.11421584,-0.2511033,0.27893174,0.6384996,0.80790603,1.3835542,1.8000495,2.249461,1.4026878,0.7851167,-0.35052946,0.041820426,-0.39790183,0.45703772,-0.30459648,0.18287674],[0.72289664,-0.77138704,-0.5025135,-0.49323097,-0.39893976,-0.8779149,0.6848096,-0.58729875,-0.16643623,-0.14427555,-0.15013328,-0.11467142,-0.27280045,0.48508415,0.52080667,-0.0029569597,-0.28170735,0.06367212],[0.00014026981,-2.0353239,0.0060915067,0.4794941,1.1882906,-1.512865,0.80642134,-0.26044324,-0.56213886,-0.365122,0.55078083,-0.34897435,-0.32031298,0.46106994,0.37792024,-0.14116105,0.15597256,-0.32811671],[0.0011494387,1.9060265,8.3941965,-0.3078165,-0.9530427,0.6589645,-1.2487054,-0.541133,0.13451256,0.2805466,-0.33187166,0.9900705,0.2821258,-0.51270896,-0.5130031,-0.28222615,0.042734932,0.27233443],[-0.0014444552,-1.0933362,0.003359957,-0.15052961,0.37165833,1.7087307,-1.4971043,0.673802,-0.108465396,-0.088505454,0.21561684,0.6252258,-0.15019403,-0.34727478,0.08958758,-0.1723621,-0.25557828,0.29778987]],"activation":"σ"},{"dense_2_W":[[0.20810607,-0.13481373,-0.15003344,-0.6067625,-0.31937903,-0.37380016,0.4666911],[0.71834767,0.15669753,-0.11389502,0.27131546,-0.060118295,0.039282244,0.52961355],[-0.27200606,0.43380752,-0.106262706,-0.49363258,0.35659012,-0.01706296,-1.0807354],[-0.79583454,-0.66428274,-0.42157334,-0.52979547,-0.2803004,-0.57637554,0.084149174],[0.1230394,-0.57023287,0.28639448,-0.506744,-0.9920808,0.7510901,0.8584937],[-0.41256845,0.35423175,0.13009231,0.5198333,0.7576573,-0.7053181,-0.3390053],[-0.15090485,0.33375353,-0.64164793,0.57386595,0.25700107,-0.15245672,-0.49020413],[-0.50120676,0.5210849,-0.3282951,0.4276323,1.0257447,-1.0398436,-0.8911315],[0.11402861,-0.41491523,0.247507,-0.39776865,-0.6089287,0.20646147,0.6692102],[0.09411492,0.31819808,0.41330767,0.024243973,0.2314893,0.08529045,0.14911193],[0.5179265,0.20473345,-0.36762783,-0.009045922,-0.19436747,-0.548099,-0.08656279],[-0.69121784,-0.14201449,0.3887621,0.10787631,1.0371574,-0.64747447,-0.73437464],[-0.07860244,-0.597764,0.019551078,0.010199122,-0.7493642,0.66619915,0.121666186]],"activation":"σ","dense_2_b":[[-0.04259814],[-0.053309314],[-0.28045595],[-0.23801634],[0.00944943],[-0.109921046],[-0.037457183],[0.24627604],[-0.0069056284],[-0.04725389],[-0.03361769],[0.044101644],[-0.0009850285]]},{"dense_3_W":[[-0.19631335,-0.47722518,-0.019853225,-0.29363275,-0.625923,0.35145283,0.62401354,0.14337404,-0.25707108,-0.51310915,0.2565006,0.61742216,-0.07952821],[0.5868974,-0.36786363,-0.0177682,-0.45121866,0.68608487,-0.55178356,-0.35236016,-0.7226455,-0.015394288,-0.10650332,0.5391039,0.17791761,0.34196886],[0.16821232,-0.35580373,0.26906335,0.41736925,-0.6979869,0.41801625,0.34707317,0.7784011,-0.10002936,0.32485273,-0.3644285,0.49092358,-0.43872768]],"activation":"identity","dense_3_b":[[-0.019481273],[0.031026587],[-0.03595322]]},{"dense_4_W":[[-0.72340566,0.21244061,-0.67248434]],"dense_4_b":[[0.026229527]],"activation":"identity"}]}

frogpilot/assets/nnff_models/CHEVROLET_VOLT_CC.json

@@ -0,0 +1 @@
+{"input_std":[[9.342214],[1.5915664],[0.60113484],[0.048193663],[1.5680411],[1.57577],[1.5836853],[1.5711677],[1.5445132],[1.5007596],[1.4529978],[0.047915205],[0.04800539],[0.04808892],[0.04822398],[0.04817677],[0.047881734],[0.047405947]],"model_test_loss":0.019342588260769844,"input_size":18,"current_date_and_time":"2023-08-05_06-09-11","input_mean":[[22.757933],[-0.016342578],[-0.001405228],[-0.014619173],[-0.018091483],[-0.018382493],[-0.019270267],[-0.018759886],[-0.019559544],[-0.017848592],[-0.020014366],[-0.014564899],[-0.01457757],[-0.014600966],[-0.014757987],[-0.014915743],[-0.015121007],[-0.015359475]],"input_vars":["v_ego","lateral_accel","lateral_jerk","roll","lateral_accel_m03","lateral_accel_m02","lateral_accel_m01","lateral_accel_p03","lateral_accel_p06","lateral_accel_p10","lateral_accel_p15","roll_m03","roll_m02","roll_m01","roll_p03","roll_p06","roll_p10","roll_p15"],"output_size":1,"layers":[{"dense_1_b":[[-0.045577038],[-2.8160777],[-0.21418032],[2.9552083],[-0.06852827],[0.029141279],[-0.053249933]],"dense_1_W":[[0.0010664682,1.3813498,-8.153277,-0.009101015,-0.1484779,1.0008405,-1.5930991,-1.195274,0.6136762,0.3560462,-0.30077773,0.93531257,0.14550218,-0.40074933,-0.21716364,0.13834935,-0.0658936,-0.49427196],[-0.7338253,-0.037501235,-0.49922377,-1.0526338,-0.46141604,-1.3649396,0.7309814,-0.91667104,0.044683233,-0.18628967,-0.20878822,-0.2678598,0.48446324,0.51164204,0.09547851,0.41491362,-0.4524314,0.16594785],[-0.0032175342,3.5451593,-0.11421584,-0.2511033,0.27893174,0.6384996,0.80790603,1.3835542,1.8000495,2.249461,1.4026878,0.7851167,-0.35052946,0.041820426,-0.39790183,0.45703772,-0.30459648,0.18287674],[0.72289664,-0.77138704,-0.5025135,-0.49323097,-0.39893976,-0.8779149,0.6848096,-0.58729875,-0.16643623,-0.14427555,-0.15013328,-0.11467142,-0.27280045,0.48508415,0.52080667,-0.0029569597,-0.28170735,0.06367212],[0.00014026981,-2.0353239,0.0060915067,0.4794941,1.1882906,-1.512865,0.80642134,-0.26044324,-0.56213886,-0.365122,0.55078083,-0.34897435,-0.32031298,0.46106994,0.37792024,-0.14116105,0.15597256,-0.32811671],[0.0011494387,1.9060265,8.3941965,-0.3078165,-0.9530427,0.6589645,-1.2487054,-0.541133,0.13451256,0.2805466,-0.33187166,0.9900705,0.2821258,-0.51270896,-0.5130031,-0.28222615,0.042734932,0.27233443],[-0.0014444552,-1.0933362,0.003359957,-0.15052961,0.37165833,1.7087307,-1.4971043,0.673802,-0.108465396,-0.088505454,0.21561684,0.6252258,-0.15019403,-0.34727478,0.08958758,-0.1723621,-0.25557828,0.29778987]],"activation":"σ"},{"dense_2_W":[[0.20810607,-0.13481373,-0.15003344,-0.6067625,-0.31937903,-0.37380016,0.4666911],[0.71834767,0.15669753,-0.11389502,0.27131546,-0.060118295,0.039282244,0.52961355],[-0.27200606,0.43380752,-0.106262706,-0.49363258,0.35659012,-0.01706296,-1.0807354],[-0.79583454,-0.66428274,-0.42157334,-0.52979547,-0.2803004,-0.57637554,0.084149174],[0.1230394,-0.57023287,0.28639448,-0.506744,-0.9920808,0.7510901,0.8584937],[-0.41256845,0.35423175,0.13009231,0.5198333,0.7576573,-0.7053181,-0.3390053],[-0.15090485,0.33375353,-0.64164793,0.57386595,0.25700107,-0.15245672,-0.49020413],[-0.50120676,0.5210849,-0.3282951,0.4276323,1.0257447,-1.0398436,-0.8911315],[0.11402861,-0.41491523,0.247507,-0.39776865,-0.6089287,0.20646147,0.6692102],[0.09411492,0.31819808,0.41330767,0.024243973,0.2314893,0.08529045,0.14911193],[0.5179265,0.20473345,-0.36762783,-0.009045922,-0.19436747,-0.548099,-0.08656279],[-0.69121784,-0.14201449,0.3887621,0.10787631,1.0371574,-0.64747447,-0.73437464],[-0.07860244,-0.597764,0.019551078,0.010199122,-0.7493642,0.66619915,0.121666186]],"activation":"σ","dense_2_b":[[-0.04259814],[-0.053309314],[-0.28045595],[-0.23801634],[0.00944943],[-0.109921046],[-0.037457183],[0.24627604],[-0.0069056284],[-0.04725389],[-0.03361769],[0.044101644],[-0.0009850285]]},{"dense_3_W":[[-0.19631335,-0.47722518,-0.019853225,-0.29363275,-0.625923,0.35145283,0.62401354,0.14337404,-0.25707108,-0.51310915,0.2565006,0.61742216,-0.07952821],[0.5868974,-0.36786363,-0.0177682,-0.45121866,0.68608487,-0.55178356,-0.35236016,-0.7226455,-0.015394288,-0.10650332,0.5391039,0.17791761,0.34196886],[0.16821232,-0.35580373,0.26906335,0.41736925,-0.6979869,0.41801625,0.34707317,0.7784011,-0.10002936,0.32485273,-0.3644285,0.49092358,-0.43872768]],"activation":"identity","dense_3_b":[[-0.019481273],[0.031026587],[-0.03595322]]},{"dense_4_W":[[-0.72340566,0.21244061,-0.67248434]],"dense_4_b":[[0.026229527]],"activation":"identity"}]}

frogpilot/assets/theme_manager.py

@@ -96,9 +96,9 @@ class ThemeManager:
   def download_theme(self, theme_component, theme_name, asset_param, frogpilot_toggles):
     self.downloading_theme = True
 
-    repo_url = get_repository_url(self.session)
+    repo_url = get_repository_url()
     if not repo_url:
-      handle_error(None, "GitHub and GitLab are offline...", "Repository unavailable", asset_param, DOWNLOAD_PROGRESS_PARAM)
+      handle_error(None, "GitHub and GitLab are offline...", "Repository unavailable", asset_param, DOWNLOAD_PROGRESS_PARAM, params_memory)
       self.downloading_theme = False
       return
 
@@ -122,16 +122,16 @@ class ThemeManager:
       delete_file(theme_path)
 
       print(f"Downloading theme from GitHub: {theme_name}")
-      download_file(CANCEL_DOWNLOAD_PARAM, theme_path, DOWNLOAD_PROGRESS_PARAM, theme_url, asset_param, self.session)
+      download_file(CANCEL_DOWNLOAD_PARAM, theme_path, DOWNLOAD_PROGRESS_PARAM, theme_url, asset_param, params_memory)
 
       if params_memory.get_bool(CANCEL_DOWNLOAD_PARAM):
         delete_file(theme_path)
-        handle_error(None, "Download cancelled...", "Download cancelled...", asset_param, DOWNLOAD_PROGRESS_PARAM)
+        handle_error(None, "Download cancelled...", "Download cancelled...", asset_param, DOWNLOAD_PROGRESS_PARAM, params_memory)
 
         self.downloading_theme = False
         return
 
-      if verify_download(theme_path, theme_url, self.session):
+      if verify_download(theme_path, theme_url):
         print(f"Theme {theme_name} downloaded and verified successfully from GitHub!")
         self.update_theme_size(theme_component, theme_name, theme_path.stat().st_size)
 
@@ -149,7 +149,7 @@ class ThemeManager:
       elif self.handle_verification_failure(extension, theme_component, theme_name, asset_param, theme_path, download_path, frogpilot_toggles):
         return
 
-    handle_error(download_path, "Download failed...", "Download failed...", asset_param, DOWNLOAD_PROGRESS_PARAM)
+    handle_error(download_path, "Download failed...", "Download failed...", asset_param, DOWNLOAD_PROGRESS_PARAM, params_memory)
     self.downloading_theme = False
 
   def fetch_assets(self, repo_url, frogpilot_toggles):
@@ -252,7 +252,7 @@ class ThemeManager:
 
     except requests.exceptions.RequestException as error:
       print(f"Request failed: {error}")
-      handle_request_error(f"Failed to fetch theme sizes from {'GitHub' if is_github else 'GitLab'}: {error}", None, None, None)
+      handle_request_error(f"Failed to fetch theme sizes from {'GitHub' if is_github else 'GitLab'}: {error}", None, None, None, None)
       return {}
 
   @staticmethod
@@ -332,9 +332,9 @@ class ThemeManager:
 
     theme_url = download_link + extension
     print(f"Downloading theme from GitLab: {theme_name}")
-    download_file(CANCEL_DOWNLOAD_PARAM, theme_path, DOWNLOAD_PROGRESS_PARAM, theme_url, asset_param, self.session)
+    download_file(CANCEL_DOWNLOAD_PARAM, theme_path, DOWNLOAD_PROGRESS_PARAM, theme_url, asset_param, params_memory)
 
-    if verify_download(theme_path, theme_url, self.session):
+    if verify_download(theme_path, theme_url):
       print(f"Theme {theme_name} downloaded and verified successfully from GitLab!")
       self.update_theme_size(theme_component, theme_name, theme_path.stat().st_size)
 
@@ -350,7 +350,7 @@ class ThemeManager:
       self.update_themes(frogpilot_toggles)
       return True
 
-    handle_error(None, "Download failed...", "Download failed...", asset_param, DOWNLOAD_PROGRESS_PARAM)
+    handle_error(None, "Download failed...", "Download failed...", asset_param, DOWNLOAD_PROGRESS_PARAM, params_memory)
     self.downloading_theme = False
     return False
 
@@ -563,7 +563,7 @@ class ThemeManager:
     if self.downloading_theme:
       return
 
-    repo_url = get_repository_url(self.session)
+    repo_url = get_repository_url()
     if repo_url is None:
       print("GitHub and GitLab are offline...")
       return

frogpilot/common/frogpilot_functions.py

@@ -150,7 +150,7 @@ def frogpilot_boot_functions(build_metadata, params_cache):
     params_cache.clear_all()
 
   FrogPilotVariables().update(holiday_theme="stock", started=False)
-  ModelManager(boot_run=True)
+  ModelManager()
   ThemeManager(boot_run=True).update_active_theme(time_validated=system_time_valid(), frogpilot_toggles=get_frogpilot_toggles(), boot_run=True)
 
   if VIDEO_CACHE_PATH.exists():

frogpilot/common/frogpilot_utilities.py

@@ -296,12 +296,12 @@ def update_openpilot():
   if params.get("UpdaterState", encoding="utf-8") != "idle":
     return
 
-  while params.get_bool("IsOnroad") or params_memory.get_bool("UpdateSpeedLimits") or running_threads.get("lock_doors", threading.Thread()).is_alive():
-    time.sleep(60)
-
   if not update_available():
     return
 
+  while params.get_bool("IsOnroad") or params_memory.get_bool("UpdateSpeedLimits") or running_threads.get("lock_doors", threading.Thread()).is_alive():
+    time.sleep(60)
+
   while True:
     if not update_available():
       break

frogpilot/common/frogpilot_variables.py

@@ -13,7 +13,8 @@ from openpilot.common.conversions import Conversions as CV
 from openpilot.common.params import Params
 from openpilot.selfdrive.car import gen_empty_fingerprint
 from openpilot.selfdrive.car.car_helpers import interfaces
-from openpilot.selfdrive.car.gm.values import GMFlags
+from openpilot.selfdrive.car.gm.values import EV_CAR as GM_EV_CAR, GMFlags
+from openpilot.selfdrive.car.hyundai.values import EV_CAR as HYUNDAI_EV_CAR
 from openpilot.selfdrive.car.interfaces import CarInterfaceBase
 from openpilot.selfdrive.car.mock.interface import CarInterface
 from openpilot.selfdrive.car.mock.values import CAR as MOCK
@@ -32,6 +33,7 @@ params_memory = Params("/dev/shm/params")
 
 GearShifter = car.CarState.GearShifter
 SafetyModel = car.CarParams.SafetyModel
+TransmissionType = car.CarParams.TransmissionType
 
 CITY_SPEED_LIMIT = 25                     # 55mph is typically the minimum speed for highways
 CRUISING_SPEED = 5                        # Roughly the speed cars go when not touching the gas while in drive
@@ -40,11 +42,16 @@ EARTH_RADIUS = 6378137                    # Radius of the Earth in meters
 MAX_T_FOLLOW = 3.0                        # Maximum allowed following duration. Larger values risk losing track of the lead but may be increased as models improve
 MINIMUM_LATERAL_ACCELERATION = 1.3        # m/s^2, typical minimum lateral acceleration when taking curves
 PLANNER_TIME = ModelConstants.T_IDXS[-1]  # Length of time the model projects out for
+
 THRESHOLD = 0.63                          # Requires the condition to be true for ~1 second
 
+def scale_threshold(v_ego):#0   40    60    80   100       0    40    60   80   100
+  # More aggressive with hysteresis and lead probability: faster activation at higher speeds
+  return np.interp(v_ego, [0, 17.9, 26.8, 35.8, 44.7], [0.58, 0.60, 0.62, 0.75, 0.9])
+
 NON_DRIVING_GEARS = [GearShifter.neutral, GearShifter.park, GearShifter.reverse, GearShifter.unknown]
 
-RESOURCES_REPO = "FrogAi/FrogPilot-Resources"
+RESOURCES_REPO = "firestar5683/StarPilot-Resources"
 
 ACTIVE_THEME_PATH = Path(__file__).parents[1] / "assets/active_theme"
 METADATAS_PATH = Path(__file__).parents[1] / "assets/model_metadata"
@@ -66,12 +73,11 @@ KONIK_PATH = Path("/cache/use_konik")
 
 MAPD_PATH = Path("/data/media/0/osm/mapd")
 MAPS_PATH = Path("/data/media/0/osm/offline")
-
 NNFF_MODELS_PATH = Path(BASEDIR) / "frogpilot/assets/nnff_models"
 
-DEFAULT_MODEL = "firehose"
+DEFAULT_MODEL = "bd2"
 DEFAULT_MODEL_NAME = "Firehose (Default) 👀📡"
-DEFAULT_MODEL_VERSION = "v9"
+DEFAULT_MODEL_VERSION = "v11"
 
 BUTTON_FUNCTIONS = {
   "NOTHING": 0,
@@ -90,12 +96,15 @@ EXCLUDED_KEYS = {
 }
 
 TINYGRAD_FILES = [
+  ("driving_off_policy_metadata.pkl", "off-policy metadata"),
+  ("driving_off_policy_tinygrad.pkl", "off-policy model"),
   ("driving_policy_metadata.pkl", "policy metadata"),
   ("driving_policy_tinygrad.pkl", "policy model"),
   ("driving_vision_metadata.pkl", "vision metadata"),
   ("driving_vision_tinygrad.pkl", "vision model"),
 ]
 
+
 @cache
 def get_nnff_model_files():
   model_dir = Path(NNFF_MODELS_PATH)
@@ -117,13 +126,15 @@ def update_frogpilot_toggles():
 frogpilot_default_params: list[tuple[str, str | bytes, int, str]] = [
   ("AccelerationPath", "1", 2, "0"),
   ("AccelerationProfile", "2", 0, "0"),
-  ("AdjacentLeadsUI", "1", 3, "0"),
+  ("AdjacentLeadsUI", "0", 3, "0"),
   ("AdjacentPath", "0", 3, "0"),
   ("AdjacentPathMetrics", "0", 3, "0"),
   ("AdvancedCustomUI", "0", 2, "0"),
-  ("AdvancedLateralTune", "0", 3, "0"),
+  ("AdvancedLateralTune", "1", 2, "0"),
   ("AdvancedLongitudinalTune", "0", 3, "0"),
+  ("EVTuning", "", 3, "0"),
   ("AggressiveFollow", "1.25", 2, "1.25"),
+  ("AggressiveFollowHigh", "1.25", 2, "1.25"),
   ("AggressiveJerkAcceleration", "50", 3, "50"),
   ("AggressiveJerkDanger", "100", 3, "100"),
   ("AggressiveJerkDeceleration", "50", 3, "50"),
@@ -133,19 +144,22 @@ frogpilot_default_params: list[tuple[str, str | bytes, int, str]] = [
   ("AlertVolumeControl", "0", 2, "0"),
   ("AlwaysOnDM", "0", 0, "0"),
   ("AlwaysOnLateral", "1", 0, "0"),
-  ("AlwaysOnLateralLKAS", "1", 2, "0"),
-  ("AlwaysOnLateralMain", "1", 2, "0"),
+  ("AlwaysOnLateralLKAS", "1", 0, "0"),
+  ("AlwaysOnLateralMain", "1", 0, "0"),
   ("AMapKey1", "", 0, ""),
   ("AMapKey2", "", 0, ""),
   ("AutomaticallyDownloadModels", "1", 1, "0"),
   ("AutomaticUpdates", "1", 0, "1"),
   ("AvailableModelNames", "", 1, ""),
+  ("AvailableModelSeries", "", 1, ""),
   ("AvailableModels", "", 1, ""),
+  ("CommunityFavorites", "", 1, ""),
+  ("UserFavorites", "", 0, ""),
   ("BigMap", "0", 2, "0"),
   ("BlacklistedModels", "", 2, ""),
   ("BlindSpotMetrics", "1", 3, "0"),
   ("BlindSpotPath", "1", 1, "0"),
-  ("BorderMetrics", "0", 3, "0"),
+  ("BorderMetrics", "1", 3, "0"),
   ("CalibratedLateralAcceleration", str(DEFAULT_LATERAL_ACCELERATION), 2, str(DEFAULT_LATERAL_ACCELERATION)),
   ("CalibrationProgress", "0", 3, "0"),
   ("CameraView", "3", 2, "0"),
@@ -157,16 +171,16 @@ frogpilot_default_params: list[tuple[str, str | bytes, int, str]] = [
   ("CECurvesLead", "0", 1, "0"),
   ("CELead", "0", 1, "0"),
   ("CEModelStopTime", str(PLANNER_TIME - 2), 2, "0"),
-  ("CENavigation", "1", 2, "0"),
-  ("CENavigationIntersections", "0", 2, "0"),
+  ("CENavigation", "0", 2, "0"),
+  ("CENavigationIntersections", "1", 2, "0"),
   ("CENavigationLead", "1", 2, "0"),
   ("CENavigationTurns", "1", 2, "0"),
   ("CESignalSpeed", "55", 2, "0"),
   ("CESignalLaneDetection", "1", 2, "0"),
-  ("CESlowerLead", "0", 1, "0"),
+  ("CESlowerLead", "1", 1, "0"),
   ("CESpeed", "0", 1, "0"),
   ("CESpeedLead", "0", 1, "0"),
-  ("CEStoppedLead", "0", 1, "0"),
+  ("CEStoppedLead", "1", 1, "0"),
   ("ClusterOffset", "1.015", 2, "1.015"),
   ("Compass", "0", 1, "0"),
   ("ConditionalExperimental", "1", 1, "0"),
@@ -184,7 +198,7 @@ frogpilot_default_params: list[tuple[str, str | bytes, int, str]] = [
   ("CustomUI", "1", 1, "0"),
   ("DecelerationProfile", "1", 2, "0"),
   ("DeveloperMetrics", "1", 3, "0"),
-  ("DeveloperSidebar", "1", 3, "0"),
+  ("DeveloperSidebar", "0", 3, "0"),
   ("DeveloperSidebarMetric1", "1", 3, "0"),
   ("DeveloperSidebarMetric2", "2", 3, "0"),
   ("DeveloperSidebarMetric3", "3", 3, "0"),
@@ -193,7 +207,7 @@ frogpilot_default_params: list[tuple[str, str | bytes, int, str]] = [
   ("DeveloperSidebarMetric6", "6", 3, "0"),
   ("DeveloperSidebarMetric7", "7", 3, "0"),
   ("DeveloperWidgets", "1", 3, "0"),
-  ("DeveloperUI", "0", 3, "0"),
+  ("DeveloperUI", "1", 3, "0"),
   ("DeviceManagement", "1", 1, "0"),
   ("DeviceShutdown", "9", 1, "33"),
   ("DisableOnroadUploads", "0", 2, "0"),
@@ -203,17 +217,17 @@ frogpilot_default_params: list[tuple[str, str | bytes, int, str]] = [
   ("DistanceButtonControl", "1", 2, "0"),
   ("DriverCamera", "0", 1, "0"),
   ("DynamicPathWidth", "0", 2, "0"),
-  ("DynamicPedalsOnUI", "1", 1, "0"),
+  ("DynamicPedalsOnUI", "1", 2, "0"),
   ("EngageVolume", "101", 2, "101"),
   ("ExperimentalGMTune", "0", 2, "0"),
   ("ExperimentalLongitudinalEnabled", "0", 0, "0"),
   ("ExperimentalModeConfirmed", "0", 0, "0"),
   ("Fahrenheit", "0", 3, "0"),
   ("FavoriteDestinations", "", 0, ""),
-  ("ForceAutoTune", "0", 3, "0"),
-  ("ForceAutoTuneOff", "0", 3, "0"),
+  ("ForceAutoTune", "0", 2, "0"),
+  ("ForceAutoTuneOff", "1", 2, "0"),
   ("ForceFingerprint", "0", 2, "0"),
-  ("ForceMPHDashboard", "0", 3, "0"),
+  ("ForceMPHDashboard", "0", 2, "0"),
   ("ForceStops", "0", 2, "0"),
   ("ForceTorqueController", "0", 3, "0"),
   ("FPSCounter", "1", 3, "0"),
@@ -222,6 +236,7 @@ frogpilot_default_params: list[tuple[str, str | bytes, int, str]] = [
   ("FrogsGoMoosTweak", "1", 2, "0"),
   ("FullMap", "0", 2, "0"),
   ("GasRegenCmd", "1", 2, "0"),
+  ("GMPedalLongitudinal", "1", 2, "1"),
   ("GithubSshKeys", "", 0, ""),
   ("GithubUsername", "", 0, ""),
   ("GoatScream", "0", 1, "0"),
@@ -235,10 +250,10 @@ frogpilot_default_params: list[tuple[str, str | bytes, int, str]] = [
   ("HideMaxSpeed", "0", 2, "0"),
   ("HideSpeed", "0", 2, "0"),
   ("HideSpeedLimit", "0", 2, "0"),
-  ("HigherBitrate", "0", 2, "0"),
+  ("HigherBitrate", "0", 3, "0"),
   ("HolidayThemes", "1", 0, "0"),
-  ("HumanAcceleration", "1", 2, "0"),
-  ("HumanFollowing", "1", 2, "0"),
+  ("HumanAcceleration", "0", 2, "0"),
+  ("HumanFollowing", "0", 2, "0"),
   ("IncreasedStoppedDistance", "0", 1, "0"),
   ("IncreaseThermalLimits", "0", 2, "0"),
   ("IsLdwEnabled", "0", 0, "0"),
@@ -246,13 +261,13 @@ frogpilot_default_params: list[tuple[str, str | bytes, int, str]] = [
   ("KonikDongleId", "", 0, ""),
   ("KonikMinutes", "0", 0, "0"),
   ("LaneChanges", "1", 0, "1"),
-  ("LaneChangeTime", "1.0", 1, "0"),
-  ("LaneDetectionWidth", "0", 1, "0"),
+  ("LaneChangeTime", "2.0", 0, "0"),
+  ("LaneDetectionWidth", "0", 2, "0"),
   ("LaneLinesWidth", "4", 2, "2"),
-  ("LateralTune", "1", 1, "0"),
+  ("LateralTune", "1", 2, "0"),
   ("LeadDepartingAlert", "0", 0, "0"),
   ("LeadDetectionThreshold", "35", 3, "50"),
-  ("LeadInfo", "1", 3, "0"),
+  ("LeadInfo", "1", 2, "0"),
   ("LiveDelay", "", 0, ""),
   ("LKASButtonControl", "5", 2, "0"),
   ("LockDoors", "1", 0, "0"),
@@ -261,33 +276,36 @@ frogpilot_default_params: list[tuple[str, str | bytes, int, str]] = [
   ("LongitudinalActuatorDelay", "", 3, ""),
   ("LongitudinalActuatorDelayStock", "", 3, ""),
   ("LongitudinalTune", "1", 0, "0"),
+  ("TrailerLoad", "0", 2, "0"),
   ("LongPitch", "1", 2, "0"),
   ("LoudBlindspotAlert", "0", 0, "0"),
-  ("LowVoltageShutdown", str(VBATT_PAUSE_CHARGING), 3, str(VBATT_PAUSE_CHARGING)),
+  ("LowVoltageShutdown", str(VBATT_PAUSE_CHARGING), 2, str(VBATT_PAUSE_CHARGING)),
   ("MapAcceleration", "0", 1, "0"),
   ("MapboxPublicKey", "", 0, ""),
   ("MapboxSecretKey", "", 0, ""),
   ("MapDeceleration", "0", 1, "0"),
-  ("MapGears", "0", 2, "0"),
+  ("MapGears", "0", 1, "0"),
   ("MapsSelected", "", 0, ""),
   ("MapStyle", "1", 2, "0"),
   ("MaxDesiredAcceleration", "4.0", 2, "2.0"),
   ("MinimumLaneChangeSpeed", str(LANE_CHANGE_SPEED_MIN / CV.MPH_TO_MS), 2, str(LANE_CHANGE_SPEED_MIN / CV.MPH_TO_MS)),
-  ("Model", DEFAULT_MODEL + "_default", 1, DEFAULT_MODEL + "_default"),
+  ("Model", DEFAULT_MODEL, 1, DEFAULT_MODEL),
   ("ModelDrivesAndScores", "", 2, ""),
   ("ModelRandomizer", "0", 2, "0"),
+  ("ModelReleasedDates", "", 1, ""),
   ("ModelUI", "1", 2, "0"),
   ("ModelVersions", "", 2, ""),
+  ("SortModelsByDate", "0", 2, "0"),
   ("NavigationUI", "1", 1, "0"),
   ("NavSettingLeftSide", "0", 0, "0"),
   ("NavSettingTime24h", "0", 0, "0"),
-  ("NewLongAPI", "1", 3, "1"),
+  ("NewLongAPI", "0", 2, "1"),
   ("NNFF", "1", 2, "0"),
-  ("NNFFLite", "1", 2, "0"),
+  ("NNFFLite", "0", 2, "0"),
   ("NoLogging", "0", 2, "0"),
   ("NoUploads", "0", 2, "0"),
-  ("NudgelessLaneChange", "1", 0, "0"),
-  ("NumericalTemp", "1", 3, "0"),
+  ("NudgelessLaneChange", "0", 0, "0"),
+  ("NumericalTemp", "1", 2, "0"),
   ("Offset1", "5", 0, "0"),
   ("Offset2", "5", 0, "0"),
   ("Offset3", "5", 0, "0"),
@@ -300,15 +318,15 @@ frogpilot_default_params: list[tuple[str, str | bytes, int, str]] = [
   ("openpilotMinutes", "0", 0, "0"),
   ("PathEdgeWidth", "20", 2, "0"),
   ("PathWidth", "6.1", 2, "5.9"),
-  ("PauseAOLOnBrake", "0", 1, "0"),
-  ("PauseLateralOnSignal", "0", 1, "0"),
-  ("PauseLateralSpeed", "0", 1, "0"),
-  ("PedalsOnUI", "0", 1, "0"),
+  ("PauseAOLOnBrake", "0", 2, "0"),
+  ("PauseLateralOnSignal", "0", 2, "0"),
+  ("PauseLateralSpeed", "0", 2, "0"),
+  ("PedalsOnUI", "0", 2, "0"),
   ("PersonalizeOpenpilot", "1", 0, "0"),
   ("PreferredSchedule", "2", 0, "0"),
   ("PromptDistractedVolume", "101", 2, "101"),
   ("PromptVolume", "101", 2, "101"),
-  ("QOLLateral", "1", 1, "0"),
+  ("QOLLateral", "1", 2, "0"),
   ("QOLLongitudinal", "1", 1, "0"),
   ("QOLVisuals", "1", 0, "0"),
   ("RadarTracksUI", "0", 3, "0"),
@@ -318,19 +336,20 @@ frogpilot_default_params: list[tuple[str, str | bytes, int, str]] = [
   ("RecordFront", "0", 0, "0"),
   ("RefuseVolume", "101", 2, "101"),
   ("RelaxedFollow", "1.75", 2, "1.75"),
-  ("RelaxedJerkAcceleration", "100", 3, "100"),
+  ("RelaxedFollowHigh", "1.75", 2, "1.75"),
+  ("RelaxedJerkAcceleration", "50", 3, "50"),
   ("RelaxedJerkDanger", "100", 3, "100"),
-  ("RelaxedJerkDeceleration", "100", 3, "100"),
-  ("RelaxedJerkSpeed", "100", 3, "100"),
-  ("RelaxedJerkSpeedDecrease", "100", 3, "100"),
+  ("RelaxedJerkDeceleration", "50", 3, "50"),
+  ("RelaxedJerkSpeed", "50", 3, "50"),
+  ("RelaxedJerkSpeedDecrease", "50", 3, "50"),
   ("RelaxedPersonalityProfile", "1", 2, "0"),
-  ("ReverseCruise", "0", 1, "0"),
+  ("ReverseCruise", "1", 1, "0"),
   ("RoadEdgesWidth", "2", 2, "2"),
-  ("RoadNameUI", "1", 1, "0"),
+  ("RoadNameUI", "1", 2, "0"),
   ("RotatingWheel", "1", 1, "0"),
   ("ScreenBrightness", "101", 2, "101"),
   ("ScreenBrightnessOnroad", "101", 2, "101"),
-  ("ScreenManagement", "1", 1, "0"),
+  ("ScreenManagement", "1", 2, "0"),
   ("ScreenRecorder", "1", 2, "0"),
   ("ScreenTimeout", "30", 2, "30"),
   ("ScreenTimeoutOnroad", "30", 2, "10"),
@@ -348,13 +367,13 @@ frogpilot_default_params: list[tuple[str, str | bytes, int, str]] = [
   ("ShownToggleDescriptions", "", 0, ""),
   ("ShowSLCOffset", "1", 0, "0"),
   ("ShowSpeedLimits", "1", 1, "0"),
-  ("ShowSteering", "0", 3, "0"),
-  ("ShowStoppingPoint", "1", 3, "0"),
-  ("ShowStoppingPointMetrics", "1", 3, "0"),
+  ("ShowSteering", "1", 3, "0"),
+  ("ShowStoppingPoint", "0", 2, "0"),
+  ("ShowStoppingPointMetrics", "0", 2, "0"),
   ("ShowStorageLeft", "0", 3, "0"),
   ("ShowStorageUsed", "0", 3, "0"),
   ("Sidebar", "0", 0, "0"),
-  ("SignalMetrics", "0", 3, "0"),
+  ("SignalMetrics", "0", 2, "0"),
   ("SLCConfirmation", "0", 0, "0"),
   ("SLCConfirmationHigher", "0", 0, "0"),
   ("SLCConfirmationLower", "0", 0, "0"),
@@ -367,28 +386,31 @@ frogpilot_default_params: list[tuple[str, str | bytes, int, str]] = [
   ("SLCPriority2", "Map Data", 2, "Map Data"),
   ("SLCPriority3", "Dashboard", 2, "Dashboard"),
   ("SNGHack", "1", 2, "0"),
-  ("SpeedLimitChangedAlert", "0", 0, "0"),
+  ("SpeedLimitChangedAlert", "1", 0, "0"),
   ("SpeedLimitController", "1", 0, "0"),
   ("SpeedLimitFiller", "0", 0, "0"),
-  ("SpeedLimitSources", "0", 3, "0"),
+  ("SpeedLimitSources", "0", 2, "0"),
   ("SshEnabled", "0", 0, "0"),
   ("StartupMessageBottom", "Human-tested, frog-approved 🐸", 0, "Always keep hands on wheel and eyes on road"),
   ("StartupMessageTop", "Hop in and buckle up!", 0, "Be ready to take over at any time"),
   ("StandardFollow", "1.45", 2, "1.45"),
-  ("StandardJerkAcceleration", "100", 3, "100"),
+  ("StandardFollowHigh", "1.45", 2, "1.45"),
+  ("StandardJerkAcceleration", "50", 3, "50"),
   ("StandardJerkDanger", "100", 3, "100"),
-  ("StandardJerkDeceleration", "100", 3, "100"),
-  ("StandardJerkSpeed", "100", 3, "100"),
-  ("StandardJerkSpeedDecrease", "100", 3, "100"),
+  ("StandardJerkDeceleration", "50", 3, "50"),
+  ("StandardJerkSpeed", "50", 3, "50"),
+  ("StandardJerkSpeedDecrease", "50", 3, "50"),
   ("StandardPersonalityProfile", "1", 2, "0"),
-  ("StandbyMode", "0", 1, "0"),
+  ("StandbyMode", "0", 2, "0"),
   ("StartAccel", "", 3, ""),
   ("StartAccelStock", "", 3, ""),
-  ("StaticPedalsOnUI", "0", 1, "0"),
+  ("StaticPedalsOnUI", "0", 2, "0"),
   ("SteerDelay", "", 3, ""),
   ("SteerDelayStock", "", 3, ""),
   ("SteerFriction", "", 3, ""),
   ("SteerFrictionStock", "", 3, ""),
+  ("SteerOffset", "", 3, ""),
+  ("SteerOffsetStock", "", 3, ""),
   ("SteerKP", "", 3, ""),
   ("SteerKPStock", "", 3, ""),
   ("SteerLatAccel", "", 3, ""),
@@ -403,8 +425,6 @@ frogpilot_default_params: list[tuple[str, str | bytes, int, str]] = [
   ("TacoTune", "0", 2, "0"),
   ("TacoTuneHacks", "0", 2, "0"),
   ("TetheringEnabled", "0", 0, "0"),
-  ("ThemesDownloaded", "", 0, ""),
-  ("TinygradUpdateAvailable", "0", 1, "0"),
   ("ToyotaDoors", "1", 0, "0"),
   ("TrafficFollow", "0.5", 2, "0.5"),
   ("TrafficJerkAcceleration", "50", 3, "50"),
@@ -413,8 +433,8 @@ frogpilot_default_params: list[tuple[str, str | bytes, int, str]] = [
   ("TrafficJerkSpeed", "50", 3, "50"),
   ("TrafficJerkSpeedDecrease", "50", 3, "50"),
   ("TrafficPersonalityProfile", "1", 2, "0"),
-  ("TuningLevel", "0", 0, "0"),
-  ("TuningLevelConfirmed", "0", 0, "0"),
+  ("TuningLevel", "3", 0, "0"),
+  ("TuningLevelConfirmed", "1", 0, "0"),
   ("TurnDesires", "0", 2, "0"),
   ("UnlimitedLength", "1", 2, "0"),
   ("UnlockDoors", "1", 0, "0"),
@@ -431,7 +451,9 @@ frogpilot_default_params: list[tuple[str, str | bytes, int, str]] = [
   ("WarningImmediateVolume", "101", 2, "101"),
   ("WarningSoftVolume", "101", 2, "101"),
   ("WheelIcon", "frog", 0, "stock"),
-  ("WheelSpeed", "0", 2, "0")
+  ("WheelSpeed", "0", 2, "0"),
+  ("StopDistance", "6", 3, "6"),
+  ("RecoveryPower", "1.0", 2, "1.0")
 ]
 
 misc_tuning_levels: list[tuple[str, str | bytes, int, str]] = [
@@ -526,6 +548,10 @@ class FrogPilotVariables:
       safety_config.safetyModel = car.CarParams.SafetyModel.noOutput
       CP.safetyConfigs = [safety_config]
 
+    is_torque_car = CP.lateralTuning.which() == "torque"
+    if not is_torque_car:
+      CarInterfaceBase.configure_torque_tune(MOCK.MOCK, CP.lateralTuning)
+
     fpmsg_bytes = params.get("FrogPilotCarParams" if started else "FrogPilotCarParamsPersistent", block=started)
     if fpmsg_bytes:
       with custom.FrogPilotCarParams.from_bytes(fpmsg_bytes) as fpcp_reader:
@@ -534,40 +560,37 @@ class FrogPilotVariables:
       CarInterface, _, _ = interfaces[MOCK.MOCK]
       FPCP = CarInterface.get_frogpilot_params(MOCK.MOCK, gen_empty_fingerprint(), [], CP, toggle)
 
-    is_torque_car = FPCP.lateralTuning.which() == "torque"
-    if not is_torque_car:
-      CarInterfaceBase.configure_torque_tune(MOCK.MOCK, FPCP.lateralTuning)
 
     toggle.always_on_lateral_set = bool(CP.alternativeExperience & ALTERNATIVE_EXPERIENCE.ALWAYS_ON_LATERAL)
     toggle.car_make = CP.carName
     toggle.car_model = CP.carFingerprint
     toggle.disable_openpilot_long = params.get_bool("DisableOpenpilotLongitudinal") if tuning_level >= level["DisableOpenpilotLongitudinal"] else default.get_bool("DisableOpenpilotLongitudinal")
-    friction = FPCP.lateralTuning.torque.friction
-    has_auto_tune = toggle.car_make in {"hyundai", "toyota"} and FPCP.lateralTuning.which() == "torque"
+    friction = CP.lateralTuning.torque.friction
+    has_auto_tune = toggle.car_make in {"hyundai", "toyota"} and CP.lateralTuning.which() == "torque"
     has_bsm = CP.enableBsm
     toggle.has_cc_long = toggle.car_make == "gm" and bool(CP.flags & GMFlags.CC_LONG.value)
     has_nnff = nnff_supported(toggle.car_model)
     toggle.has_pedal = CP.enableGasInterceptor
     has_radar = not CP.radarUnavailable
     toggle.has_sdsu = toggle.car_make == "toyota" and bool(CP.flags & ToyotaFlags.SMART_DSU.value)
+    toggle.has_sascm = toggle.car_make == "gm" and bool(CP.flags & GMFlags.SASCM.value)
     has_sng = CP.autoResumeSng
     toggle.has_zss = toggle.car_make == "toyota" and bool(FPCP.fpFlags & ToyotaFrogPilotFlags.ZSS.value)
     is_angle_car = CP.steerControlType == car.CarParams.SteerControlType.angle
-    latAccelFactor = FPCP.lateralTuning.torque.latAccelFactor
+    latAccelFactor = CP.lateralTuning.torque.latAccelFactor
     longitudinalActuatorDelay = CP.longitudinalActuatorDelay
     toggle.openpilot_longitudinal = CP.openpilotLongitudinalControl and not toggle.disable_openpilot_long
     pcm_cruise = CP.pcmCruise
     startAccel = CP.startAccel
     stopAccel = CP.stopAccel
     steerActuatorDelay = CP.steerActuatorDelay
-    steerKp = FPCP.lateralTuning.torque.kp
+    steerKp = CP.lateralTuning.torque.kp
     steerRatio = CP.steerRatio
     toggle.stoppingDecelRate = CP.stoppingDecelRate
     taco_hacks_allowed = CP.safetyConfigs[0].safetyModel == SafetyModel.hyundaiCanfd
     toggle.use_lkas_for_aol = not toggle.openpilot_longitudinal and CP.safetyConfigs[0].safetyModel == SafetyModel.hyundaiCanfd
     toggle.vEgoStarting = CP.vEgoStarting
     toggle.vEgoStopping = CP.vEgoStopping
-
     msg_bytes = params.get("LiveTorqueParameters")
     if msg_bytes:
       with log.LiveTorqueParametersData.from_bytes(msg_bytes) as LTP:
@@ -594,6 +617,7 @@ class FrogPilotVariables:
     toggle.steerActuatorDelay = np.clip(params.get_float("SteerDelay"), 0.01, 1.0) if advanced_lateral_tuning and tuning_level >= level["SteerDelay"] else steerActuatorDelay
     toggle.use_custom_steerActuatorDelay = bool(round(toggle.steerActuatorDelay, 2) != round(steerActuatorDelay, 2))
     toggle.friction = np.clip(params.get_float("SteerFriction"), 0, 0.5) if advanced_lateral_tuning and tuning_level >= level["SteerFriction"] else friction
+    toggle.steer_offset = np.clip(params.get_float("SteerOffset"), -0.2, 0.2) if advanced_lateral_tuning and tuning_level >= level["SteerOffset"] and toggle.car_make == "gm" else 0.0
     toggle.use_custom_friction = bool(round(toggle.friction, 2) != round(friction, 2)) and is_torque_car and not toggle.force_auto_tune or toggle.force_auto_tune_off
     toggle.steerKp = [[0], [np.clip(params.get_float("SteerKP"), steerKp * 0.5, steerKp * 1.5) if advanced_lateral_tuning and is_torque_car and tuning_level >= level["SteerKP"] else steerKp]]
     toggle.latAccelFactor = np.clip(params.get_float("SteerLatAccel"), latAccelFactor * 0.75, latAccelFactor * 1.25) if advanced_lateral_tuning and tuning_level >= level["SteerLatAccel"] else latAccelFactor
@@ -602,6 +626,13 @@ class FrogPilotVariables:
     toggle.use_custom_steerRatio = bool(round(toggle.steerRatio, 2) != round(steerRatio, 2)) and not toggle.force_auto_tune or toggle.force_auto_tune_off
 
     advanced_longitudinal_tuning = params.get_bool("AdvancedLongitudinalTune") if tuning_level >= level["AdvancedLongitudinalTune"] else default.get_bool("AdvancedLongitudinalTune")
+    ev_vehicle = toggle.car_make == "gm" and not (toggle.car_model.startswith("CHEVROLET_VOLT") and not toggle.car_model.endswith("_CC")) and CP.carFingerprint in GM_EV_CAR or toggle.car_make == "hyundai" and CP.carFingerprint in HYUNDAI_EV_CAR
+    ev_vehicle |= CP.transmissionType == TransmissionType.direct
+
+    if params.get("EVTuning") == b"":
+      params.put_bool("EVTuning", ev_vehicle)
+
+    toggle.ev_tuning = params.get_bool("EVTuning") if advanced_longitudinal_tuning and tuning_level >= level["EVTuning"] else ev_vehicle
     toggle.longitudinalActuatorDelay = np.clip(params.get_float("LongitudinalActuatorDelay"), 0, 1) if advanced_longitudinal_tuning and tuning_level >= level["LongitudinalActuatorDelay"] else longitudinalActuatorDelay
     toggle.startAccel = np.clip(params.get_float("StartAccel"), 0, 4) if advanced_longitudinal_tuning and tuning_level >= level["StartAccel"] else startAccel
     toggle.stopAccel = np.clip(params.get_float("StopAccel"), -4, 0) if advanced_longitudinal_tuning and tuning_level >= level["StopAccel"] else stopAccel
@@ -609,6 +640,10 @@ class FrogPilotVariables:
     toggle.vEgoStarting = np.clip(params.get_float("VEgoStarting"), 0.01, 1) if advanced_longitudinal_tuning and tuning_level >= level["VEgoStarting"] else toggle.vEgoStarting
     toggle.vEgoStopping = np.clip(params.get_float("VEgoStopping"), 0.01, 1) if advanced_longitudinal_tuning and tuning_level >= level["VEgoStopping"] else toggle.vEgoStopping
 
+    toggle.stop_distance = params.get_float("StopDistance") if advanced_longitudinal_tuning and tuning_level >= level["StopDistance"] else 6.0
+
+    toggle.recovery_power = np.clip(params.get_float("RecoveryPower"), 0.5, 2.0) if advanced_longitudinal_tuning and tuning_level >= level["RecoveryPower"] else 1.0
+
     toggle.alert_volume_controller = params.get_bool("AlertVolumeControl") if tuning_level >= level["AlertVolumeControl"] else default.get_bool("AlertVolumeControl")
     toggle.disengage_volume = params.get_int("DisengageVolume") if toggle.alert_volume_controller and tuning_level >= level["DisengageVolume"] else default.get_int("DisengageVolume")
     toggle.engage_volume = params.get_int("EngageVolume") if toggle.alert_volume_controller and tuning_level >= level["EngageVolume"] else default.get_int("EngageVolume")
@@ -624,7 +659,7 @@ class FrogPilotVariables:
     toggle.always_on_lateral_main = toggle.always_on_lateral_set and not toggle.use_lkas_for_aol and (params.get_bool("AlwaysOnLateralMain") if tuning_level >= level["AlwaysOnLateralMain"] else default.get_bool("AlwaysOnLateralMain"))
     toggle.always_on_lateral_pause_speed = params.get_int("PauseAOLOnBrake") if toggle.always_on_lateral_set and tuning_level >= level["PauseAOLOnBrake"] else default.get_int("PauseAOLOnBrake")
 
-    toggle.automatic_updates = (params.get_bool("AutomaticUpdates") if tuning_level >= level["AutomaticUpdates"] and (self.release_branch or self.vetting_branch) else default.get_bool("AutomaticUpdates")) and not BACKUP_PATH.is_file()
+    toggle.automatic_updates = (params.get_bool("AutomaticUpdates") if tuning_level >= level["AutomaticUpdates"] else default.get_bool("AutomaticUpdates")) and not BACKUP_PATH.is_file()
 
     toggle.car_model = params.get("CarModel", encoding="utf-8") or toggle.car_model
 
@@ -664,28 +699,31 @@ class FrogPilotVariables:
     toggle.aggressive_jerk_danger = np.clip(params.get_int("AggressiveJerkDanger") / 100, 0.25, 2) if aggressive_profile and tuning_level >= level["AggressiveJerkDanger"] else default.get_int("AggressiveJerkDanger") / 100
     toggle.aggressive_jerk_speed = np.clip(params.get_int("AggressiveJerkSpeed") / 100, 0.25, 2) if aggressive_profile and tuning_level >= level["AggressiveJerkSpeed"] else default.get_int("AggressiveJerkSpeed") / 100
     toggle.aggressive_jerk_speed_decrease = np.clip(params.get_int("AggressiveJerkSpeedDecrease") / 100, 0.25, 2) if aggressive_profile and tuning_level >= level["AggressiveJerkSpeedDecrease"] else default.get_int("AggressiveJerkSpeedDecrease") / 100
-    toggle.aggressive_follow = np.clip(params.get_float("AggressiveFollow"), 1, MAX_T_FOLLOW) if aggressive_profile and tuning_level >= level["AggressiveFollow"] else default.get_float("AggressiveFollow")
+    toggle.aggressive_follow = [np.clip(params.get_float("AggressiveFollow"), 1, MAX_T_FOLLOW) if aggressive_profile and tuning_level >= level["AggressiveFollow"] else default.get_float("AggressiveFollow"),
+                                np.clip(params.get_float("AggressiveFollowHigh"), 1, MAX_T_FOLLOW) if aggressive_profile and tuning_level >= level["AggressiveFollowHigh"] else default.get_float("AggressiveFollowHigh")]
     standard_profile = toggle.custom_personalities and (params.get_bool("StandardPersonalityProfile") if tuning_level >= level["StandardPersonalityProfile"] else default.get_bool("StandardPersonalityProfile"))
     toggle.standard_jerk_acceleration = np.clip(params.get_int("StandardJerkAcceleration") / 100, 0.25, 2) if standard_profile and tuning_level >= level["StandardJerkAcceleration"] else default.get_int("StandardJerkAcceleration") / 100
     toggle.standard_jerk_deceleration = np.clip(params.get_int("StandardJerkDeceleration") / 100, 0.25, 2) if standard_profile and tuning_level >= level["StandardJerkDeceleration"] else default.get_int("StandardJerkDeceleration") / 100
     toggle.standard_jerk_danger = np.clip(params.get_int("StandardJerkDanger") / 100, 0.25, 2) if standard_profile and tuning_level >= level["StandardJerkDanger"] else default.get_int("StandardJerkDanger") / 100
     toggle.standard_jerk_speed = np.clip(params.get_int("StandardJerkSpeed") / 100, 0.25, 2) if standard_profile and tuning_level >= level["StandardJerkSpeed"] else default.get_int("StandardJerkSpeed") / 100
     toggle.standard_jerk_speed_decrease = np.clip(params.get_int("StandardJerkSpeedDecrease") / 100, 0.25, 2) if standard_profile and tuning_level >= level["StandardJerkSpeedDecrease"] else default.get_int("StandardJerkSpeedDecrease") / 100
-    toggle.standard_follow = np.clip(params.get_float("StandardFollow"), 1, MAX_T_FOLLOW) if standard_profile and tuning_level >= level["StandardFollow"] else default.get_float("StandardFollow")
+    toggle.standard_follow = [np.clip(params.get_float("StandardFollow"), 1, MAX_T_FOLLOW) if standard_profile and tuning_level >= level["StandardFollow"] else default.get_float("StandardFollow"),
+                              np.clip(params.get_float("StandardFollowHigh"), 1, MAX_T_FOLLOW) if standard_profile and tuning_level >= level["StandardFollowHigh"] else default.get_float("StandardFollowHigh")]
     relaxed_profile = toggle.custom_personalities and (params.get_bool("RelaxedPersonalityProfile") if tuning_level >= level["RelaxedPersonalityProfile"] else default.get_bool("RelaxedPersonalityProfile"))
     toggle.relaxed_jerk_acceleration = np.clip(params.get_int("RelaxedJerkAcceleration") / 100, 0.25, 2) if relaxed_profile and tuning_level >= level["RelaxedJerkAcceleration"] else default.get_int("RelaxedJerkAcceleration") / 100
     toggle.relaxed_jerk_deceleration = np.clip(params.get_int("RelaxedJerkDeceleration") / 100, 0.25, 2) if relaxed_profile and tuning_level >= level["RelaxedJerkDeceleration"] else default.get_int("RelaxedJerkDeceleration") / 100
     toggle.relaxed_jerk_danger = np.clip(params.get_int("RelaxedJerkDanger") / 100, 0.25, 2) if relaxed_profile and tuning_level >= level["RelaxedJerkDanger"] else default.get_int("RelaxedJerkDanger") / 100
     toggle.relaxed_jerk_speed = np.clip(params.get_int("RelaxedJerkSpeed") / 100, 0.25, 2) if relaxed_profile and tuning_level >= level["RelaxedJerkSpeed"] else default.get_int("RelaxedJerkSpeed") / 100
     toggle.relaxed_jerk_speed_decrease = np.clip(params.get_int("RelaxedJerkSpeedDecrease") / 100, 0.25, 2) if relaxed_profile and tuning_level >= level["RelaxedJerkSpeedDecrease"] else default.get_int("RelaxedJerkSpeedDecrease") / 100
-    toggle.relaxed_follow = np.clip(params.get_float("RelaxedFollow"), 1, MAX_T_FOLLOW) if relaxed_profile and tuning_level >= level["RelaxedFollow"] else default.get_float("RelaxedFollow")
+    toggle.relaxed_follow = [np.clip(params.get_float("RelaxedFollow"), 1, MAX_T_FOLLOW) if relaxed_profile and tuning_level >= level["RelaxedFollow"] else default.get_float("RelaxedFollow"),
+                             np.clip(params.get_float("RelaxedFollowHigh"), 1, MAX_T_FOLLOW) if relaxed_profile and tuning_level >= level["RelaxedFollowHigh"] else default.get_float("RelaxedFollowHigh")]
     traffic_profile = toggle.custom_personalities and (params.get_bool("TrafficPersonalityProfile") if tuning_level >= level["TrafficPersonalityProfile"] else default.get_bool("TrafficPersonalityProfile"))
     toggle.traffic_mode_jerk_acceleration = [np.clip(params.get_int("TrafficJerkAcceleration") / 100, 0.25, 2) if traffic_profile and tuning_level >= level["TrafficJerkAcceleration"] else default.get_int("TrafficJerkAcceleration") / 100, toggle.aggressive_jerk_acceleration]
     toggle.traffic_mode_jerk_deceleration = [np.clip(params.get_int("TrafficJerkDeceleration") / 100, 0.25, 2) if traffic_profile and tuning_level >= level["TrafficJerkDeceleration"] else default.get_int("TrafficJerkDeceleration") / 100, toggle.aggressive_jerk_deceleration]
     toggle.traffic_mode_jerk_danger = [np.clip(params.get_int("TrafficJerkDanger") / 100, 0.25, 2) if traffic_profile and tuning_level >= level["TrafficJerkDanger"] else default.get_int("TrafficJerkDanger") / 100, toggle.aggressive_jerk_danger]
     toggle.traffic_mode_jerk_speed = [np.clip(params.get_int("TrafficJerkSpeed") / 100, 0.25, 2) if traffic_profile and tuning_level >= level["TrafficJerkSpeed"] else default.get_int("TrafficJerkSpeed") / 100, toggle.aggressive_jerk_speed]
     toggle.traffic_mode_jerk_speed_decrease = [np.clip(params.get_int("TrafficJerkSpeedDecrease") / 100, 0.25, 2) if traffic_profile and tuning_level >= level["TrafficJerkSpeedDecrease"] else default.get_int("TrafficJerkSpeedDecrease") / 100, toggle.aggressive_jerk_speed_decrease]
-    toggle.traffic_mode_follow = [np.clip(params.get_float("TrafficFollow"), 0.5, MAX_T_FOLLOW) if traffic_profile and tuning_level >= level["TrafficFollow"] else default.get_float("TrafficFollow"), toggle.aggressive_follow]
+    toggle.traffic_mode_follow = [np.clip(params.get_float("TrafficFollow"), 0.5, MAX_T_FOLLOW) if traffic_profile and tuning_level >= level["TrafficFollow"] else default.get_float("TrafficFollow"), toggle.aggressive_follow[0]]
 
     custom_ui = params.get_bool("CustomUI") if tuning_level >= level["CustomUI"] else default.get_bool("CustomUI")
     toggle.acceleration_path = toggle.openpilot_longitudinal and (custom_ui and (params.get_bool("AccelerationPath") if tuning_level >= level["AccelerationPath"] else default.get_bool("AccelerationPath")) or toggle.debug_mode)
@@ -814,33 +852,49 @@ class FrogPilotVariables:
     toggle.human_following = longitudinal_tuning and (params.get_bool("HumanFollowing") if tuning_level >= level["HumanFollowing"] else default.get_bool("HumanFollowing"))
     toggle.lead_detection_probability = np.clip(params.get_int("LeadDetectionThreshold") / 100, 0.25, 0.50) if longitudinal_tuning and tuning_level >= level["LeadDetectionThreshold"] else default.get_int("LeadDetectionThreshold") / 100
     toggle.max_desired_acceleration = np.clip(params.get_float("MaxDesiredAcceleration"), 0.1, 4.0) if longitudinal_tuning and tuning_level >= level["MaxDesiredAcceleration"] else default.get_float("MaxDesiredAcceleration")
+    toggle.trailer_load_kg = (np.clip(params.get_int("TrailerLoad"), 0, 15000) if longitudinal_tuning and tuning_level >= level["TrailerLoad"] else default.get_int("TrailerLoad")) * CV.LB_TO_KG
     toggle.taco_tune = longitudinal_tuning and (params.get_bool("TacoTune") if tuning_level >= level["TacoTune"] else default.get_bool("TacoTune"))
 
-    toggle.available_models = (params.get("AvailableModels", encoding="utf-8") or "") + f",{DEFAULT_MODEL}"
-    toggle.available_model_names = (params.get("AvailableModelNames", encoding="utf-8") or "") + f",{DEFAULT_MODEL_NAME}"
-    downloaded_models = [model for model in toggle.available_models.split(",") if (MODELS_PATH / f"{model}.thneed").is_file() or all((MODELS_PATH / f"{model}_{filename}").is_file() for filename, _ in TINYGRAD_FILES)]
-    model_versions = (params.get("ModelVersions", encoding="utf-8") or "") + f",{DEFAULT_MODEL_VERSION}"
-    toggle.model_randomizer = params.get_bool("ModelRandomizer") if tuning_level >= level["ModelRandomizer"] else default.get_bool("ModelRandomizer")
-    if toggle.model_randomizer:
-      if not started:
-        blacklisted_models = (params.get("BlacklistedModels", encoding="utf-8") or "").split(",")
-        selectable_models = [model for model in downloaded_models if model not in blacklisted_models]
-        toggle.model = random.choice(selectable_models) if selectable_models else DEFAULT_MODEL
-        toggle.model_name = "Mystery Model 👻"
-        toggle.model_version = model_versions.split(",")[toggle.available_models.split(",").index(toggle.model)]
-    else:
-      model = ((params.get("Model", encoding="utf-8") if tuning_level >= level["Model"] else default.get("Model", encoding="utf-8")) or DEFAULT_MODEL).removesuffix("_default")
-      if model in downloaded_models:
-        toggle.model = model
-        toggle.model_name = dict(zip(toggle.available_models.split(","), toggle.available_model_names.split(",")))[toggle.model]
-        toggle.model_version = dict(zip(toggle.available_models.split(","), model_versions.split(",")))[toggle.model]
+    toggle.available_models = params.get("AvailableModels", encoding="utf-8") or ""
+    toggle.available_model_names = params.get("AvailableModelNames", encoding="utf-8") or ""
+    toggle.available_model_series = params.get("AvailableModelSeries", encoding="utf-8") or ""
+    toggle.community_favorites = params.get("CommunityFavorites", encoding="utf-8") or ""
+    toggle.model_released_dates = params.get("ModelReleasedDates", encoding="utf-8") or ""
+    toggle.model_versions = params.get("ModelVersions", encoding="utf-8") or ""
+    toggle.sort_models_by_date = params.get_bool("SortModelsByDate") if tuning_level >= level["SortModelsByDate"] else default.get_bool("SortModelsByDate")
+    toggle.user_favorites = params.get("UserFavorites", encoding="utf-8") or ""
+    downloaded_models = [model for model in toggle.available_models.split(",") if any(MODELS_PATH.glob(f"{model}*"))]
+    toggle.model_randomizer = downloaded_models and (params.get_bool("ModelRandomizer") if tuning_level >= level["ModelRandomizer"] else default.get_bool("ModelRandomizer"))
+    if toggle.available_models and toggle.available_model_names and downloaded_models and toggle.model_versions:
+      if DEFAULT_MODEL not in toggle.available_models.split(","):
+        toggle.available_models += f",{DEFAULT_MODEL}"
+        toggle.available_model_names += f",{DEFAULT_MODEL_NAME}"
+        toggle.model_versions += f",{DEFAULT_MODEL_VERSION}"
+        downloaded_models += [DEFAULT_MODEL]
+      if toggle.model_randomizer:
+        if not started:
+          blacklisted_models = (params.get("BlacklistedModels", encoding="utf-8") or "").split(",")
+          selectable_models = [model for model in downloaded_models if model not in blacklisted_models]
+          toggle.model = random.choice(selectable_models) if selectable_models else default.get("Model", encoding="utf-8")
+          toggle.model_name = "Mystery Model 👻"
+          toggle.model_version = toggle.model_versions.split(",")[toggle.available_models.split(",").index(toggle.model)]
       else:
+        toggle.model = params.get("Model", encoding="utf-8") if tuning_level >= level["Model"] else default.get("Model", encoding="utf-8")
+        if toggle.model in downloaded_models:
+          toggle.model_name = toggle.available_model_names.split(",")[toggle.available_models.split(",").index(toggle.model)]
+          toggle.model_version = toggle.model_versions.split(",")[toggle.available_models.split(",").index(toggle.model)]
+        else:
+          toggle.model = default.get("Model", encoding="utf-8")
+          toggle.model_name = toggle.available_model_names.split(",")[toggle.available_models.split(",").index(toggle.model)]
+          toggle.model_version = toggle.model_versions.split(",")[toggle.available_models.split(",").index(toggle.model)]
+    else:
         toggle.model = DEFAULT_MODEL
         toggle.model_name = DEFAULT_MODEL_NAME
         toggle.model_version = DEFAULT_MODEL_VERSION
+    toggle.classic_longitudinal = toggle.model_version in {"v1", "v2", "v3", "v4"}
     toggle.classic_model = toggle.model_version in {"v1", "v2", "v3", "v4"}
-    toggle.classic_longitudinal = toggle.model_version in {"v1", "v2", "v3", "v4", "v5", "v6"}
-    toggle.tinygrad_model = not toggle.classic_model and toggle.model_version not in {"v5", "v6"}
+    toggle.tinygrad_model = toggle.model_version in {"v8", "v9", "v10", "v11", "v12"}
+    toggle.tomb_raider = toggle.model == "space-lab"
 
     toggle.model_ui = params.get_bool("ModelUI") if tuning_level >= level["ModelUI"] else default.get_bool("ModelUI")
     toggle.dynamic_path_width = toggle.model_ui and (params.get_bool("DynamicPathWidth") if tuning_level >= level["DynamicPathWidth"] else default.get_bool("DynamicPathWidth"))
@@ -906,7 +960,6 @@ class FrogPilotVariables:
     toggle.screen_timeout = params.get_int("ScreenTimeout") if screen_management and tuning_level >= level["ScreenTimeout"] else default.get_int("ScreenTimeout")
     toggle.screen_timeout_onroad = params.get_int("ScreenTimeoutOnroad") if screen_management and tuning_level >= level["ScreenTimeoutOnroad"] else default.get_int("ScreenTimeoutOnroad")
     toggle.standby_mode = screen_management and (params.get_bool("StandbyMode") if tuning_level >= level["StandbyMode"] else default.get_bool("StandbyMode"))
-
     toggle.sng_hack = toggle.openpilot_longitudinal and toggle.car_make == "toyota" and not toggle.has_pedal and not has_sng and (params.get_bool("SNGHack") if tuning_level >= level["SNGHack"] else default.get_bool("SNGHack"))
 
     toggle.speed_limit_controller = toggle.openpilot_longitudinal and (params.get_bool("SpeedLimitController") if tuning_level >= level["SpeedLimitController"] else default.get_bool("SpeedLimitController"))
@@ -953,7 +1006,16 @@ class FrogPilotVariables:
     toggle.lock_doors = toyota_doors and (params.get_bool("LockDoors") if tuning_level >= level["LockDoors"] else default.get_bool("LockDoors"))
     toggle.unlock_doors = toyota_doors and (params.get_bool("UnlockDoors") if tuning_level >= level["UnlockDoors"] else default.get_bool("UnlockDoors"))
 
-    toggle.volt_sng = toggle.car_model == "CHEVROLET_VOLT" and (params.get_bool("VoltSNG") if tuning_level >= level["VoltSNG"] else default.get_bool("VoltSNG"))
+    volt_models = {
+      "CHEVROLET_VOLT",
+      "CHEVROLET_VOLT_2019",
+      "CHEVROLET_VOLT_ASCM",
+      "CHEVROLET_VOLT_CAMERA",
+    }
+
+    toggle.volt_sng = toggle.car_model in volt_models and (params.get_bool("VoltSNG") if tuning_level >= level["VoltSNG"] else default.get_bool("VoltSNG"))
+
+    toggle.gm_pedal_longitudinal = params.get_bool("GMPedalLongitudinal") if tuning_level >= level["GMPedalLongitudinal"] else default.get_bool("GMPedalLongitudinal")
 
     params_memory.put("FrogPilotToggles", json.dumps(toggle.__dict__))
     params_memory.remove("FrogPilotTogglesUpdated")

frogpilot/controls/frogpilot_planner.py

@@ -9,7 +9,7 @@ from openpilot.common.conversions import Conversions as CV
 from openpilot.common.filter_simple import FirstOrderFilter
 from openpilot.common.realtime import DT_MDL
 from openpilot.selfdrive.controls.lib.drive_helpers import V_CRUISE_MAX
-from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import A_CHANGE_COST, DANGER_ZONE_COST, J_EGO_COST, STOP_DISTANCE
+from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import A_CHANGE_COST, COMFORT_BRAKE, DANGER_ZONE_COST, J_EGO_COST
 
 from openpilot.frogpilot.common.frogpilot_utilities import calculate_lane_width, calculate_road_curvature
 from openpilot.frogpilot.common.frogpilot_variables import CRUISING_SPEED, MINIMUM_LATERAL_ACCELERATION, PLANNER_TIME, THRESHOLD, params, params_memory
@@ -65,6 +65,8 @@ class FrogPilotPlanner:
       self.cem.curve_detected = False
       self.cem.stop_sign_and_light(v_ego, sm, PLANNER_TIME - 2)
 
+
+
     self.driving_in_curve = abs(self.lateral_acceleration) >= MINIMUM_LATERAL_ACCELERATION
 
     self.frogpilot_events.update(v_cruise, sm, frogpilot_toggles)
@@ -85,7 +87,7 @@ class FrogPilotPlanner:
 
       params_memory.remove("LastGPSPosition")
 
-    self.lateral_acceleration = v_ego**2 * (sm["carState"].steeringAngleDeg - sm["liveParameters"].angleOffsetDeg) * CV.DEG_TO_RAD / (self.CP.steerRatio * self.CP.wheelbase)
+    self.lateral_acceleration = v_ego**2 * sm["controlsState"].curvature
 
     check_lane_width = frogpilot_toggles.adjacent_paths or frogpilot_toggles.adjacent_path_metrics or frogpilot_toggles.blind_spot_path or frogpilot_toggles.lane_detection
     if check_lane_width and v_ego >= frogpilot_toggles.minimum_lane_change_speed:
@@ -115,7 +117,9 @@ class FrogPilotPlanner:
 
   def update_lead_status(self):
     following_lead = self.lead_one.status
-    following_lead &= self.lead_one.dRel < self.model_length + STOP_DISTANCE
+    from frogpilot.common.frogpilot_variables import get_frogpilot_toggles
+    fp_toggles = get_frogpilot_toggles()
+    following_lead &= self.lead_one.dRel < self.model_length + fp_toggles.stop_distance
 
     self.tracking_lead_filter.update(following_lead)
     return self.tracking_lead_filter.x >= THRESHOLD
@@ -138,6 +142,8 @@ class FrogPilotPlanner:
 
     frogpilotPlan.desiredFollowDistance = self.frogpilot_following.desired_follow_distance
 
+    frogpilotPlan.disableThrottle = self.frogpilot_following.disable_throttle
+
     frogpilotPlan.experimentalMode = self.cem.experimental_mode or self.frogpilot_vcruise.slc.experimental_mode
 
     frogpilotPlan.forcingStop = self.frogpilot_vcruise.forcing_stop

frogpilot/controls/lib/conditional_experimental_mode.py

@@ -1,20 +1,54 @@
 #!/usr/bin/env python3
 from openpilot.common.filter_simple import FirstOrderFilter
 from openpilot.common.realtime import DT_MDL
+from openpilot.common.numpy_fast import interp
+from openpilot.common.conversions import Conversions as CV
 
-from openpilot.frogpilot.common.frogpilot_variables import CITY_SPEED_LIMIT, CRUISING_SPEED, THRESHOLD, params_memory
+from openpilot.frogpilot.common.frogpilot_variables import CITY_SPEED_LIMIT, CRUISING_SPEED, THRESHOLD, params_memory, scale_threshold
 
 class ConditionalExperimentalMode:
+  # ===== CONDITIONAL EXPERIMENTAL MODE SPEED-BASED TUNING =====
+  # Speed ranges: [0-35, 35-55, 55-70, 70+ mph]
+
+  # FILTER TIME CONSTANTS (Lower = More responsive, Higher = Smoother)
+  # [City, Urban Hwy, Rural Hwy, High Speed]
+  FILTER_TIME_CURVES = [0.9, 0.8, 0.6, 0.5]    # Faster detection at highway speeds
+  FILTER_TIME_LEADS = [0.9, 0.8, 0.7, 0.5]     # Less sensitive at 70+ mph for slow leads
+  FILTER_TIME_LIGHTS = [0.9, 0.8, 0.75, 0.55]  # Less sensitive at 60+ mph for stoplights
+
+  # HIGHWAY LIGHT DETECTION MULTIPLIERS
+  # How much to increase model stop time at highway speeds
+  LIGHT_BOOSTS = [1.0, 1.2, 1.1, 1.0]         # Keep conservative boost for highest speeds
+  LIGHT_SPEED_LOW = 50 * CV.MPH_TO_MS     # 50 mph threshold
+  LIGHT_SPEED_HIGH = 60 * CV.MPH_TO_MS    # 60 mph threshold
+  LIGHT_MAX_TIME = 9       # Balanced max time preserving city performance
+
+  # ===== END TUNING PARAMETERS =====
+
+  # Current active values
+  FILTER_TIME_CURVE = 0.8
+  FILTER_TIME_LEAD = 0.8
+  FILTER_TIME_LIGHT = 0.8
+  LIGHT_BOOST_LOW = 1.15
+  LIGHT_BOOST_HIGH = 1.2
+
+  @staticmethod
+  def get_speed_based_param(speed_mph, param_array):
+    """Get parameter value based on current speed using smooth interpolation between breakpoints [0, 35, 55, 70]"""
+    return interp(speed_mph, [0, 35, 55, 70], param_array)
+
   def __init__(self, FrogPilotPlanner):
     self.frogpilot_planner = FrogPilotPlanner
 
-    self.curvature_filter = FirstOrderFilter(0, 1, DT_MDL)
-    self.slow_lead_filter = FirstOrderFilter(0, 1, DT_MDL)
-    self.stop_light_filter = FirstOrderFilter(0, 0.5, DT_MDL)
+    # Faster filters with hysteresis for better responsiveness
+    self.curvature_filter = FirstOrderFilter(0, self.FILTER_TIME_CURVE, DT_MDL)
+    self.slow_lead_filter = FirstOrderFilter(0, self.FILTER_TIME_LEAD, DT_MDL)
+    self.stop_light_filter = FirstOrderFilter(0, self.FILTER_TIME_LIGHT, DT_MDL)
 
     self.curve_detected = False
     self.experimental_mode = False
     self.stop_light_detected = False
+    self.prev_experimental_mode = False  # For hysteresis
 
   def update(self, v_ego, sm, frogpilot_toggles):
     if frogpilot_toggles.experimental_mode_via_press:
@@ -24,9 +58,26 @@ class ConditionalExperimentalMode:
 
     if self.status_value not in {1, 2} and not sm["carState"].standstill:
       self.update_conditions(v_ego, sm, frogpilot_toggles)
+      new_experimental_mode = self.check_conditions(v_ego, sm, frogpilot_toggles)
+
+      # Add hysteresis to prevent rapid toggling
+      if new_experimental_mode and not self.prev_experimental_mode:
+        # Require weaker conditions to turn on
+        hysteresis_factor = 0.9
+      elif not new_experimental_mode and self.prev_experimental_mode:
+        # Require stronger conditions to turn off
+        hysteresis_factor = 1.2
+      else:
+        hysteresis_factor = 1.0
+
+      # Apply hysteresis to key conditions
+      if hasattr(self, 'slow_lead_detected'):
+        self.slow_lead_detected = self.slow_lead_detected if hysteresis_factor == 1.0 else (self.slow_lead_filter.x >= scale_threshold(v_ego) * hysteresis_factor)
+      if hasattr(self, 'curve_detected'):
+        self.curve_detected = self.curve_detected if hysteresis_factor == 1.0 else (self.curvature_filter.x >= THRESHOLD * hysteresis_factor)
 
       self.experimental_mode = self.check_conditions(v_ego, sm, frogpilot_toggles)
-
+      self.prev_experimental_mode = self.experimental_mode
       params_memory.put_int("CEStatus", self.status_value if self.experimental_mode else 0)
     else:
       self.experimental_mode = self.status_value == 2 or sm["carState"].standstill and self.experimental_mode and self.frogpilot_planner.model_stopped
@@ -55,7 +106,7 @@ class ConditionalExperimentalMode:
       self.status_value = 8
       return True
 
-    if frogpilot_toggles.conditional_lead and self.slow_lead_detected:
+    if frogpilot_toggles.conditional_lead and self.slow_lead_detected and v_ego <= 35.31:
       self.status_value = 9 if self.frogpilot_planner.lead_one.vLead < 1 else 10
       return True
 
@@ -71,30 +122,70 @@ class ConditionalExperimentalMode:
 
   def update_conditions(self, v_ego, sm, frogpilot_toggles):
     self.curve_detection(v_ego, frogpilot_toggles)
-    self.slow_lead(frogpilot_toggles)
+    self.slow_lead(frogpilot_toggles, v_ego)
     self.stop_sign_and_light(v_ego, sm, frogpilot_toggles.conditional_model_stop_time)
 
   def curve_detection(self, v_ego, frogpilot_toggles):
     self.curvature_filter.update(self.frogpilot_planner.road_curvature_detected or self.frogpilot_planner.driving_in_curve)
     self.curve_detected = self.curvature_filter.x >= THRESHOLD and v_ego > CRUISING_SPEED
 
-  def slow_lead(self, frogpilot_toggles):
+  def slow_lead(self, frogpilot_toggles, v_ego):
     if self.frogpilot_planner.tracking_lead:
       slower_lead = frogpilot_toggles.conditional_slower_lead and self.frogpilot_planner.frogpilot_following.slower_lead
       stopped_lead = frogpilot_toggles.conditional_stopped_lead and self.frogpilot_planner.lead_one.vLead < 1
+      lead_threshold = scale_threshold(v_ego)
+
+      # Adjust threshold based on lead probability for vision-only accuracy
+      lead_prob = getattr(self.frogpilot_planner.lead_one, 'modelProb', 1.0)
+      adjusted_threshold = lead_threshold * (1.0 + 0.2 * (1.0 - lead_prob))  # Higher threshold for lower confidence
 
       self.slow_lead_filter.update(slower_lead or stopped_lead)
-      self.slow_lead_detected = self.slow_lead_filter.x >= THRESHOLD
+      self.slow_lead_detected = self.slow_lead_filter.x >= adjusted_threshold
     else:
       self.slow_lead_filter.x = 0
       self.slow_lead_detected = False
 
   def stop_sign_and_light(self, v_ego, sm, model_time):
     if not sm["frogpilotCarState"].trafficModeEnabled:
-      model_stopping = self.frogpilot_planner.model_length < v_ego * model_time
+      speed_mph = v_ego * CV.MS_TO_MPH  # Convert m/s to mph
+
+      # Interp for smooth scaling in 35-45 mph
+      bp = [0, 35, 45]
+      low_filter_time = 0.0  # No filtering under 35 mph
+      tuned_filter_time_curves = self.FILTER_TIME_CURVES[1]  # At 35-55 mph
+      tuned_filter_time_leads = self.FILTER_TIME_LEADS[1]
+      tuned_filter_time_lights = self.FILTER_TIME_LIGHTS[1]
+      low_boost = 1.0
+      tuned_boost = self.LIGHT_BOOSTS[1]
+      low_cap_factor = 0.0  # No cap under 35 mph
+      tuned_cap_factor = 1.0
+
+      filter_time_curves = interp(speed_mph, bp, [low_filter_time, low_filter_time, tuned_filter_time_curves])
+      filter_time_leads = interp(speed_mph, bp, [low_filter_time, low_filter_time, tuned_filter_time_leads])
+      filter_time_lights = interp(speed_mph, bp, [low_filter_time, low_filter_time, tuned_filter_time_lights])
+      light_boost = interp(speed_mph, bp, [low_boost, low_boost, tuned_boost])
+      cap_factor = interp(speed_mph, bp, [low_cap_factor, low_cap_factor, tuned_cap_factor])
+
+      # Update filter times with interp
+      self.curvature_filter = FirstOrderFilter(self.curvature_filter.x, filter_time_curves, DT_MDL)
+      self.slow_lead_filter = FirstOrderFilter(self.slow_lead_filter.x, filter_time_leads, DT_MDL)
+      self.stop_light_filter = FirstOrderFilter(self.stop_light_filter.x, filter_time_lights, DT_MDL)
+
+      # Disable stoplight detection at very high speeds to prevent false positives
+      if speed_mph > 75:  # Disable above 75 mph
+        self.stop_light_filter.x = 0
+        self.stop_light_detected = False
+        return
+
+      # Adjust model time with interp boost and gradual cap
+      adjusted_model_time = model_time * light_boost
+      if cap_factor > 0:
+        adjusted_model_time = min(adjusted_model_time, self.LIGHT_MAX_TIME * cap_factor + model_time * (1 - cap_factor))  # Gradual cap
+
+      model_stopping = self.frogpilot_planner.model_length < v_ego * adjusted_model_time
 
       self.stop_light_filter.update(self.frogpilot_planner.model_stopped or model_stopping)
-      self.stop_light_detected = self.stop_light_filter.x >= THRESHOLD and not self.frogpilot_planner.tracking_lead
+      self.stop_light_detected = self.stop_light_filter.x >= THRESHOLD**2 and not self.frogpilot_planner.tracking_lead
     else:
       self.stop_light_filter.x = 0
       self.stop_light_detected = False

frogpilot/controls/lib/frogpilot_acceleration.py

@@ -1,33 +1,73 @@
 #!/usr/bin/env python3
 import numpy as np
 
-from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import CRUISE_MIN_ACCEL
-from openpilot.selfdrive.controls.lib.longitudinal_planner import ACCEL_MIN, get_max_accel
+def cubic_interp(x, xp, fp):
+     """Cubic interpolation using NumPy's native operations for speed."""
+     # Boundary conditions
+     if x <= xp[0]:
+         return fp[0]
+     elif x >= xp[-1]:
+         return fp[-1]
+
+     # Find interval
+     i = np.searchsorted(xp, x) - 1
+     i = max(0, min(i, len(xp)-2))  # clamp the index
+
+     # Normalized position
+     t = (x - xp[i]) / float(xp[i+1] - xp[i])
+
+     # Hermite cubic formula
+     return fp[i]*(1 - 3*t**2 + 2*t**3) + fp[i+1]*(3*t**2 - 2*t**3)
+
+def akima_interp(x, xp, fp):
+     """Akima-inspired interpolation with reduced overshoot characteristics."""
+     if x <= xp[0]:
+         return fp[0]
+     elif x >= xp[-1]:
+         return fp[-1]
+
+     i = np.searchsorted(xp, x) - 1
+     i = max(0, min(i, len(xp)-2))  # clamp the index
+
+     t = (x - xp[i]) / float(xp[i+1] - xp[i])
+
+     # Quintic polynomial to reduce overshoot
+     t2 = t*t
+     t4 = t2*t2
+     t3 = t2*t
+     return (fp[i]*(1 - 10*t3 + 15*t4 - 6*t3*t2)
+             + fp[i+1]*(10*t3 - 15*t4 + 6*t3*t2))
+
+from openpilot.selfdrive.controls.lib.longitudinal_planner import A_CRUISE_MIN, get_max_accel
 
 from openpilot.frogpilot.common.frogpilot_variables import CITY_SPEED_LIMIT
 
-A_CRUISE_MIN_ECO =   CRUISE_MIN_ACCEL / 2
-A_CRUISE_MIN_SPORT = CRUISE_MIN_ACCEL * 2
+A_CRUISE_MIN_ECO =   A_CRUISE_MIN / 2
+A_CRUISE_MIN_SPORT = A_CRUISE_MIN * 2
 
-                  # MPH = [0.0,  11,  22,  34,  45,  56,  89]
-A_CRUISE_MAX_BP_CUSTOM =  [0.0,  5., 10., 15., 20., 25., 40.]
-A_CRUISE_MAX_VALS_ECO =   [2.0, 1.5, 1.0, 0.8, 0.6, 0.4, 0.2]
-A_CRUISE_MAX_VALS_SPORT = [3.0, 2.5, 2.0, 1.5, 1.0, 0.8, 0.6]
+                       # MPH = [0.0,  11,  22,  34,  45,  56,  89]
+A_CRUISE_MAX_BP_CUSTOM =       [0.0,  5., 10., 15., 20., 25., 40.]
+A_CRUISE_MAX_VALS_ECO_EV =     [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
+A_CRUISE_MAX_VALS_SPORT_EV =   [1.25, 1.25, 1.25, 1.25, 1.5, 1.5, 2.0]
+A_CRUISE_MAX_VALS_ECO_GAS =    [2.0, 1.5, 1.0, 0.8, 0.6, 0.4, 0.2]
+A_CRUISE_MAX_VALS_SPORT_GAS =  [3.0, 2.5, 2.0, 1.5, 1.0, 0.8, 0.6]
 
-def get_max_accel_eco(v_ego):
-  return float(np.interp(v_ego, A_CRUISE_MAX_BP_CUSTOM, A_CRUISE_MAX_VALS_ECO))
+def get_max_accel_eco(v_ego, ev_tuning=True):
+  cruise_vals = A_CRUISE_MAX_VALS_ECO_EV if ev_tuning else A_CRUISE_MAX_VALS_ECO_GAS
+  return float(akima_interp(v_ego, A_CRUISE_MAX_BP_CUSTOM, cruise_vals))
 
-def get_max_accel_sport(v_ego):
-  return float(np.interp(v_ego, A_CRUISE_MAX_BP_CUSTOM, A_CRUISE_MAX_VALS_SPORT))
+def get_max_accel_sport(v_ego, ev_tuning=True):
+  cruise_vals = A_CRUISE_MAX_VALS_SPORT_EV if ev_tuning else A_CRUISE_MAX_VALS_SPORT_GAS
+  return float(akima_interp(v_ego, A_CRUISE_MAX_BP_CUSTOM, cruise_vals))
 
 def get_max_accel_low_speeds(max_accel, v_cruise):
-  return float(np.interp(v_cruise, [0., CITY_SPEED_LIMIT / 2, CITY_SPEED_LIMIT], [max_accel / 4, max_accel / 2, max_accel]))
+  return float(akima_interp(v_cruise, [0., CITY_SPEED_LIMIT / 2, CITY_SPEED_LIMIT], [max_accel / 4, max_accel / 2, max_accel]))
 
 def get_max_accel_ramp_off(max_accel, v_cruise, v_ego):
-  return float(np.interp(v_cruise - v_ego, [0., 1., 5.], [0., 0.5, max_accel]))
+  return float(akima_interp(v_cruise - v_ego, [0., 1., 5., 10.], [0., 0.5, 1.0, max_accel]))
 
 def get_max_allowed_accel(v_ego):
-  return float(np.interp(v_ego, [0., 5., 20.], [4.0, 4.0, 2.0]))  # ISO 15622:2018
+  return float(akima_interp(v_ego, [0., 5., 20.], [4.0, 4.0, 2.0]))  # ISO 15622:2018
 
 class FrogPilotAcceleration:
   def __init__(self, FrogPilotPlanner):
@@ -39,22 +79,23 @@ class FrogPilotAcceleration:
   def update(self, v_ego, sm, frogpilot_toggles):
     eco_gear = sm["frogpilotCarState"].ecoGear
     sport_gear = sm["frogpilotCarState"].sportGear
+    ev_tuning = frogpilot_toggles.ev_tuning
 
     if sm["frogpilotCarState"].trafficModeEnabled:
       self.max_accel = get_max_accel(v_ego)
     elif frogpilot_toggles.map_acceleration and (eco_gear or sport_gear):
       if eco_gear:
-        self.max_accel = get_max_accel_eco(v_ego)
+        self.max_accel = get_max_accel_eco(v_ego, ev_tuning)
       else:
         if frogpilot_toggles.acceleration_profile == 2:
-          self.max_accel = get_max_accel_sport(v_ego)
+          self.max_accel = get_max_accel_sport(v_ego, ev_tuning)
         else:
           self.max_accel = get_max_allowed_accel(v_ego)
     else:
       if frogpilot_toggles.acceleration_profile == 1:
-        self.max_accel = get_max_accel_eco(v_ego)
+        self.max_accel = get_max_accel_eco(v_ego, ev_tuning)
       elif frogpilot_toggles.acceleration_profile == 2:
-        self.max_accel = get_max_accel_sport(v_ego)
+        self.max_accel = get_max_accel_sport(v_ego, ev_tuning)
       elif frogpilot_toggles.acceleration_profile == 3:
         self.max_accel = get_max_allowed_accel(v_ego)
       else:
@@ -64,9 +105,7 @@ class FrogPilotAcceleration:
       self.max_accel = min(get_max_accel_low_speeds(self.max_accel, self.frogpilot_planner.v_cruise), self.max_accel)
       self.max_accel = min(get_max_accel_ramp_off(self.max_accel, self.frogpilot_planner.v_cruise, v_ego), self.max_accel)
 
-    if self.frogpilot_planner.tracking_lead:
-      self.min_accel = ACCEL_MIN
-    elif sm["frogpilotCarState"].forceCoast:
+    if sm["frogpilotCarState"].forceCoast:
       self.min_accel = A_CRUISE_MIN_ECO
     elif frogpilot_toggles.map_deceleration and (eco_gear or sport_gear):
       if eco_gear:
@@ -79,4 +118,4 @@ class FrogPilotAcceleration:
       elif frogpilot_toggles.deceleration_profile == 2:
         self.min_accel = A_CRUISE_MIN_SPORT
       else:
-        self.min_accel = CRUISE_MIN_ACCEL
+        self.min_accel = A_CRUISE_MIN

frogpilot/controls/lib/frogpilot_following.py

@@ -1,16 +1,19 @@
 #!/usr/bin/env python3
 import numpy as np
 
-from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import COMFORT_BRAKE, STOP_DISTANCE, desired_follow_distance, get_jerk_factor, get_T_FOLLOW
+from openpilot.common.conversions import Conversions as CV
+from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import COMFORT_BRAKE, desired_follow_distance, get_jerk_factor, get_T_FOLLOW
 
 from openpilot.frogpilot.common.frogpilot_variables import CITY_SPEED_LIMIT
 
 TRAFFIC_MODE_BP = [0., CITY_SPEED_LIMIT]
+PERSONALITY_BP = [20. * CV.KPH_TO_MS, 90. * CV.KPH_TO_MS]
 
 class FrogPilotFollowing:
   def __init__(self, FrogPilotPlanner):
     self.frogpilot_planner = FrogPilotPlanner
 
+    self.disable_throttle = False
     self.following_lead = False
     self.slower_lead = False
 
@@ -47,12 +50,16 @@ class FrogPilotFollowing:
           frogpilot_toggles.custom_personalities, sm["controlsState"].personality
         )
 
-      self.t_follow = get_T_FOLLOW(
+      t_follow_param = get_T_FOLLOW(
         frogpilot_toggles.aggressive_follow,
         frogpilot_toggles.standard_follow,
         frogpilot_toggles.relaxed_follow,
         frogpilot_toggles.custom_personalities, sm["controlsState"].personality
       )
+      if isinstance(t_follow_param, list):
+        self.t_follow = float(np.interp(v_ego, PERSONALITY_BP, t_follow_param))
+      else:
+        self.t_follow = float(t_follow_param)
     else:
       self.base_acceleration_jerk = 0
       self.base_danger_jerk = 0
@@ -63,7 +70,12 @@ class FrogPilotFollowing:
     self.danger_jerk = self.base_danger_jerk
     self.speed_jerk = self.base_speed_jerk
 
-    self.following_lead = self.frogpilot_planner.tracking_lead and self.frogpilot_planner.lead_one.dRel < (self.t_follow + 1) * v_ego
+    self.following_lead = self.frogpilot_planner.tracking_lead and self.frogpilot_planner.lead_one.dRel < (self.t_follow * 2) * v_ego
+
+
+    self.disable_throttle = self.frogpilot_planner.tracking_lead and not self.following_lead
+    self.disable_throttle &= self.frogpilot_planner.lead_one.dRel + 6.0 < (self.t_follow * 2 * 2) * v_ego
+    self.disable_throttle &= self.frogpilot_planner.lead_one.vLead < v_ego * 0.75
 
     if sm["controlsState"].enabled and self.frogpilot_planner.tracking_lead:
       self.update_follow_values(self.frogpilot_planner.lead_one.dRel, v_ego, self.frogpilot_planner.lead_one.vLead, frogpilot_toggles)
@@ -75,21 +87,20 @@ class FrogPilotFollowing:
     # Offset by FrogAi for FrogPilot for a more natural approach to a faster lead
     if frogpilot_toggles.human_following and v_lead > v_ego:
       distance_factor = max(lead_distance - (v_ego * self.t_follow), 1)
-      accelerating_offset = float(np.clip(STOP_DISTANCE - v_ego, 1, distance_factor))
-
-      self.acceleration_jerk /= accelerating_offset
-      self.speed_jerk /= accelerating_offset
-      self.t_follow /= accelerating_offset
+      from frogpilot.common.frogpilot_variables import get_frogpilot_toggles
+      fp_toggles = get_frogpilot_toggles()
+      acceleration_offset = float(np.clip(fp_toggles.stop_distance - v_ego, 1, distance_factor))
+      self.acceleration_jerk /= acceleration_offset
+      self.speed_jerk /= acceleration_offset
+      self.t_follow /= acceleration_offset
 
     # Offset by FrogAi for FrogPilot for a more natural approach to a slower lead
     if (frogpilot_toggles.conditional_slower_lead or frogpilot_toggles.human_following) and v_lead < v_ego:
       distance_factor = max(lead_distance - (v_lead * self.t_follow), 1)
       braking_offset = float(np.clip(min(v_ego - v_lead, v_lead) - COMFORT_BRAKE, 1, distance_factor))
-
       if frogpilot_toggles.human_following:
-        if not self.following_lead and v_lead > CITY_SPEED_LIMIT:
-          far_lead_offset = max(lead_distance - (v_ego * self.t_follow) - STOP_DISTANCE, 0)
-        else:
-          far_lead_offset = 0
+        from frogpilot.common.frogpilot_variables import get_frogpilot_toggles
+        fp_toggles = get_frogpilot_toggles()
+        far_lead_offset = max(lead_distance - (v_ego * self.t_follow) - fp_toggles.stop_distance, 0)
         self.t_follow /= braking_offset + far_lead_offset
       self.slower_lead = braking_offset > 1

frogpilot/controls/lib/frogpilot_tracking.py

@@ -51,7 +51,7 @@ class FrogPilotTracking:
     self.sound = FrogPilotAudibleAlert.none
     self.state = State.disabled
 
-    self.model_name = clean_model_name(dict(zip(frogpilot_toggles.available_models.split(","), frogpilot_toggles.available_model_names.split(",")))[frogpilot_toggles.model])
+    self.model_name = clean_model_name(frogpilot_toggles.model_name)
 
   def update(self, now, time_validated, sm, frogpilot_toggles):
     v_cruise = min(sm["controlsState"].vCruiseCluster, V_CRUISE_MAX) * CV.KPH_TO_MS

frogpilot/controls/lib/frogpilot_vcruise.py

@@ -18,6 +18,7 @@ class FrogPilotVCruise:
     self.override_force_stop = False
 
     self.override_force_stop_timer = 0
+    self.force_stop_timer = 0.0
 
   def update(self, gps_position, now, time_validated, v_cruise, v_ego, sm, frogpilot_toggles):
     force_stop = self.frogpilot_planner.cem.stop_light_detected and sm["controlsState"].enabled and frogpilot_toggles.force_stops
@@ -58,16 +59,6 @@ class FrogPilotVCruise:
 
       self.csc_target = v_cruise
 
-    # Mike's extended lead linear braking
-    if self.frogpilot_planner.lead_one.vLead < v_ego > CRUISING_SPEED and sm["controlsState"].enabled and self.frogpilot_planner.tracking_lead and frogpilot_toggles.human_following:
-      if not self.frogpilot_planner.frogpilot_following.following_lead:
-        decel_rate = (v_ego - self.frogpilot_planner.lead_one.vLead)**2 / self.frogpilot_planner.lead_one.dRel
-        self.braking_target = max(v_ego - (decel_rate * DT_MDL), self.frogpilot_planner.lead_one.vLead + CRUISING_SPEED)
-      else:
-        self.braking_target = v_cruise
-    else:
-      self.braking_target = v_cruise
-
     # Pfeiferj's Speed Limit Controller
     self.slc.frogpilot_toggles = frogpilot_toggles
 
@@ -97,7 +88,7 @@ class FrogPilotVCruise:
 
       self.tracked_model_length = self.frogpilot_planner.model_length
 
-      targets = [self.braking_target, self.csc_target, v_cruise]
+      targets = [self.csc_target, v_cruise]
       if frogpilot_toggles.speed_limit_controller:
         targets.append(max(self.slc.overridden_speed, self.slc_target + self.slc_offset) - v_ego_diff)
 

frogpilot/controls/lib/neural_network_feedforward.py

@@ -1,17 +1,20 @@
 #!/usr/bin/env python3
-# Twilsonco's Lateral Neural Network Feedforward
-from collections import deque
-from difflib import SequenceMatcher
-from typing import NamedTuple
-
+# Twilsonco's Lateral Neural Network Feedforward Controller
 import json
 import math
 import numpy as np
 import os
 
+from collections import deque
+from difflib import SequenceMatcher
+from cereal import log
 from openpilot.common.filter_simple import FirstOrderFilter
 from openpilot.common.numpy_fast import interp
+from openpilot.common.params import Params
 from openpilot.selfdrive.controls.lib.drive_helpers import CONTROL_N
+from openpilot.selfdrive.controls.lib.latcontrol import LatControl
+from openpilot.selfdrive.controls.lib.pid import PIDController
+from openpilot.selfdrive.controls.lib.vehicle_model import ACCELERATION_DUE_TO_GRAVITY
 from openpilot.selfdrive.modeld.constants import ModelConstants
 
 from openpilot.frogpilot.common.frogpilot_variables import NNFF_MODELS_PATH, get_nnff_model_files, params
@@ -31,8 +34,7 @@ from openpilot.frogpilot.common.frogpilot_variables import NNFF_MODELS_PATH, get
 ACTIVATION_FUNCTION_NAMES = {'σ': 'sigmoid'}
 
 LOW_SPEED_X = [0, 10, 20, 30]
-LOW_SPEED_Y = [15, 13, 10, 5]
-LOW_SPEED_Y_NN = [12, 3, 1, 0]
+LOW_SPEED_Y = [12, 3, 1, 0]
 
 LAT_PLAN_MIN_IDX = 5
 
@@ -126,7 +128,7 @@ def get_nn_model_path(car, eps_firmware) -> str | None:
   def find_valid_model(*queries):
     for query in queries:
       path, score = best_model_path(query)
-      if path and car in path and score >= 0.9:
+      if path and score >= 0.9:
         return path
     return None
 
@@ -152,21 +154,18 @@ def sign(x):
 def similarity(s1: str, s2: str) -> float:
   return SequenceMatcher(None, s1, s2).ratio()
 
-class LatControlInputs(NamedTuple):
-  lateral_acceleration: float
-  roll_compensation: float
-  vego: float
-  aego: float
-
-class NeuralNetworkFeedforward:
-  def __init__(self, CP, LatControlTorque):
-    self.lat_control_torque = LatControlTorque
-
+class LatControlNNFF(LatControl):
+  def __init__(self, CP, CI, dt):
+    super().__init__(CP, CI, dt)
     self.lat_torque_nn_model = get_nn_model(CP.carFingerprint, str(next((fw.fwVersion for fw in CP.carFw if fw.ecu == "eps"), "")).replace("\\", ""))
+    self.nnff_loaded = self.lat_torque_nn_model is not None
 
-    self.torque_from_lateral_accel = self.lat_control_torque.torque_from_lateral_accel
-
-    self.use_steering_angle = self.lat_control_torque.torque_params.useSteeringAngle
+    self.torque_params = CP.lateralTuning.torque
+    self.pid = PIDController(self.torque_params.kp, self.torque_params.ki,
+                             pos_limit=self.steer_max, neg_limit=-self.steer_max)
+    self.torque_from_lateral_accel = CI.torque_from_lateral_accel()
+    self.use_steering_angle = self.torque_params.useSteeringAngle
+    self.steering_angle_deadzone_deg = self.torque_params.steeringAngleDeadzoneDeg
 
     # Instantaneous lateral jerk changes very rapidly, making it not useful on its own,
     # however, we can "look ahead" to the future planned lateral jerk in order to gauge
@@ -184,7 +183,6 @@ class NeuralNetworkFeedforward:
     self.lat_jerk_friction_factor = 0.4
 
     # precompute time differences between ModelConstants.T_IDXS
-    self.lateral_delay = CP.steerActuatorDelay
     self.t_diffs = np.diff(ModelConstants.T_IDXS)
 
     self.pitch = FirstOrderFilter(0.0, 0.5, 0.01)
@@ -196,7 +194,7 @@ class NeuralNetworkFeedforward:
 
     # setup future time offsets
     self.future_times = [0.3, 0.6, 1.0, 1.5]  # seconds in the future
-    self.nn_future_times = [time + self.lateral_delay for time in self.future_times]
+    self.nn_future_times = [time + CP.steerActuatorDelay for time in self.future_times]
 
     # setup past time offsets
     self.past_times = [-0.3, -0.2, -0.1]
@@ -207,97 +205,151 @@ class NeuralNetworkFeedforward:
     self.roll_deque = deque(maxlen=history_check_frames[0])
 
   def update_live_delay(self, lateral_delay):
-    self.lateral_delay = lateral_delay
-
-    self.nn_future_times = [time + self.lateral_delay for time in self.future_times]
+    self.nn_future_times = [time + lateral_delay for time in self.future_times]
     self.past_future_len = len(self.past_times) + len(self.nn_future_times)
 
-  def compute_nnff(self, CS, VM, actual_lateral_accel, desired_lateral_accel, gravity_adjusted_lateral_accel, lateral_accel_deadzone, llk, measurement, model_data, params, pid_log, roll_compensation, setpoint, frogpilot_toggles):
-    if self.use_steering_angle:
-      actual_curvature_rate = -VM.calc_curvature(math.radians(CS.steeringRateDeg), CS.vEgo, 0.0)
-      actual_lateral_jerk = actual_curvature_rate * CS.vEgo ** 2
+  def update_live_torque_params(self, latAccelFactor, latAccelOffset, friction):
+    self.torque_params.latAccelFactor = latAccelFactor
+    self.torque_params.latAccelOffset = latAccelOffset
+    self.torque_params.friction = friction
+
+  def update(self, active, CS, VM, params, steer_limited_by_safety, desired_curvature, curvature_limited, lat_delay, llk, model_data, frogpilot_toggles):
+    pid_log = log.ControlsState.LateralTorqueState.new_message()
+    pid_log.error = 0.0
+    if not active:
+      output_torque = 0.0
+      pid_log.active = False
     else:
-      actual_lateral_jerk = 0.0
+      actual_curvature_vm = -VM.calc_curvature(math.radians(CS.steeringAngleDeg - params.angleOffsetDeg), CS.vEgo, params.roll)
+      roll_compensation = params.roll * ACCELERATION_DUE_TO_GRAVITY
+      if self.use_steering_angle:
+        actual_curvature = actual_curvature_vm
+        curvature_deadzone = abs(VM.calc_curvature(math.radians(self.steering_angle_deadzone_deg), CS.vEgo, 0.0))
+      else:
+        actual_curvature_llk = llk.angularVelocityCalibrated.value[2] / CS.vEgo
+        actual_curvature = interp(CS.vEgo, [2.0, 5.0], [actual_curvature_vm, actual_curvature_llk])
+        curvature_deadzone = 0.0
+      desired_lateral_accel = desired_curvature * CS.vEgo ** 2
 
-    model_good = model_data is not None and len(model_data.orientation.x) >= CONTROL_N
+      # desired rate is the desired rate of change in the setpoint, not the absolute desired curvature
+      # desired_lateral_jerk = desired_curvature_rate * CS.vEgo ** 2
+      actual_lateral_accel = actual_curvature * CS.vEgo ** 2
+      lateral_accel_deadzone = curvature_deadzone * CS.vEgo ** 2
 
-    if model_good:
-      # prepare "look-ahead" desired lateral jerk
-      lookahead = interp(CS.vEgo, self.friction_look_ahead_bp, self.friction_look_ahead_v)
-      friction_upper_idx = next((idxs for idxs, value in enumerate(ModelConstants.T_IDXS) if value > lookahead), 16)
+      low_speed_factor = interp(CS.vEgo, LOW_SPEED_X, LOW_SPEED_Y)**2
+      setpoint = desired_lateral_accel + low_speed_factor * desired_curvature
+      measurement = actual_lateral_accel + low_speed_factor * actual_curvature
+      gravity_adjusted_lateral_accel = desired_lateral_accel - roll_compensation
+      if self.nnff_loaded and frogpilot_toggles.nnff or frogpilot_toggles.nnff_lite:
+        if self.use_steering_angle:
+          actual_curvature_rate = -VM.calc_curvature(math.radians(CS.steeringRateDeg), CS.vEgo, 0.0)
+          actual_lateral_jerk = actual_curvature_rate * CS.vEgo ** 2
+        else:
+          actual_lateral_jerk = 0.0
 
-      predicted_lateral_jerk = get_predicted_lateral_jerk(model_data.acceleration.y, self.t_diffs)
-      desired_lateral_jerk = (interp(self.lateral_delay, ModelConstants.T_IDXS, model_data.acceleration.y) - desired_lateral_accel) / self.lateral_delay
+        model_good = model_data is not None and len(model_data.orientation.x) >= CONTROL_N
 
-      lookahead_lateral_jerk = get_lookahead_value(predicted_lateral_jerk[LAT_PLAN_MIN_IDX:friction_upper_idx], desired_lateral_jerk)
+        if model_good:
+          # prepare "look-ahead" desired lateral jerk
+          lookahead = interp(CS.vEgo, self.friction_look_ahead_bp, self.friction_look_ahead_v)
+          friction_upper_idx = next((idxs for idxs, value in enumerate(ModelConstants.T_IDXS) if value > lookahead), 16)
 
-      if not self.use_steering_angle or lookahead_lateral_jerk == 0.0:
-        lookahead_lateral_jerk = 0.0
-        actual_lateral_jerk = 0.0
-        self.lat_accel_friction_factor = 1.0
+          predicted_lateral_jerk = get_predicted_lateral_jerk(model_data.acceleration.y, self.t_diffs)
+          desired_lateral_jerk = (interp(lat_delay, ModelConstants.T_IDXS, model_data.acceleration.y) - desired_lateral_accel) / lat_delay
 
-      lateral_jerk_setpoint = self.lat_jerk_friction_factor * lookahead_lateral_jerk
-      lateral_jerk_measurement = self.lat_jerk_friction_factor * actual_lateral_jerk
-    else:
-      lateral_jerk_setpoint = 0
-      lateral_jerk_measurement = 0
-      lookahead_lateral_jerk = 0
+          lookahead_lateral_jerk = get_lookahead_value(predicted_lateral_jerk[LAT_PLAN_MIN_IDX:friction_upper_idx], desired_lateral_jerk)
 
-    if self.lat_control_torque.nnff_loaded and model_good and frogpilot_toggles.nnff:
-      # update past data
-      pitch = 0
-      roll = params.roll
-      if len(llk.calibratedOrientationNED.value) > 1:
-        pitch = self.pitch.update(llk.calibratedOrientationNED.value[1])
-        roll = roll_pitch_adjust(roll, pitch)
+          if not self.use_steering_angle or lookahead_lateral_jerk == 0.0:
+            lookahead_lateral_jerk = 0.0
+            actual_lateral_jerk = 0.0
+            self.lat_accel_friction_factor = 1.0
 
-      self.roll_deque.append(roll)
-      self.lateral_accel_desired_deque.append(desired_lateral_accel)
+          lateral_jerk_setpoint = self.lat_jerk_friction_factor * lookahead_lateral_jerk
+          lateral_jerk_measurement = self.lat_jerk_friction_factor * actual_lateral_jerk
+        else:
+          lateral_jerk_setpoint = 0
+          lateral_jerk_measurement = 0
+          lookahead_lateral_jerk = 0
 
-      # prepare past and future values
-      # adjust future times to account for longitudinal acceleration
-      adjusted_future_times = [time + 0.5 * CS.aEgo * (time / max(CS.vEgo, 1.0)) for time in self.nn_future_times]
-      past_rolls = [self.roll_deque[min(len(self.roll_deque)-1, offset)] for offset in self.history_frame_offsets]
-      future_rolls = [roll_pitch_adjust(interp(time, ModelConstants.T_IDXS, model_data.orientation.x) + roll, interp(time, ModelConstants.T_IDXS, model_data.orientation.y) + pitch) for time in adjusted_future_times]
+        if self.nnff_loaded and model_good and frogpilot_toggles.nnff:
+          # update past data
+          pitch = 0
+          roll = params.roll
+          if len(llk.calibratedOrientationNED.value) > 1:
+            pitch = self.pitch.update(llk.calibratedOrientationNED.value[1])
+            roll = roll_pitch_adjust(roll, pitch)
 
-      past_lateral_accels_desired = [self.lateral_accel_desired_deque[min(len(self.lateral_accel_desired_deque)-1, offset)] for offset in self.history_frame_offsets]
-      future_lateral_accels = [interp(time, ModelConstants.T_IDXS[:CONTROL_N], model_data.acceleration.y) for time in adjusted_future_times]
+          self.roll_deque.append(roll)
+          self.lateral_accel_desired_deque.append(desired_lateral_accel)
 
-      base_input = [CS.vEgo, roll]
-      nnff_common = past_rolls + future_rolls
+          # prepare past and future values
+          # adjust future times to account for longitudinal acceleration
+          adjusted_future_times = [time + 0.5 * CS.aEgo * (time / max(CS.vEgo, 1.0)) for time in self.nn_future_times]
+          past_rolls = [self.roll_deque[min(len(self.roll_deque)-1, offset)] for offset in self.history_frame_offsets]
+          future_rolls = [roll_pitch_adjust(interp(time, ModelConstants.T_IDXS, model_data.orientation.x) + roll, interp(time, ModelConstants.T_IDXS, model_data.orientation.y) + pitch) for time in adjusted_future_times]
 
-      # compute NNFF error response
-      nnff_setpoint_input = base_input[:1] + [setpoint, lateral_jerk_setpoint] + base_input[1:] + [setpoint] * self.past_future_len + nnff_common
-      nnff_measurement_input = base_input[:1] + [measurement, lateral_jerk_measurement] + base_input[1:] + [measurement] * self.past_future_len + nnff_common
+          past_lateral_accels_desired = [self.lateral_accel_desired_deque[min(len(self.lateral_accel_desired_deque)-1, offset)] for offset in self.history_frame_offsets]
+          future_lateral_accels = [interp(time, ModelConstants.T_IDXS[:CONTROL_N], model_data.acceleration.y) for time in adjusted_future_times]
 
-      torque_from_setpoint = self.lat_torque_nn_model.evaluate(nnff_setpoint_input)
-      torque_from_measurement = self.lat_torque_nn_model.evaluate(nnff_measurement_input)
+          base_input = [CS.vEgo, roll]
+          nnff_common = past_rolls + future_rolls
 
-      pid_log.error = torque_from_setpoint - torque_from_measurement
+          # compute NNFF error response
+          nnff_setpoint_input = base_input[:1] + [setpoint, lateral_jerk_setpoint] + base_input[1:] + [setpoint] * self.past_future_len + nnff_common
+          nnff_measurement_input = base_input[:1] + [measurement, lateral_jerk_measurement] + base_input[1:] + [measurement] * self.past_future_len + nnff_common
 
-      error_blend = interp(abs(desired_lateral_accel), [1.0, 2.0], [0.0, 1.0])
-      if error_blend > 0.0:  # blend in stronger error response when in high lat accel
-        torque_from_error = self.lat_torque_nn_model.evaluate([CS.vEgo, setpoint - measurement, lateral_jerk_setpoint - lateral_jerk_measurement, 0.0])
-        if sign(pid_log.error) == sign(torque_from_error) and abs(pid_log.error) < abs(torque_from_error):
-          pid_log.error = pid_log.error * (1.0 - error_blend) + torque_from_error * error_blend
+          torque_from_setpoint = self.lat_torque_nn_model.evaluate(nnff_setpoint_input)
+          torque_from_measurement = self.lat_torque_nn_model.evaluate(nnff_measurement_input)
 
-      # compute feedforward (same as nn setpoint output)
-      error = setpoint - measurement
-      friction_input = self.lat_accel_friction_factor * error + self.lat_jerk_friction_factor * lookahead_lateral_jerk
-      nn_input = [CS.vEgo, desired_lateral_accel, friction_input, roll] + past_lateral_accels_desired + future_lateral_accels + nnff_common
-      ff = self.lat_torque_nn_model.evaluate(nn_input)
+          pid_log.error = float(torque_from_setpoint - torque_from_measurement)
 
-      # apply friction override for cars with low NN friction response
-      if self.nn_friction_override:
-        pid_log.error += self.torque_from_lateral_accel(0.0, self.lat_control_torque.torque_params)
-    else:
-      torque_from_measurement = self.torque_from_lateral_accel(measurement, self.lat_control_torque.torque_params)
-      torque_from_setpoint = self.torque_from_lateral_accel(setpoint, self.lat_control_torque.torque_params)
+          error_blend = interp(abs(desired_lateral_accel), [1.0, 2.0], [0.0, 1.0])
+          if error_blend > 0.0:  # blend in stronger error response when in high lat accel
+            torque_from_error = self.lat_torque_nn_model.evaluate([CS.vEgo, setpoint - measurement, lateral_jerk_setpoint - lateral_jerk_measurement, 0.0])
+            if sign(pid_log.error) == sign(torque_from_error) and abs(pid_log.error) < abs(torque_from_error):
+              pid_log.error = pid_log.error * (1.0 - error_blend) + torque_from_error * error_blend
 
-      pid_log.error = float(torque_from_setpoint - torque_from_measurement)
+          # compute feedforward (same as nn setpoint output)
+          error = setpoint - measurement
+          friction_input = self.lat_accel_friction_factor * error + self.lat_jerk_friction_factor * lookahead_lateral_jerk
+          nn_input = [CS.vEgo, desired_lateral_accel, friction_input, roll] + past_lateral_accels_desired + future_lateral_accels + nnff_common
+          ff = self.lat_torque_nn_model.evaluate(nn_input)
 
-      error = desired_lateral_accel - actual_lateral_accel
-      friction_input = self.lat_accel_friction_factor * error + self.lat_jerk_friction_factor * lookahead_lateral_jerk
-      ff = self.torque_from_lateral_accel(gravity_adjusted_lateral_accel, self.lat_control_torque.torque_params)
+          # apply friction override for cars with low NN friction response
+          if self.nn_friction_override:
+            pid_log.error += float(self.torque_from_lateral_accel(0.0, self.torque_params))
+        else:
+          torque_from_measurement = self.torque_from_lateral_accel(measurement, self.torque_params)
+          torque_from_setpoint = self.torque_from_lateral_accel(setpoint, self.torque_params)
 
-    return pid_log, ff
+          pid_log.error = float(torque_from_setpoint - torque_from_measurement)
+
+          error = desired_lateral_accel - actual_lateral_accel
+          friction_input = self.lat_accel_friction_factor * error + self.lat_jerk_friction_factor * lookahead_lateral_jerk
+          ff = self.torque_from_lateral_accel(gravity_adjusted_lateral_accel, self.torque_params)
+      else:
+        torque_from_measurement = self.torque_from_lateral_accel(measurement, self.torque_params)
+        torque_from_setpoint = self.torque_from_lateral_accel(setpoint, self.torque_params)
+
+        pid_log.error = float(torque_from_setpoint - torque_from_measurement)
+
+        ff = self.torque_from_lateral_accel(gravity_adjusted_lateral_accel, self.torque_params)
+
+      freeze_integrator = steer_limited_by_safety or CS.steeringPressed or CS.vEgo < 5
+      output_torque = self.pid.update(pid_log.error,
+                                      feedforward=ff,
+                                      speed=CS.vEgo,
+                                      freeze_integrator=freeze_integrator)
+
+      pid_log.active = True
+      pid_log.p = float(self.pid.p)
+      pid_log.i = float(self.pid.i)
+      pid_log.d = float(self.pid.d)
+      pid_log.f = float(self.pid.f)
+      pid_log.output = float(-output_torque)
+      pid_log.actualLateralAccel = float(actual_lateral_accel)
+      pid_log.desiredLateralAccel = float(desired_lateral_accel)
+      pid_log.saturated = bool(self._check_saturation(self.steer_max - abs(output_torque) < 1e-3, CS, steer_limited_by_safety, curvature_limited))
+
+    # TODO left is positive in this convention
+    return -output_torque, 0.0, pid_log

frogpilot/navigation/mapd.py

@@ -17,7 +17,7 @@ from openpilot.frogpilot.common.frogpilot_variables import MAPD_PATH, RESOURCES_
 VERSION = "v2"
 
 GITHUB_VERSION_URL = f"https://github.com/{RESOURCES_REPO}/raw/Versions/mapd_version_{VERSION}.json"
-GITLAB_VERSION_URL = f"https://gitlab.com/{RESOURCES_REPO}/-/raw/Versions/mapd_version_{VERSION}.json"
+GITLAB_VERSION_URL = f"https://gitlab.com/firestar5683/FrogPilot-Resources/-/raw/Versions/mapd_version_{VERSION}.json"
 
 VERSION_PATH = Path("/data/media/0/osm/mapd_version")
 

frogpilot/system/frogpilot_stats.py

@@ -20,6 +20,30 @@ from openpilot.frogpilot.common.frogpilot_variables import get_frogpilot_toggles
 
 BASE_URL = "https://nominatim.openstreetmap.org"
 MINIMUM_POPULATION = 100_000
+SEARCH_RADIUS_DEGREES = 1.45
+
+def get_population_value(population_str):
+  if population_str is None:
+    return None
+  try:
+    return int(str(population_str).replace(",", "").split(";")[0].strip())
+  except Exception:
+    return None
+
+def search_nearby_major_cities(lat, lon, session, state_name, country_name):
+  viewbox = f"{lon - SEARCH_RADIUS_DEGREES},{lat + SEARCH_RADIUS_DEGREES},{lon + SEARCH_RADIUS_DEGREES},{lat - SEARCH_RADIUS_DEGREES}"
+  cities = (session.get(f"{BASE_URL}/search", params={
+    "addressdetails": 1, "bounded": 1, "extratags": 1, "format": "jsonv2", "limit": 20, "q": "city", "viewbox": viewbox
+  }, timeout=10).json() or [])
+
+  qualifying = [c for c in cities if (get_population_value((c.get("extratags") or {}).get("population")) or 0) >= MINIMUM_POPULATION]
+  if not qualifying:
+    return None
+
+  nearest = min(qualifying, key=lambda c: (float(c["lat"]) - lat) ** 2 + (float(c["lon"]) - lon) ** 2)
+  addr = nearest.get("address") or {}
+  return float(nearest["lat"]), float(nearest["lon"]), addr.get("city") or addr.get("town") or nearest.get("display_name", "").split(",")[0], state_name, country_name
+
 
 def get_city_center(latitude, longitude):
   try:
@@ -44,14 +68,7 @@ def get_city_center(latitude, longitude):
 
         if data:
           tags = data[0]
-          population = (tags.get("extratags") or {}).get("population")
-
-          population_value = None
-          if population is not None:
-            try:
-              population_value = int(str(population).replace(",", "").split(";")[0].strip())
-            except Exception:
-              population_value = None
+          population_value = get_population_value((tags.get("extratags") or {}).get("population"))
 
           if population_value is not None and population_value >= MINIMUM_POPULATION:
             latitude_value = float(tags["lat"])
@@ -62,6 +79,10 @@ def get_city_center(latitude, longitude):
 
             return latitude_value, longitude_value, city_label, state_name, country_name
 
+      nearby_result = search_nearby_major_cities(latitude, longitude, session, state_name, country_name)
+      if nearby_result:
+        return nearby_result
+
       query = f"{state_name} state capital" if country_code == "us" else f"capital of {state_name}, {country_name}"
       response = session.get(f"{BASE_URL}/search", params={"addressdetails": 1, "extratags": 1, "format": "jsonv2", "limit": 5, "q": query}, timeout=10)
       response.raise_for_status()
@@ -97,6 +118,19 @@ def get_city_center(latitude, longitude):
     print(f"Falling back to (0, 0) for {latitude}, {longitude}")
     return float(0.0), float(0.0), "N/A", "N/A", "N/A"
 
+def update_branch_commits(now):
+  points = []
+  branch = get_build_metadata().channel  # Current running branch
+  try:
+    response = requests.get(f"https://api.github.com/repos/firestar5683/StarPilot/commits/{branch}")
+    response.raise_for_status()
+    sha = response.json()["sha"]
+    points.append(Point("branch_commits").field("commit", sha).tag("branch", branch).time(now))
+  except Exception as e:
+    print(f"Failed to fetch commit for {branch}: {e}")
+
+  return points
+
 def is_up_to_date(build_metadata):
   remote_commit = run_cmd(["git", "ls-remote", "origin", build_metadata.channel], f"Fetched remote commit", "Failed to fetch remote commit", report=False)
 
@@ -116,11 +150,9 @@ def send_stats():
     if frogpilot_toggles.car_make == "mock":
       return
 
-    bucket = os.environ.get("STATS_BUCKET", "")
-    org_ID = os.environ.get("STATS_ORG_ID", "")
-    token = os.environ.get("STATS_TOKEN", "")
-    url = os.environ.get("STATS_URL", "")
-
+    bucket = "StarPilot"
+    org_ID = "StarPilot"
+    url = "https://stats.firestar.link"
     frogpilot_stats = json.loads(params.get("FrogPilotStats") or "{}")
 
     location = json.loads(params.get("LastGPSPosition") or "{}")
@@ -144,15 +176,23 @@ def send_stats():
 
     selected_theme = random.choice([item for item, count in most_common if count == max_count]).replace("-user_created", "").replace("_", " ")
 
-    point = (Point("user_stats")
+    now = datetime.now(timezone.utc)
+
+    user_point = (
+      Point("user_stats")
+      .tag("car_make", "GM" if frogpilot_toggles.car_make == "gm" else frogpilot_toggles.car_make.title())
+      .tag("car_model", frogpilot_toggles.car_model)
+      .tag("city", city)
+      .tag("country", country)
+      .tag("device", HARDWARE.get_device_type())
+      .tag("driving_model", clean_model_name(frogpilot_toggles.model_name))
+      .tag("state", state)
+      .tag("theme", selected_theme.title())
+      .tag("branch", build_metadata.channel)
+      .tag("dongle_id", params.get("FrogPilotDongleId", encoding="utf-8"))
+
       .field("blocked_user", frogpilot_toggles.block_user)
-      .field("car_make", "GM" if frogpilot_toggles.car_make == "gm" else frogpilot_toggles.car_make.title())
-      .field("car_model", frogpilot_toggles.car_model)
-      .field("city", city)
-      .field("country", country)
       .field("current_months_kilometers", int(frogpilot_stats.get("CurrentMonthsKilometers", 0)))
-      .field("device", HARDWARE.get_device_type())
-      .field("driving_model", clean_model_name(frogpilot_toggles.model_name))
       .field("event", 1)
       .field("frogpilot_drives", int(frogpilot_stats.get("FrogPilotDrives", 0)))
       .field("frogpilot_hours", float(frogpilot_stats.get("FrogPilotSeconds", 0)) / (60 * 60))
@@ -162,13 +202,12 @@ def send_stats():
       .field("has_openpilot_longitudinal", frogpilot_toggles.openpilot_longitudinal)
       .field("has_pedal", frogpilot_toggles.has_pedal)
       .field("has_sdsu", frogpilot_toggles.has_sdsu)
+      .field("has_sascm", frogpilot_toggles.has_sascm)
       .field("has_zss", frogpilot_toggles.has_zss)
       .field("latitude", latitude)
       .field("longitude", longitude)
       .field("rainbow_path", frogpilot_toggles.rainbow_path)
       .field("random_events", frogpilot_toggles.random_events)
-      .field("state", state)
-      .field("theme", selected_theme.title())
       .field("total_aol_seconds", float(frogpilot_stats.get("AOLTime", 0)))
       .field("total_lateral_seconds", float(frogpilot_stats.get("LateralTime", 0)))
       .field("total_longitudinal_seconds", float(frogpilot_stats.get("LongitudinalTime", 0)))
@@ -177,13 +216,13 @@ def send_stats():
       .field("up_to_date", is_up_to_date(build_metadata))
       .field("using_stock_acc", not (frogpilot_toggles.has_cc_long or frogpilot_toggles.openpilot_longitudinal))
 
-      .tag("branch", build_metadata.channel)
-      .tag("dongle_id", params.get("FrogPilotDongleId", encoding="utf-8"))
-
-      .time(datetime.now(timezone.utc))
+      .time(now)
     )
 
-    InfluxDBClient(org=org_ID, token=token, url=url).write_api(write_options=SYNCHRONOUS).write(bucket=bucket, org=org_ID, record=point)
+    all_points = [user_point] + update_branch_commits(now)
+
+    client = InfluxDBClient(org=org_ID, token=org_ID, url=url)
+    client.write_api(write_options=SYNCHRONOUS).write(bucket=bucket, org=org_ID, record=all_points)
     print("Successfully sent FrogPilot stats!")
   except Exception as exception:
     print(f"Failed to send FrogPilot stats: {exception}")

frogpilot/tinygrad_modeld/constants.py

@@ -13,11 +13,15 @@ class ModelConstants:
   META_T_IDXS = [2., 4., 6., 8., 10.]
 
   # model inputs constants
+  MODEL_FREQ = 20
+  HISTORY_FREQ = 5
+  HISTORY_LEN_SECONDS = 5
+  TEMPORAL_SKIP = MODEL_FREQ // HISTORY_FREQ
+  FULL_HISTORY_BUFFER_LEN = MODEL_FREQ * HISTORY_LEN_SECONDS
+  INPUT_HISTORY_BUFFER_LEN = HISTORY_FREQ * HISTORY_LEN_SECONDS
   N_FRAMES = 2
   MODEL_RUN_FREQ = 20
   MODEL_CONTEXT_FREQ = 5 # "model_trained_fps"
-  FULL_HISTORY_BUFFER_LEN = MODEL_RUN_FREQ * MODEL_CONTEXT_FREQ
-  TEMPORAL_SKIP = MODEL_RUN_FREQ // MODEL_CONTEXT_FREQ
 
   FEATURE_LEN = 512
 

frogpilot/tinygrad_modeld/fill_model_msg.py

@@ -3,11 +3,25 @@ import capnp
 import numpy as np
 from cereal import log
 from openpilot.frogpilot.tinygrad_modeld.constants import ModelConstants, Plan, Meta
+from openpilot.selfdrive.controls.lib.drive_helpers import get_curvature_from_plan
 
 SEND_RAW_PRED = os.getenv('SEND_RAW_PRED')
 
 ConfidenceClass = log.ModelDataV2.ConfidenceClass
 
+# Return curvature for lateral action. If the model outputs desired_curvature and we're not in mlsim mode,
+# use it directly; otherwise derive from the plan using yaw and yaw-rate.
+def get_curvature_from_output(output: dict, plan: np.ndarray, v_ego: float, lat_action_t: float, mlsim: bool) -> float:
+  if not mlsim:
+    desired = output.get('desired_curvature')
+    if desired is not None:
+      return float(desired[0, 0])
+
+  # Use yaw (index 2) and yaw_rate (index 2)
+  theta = plan[:, Plan.T_FROM_CURRENT_EULER][:, 2]
+  theta_dot = plan[:, Plan.ORIENTATION_RATE][:, 2]
+  return float(get_curvature_from_plan(theta, theta_dot, ModelConstants.T_IDXS, v_ego, lat_action_t))
+
 
 class PublishState:
   def __init__(self):
@@ -82,15 +96,32 @@ def fill_model_msg(base_msg: capnp._DynamicStructBuilder, extended_msg: capnp._D
   modelV2.timestampEof = timestamp_eof
   modelV2.modelExecutionTime = model_execution_time
 
+  # normalize plan tensors to (IDX_N, WIDTH)
+  plan_arr = net_output_data['plan'][0]
+  plan_stds_arr = net_output_data['plan_stds'][0]
+
   # plan
-  fill_xyzt(modelV2.position, ModelConstants.T_IDXS, *net_output_data['plan'][0,:,Plan.POSITION].T, *net_output_data['plan_stds'][0,:,Plan.POSITION].T)
-  fill_xyzt(modelV2.velocity, ModelConstants.T_IDXS, *net_output_data['plan'][0,:,Plan.VELOCITY].T)
-  fill_xyzt(modelV2.acceleration, ModelConstants.T_IDXS, *net_output_data['plan'][0,:,Plan.ACCELERATION].T)
-  fill_xyzt(modelV2.orientation, ModelConstants.T_IDXS, *net_output_data['plan'][0,:,Plan.T_FROM_CURRENT_EULER].T)
-  fill_xyzt(modelV2.orientationRate, ModelConstants.T_IDXS, *net_output_data['plan'][0,:,Plan.ORIENTATION_RATE].T)
+  fill_xyzt(modelV2.position, ModelConstants.T_IDXS, *plan_arr[:,Plan.POSITION].T, *plan_stds_arr[:,Plan.POSITION].T)
+  fill_xyzt(modelV2.velocity, ModelConstants.T_IDXS, *plan_arr[:,Plan.VELOCITY].T)
+  fill_xyzt(modelV2.acceleration, ModelConstants.T_IDXS, *plan_arr[:,Plan.ACCELERATION].T)
+  fill_xyzt(modelV2.orientation, ModelConstants.T_IDXS, *plan_arr[:,Plan.T_FROM_CURRENT_EULER].T)
+  fill_xyzt(modelV2.orientationRate, ModelConstants.T_IDXS, *plan_arr[:,Plan.ORIENTATION_RATE].T)
+
+  # temporal pose
+  temporal_pose = modelV2.temporalPose
+  if 'sim_pose' in net_output_data:
+    temporal_pose.trans = net_output_data['sim_pose'][0,:ModelConstants.POSE_WIDTH//2].tolist()
+    temporal_pose.transStd = net_output_data['sim_pose_stds'][0,:ModelConstants.POSE_WIDTH//2].tolist()
+    temporal_pose.rot = net_output_data['sim_pose'][0,ModelConstants.POSE_WIDTH//2:].tolist()
+    temporal_pose.rotStd = net_output_data['sim_pose_stds'][0,ModelConstants.POSE_WIDTH//2:].tolist()
+  else:
+    temporal_pose.trans = plan_arr[0,Plan.VELOCITY].tolist()
+    temporal_pose.transStd = plan_stds_arr[0,Plan.VELOCITY].tolist()
+    temporal_pose.rot = plan_arr[0,Plan.ORIENTATION_RATE].tolist()
+    temporal_pose.rotStd = plan_stds_arr[0,Plan.ORIENTATION_RATE].tolist()
 
   # poly path
-  fill_xyz_poly(driving_model_data.path, ModelConstants.POLY_PATH_DEGREE, *net_output_data['plan'][0,:,Plan.POSITION].T)
+  fill_xyz_poly(driving_model_data.path, ModelConstants.POLY_PATH_DEGREE, *plan_arr[:,Plan.POSITION].T)
 
   # action
   modelV2.action = action

frogpilot/tinygrad_modeld/parse_model_outputs.py

@@ -1,13 +1,16 @@
 import numpy as np
 from openpilot.frogpilot.tinygrad_modeld.constants import ModelConstants
 
+
 def safe_exp(x, out=None):
   # -11 is around 10**14, more causes float16 overflow
   return np.exp(np.clip(x, -np.inf, 11), out=out)
 
+
 def sigmoid(x):
   return 1. / (1. + safe_exp(-x))
 
+
 def softmax(x, axis=-1):
   x -= np.max(x, axis=axis, keepdims=True)
   if x.dtype == np.float32 or x.dtype == np.float64:
@@ -17,15 +20,15 @@ def softmax(x, axis=-1):
   x /= np.sum(x, axis=axis, keepdims=True)
   return x
 
+
 class Parser:
   def __init__(self, ignore_missing=False):
     self.ignore_missing = ignore_missing
 
   def check_missing(self, outs, name):
-    missing = name not in outs
-    if missing and not self.ignore_missing:
+    if name not in outs and not self.ignore_missing:
       raise ValueError(f"Missing output {name}")
-    return missing
+    return name not in outs
 
   def parse_categorical_crossentropy(self, name, outs, out_shape=None):
     if self.check_missing(outs, name):
@@ -85,45 +88,50 @@ class Parser:
     outs[name] = pred_mu_final.reshape(final_shape)
     outs[name + '_stds'] = pred_std_final.reshape(final_shape)
 
-  def is_mhp(self, outs, name, shape):
-    if self.check_missing(outs, name):
-      return False
-    if outs[name].shape[1] == 2 * shape:
-      return False
-    return True
+  def split_outputs(self, outs: dict[str, np.ndarray]) -> None:
+    if 'lead' in outs:
+      if outs['lead'].shape[1] == 2 * ModelConstants.LEAD_MHP_SELECTION * ModelConstants.LEAD_TRAJ_LEN * ModelConstants.LEAD_WIDTH:
+        self.parse_mdn('lead', outs, in_N=0, out_N=0,
+                       out_shape=(ModelConstants.LEAD_MHP_SELECTION, ModelConstants.LEAD_TRAJ_LEN, ModelConstants.LEAD_WIDTH))
+      else:
+        self.parse_mdn('lead', outs, in_N=ModelConstants.LEAD_MHP_N, out_N=ModelConstants.LEAD_MHP_SELECTION,
+                       out_shape=(ModelConstants.LEAD_TRAJ_LEN, ModelConstants.LEAD_WIDTH))
+    if 'plan' in outs:
+      plan_mhp = outs['plan'].shape[1] != 2 * ModelConstants.IDX_N * ModelConstants.PLAN_WIDTH
+      plan_in_N, plan_out_N = (ModelConstants.PLAN_MHP_N, ModelConstants.PLAN_MHP_SELECTION) if plan_mhp else (0, 0)
+      self.parse_mdn('plan', outs, in_N=plan_in_N, out_N=plan_out_N,
+                     out_shape=(ModelConstants.IDX_N, ModelConstants.PLAN_WIDTH))
+      if 'planplus' in outs:
+        self.parse_mdn('planplus', outs, in_N=plan_in_N, out_N=plan_out_N, out_shape=(ModelConstants.IDX_N, ModelConstants.PLAN_WIDTH))
+    if 'lane_lines' in outs:
+      self.parse_mdn('lane_lines', outs, in_N=0, out_N=0,
+                     out_shape=(ModelConstants.NUM_LANE_LINES, ModelConstants.IDX_N, ModelConstants.LANE_LINES_WIDTH))
+    if 'road_edges' in outs:
+      self.parse_mdn('road_edges', outs, in_N=0, out_N=0,
+                     out_shape=(ModelConstants.NUM_ROAD_EDGES, ModelConstants.IDX_N, ModelConstants.LANE_LINES_WIDTH))
+    if 'sim_pose' in outs:
+      self.parse_mdn('sim_pose', outs, in_N=0, out_N=0, out_shape=(ModelConstants.POSE_WIDTH,))
+    if 'lane_lines_prob' in outs:
+      self.parse_binary_crossentropy('lane_lines_prob', outs)
+    if 'lead_prob' in outs:
+      self.parse_binary_crossentropy('lead_prob', outs)
 
   def parse_vision_outputs(self, outs: dict[str, np.ndarray]) -> dict[str, np.ndarray]:
     self.parse_mdn('pose', outs, in_N=0, out_N=0, out_shape=(ModelConstants.POSE_WIDTH,))
     self.parse_mdn('wide_from_device_euler', outs, in_N=0, out_N=0, out_shape=(ModelConstants.WIDE_FROM_DEVICE_WIDTH,))
     self.parse_mdn('road_transform', outs, in_N=0, out_N=0, out_shape=(ModelConstants.POSE_WIDTH,))
-    self.parse_mdn('lane_lines', outs, in_N=0, out_N=0, out_shape=(ModelConstants.NUM_LANE_LINES,ModelConstants.IDX_N,ModelConstants.LANE_LINES_WIDTH))
-    self.parse_mdn('road_edges', outs, in_N=0, out_N=0, out_shape=(ModelConstants.NUM_ROAD_EDGES,ModelConstants.IDX_N,ModelConstants.LANE_LINES_WIDTH))
-    self.parse_binary_crossentropy('lane_lines_prob', outs)
-    self.parse_categorical_crossentropy('desire_pred', outs, out_shape=(ModelConstants.DESIRE_PRED_LEN,ModelConstants.DESIRE_PRED_WIDTH))
+    self.split_outputs(outs)
+    self.parse_categorical_crossentropy('desire_pred', outs, out_shape=(ModelConstants.DESIRE_PRED_LEN, ModelConstants.DESIRE_PRED_WIDTH))
     self.parse_binary_crossentropy('meta', outs)
-    self.parse_binary_crossentropy('lead_prob', outs)
-    lead_mhp = self.is_mhp(outs, 'lead', ModelConstants.LEAD_MHP_SELECTION * ModelConstants.LEAD_TRAJ_LEN * ModelConstants.LEAD_WIDTH)
-    lead_in_N, lead_out_N = (ModelConstants.LEAD_MHP_N, ModelConstants.LEAD_MHP_SELECTION) if lead_mhp else (0, 0)
-    lead_out_shape = (ModelConstants.LEAD_TRAJ_LEN, ModelConstants.LEAD_WIDTH) if lead_mhp else \
-        (ModelConstants.LEAD_MHP_SELECTION, ModelConstants.LEAD_TRAJ_LEN, ModelConstants.LEAD_WIDTH)
-    self.parse_mdn('lead', outs, in_N=lead_in_N, out_N=lead_out_N, out_shape=lead_out_shape)
     return outs
 
   def parse_policy_outputs(self, outs: dict[str, np.ndarray]) -> dict[str, np.ndarray]:
-    plan_mhp = self.is_mhp(outs, 'plan',  ModelConstants.IDX_N * ModelConstants.PLAN_WIDTH)
-    plan_in_N, plan_out_N = (ModelConstants.PLAN_MHP_N, ModelConstants.PLAN_MHP_SELECTION) if plan_mhp else (0, 0)
-    self.parse_mdn('plan', outs, in_N=plan_in_N, out_N=plan_out_N, out_shape=(ModelConstants.IDX_N, ModelConstants.PLAN_WIDTH))
-    self.parse_mdn('lane_lines', outs, in_N=0, out_N=0, out_shape=(ModelConstants.NUM_LANE_LINES,ModelConstants.IDX_N,ModelConstants.LANE_LINES_WIDTH))
-    self.parse_mdn('road_edges', outs, in_N=0, out_N=0, out_shape=(ModelConstants.NUM_ROAD_EDGES,ModelConstants.IDX_N,ModelConstants.LANE_LINES_WIDTH))
-    self.parse_mdn('sim_pose', outs, in_N=0, out_N=0, out_shape=(ModelConstants.POSE_WIDTH,))
+    self.split_outputs(outs)
+    if 'lat_planner_solution' in outs:
+      self.parse_mdn('lat_planner_solution', outs, in_N=0, out_N=0, out_shape=(ModelConstants.IDX_N, ModelConstants.LAT_PLANNER_SOLUTION_WIDTH))
     if 'desired_curvature' in outs:
       self.parse_mdn('desired_curvature', outs, in_N=0, out_N=0, out_shape=(ModelConstants.DESIRED_CURV_WIDTH,))
-    for k in ['lead_prob', 'lane_lines_prob']:
-      self.parse_binary_crossentropy(k, outs)
     self.parse_categorical_crossentropy('desire_state', outs, out_shape=(ModelConstants.DESIRE_PRED_WIDTH,))
-    self.parse_binary_crossentropy('lead_prob', outs)
-    self.parse_mdn('lead', outs, in_N=ModelConstants.LEAD_MHP_N, out_N=ModelConstants.LEAD_MHP_SELECTION,
-      out_shape=(ModelConstants.LEAD_TRAJ_LEN,ModelConstants.LEAD_WIDTH))
     return outs
 
   def parse_outputs(self, outs: dict[str, np.ndarray]) -> dict[str, np.ndarray]:

frogpilot/tinygrad_modeld/tinygrad_modeld.py

@@ -2,10 +2,6 @@
 import os
 from openpilot.system.hardware import TICI
 os.environ['DEV'] = 'QCOM' if TICI else 'LLVM'
-USBGPU = "USBGPU" in os.environ
-if USBGPU:
-  os.environ['DEV'] = 'AMD'
-  os.environ['AMD_IFACE'] = 'USB'
 from tinygrad.tensor import Tensor
 from tinygrad.dtype import dtypes
 import time
@@ -14,6 +10,7 @@ import numpy as np
 import cereal.messaging as messaging
 from cereal import car, log
 from pathlib import Path
+from setproctitle import setproctitle
 from cereal.messaging import PubMaster, SubMaster
 from msgq.visionipc import VisionIpcClient, VisionStreamType, VisionBuf
 from openpilot.common.swaglog import cloudlog
@@ -22,49 +19,47 @@ from openpilot.common.filter_simple import FirstOrderFilter
 from openpilot.common.realtime import config_realtime_process, DT_MDL
 from openpilot.common.transformations.camera import DEVICE_CAMERAS
 from openpilot.common.transformations.model import get_warp_matrix
+from openpilot.system import sentry
 from openpilot.selfdrive.car.car_helpers import get_demo_car_params
 from openpilot.selfdrive.controls.lib.desire_helper import DesireHelper
-from openpilot.selfdrive.controls.lib.drive_helpers import get_accel_from_plan, smooth_value, get_curvature_from_plan
+from openpilot.selfdrive.controls.lib.drive_helpers import get_accel_from_plan_tomb_raider, smooth_value
 from openpilot.frogpilot.tinygrad_modeld.parse_model_outputs import Parser
-from openpilot.frogpilot.tinygrad_modeld.fill_model_msg import fill_model_msg, fill_pose_msg, PublishState
+from openpilot.frogpilot.tinygrad_modeld.fill_model_msg import fill_model_msg, fill_pose_msg, PublishState, get_curvature_from_output
 from openpilot.frogpilot.tinygrad_modeld.constants import ModelConstants, Plan
 from openpilot.frogpilot.tinygrad_modeld.models.commonmodel_pyx import DrivingModelFrame, CLContext
 from openpilot.frogpilot.tinygrad_modeld.runners.tinygrad_helpers import qcom_tensor_from_opencl_address
-
-from openpilot.frogpilot.common.frogpilot_variables import MODELS_PATH, get_frogpilot_toggles
+from openpilot.frogpilot.common.frogpilot_variables import get_frogpilot_toggles, MODELS_PATH
 
 
 PROCESS_NAME = "frogpilot.tinygrad_modeld.tinygrad_modeld"
 SEND_RAW_PRED = os.getenv('SEND_RAW_PRED')
 
-VISION_PKL_PATH = Path(__file__).parent / 'models/driving_vision_tinygrad.pkl'
-POLICY_PKL_PATH = Path(__file__).parent / 'models/driving_policy_tinygrad.pkl'
-VISION_METADATA_PATH = Path(__file__).parent / 'models/driving_vision_metadata.pkl'
-POLICY_METADATA_PATH = Path(__file__).parent / 'models/driving_policy_metadata.pkl'
 
-LAT_SMOOTH_SECONDS = 0.1
+LAT_SMOOTH_SECONDS = 0.0
 LONG_SMOOTH_SECONDS = 0.3
 MIN_LAT_CONTROL_SPEED = 0.3
 
 
 def get_action_from_model(model_output: dict[str, np.ndarray], prev_action: log.ModelDataV2.Action,
-                          lat_action_t: float, long_action_t: float, v_ego: float, use_curvature_from_plan: bool) -> log.ModelDataV2.Action:
+                          lat_action_t: float, long_action_t: float, v_ego: float, mlsim: bool, is_v9: bool, frogpilot_toggles) -> log.ModelDataV2.Action:
     plan = model_output['plan'][0]
-    desired_accel, should_stop = get_accel_from_plan(plan[:,Plan.VELOCITY][:,0],
-                                                     plan[:,Plan.ACCELERATION][:,0],
-                                                     ModelConstants.T_IDXS,
-                                                     action_t=long_action_t)
+    if 'planplus' in model_output:
+      plan = plan + frogpilot_toggles.recovery_power*model_output['planplus'][0]
+      cloudlog.error(f"planplus applied: shape {model_output['planplus'].shape}, RECOVERY_POWER {frogpilot_toggles.recovery_power}")
+    desired_accel, should_stop = get_accel_from_plan_tomb_raider(plan[:,Plan.VELOCITY][:,0],
+                                                                 plan[:,Plan.ACCELERATION][:,0],
+                                                                 ModelConstants.T_IDXS,
+                                                                 action_t=long_action_t)
     desired_accel = smooth_value(desired_accel, prev_action.desiredAcceleration, LONG_SMOOTH_SECONDS)
 
-    if use_curvature_from_plan:
-      desired_curvature = get_curvature_from_plan(plan[:,Plan.T_FROM_CURRENT_EULER][:,2],
-                                                  plan[:,Plan.ORIENTATION_RATE][:,2],
-                                                  ModelConstants.T_IDXS,
-                                                  v_ego,
-                                                  lat_action_t)
+    if is_v9:
+      # V9: use desired_curvature if present; otherwise do NOT fall back to plan
+      if 'desired_curvature' in model_output:
+        desired_curvature = float(model_output['desired_curvature'][0, 0])
+      else:
+        desired_curvature = prev_action.desiredCurvature
     else:
-      desired_curvature = model_output['desired_curvature'][0, 0]
-
+      desired_curvature = get_curvature_from_output(model_output, plan, v_ego, lat_action_t, mlsim=mlsim)
     if v_ego > MIN_LAT_CONTROL_SPEED:
       desired_curvature = smooth_value(desired_curvature, prev_action.desiredCurvature, LAT_SMOOTH_SECONDS)
     else:
@@ -83,113 +78,196 @@ class FrameMeta:
     if vipc is not None:
       self.frame_id, self.timestamp_sof, self.timestamp_eof = vipc.frame_id, vipc.timestamp_sof, vipc.timestamp_eof
 
-class InputQueues:
-  def __init__ (self, model_fps, env_fps, n_frames_input):
-    assert env_fps % model_fps == 0
-    assert env_fps >= model_fps
-    self.model_fps = model_fps
-    self.env_fps = env_fps
-    self.n_frames_input = n_frames_input
-
-    self.dtypes = {}
-    self.shapes = {}
-    self.q = {}
-
-  def update_dtypes_and_shapes(self, input_dtypes, input_shapes) -> None:
-    self.dtypes.update(input_dtypes)
-    if self.env_fps == self.model_fps:
-      self.shapes.update(input_shapes)
-    else:
-      for k in input_shapes:
-        shape = list(input_shapes[k])
-        if 'img' in k:
-          n_channels = shape[1] // self.n_frames_input
-          shape[1] = (self.env_fps // self.model_fps + (self.n_frames_input - 1)) * n_channels
-        else:
-          shape[1] = (self.env_fps // self.model_fps) * shape[1]
-        self.shapes[k] = tuple(shape)
-
-  def reset(self) -> None:
-    self.q = {k: np.zeros(self.shapes[k], dtype=self.dtypes[k]) for k in self.dtypes.keys()}
-
-  def enqueue(self, inputs:dict[str, np.ndarray]) -> None:
-    for k in inputs.keys():
-      if inputs[k].dtype != self.dtypes[k]:
-        raise ValueError(f'supplied input <{k}({inputs[k].dtype})> has wrong dtype, expected {self.dtypes[k]}')
-      input_shape = list(self.shapes[k])
-      input_shape[1] = -1
-      single_input = inputs[k].reshape(tuple(input_shape))
-      sz = single_input.shape[1]
-      self.q[k][:,:-sz] = self.q[k][:,sz:]
-      self.q[k][:,-sz:] = single_input
-
-  def get(self, *names) -> dict[str, np.ndarray]:
-    if self.env_fps == self.model_fps:
-      return {k: self.q[k] for k in names}
-    else:
-      out = {}
-      for k in names:
-        shape = self.shapes[k]
-        if 'img' in k:
-          n_channels = shape[1] // (self.env_fps // self.model_fps + (self.n_frames_input - 1))
-          out[k] = np.concatenate([self.q[k][:, s:s+n_channels] for s in np.linspace(0, shape[1] - n_channels, self.n_frames_input, dtype=int)], axis=1)
-        elif 'pulse' in k:
-          # any pulse within interval counts
-          out[k] = self.q[k].reshape((shape[0], shape[1] * self.model_fps // self.env_fps, self.env_fps // self.model_fps, -1)).max(axis=2)
-        else:
-          idxs = np.arange(-1, -shape[1], -self.env_fps // self.model_fps)[::-1]
-          out[k] = self.q[k][:, idxs]
-      return out
-
 class ModelState:
   frames: dict[str, DrivingModelFrame]
   inputs: dict[str, np.ndarray]
   output: np.ndarray
   prev_desire: np.ndarray  # for tracking the rising edge of the pulse
 
-  def __init__(self, context: CLContext, model: str):
-    with open(MODELS_PATH / f'{model}_driving_vision_metadata.pkl', 'rb') as f:
-      vision_metadata = pickle.load(f)
-      self.vision_input_shapes =  vision_metadata['input_shapes']
-      self.vision_input_names = list(self.vision_input_shapes.keys())
-      self.vision_output_slices = vision_metadata['output_slices']
-      vision_output_size = vision_metadata['output_shapes']['outputs'][1]
+  def _build_policy_inputs(self, input_shapes: dict[str, tuple[int, ...]]) -> tuple[dict[str, np.ndarray], str | None]:
+    numpy_inputs: dict[str, np.ndarray] = {}
 
-    with open(MODELS_PATH / f'{model}_driving_policy_metadata.pkl', 'rb') as f:
-      policy_metadata = pickle.load(f)
-      self.policy_input_shapes =  policy_metadata['input_shapes']
-      self.policy_output_slices = policy_metadata['output_slices']
-      policy_output_size = policy_metadata['output_shapes']['outputs'][1]
+    # Always-supported inputs (if model expects them)
+    desire_key_init = next((k for k in input_shapes if k.startswith('desire')), None)
+    if desire_key_init:
+      numpy_inputs[desire_key_init] = np.zeros((1, ModelConstants.INPUT_HISTORY_BUFFER_LEN, ModelConstants.DESIRE_LEN), dtype=np.float32)
+    if 'traffic_convention' in input_shapes:
+      numpy_inputs['traffic_convention'] = np.zeros((1, ModelConstants.TRAFFIC_CONVENTION_LEN), dtype=np.float32)
+    if 'features_buffer' in input_shapes:
+      numpy_inputs['features_buffer'] = np.zeros((1, ModelConstants.INPUT_HISTORY_BUFFER_LEN,  ModelConstants.FEATURE_LEN), dtype=np.float32)
 
-    self.desire_type = 'desire_pulse' if 'desire_pulse' in self.policy_input_shapes else 'desire'
-    self.use_lateral_control_params = 'lateral_control_params' in self.policy_input_shapes
+    # Optional inputs for non-v11 (and some v10/v9 variants)
+    # Lateral control params
+    if 'lateral_control_params' in input_shapes:
+      numpy_inputs['lateral_control_params'] = np.zeros((1, ModelConstants.LATERAL_CONTROL_PARAMS_LEN), dtype=np.float32)
 
-    self.frames = {name: DrivingModelFrame(context, ModelConstants.MODEL_RUN_FREQ//ModelConstants.MODEL_CONTEXT_FREQ) for name in self.vision_input_names}
+    # Previous desired curvature: handle both singular and plural key names across model versions
+    prev_desired_curv_key = None
+    if 'prev_desired_curv' in input_shapes:
+      prev_desired_curv_key = 'prev_desired_curv'
+      numpy_inputs['prev_desired_curv'] = np.zeros((1, ModelConstants.INPUT_HISTORY_BUFFER_LEN, ModelConstants.PREV_DESIRED_CURV_LEN), dtype=np.float32)
+    elif 'prev_desired_curvs' in input_shapes:
+      prev_desired_curv_key = 'prev_desired_curvs'
+      numpy_inputs['prev_desired_curvs'] = np.zeros((1, ModelConstants.INPUT_HISTORY_BUFFER_LEN, ModelConstants.PREV_DESIRED_CURV_LEN), dtype=np.float32)
+
+    return numpy_inputs, prev_desired_curv_key
+
+  def __init__(self, context: CLContext):
+    # Dynamically build paths based on current model ID
+    params = Params()
+    model_id = params.get("Model", encoding="utf-8")
+
+    # Try to get ModelVersion, but handle case where parameter doesn't exist
+    model_version = None
+    try:
+      model_version = params.get("ModelVersion", encoding="utf-8")
+    except Exception as e:
+      cloudlog.warning(f"ModelVersion parameter not available: {e}")
+
+    model_dir = MODELS_PATH
+    # For the default "bd2" model, use built-in files from the models directory
+    if model_id == "bd2":
+        models_dir = Path(__file__).parent / "models"
+        VISION_PKL_PATH = models_dir / "driving_vision_tinygrad.pkl"
+        POLICY_PKL_PATH = models_dir / "driving_policy_tinygrad.pkl"
+        OFF_POLICY_PKL_PATH = models_dir / "driving_off_policy_tinygrad.pkl"
+        VISION_METADATA_PATH = models_dir / "driving_vision_metadata.pkl"
+        POLICY_METADATA_PATH = models_dir / "driving_policy_metadata.pkl"
+        OFF_POLICY_METADATA_PATH = models_dir / "driving_off_policy_metadata.pkl"
+    else:
+        VISION_PKL_PATH = model_dir / f"{model_id}_driving_vision_tinygrad.pkl"
+        POLICY_PKL_PATH = model_dir / f"{model_id}_driving_policy_tinygrad.pkl"
+        OFF_POLICY_PKL_PATH = model_dir / f"{model_id}_driving_off_policy_tinygrad.pkl"
+        VISION_METADATA_PATH = model_dir / f"{model_id}_driving_vision_metadata.pkl"
+        POLICY_METADATA_PATH = model_dir / f"{model_id}_driving_policy_metadata.pkl"
+        OFF_POLICY_METADATA_PATH = model_dir / f"{model_id}_driving_off_policy_metadata.pkl"
+
+    # If ModelVersion is not set or not available, try to determine it from available model data
+    if not model_version:
+      cloudlog.warning(f"ModelVersion not available for model {model_id}, attempting to determine from model data")
+      try:
+        # Try to get version from the model versions JSON file
+        versions_file = model_dir / ".model_versions.json"
+        if versions_file.is_file():
+          import json
+          with open(versions_file, "r") as f:
+            version_map = json.load(f)
+          if model_id in version_map:
+            model_version = version_map[model_id]
+            cloudlog.warning(f"Determined model version from JSON: {model_version}")
+        else:
+          cloudlog.error("Model versions JSON file not found, defaulting to v8")
+          model_version = "v8"
+      except Exception as e:
+        cloudlog.error(f"Failed to determine model version: {e}, defaulting to v8")
+        model_version = "v8"
+
+    try:
+      with open(VISION_METADATA_PATH, 'rb') as f:
+        vision_metadata = pickle.load(f)
+    except FileNotFoundError:
+      cloudlog.error(f"Missing metadata {VISION_METADATA_PATH}, downloading...")
+      from openpilot.frogpilot.assets.model_manager import ModelManager
+      ModelManager().download_model(model_id)
+      with open(VISION_METADATA_PATH, 'rb') as f:
+        vision_metadata = pickle.load(f)
+    self.vision_input_shapes =  vision_metadata['input_shapes']
+    self.vision_input_names = list(self.vision_input_shapes.keys())
+    self.vision_output_slices = vision_metadata['output_slices']
+    vision_output_size = vision_metadata['output_shapes']['outputs'][1]
+
+    try:
+      with open(POLICY_METADATA_PATH, 'rb') as f:
+        policy_metadata = pickle.load(f)
+    except FileNotFoundError:
+      cloudlog.error(f"Missing metadata {POLICY_METADATA_PATH}, downloading...")
+      from openpilot.frogpilot.assets.model_manager import ModelManager
+      ModelManager().download_model(model_id)
+      with open(POLICY_METADATA_PATH, 'rb') as f:
+        policy_metadata = pickle.load(f)
+    self.policy_input_shapes =  policy_metadata['input_shapes']
+    self.policy_output_slices = policy_metadata['output_slices']
+    policy_output_size = policy_metadata['output_shapes']['outputs'][1]
+    # Add policy_generation attribute after loading policy_metadata
+    self.policy_generation = model_version or "v8"
+    self.is_v11 = (self.policy_generation == "v11")
+    self.is_v9 = (self.policy_generation == "v9")
+    self.mlsim = (self.policy_generation in ("v8", "v10", "v11", "v12"))
+
+    self.frames = {name: DrivingModelFrame(context, ModelConstants.TEMPORAL_SKIP) for name in self.vision_input_names}
     self.prev_desire = np.zeros(ModelConstants.DESIRE_LEN, dtype=np.float32)
 
-    self.full_prev_desired_curv = np.zeros((1, ModelConstants.FULL_HISTORY_BUFFER_LEN, ModelConstants.PREV_DESIRED_CURV_LEN), dtype=np.float32)
-    self.temporal_idxs = slice(-1-(ModelConstants.TEMPORAL_SKIP*(ModelConstants.FULL_HISTORY_BUFFER_LEN-1)), None, ModelConstants.TEMPORAL_SKIP)
+    self.full_features_buffer = np.zeros((1, ModelConstants.FULL_HISTORY_BUFFER_LEN,  ModelConstants.FEATURE_LEN), dtype=np.float32)
+    self.full_desire = np.zeros((1, ModelConstants.FULL_HISTORY_BUFFER_LEN, ModelConstants.DESIRE_LEN), dtype=np.float32)
+    self.temporal_idxs = slice(-1-(ModelConstants.TEMPORAL_SKIP*(ModelConstants.INPUT_HISTORY_BUFFER_LEN-1)), None, ModelConstants.TEMPORAL_SKIP)
+
+
+    # policy inputs (built dynamically to support all generations)
+    self.numpy_inputs, self.prev_desired_curv_key = self._build_policy_inputs(self.policy_input_shapes)
+
+    # Off-policy model (optional)
+    self.off_policy_enabled = False
+    self.off_policy_input_shapes: dict[str, tuple[int, ...]] = {}
+    self.off_policy_output_slices: dict[str, slice] = {}
+    self.off_policy_numpy_inputs: dict[str, np.ndarray] = {}
+    self.off_policy_prev_desired_curv_key: str | None = None
+    self.off_policy_desire_key: str | None = None
+    self.off_policy_inputs: dict[str, Tensor] | None = None
+    self.off_policy_output: np.ndarray | None = None
+
+    off_policy_metadata = None
+    if self.policy_generation == "v12" or OFF_POLICY_METADATA_PATH.is_file() or OFF_POLICY_PKL_PATH.is_file():
+      try:
+        with open(OFF_POLICY_METADATA_PATH, 'rb') as f:
+          off_policy_metadata = pickle.load(f)
+      except FileNotFoundError:
+        cloudlog.error(f"Missing metadata {OFF_POLICY_METADATA_PATH}, downloading...")
+        from openpilot.frogpilot.assets.model_manager import ModelManager
+        ModelManager().download_model(model_id)
+        try:
+          with open(OFF_POLICY_METADATA_PATH, 'rb') as f:
+            off_policy_metadata = pickle.load(f)
+        except FileNotFoundError:
+          cloudlog.warning(f"Off-policy metadata still missing: {OFF_POLICY_METADATA_PATH}")
+
+    if off_policy_metadata is not None:
+      self.off_policy_input_shapes = off_policy_metadata['input_shapes']
+      self.off_policy_output_slices = off_policy_metadata['output_slices']
+      off_policy_output_size = off_policy_metadata['output_shapes']['outputs'][1]
+      self.off_policy_numpy_inputs, self.off_policy_prev_desired_curv_key = self._build_policy_inputs(self.off_policy_input_shapes)
+      self.off_policy_desire_key = next((k for k in self.off_policy_numpy_inputs if k.startswith('desire')), None)
+      self.off_policy_inputs = {k: Tensor(v, device='NPY').realize() for k, v in self.off_policy_numpy_inputs.items()}
+      self.off_policy_output = np.zeros(off_policy_output_size, dtype=np.float32)
+      try:
+        with open(OFF_POLICY_PKL_PATH, "rb") as f:
+          self.off_policy_run = pickle.load(f)
+        self.off_policy_enabled = True
+      except FileNotFoundError:
+        cloudlog.warning(f"Missing off-policy model {OFF_POLICY_PKL_PATH}, skipping off-policy")
+
+    # Optional temporal buffer for previous desired curvature (allocate only if any model expects it)
+    if self.prev_desired_curv_key is not None or self.off_policy_prev_desired_curv_key is not None:
+      self.full_prev_desired_curv = np.zeros((1, ModelConstants.FULL_HISTORY_BUFFER_LEN, ModelConstants.PREV_DESIRED_CURV_LEN), dtype=np.float32)
 
-    # policy inputs
-    self.numpy_inputs = {k: np.zeros(self.policy_input_shapes[k], dtype=np.float32) for k in self.policy_input_shapes}
-    self.full_input_queues = InputQueues(ModelConstants.MODEL_CONTEXT_FREQ, ModelConstants.MODEL_RUN_FREQ, ModelConstants.N_FRAMES)
-    for k in [self.desire_type, 'features_buffer']:
-      self.full_input_queues.update_dtypes_and_shapes({k: self.numpy_inputs[k].dtype}, {k: self.numpy_inputs[k].shape})
-    self.full_input_queues.reset()
 
     # img buffers are managed in openCL transform code
     self.vision_inputs: dict[str, Tensor] = {}
     self.vision_output = np.zeros(vision_output_size, dtype=np.float32)
     self.policy_inputs = {k: Tensor(v, device='NPY').realize() for k,v in self.numpy_inputs.items()}
     self.policy_output = np.zeros(policy_output_size, dtype=np.float32)
-    self.parser = Parser(ignore_missing=True)
+    self.parser = Parser()
+    self.off_policy_parser = Parser(ignore_missing=True)
 
-    with open(MODELS_PATH / f'{model}_driving_vision_tinygrad.pkl', "rb") as f:
+    with open(VISION_PKL_PATH, "rb") as f:
       self.vision_run = pickle.load(f)
 
-    with open(MODELS_PATH / f'{model}_driving_policy_tinygrad.pkl', "rb") as f:
+    with open(POLICY_PKL_PATH, "rb") as f:
       self.policy_run = pickle.load(f)
 
+  @property
+  def desire_key(self) -> str:
+    return next(key for key in self.numpy_inputs if key.startswith('desire'))
+
   def slice_outputs(self, model_outputs: np.ndarray, output_slices: dict[str, slice]) -> dict[str, np.ndarray]:
     parsed_model_outputs = {k: model_outputs[np.newaxis, v] for k,v in output_slices.items()}
     return parsed_model_outputs
@@ -197,15 +275,32 @@ class ModelState:
   def run(self, bufs: dict[str, VisionBuf], transforms: dict[str, np.ndarray],
                 inputs: dict[str, np.ndarray], prepare_only: bool) -> dict[str, np.ndarray] | None:
     # Model decides when action is completed, so desire input is just a pulse triggered on rising edge
-    inputs[self.desire_type][0] = 0
-    new_desire = np.where(inputs[self.desire_type] - self.prev_desire > .99, inputs[self.desire_type], 0)
-    self.prev_desire[:] = inputs[self.desire_type]
+    inputs[self.desire_key][0] = 0
+    new_desire = np.where(inputs[self.desire_key] - self.prev_desire > .99, inputs[self.desire_key], 0)
+    self.prev_desire[:] = inputs[self.desire_key]
 
-    if self.use_lateral_control_params:
+    self.full_desire[0,:-1] = self.full_desire[0,1:]
+    self.full_desire[0,-1] = new_desire
+    self.numpy_inputs[self.desire_key][:] = self.full_desire.reshape((1,ModelConstants.INPUT_HISTORY_BUFFER_LEN,ModelConstants.TEMPORAL_SKIP,-1)).max(axis=2)
+    if self.off_policy_enabled and self.off_policy_desire_key is not None:
+      self.off_policy_numpy_inputs[self.off_policy_desire_key][:] = self.numpy_inputs[self.desire_key]
+
+    if 'traffic_convention' in self.numpy_inputs:
+      self.numpy_inputs['traffic_convention'][:] = inputs['traffic_convention']
+    if self.off_policy_enabled and 'traffic_convention' in self.off_policy_numpy_inputs:
+      self.off_policy_numpy_inputs['traffic_convention'][:] = inputs['traffic_convention']
+
+    if 'lateral_control_params' in self.numpy_inputs:
       self.numpy_inputs['lateral_control_params'][:] = inputs['lateral_control_params']
+    if self.off_policy_enabled and 'lateral_control_params' in self.off_policy_numpy_inputs:
+      self.off_policy_numpy_inputs['lateral_control_params'][:] = inputs['lateral_control_params']
+
+    if prepare_only:
+      return None
+
     imgs_cl = {name: self.frames[name].prepare(bufs[name], transforms[name].flatten()) for name in self.vision_input_names}
 
-    if TICI and not USBGPU:
+    if TICI:
       # The imgs tensors are backed by opencl memory, only need init once
       for key in imgs_cl:
         if key not in self.vision_inputs:
@@ -215,54 +310,66 @@ class ModelState:
         frame_input = self.frames[key].buffer_from_cl(imgs_cl[key]).reshape(self.vision_input_shapes[key])
         self.vision_inputs[key] = Tensor(frame_input, dtype=dtypes.uint8).realize()
 
-    if prepare_only:
-      return None
-
     self.vision_output = self.vision_run(**self.vision_inputs).contiguous().realize().uop.base.buffer.numpy()
     vision_outputs_dict = self.parser.parse_vision_outputs(self.slice_outputs(self.vision_output, self.vision_output_slices))
 
-    self.full_input_queues.enqueue({'features_buffer': vision_outputs_dict['hidden_state'], self.desire_type: new_desire})
-    for k in [self.desire_type, 'features_buffer']:
-      self.numpy_inputs[k][:] = self.full_input_queues.get(k)[k]
-    self.numpy_inputs['traffic_convention'][:] = inputs['traffic_convention']
+    self.full_features_buffer[0,:-1] = self.full_features_buffer[0,1:]
+    self.full_features_buffer[0,-1] = vision_outputs_dict['hidden_state'][0, :]
+    if 'features_buffer' in self.numpy_inputs:
+      self.numpy_inputs['features_buffer'][:] = self.full_features_buffer[0, self.temporal_idxs]
+    if self.off_policy_enabled and 'features_buffer' in self.off_policy_numpy_inputs:
+      self.off_policy_numpy_inputs['features_buffer'][:] = self.full_features_buffer[0, self.temporal_idxs]
 
     self.policy_output = self.policy_run(**self.policy_inputs).contiguous().realize().uop.base.buffer.numpy()
     policy_outputs_dict = self.parser.parse_policy_outputs(self.slice_outputs(self.policy_output, self.policy_output_slices))
 
-    if self.use_lateral_control_params:
-      # TODO model only uses last value now
+    # TODO model only uses last value now
+    if hasattr(self, 'full_prev_desired_curv') and 'desired_curvature' in policy_outputs_dict:
       self.full_prev_desired_curv[0,:-1] = self.full_prev_desired_curv[0,1:]
       self.full_prev_desired_curv[0,-1,:] = policy_outputs_dict['desired_curvature'][0, :]
-      self.numpy_inputs['prev_desired_curv'][:] = 0*self.full_prev_desired_curv[0, self.temporal_idxs]
+
+      if self.prev_desired_curv_key is not None:
+        # v9 models expect zeros for prev_desired_curv(s); others use history
+        if self.is_v9:
+          self.numpy_inputs[self.prev_desired_curv_key][:] = 0 * self.full_prev_desired_curv[0, self.temporal_idxs]
+        else:
+          self.numpy_inputs[self.prev_desired_curv_key][:] = self.full_prev_desired_curv[0, self.temporal_idxs]
+
+      if self.off_policy_enabled and self.off_policy_prev_desired_curv_key is not None:
+        if self.is_v9:
+          self.off_policy_numpy_inputs[self.off_policy_prev_desired_curv_key][:] = 0 * self.full_prev_desired_curv[0, self.temporal_idxs]
+        else:
+          self.off_policy_numpy_inputs[self.off_policy_prev_desired_curv_key][:] = self.full_prev_desired_curv[0, self.temporal_idxs]
 
     combined_outputs_dict = {**vision_outputs_dict, **policy_outputs_dict}
+    if self.off_policy_enabled:
+      self.off_policy_output = self.off_policy_run(**self.off_policy_inputs).contiguous().realize().uop.base.buffer.numpy()
+      off_policy_outputs_dict = self.off_policy_parser.parse_policy_outputs(
+        self.slice_outputs(self.off_policy_output, self.off_policy_output_slices)
+      )
+      combined_outputs_dict.update(off_policy_outputs_dict)
     if SEND_RAW_PRED:
-      combined_outputs_dict['raw_pred'] = np.concatenate([self.vision_output.copy(), self.policy_output.copy()])
+      raw_pred = [self.vision_output.copy(), self.policy_output.copy()]
+      if self.off_policy_enabled and self.off_policy_output is not None:
+        raw_pred.append(self.off_policy_output.copy())
+      combined_outputs_dict['raw_pred'] = np.concatenate(raw_pred)
 
     return combined_outputs_dict
 
 
 def main(demo=False):
-  # FrogPilot variables
-  frogpilot_toggles = get_frogpilot_toggles()
+  cloudlog.warning("modeld init")
 
-  model_name = frogpilot_toggles.model
-  model_version = frogpilot_toggles.model_version
-  use_curvature_from_plan = frogpilot_toggles.model_version != "v7"
+  sentry.set_tag("daemon", PROCESS_NAME)
+  cloudlog.bind(daemon=PROCESS_NAME)
+  setproctitle(PROCESS_NAME)
+  config_realtime_process(7, 54)
 
-  cloudlog.warning("tinygrad_modeld init")
-
-  if not USBGPU:
-    # USB GPU currently saturates a core so can't do this yet,
-    # also need to move the aux USB interrupts for good timings
-    config_realtime_process(7, 54)
-
-  st = time.monotonic()
   cloudlog.warning("setting up CL context")
   cl_context = CLContext()
   cloudlog.warning("CL context ready; loading model")
-  model = ModelState(cl_context, model_name)
-  cloudlog.warning(f"models loaded in {time.monotonic() - st:.1f}s, tinygrad_modeld starting")
+  model = ModelState(cl_context)
+  cloudlog.warning("models loaded, modeld starting")
 
   # visionipc clients
   while True:
@@ -295,7 +402,7 @@ def main(demo=False):
   params = Params()
 
   # setup filter to track dropped frames
-  frame_dropped_filter = FirstOrderFilter(0., 10., 1. / ModelConstants.MODEL_RUN_FREQ)
+  frame_dropped_filter = FirstOrderFilter(0., 10., 1. / ModelConstants.MODEL_FREQ)
   frame_id = 0
   last_vipc_frame_id = 0
   run_count = 0
@@ -322,6 +429,9 @@ def main(demo=False):
 
   DH = DesireHelper()
 
+  # FrogPilot variables
+  frogpilot_toggles = get_frogpilot_toggles()
+
   while True:
     # Keep receiving frames until we are at least 1 frame ahead of previous extra frame
     while meta_main.timestamp_sof < meta_extra.timestamp_sof + 25000000:
@@ -391,11 +501,14 @@ def main(demo=False):
 
     bufs = {name: buf_extra if 'big' in name else buf_main for name in model.vision_input_names}
     transforms = {name: model_transform_extra if 'big' in name else model_transform_main for name in model.vision_input_names}
+
     inputs:dict[str, np.ndarray] = {
-      model.desire_type: vec_desire,
+      model.desire_key: vec_desire,
       'traffic_convention': traffic_convention,
-      **({'lateral_control_params': lateral_control_params} if model.use_lateral_control_params else {}),
     }
+    # Include optional inputs only if the loaded model expects them
+    if 'lateral_control_params' in model.numpy_inputs:
+      inputs['lateral_control_params'] = lateral_control_params
 
     mt1 = time.perf_counter()
     model_output = model.run(bufs, transforms, inputs, prepare_only)
@@ -408,7 +521,7 @@ def main(demo=False):
       drivingdata_send = messaging.new_message('drivingModelData')
       posenet_send = messaging.new_message('cameraOdometry')
 
-      action = get_action_from_model(model_output, prev_action, lat_delay + DT_MDL, long_delay + DT_MDL, v_ego, use_curvature_from_plan)
+      action = get_action_from_model(model_output, prev_action, lat_delay + DT_MDL, long_delay + DT_MDL, v_ego, model.mlsim, model.is_v9, frogpilot_toggles)
       prev_action = action
       fill_model_msg(drivingdata_send, modelv2_send, model_output, action,
                      publish_state, meta_main.frame_id, meta_extra.frame_id, frame_id,
@@ -432,7 +545,7 @@ def main(demo=False):
       pm.send('cameraOdometry', posenet_send)
     last_vipc_frame_id = meta_main.frame_id
 
-    # Update FrogPilot variables
+    # Update FrogPilot parameters
     if sm['frogpilotPlan'].togglesUpdated:
       frogpilot_toggles = get_frogpilot_toggles()
 
@@ -444,4 +557,7 @@ if __name__ == "__main__":
     args = parser.parse_args()
     main(demo=args.demo)
   except KeyboardInterrupt:
-    cloudlog.warning("got SIGINT")
+    cloudlog.warning(f"child {PROCESS_NAME} got SIGINT")
+  except Exception:
+    sentry.capture_exception()
+    raise

frogpilot/ui/qt/offroad/expandable_multi_option_dialog.cc

@@ -0,0 +1,766 @@
+#include "frogpilot/ui/qt/offroad/expandable_multi_option_dialog.h"
+
+#include <QPushButton>
+#include <QVBoxLayout>
+#include <QHBoxLayout>
+#include <QLabel>
+#include <QScrollBar>
+#include <QTimer>
+#include <QHBoxLayout>
+#include <QSpacerItem>
+#include <QLayout>
+#include <QLayoutItem>
+#include <QGridLayout>
+#include <QPoint>
+#include <QSize>
+#include <QSizePolicy>
+#include <QSet>
+#include <QVector>
+#include <QSignalBlocker>
+#include <QScroller>
+#include <QPointer>
+#include <QObject>
+
+#include <algorithm>
+
+#include "selfdrive/ui/qt/widgets/scrollview.h"
+
+ExpandableMultiOptionDialog::ExpandableMultiOptionDialog(const QString &prompt_text,
+                                                           const QMap<QString, QStringList> &seriesToModels,
+                                                           const QString &current, QWidget *parent,
+                                                           const QStringList &userFavorites,
+                                                           const QStringList &communityFavorites,
+                                                           const QMap<QString, QString> &modelReleasedDates,
+                                                           const QMap<QString, QString> &modelFileToNameMap,
+                                                           const QString &initialSortMode)
+  : DialogBase(parent), seriesToModels(seriesToModels), currentSortMode(initialSortMode.isEmpty() ? QString("alphabetical") : initialSortMode),
+    userFavorites(userFavorites), communityFavorites(communityFavorites), modelReleasedDates(modelReleasedDates),
+    modelFileToNameMap(modelFileToNameMap), currentSelection(current) {
+
+  baseSeriesToModels = seriesToModels;
+
+  for (auto it = this->modelFileToNameMap.constBegin(); it != this->modelFileToNameMap.constEnd(); ++it) {
+    modelNameToFileMap.insert(it.value(), it.key());
+  }
+
+  for (auto it = seriesToModels.constBegin(); it != seriesToModels.constEnd(); ++it) {
+    const QStringList &models = it.value();
+    for (const QString &modelName : models) {
+      if (modelName.isEmpty() || modelNameToFileMap.contains(modelName)) {
+        continue;
+      }
+      this->modelFileToNameMap.insert(modelName, modelName);
+      modelNameToFileMap.insert(modelName, modelName);
+    }
+  }
+
+  currentSelectionKey = modelNameToFileMap.value(currentSelection);
+  if (!currentSelectionKey.isEmpty()) {
+    selectionKey = currentSelectionKey;
+    selection = this->modelFileToNameMap.value(currentSelectionKey, currentSelection);
+    currentSelection = selection;
+  } else {
+    selectionKey.clear();
+    selection.clear();
+    currentSelection.clear();
+  }
+
+  if (currentSortMode != "alphabetical" && currentSortMode != "date" &&
+      currentSortMode != "favorites" && currentSortMode != "date_oldest") {
+    currentSortMode = "alphabetical";
+  }
+
+  QFrame *container = new QFrame(this);
+  container->setStyleSheet(R"(
+    QFrame { background-color: #1B1B1B; }
+    QPushButton {
+      height: 135;
+      padding: 0px 50px;
+      text-align: left;
+      font-size: 55px;
+      font-weight: 300;
+      border-radius: 10px;
+      background-color: #4F4F4F;
+      border: 2px solid transparent;
+    }
+    QPushButton.model-option:checked {
+      background-color: #465BEA !important;
+      border: 3px solid #FFFFFF !important;
+      color: white !important;
+      font-weight: 500 !important;
+    }
+    QPushButton:hover { background-color: #5A5A5A; }
+    QPushButton.model-option:checked:hover { background-color: #5A6BEA; }
+    QPushButton:pressed {
+      background-color: #3049F4;
+    }
+    QPushButton.model-option:checked:pressed {
+      background-color: #3049F4;
+      border: 3px solid #CCCCCC;
+    }
+    QPushButton.series-header {
+      background-color: #333333;
+      font-weight: 500;
+      text-align: left;
+      padding-left: 80px;
+    }
+    QPushButton.series-header:hover { background-color: #404040; }
+    QPushButton.favorite-button {
+      background-color: transparent;
+      border: none;
+      font-size: 60px;
+      padding: 0px;
+      margin: 0px;
+      min-width: 80px;
+      max-width: 80px;
+    }
+    QPushButton.favorite-button:hover { background-color: #404040; }
+    QComboBox {
+      background-color: #4F4F4F;
+      border: 2px solid transparent;
+      border-radius: 10px;
+      padding: 10px;
+      font-size: 50px;
+      color: white;
+      min-width: 200px;
+    }
+    QComboBox:hover { background-color: #5A5A5A; }
+    QComboBox::drop-down {
+      border: none;
+      width: 50px;
+    }
+    QComboBox::down-arrow {
+      image: url("../../frogpilot/assets/toggle_icons/icon_dropdown.png");
+      width: 30px;
+      height: 30px;
+    }
+    QComboBox QAbstractItemView {
+      background-color: #4F4F4F;
+      border: 2px solid #FFFFFF;
+      border-radius: 10px;
+      color: white;
+      selection-background-color: #465BEA;
+      font-size: 50px;
+    }
+  )");
+
+  QVBoxLayout *main_layout = new QVBoxLayout(container);
+  main_layout->setContentsMargins(55, 50, 55, 50);
+
+  QLabel *title = new QLabel(prompt_text, this);
+  title->setStyleSheet("font-size: 70px; font-weight: 500;");
+  main_layout->addWidget(title, 0, Qt::AlignLeft | Qt::AlignTop);
+  main_layout->addSpacing(25);
+
+  // Sort controls - simple cycling button
+  QHBoxLayout *sortLayout = new QHBoxLayout();
+  sortLayout->setContentsMargins(0, 0, 0, 0);
+  sortLayout->setSpacing(20);
+  sortLayout->addStretch(); // Push to the right
+
+  QLabel *sortLabel = new QLabel(tr("Sort by:"), this);
+  sortLabel->setStyleSheet("font-size: 50px; color: white;");
+  sortLayout->addWidget(sortLabel);
+
+  QPushButton *sortButton = new QPushButton(tr("Alphabetical"), this);
+  sortButton->setStyleSheet(R"(
+    QPushButton {
+      background-color: #4F4F4F;
+      border: 2px solid transparent;
+      border-radius: 10px;
+      padding: 10px 20px;
+      font-size: 50px;
+      color: white;
+      min-width: 250px;
+      text-align: center;
+    }
+    QPushButton:hover { background-color: #5A5A5A; }
+  )");
+
+  // Set initial button text based on sort mode
+  if (currentSortMode == "date") {
+    sortButton->setText(tr("Date (Newest)"));
+  } else if (currentSortMode == "date_oldest") {
+    sortButton->setText(tr("Date (Oldest)"));
+  } else if (currentSortMode == "favorites") {
+    sortButton->setText(tr("Favorites First"));
+  } else {
+    sortButton->setText(tr("Alphabetical"));
+  }
+
+  QWidget *sortWidget = new QWidget(container);
+  sortWidget->setLayout(sortLayout);
+  sortWidget->setSizePolicy(QSizePolicy::Maximum, QSizePolicy::Maximum);
+  sortLayout->setSizeConstraint(QLayout::SetFixedSize);
+  sortWidget->setStyleSheet("background: transparent;");
+
+  sortLayout->addWidget(sortButton);
+
+  auto updateSortOverlayGeometry = [sortWidget, sortLayout]() {
+    if (!sortWidget) return;
+    const QSize hint = sortLayout->sizeHint();
+    sortWidget->setFixedSize(hint);
+  };
+  updateSortOverlayGeometry();
+
+  QObject::connect(sortButton, &QPushButton::clicked, [this, sortButton, updateSortOverlayGeometry]() {
+    if (currentSortMode == "alphabetical") {
+      currentSortMode = "date";
+      sortButton->setText(tr("Date (Newest)"));
+    } else if (currentSortMode == "date") {
+      currentSortMode = "date_oldest";
+      sortButton->setText(tr("Date (Oldest)"));
+    } else if (currentSortMode == "date_oldest") {
+      currentSortMode = "favorites";
+      sortButton->setText(tr("Favorites First"));
+    } else {
+      currentSortMode = "alphabetical";
+      sortButton->setText(tr("Alphabetical"));
+    }
+    updateSortOverlayGeometry();
+    updateSorting();
+  });
+
+  listWidgetContainer = new QWidget(this);
+  listLayout = new QVBoxLayout(listWidgetContainer);
+  listLayout->setSpacing(10);
+  listLayout->setContentsMargins(0, 0, 0, 0);
+
+  confirmButton = new QPushButton(tr("Select"));
+  confirmButton->setObjectName("confirm_btn");
+  confirmButton->setEnabled(!selectionKey.isEmpty());
+
+  scrollView = new ScrollView(listWidgetContainer, this);
+  scrollView->setVerticalScrollBarPolicy(Qt::ScrollBarAsNeeded);
+  if (scrollView->viewport()) {
+    scrollView->viewport()->setAttribute(Qt::WA_AcceptTouchEvents, true);
+  }
+
+  QWidget *listContainer = new QWidget(container);
+  QGridLayout *overlayLayout = new QGridLayout(listContainer);
+  overlayLayout->setContentsMargins(0, 0, 0, 0);
+  overlayLayout->setSpacing(0);
+  overlayLayout->addWidget(scrollView, 0, 0);
+  overlayLayout->setRowStretch(0, 1);
+  overlayLayout->setColumnStretch(0, 1);
+  overlayLayout->addWidget(sortWidget, 0, 0, Qt::AlignRight | Qt::AlignTop);
+
+  // Create series headers and their expandable content
+  rebuildModelList(seriesToModels.keys(), seriesToModels);
+
+  main_layout->addWidget(listContainer);
+  main_layout->addSpacing(35);
+
+  // Cancel + confirm buttons
+  QHBoxLayout *blayout = new QHBoxLayout;
+  main_layout->addLayout(blayout);
+  blayout->setSpacing(50);
+
+  QPushButton *cancel_btn = new QPushButton(tr("Cancel"));
+  QObject::connect(cancel_btn, &QPushButton::clicked, this, &ConfirmationDialog::reject);
+  QObject::connect(confirmButton, &QPushButton::clicked, this, &ConfirmationDialog::accept);
+  blayout->addWidget(cancel_btn);
+  blayout->addWidget(confirmButton);
+
+  QVBoxLayout *outer_layout = new QVBoxLayout(this);
+  outer_layout->setContentsMargins(50, 50, 50, 50);
+  outer_layout->addWidget(container);
+
+  // Initial sorting
+  updateSorting();
+}
+
+void ExpandableMultiOptionDialog::toggleSeries(const QString &series, QPushButton *headerButton) {
+  if (!headerButton) return;
+
+  QWidget *container = seriesWidgets.value(series, nullptr);
+  if (!container) return;
+
+  bool expanded = seriesExpanded[series];
+  QString seriesName = series;
+
+  if (expanded) {
+    container->hide();
+    seriesExpanded[series] = false;
+    headerButton->setText("▶ " + seriesName);
+  } else {
+    container->show();
+    seriesExpanded[series] = true;
+    headerButton->setText("▼ " + seriesName);
+
+    // Auto-scroll to place the series at the top of the viewport when expanded
+    if (scrollView) {
+      QPointer<QPushButton> headerPtr(headerButton);
+      QPointer<ScrollView> scrollPtr(scrollView);
+      QTimer::singleShot(50, [headerPtr, scrollPtr]() {
+        if (!scrollPtr || !headerPtr) return;
+        QWidget *contents = scrollPtr->widget();
+        if (!contents) return;
+        if (QScrollBar *vScrollBar = scrollPtr->verticalScrollBar()) {
+          QPoint headerTop = headerPtr->mapTo(contents, QPoint(0, 0));
+          int targetValue = qMax(headerTop.y() - 20, 0);
+          vScrollBar->setValue(targetValue);
+        }
+      });
+    }
+  }
+
+  // Update the button's appearance
+  headerButton->update();
+}
+
+QString ExpandableMultiOptionDialog::getSelection(const QString &prompt_text,
+                                                    const QMap<QString, QStringList> &seriesToModels,
+                                                    const QString &current, QWidget *parent,
+                                                    const QStringList &userFavorites,
+                                                    const QStringList &communityFavorites,
+                                                    const QMap<QString, QString> &modelReleasedDates,
+                                                    const QMap<QString, QString> &modelFileToNameMap,
+                                                    const QString &initialSortMode) {
+  ExpandableMultiOptionDialog d(prompt_text, seriesToModels, current, parent,
+                                 userFavorites, communityFavorites, modelReleasedDates, modelFileToNameMap, initialSortMode);
+  if (d.exec()) {
+    return d.selection;
+  }
+  return "";
+}
+
+QStringList ExpandableMultiOptionDialog::getUserFavorites() const {
+  QStringList filteredFavorites;
+  for (const QString &fav : userFavorites) {
+    if (modelFileToNameMap.contains(fav) && !filteredFavorites.contains(fav)) {
+      filteredFavorites.append(fav);
+    }
+  }
+  return filteredFavorites;
+}
+
+void ExpandableMultiOptionDialog::stopActiveScroll() {
+  if (!scrollView) {
+    return;
+  }
+
+  if (QScroller *scroller = QScroller::scroller(scrollView->viewport())) {
+    if (scroller->state() == QScroller::Scrolling) {
+      scroller->stop();
+    }
+  }
+}
+
+void ExpandableMultiOptionDialog::stopActiveScrollForInteraction() {
+  if (!scrollView) {
+    return;
+  }
+
+  if (QScroller *scroller = QScroller::scroller(scrollView->viewport())) {
+    const QScroller::State state = scroller->state();
+    if (state == QScroller::Scrolling || state == QScroller::Dragging || state == QScroller::Pressed) {
+      scroller->stop();
+    }
+  }
+}
+
+void ExpandableMultiOptionDialog::createModelButton(const QString &modelKey, const QString &modelName, const QString &displayName,
+                                                    QVBoxLayout *layout) {
+  QString effectiveKey = modelKey.isEmpty() ? modelName : modelKey;
+  if (effectiveKey.isEmpty()) {
+    return;
+  }
+
+  if (!modelFileToNameMap.contains(effectiveKey)) {
+    const QString storedName = !modelName.isEmpty() ? modelName : displayName;
+    modelFileToNameMap.insert(effectiveKey, storedName);
+  }
+
+  if (!modelName.isEmpty()) {
+    modelNameToFileMap.insert(modelName, effectiveKey);
+  }
+
+  QWidget *modelWidget = new QWidget();
+  QHBoxLayout *modelLayout = new QHBoxLayout(modelWidget);
+  modelLayout->setContentsMargins(0, 0, 0, 0);
+  modelLayout->setSpacing(10);
+
+  // Star button
+  QPushButton *starButton = new QPushButton();
+  starButton->setProperty("class", "favorite-button");
+  starButton->setCheckable(true);
+  starButton->setCursor(Qt::PointingHandCursor);
+  starButton->setFocusPolicy(Qt::NoFocus);
+
+  // Check if this model is a favorite
+  bool isCommunityFav = communityFavorites.contains(effectiveKey);
+  bool isUserFav = userFavorites.contains(effectiveKey);
+  bool isFavorite = isCommunityFav || isUserFav;
+
+  starButton->setChecked(isFavorite);
+  starButton->setText(isFavorite ? QString::fromUtf16(u"\u2665") : QString::fromUtf16(u"\u2661"));
+
+  QObject::connect(starButton, &QPushButton::clicked, [this, effectiveKey]() {
+    stopActiveScrollForInteraction();
+    toggleFavorite(effectiveKey);
+  });
+
+  favoriteButtons[effectiveKey].append(starButton);
+  modelLayout->addWidget(starButton);
+
+  // Model button
+  QPushButton *modelButton = new QPushButton(displayName);
+  modelButton->setCheckable(true);
+  modelButton->setProperty("class", "model-option");
+  modelButton->setSizePolicy(QSizePolicy::Expanding, QSizePolicy::Preferred);
+  modelButton->setCursor(Qt::PointingHandCursor);
+  modelButton->setFocusPolicy(Qt::NoFocus);
+  modelButton->setProperty("modelKey", effectiveKey);
+  modelButton->setProperty("modelName", modelName);
+
+  modelButtons[effectiveKey].append(modelButton);
+  if (selectionKey == effectiveKey && currentSelectionButton.isNull()) {
+    currentSelectionButton = modelButton;
+  }
+  modelLayout->addWidget(modelButton);
+
+  const QString resolvedSelection = modelFileToNameMap.value(effectiveKey, !modelName.isEmpty() ? modelName : displayName);
+
+  QObject::connect(modelButton, &QPushButton::clicked, this, [this, effectiveKey, modelButton, resolvedSelection]() {
+    stopActiveScrollForInteraction();
+    selectionKey = effectiveKey;
+    currentSelectionKey = effectiveKey;
+    selection = resolvedSelection;
+    currentSelection = resolvedSelection;
+    currentSelectionButton = modelButton;
+    if (confirmButton) {
+      confirmButton->setEnabled(true);
+    }
+
+    updateButtonStyles();
+  });
+
+  layout->addWidget(modelWidget);
+}
+
+void ExpandableMultiOptionDialog::toggleFavorite(const QString &modelKey) {
+  // Update local state
+  if (modelKey.isEmpty()) {
+    return;
+  }
+
+  if (userFavorites.contains(modelKey)) {
+    userFavorites.removeAll(modelKey);
+  } else {
+    userFavorites.append(modelKey);
+  }
+
+  updateSorting();
+}
+
+void ExpandableMultiOptionDialog::updateSorting() {
+  const QString favoritesSeriesName = QStringLiteral("♥ Favorites");
+  QMap<QString, QStringList> newSeriesToModels;
+  QStringList orderedSeries;
+  QSet<QString> validSeries;
+  QSet<QString> favoriteModelKeys;
+  QSet<QString> availableModelKeys;
+  displayOverrides.clear();
+
+  const bool sortByDate = (currentSortMode == "date" || currentSortMode == "date_oldest");
+  const bool sortDateNewestFirst = (currentSortMode == "date");
+
+  for (auto it = baseSeriesToModels.constBegin(); it != baseSeriesToModels.constEnd(); ++it) {
+    const QStringList &models = it.value();
+    for (const QString &modelName : models) {
+      const QString modelKey = modelNameToFileMap.value(modelName, modelName);
+      if (!modelKey.isEmpty()) {
+        availableModelKeys.insert(modelKey);
+      }
+    }
+  }
+
+  if (currentSortMode == "favorites") {
+    QStringList favoritesList;
+
+    for (const QString &modelKey : communityFavorites) {
+      if (availableModelKeys.contains(modelKey)) {
+        const QString modelName = modelFileToNameMap.value(modelKey);
+        favoritesList.append(modelName);
+        favoriteModelKeys.insert(modelKey);
+        displayOverrides.insert(modelKey, tr("%1 (Community Fav)").arg(modelName));
+      }
+    }
+
+    for (const QString &modelKey : userFavorites) {
+      if (availableModelKeys.contains(modelKey) && !favoriteModelKeys.contains(modelKey)) {
+        favoritesList.append(modelFileToNameMap.value(modelKey));
+        favoriteModelKeys.insert(modelKey);
+      }
+    }
+
+    if (!favoritesList.isEmpty()) {
+      std::sort(favoritesList.begin(), favoritesList.end());
+      newSeriesToModels.insert(favoritesSeriesName, favoritesList);
+      orderedSeries.append(favoritesSeriesName);
+      validSeries.insert(favoritesSeriesName);
+      seriesExpanded.insert(favoritesSeriesName, true);
+    } else {
+      seriesExpanded.remove(favoritesSeriesName);
+    }
+  } else {
+    seriesExpanded.remove(favoritesSeriesName);
+  }
+
+  struct SeriesInfo {
+    QString name;
+    QStringList models;
+    QString newestDate;
+    QString oldestDate;
+  };
+
+  QVector<SeriesInfo> seriesInfos;
+
+  for (auto it = baseSeriesToModels.constBegin(); it != baseSeriesToModels.constEnd(); ++it) {
+    QString series = it.key();
+    QStringList models = it.value();
+
+    if (sortByDate) {
+      std::sort(models.begin(), models.end(), [this, sortDateNewestFirst](const QString &a, const QString &b) {
+        QString keyA = modelNameToFileMap.value(a, a);
+        QString keyB = modelNameToFileMap.value(b, b);
+        QString dateA = modelReleasedDates.value(keyA, QStringLiteral("1970-01-01"));
+        QString dateB = modelReleasedDates.value(keyB, QStringLiteral("1970-01-01"));
+        if (dateA == dateB) {
+          return a < b;
+        }
+        return sortDateNewestFirst ? (dateA > dateB) : (dateA < dateB);
+      });
+    } else {
+      std::sort(models.begin(), models.end());
+    }
+
+    if (currentSortMode == "favorites" && !favoriteModelKeys.isEmpty()) {
+      QStringList filteredModels;
+      for (const QString &modelName : models) {
+        QString key = modelNameToFileMap.value(modelName, modelName);
+        if (!favoriteModelKeys.contains(key)) {
+          filteredModels.append(modelName);
+        }
+      }
+      models = filteredModels;
+    }
+
+    if (models.isEmpty()) {
+      continue;
+    }
+
+    QString newestDate = QStringLiteral("1970-01-01");
+    QString oldestDate = QStringLiteral("1970-01-01");
+    bool hasDate = false;
+    for (const QString &modelName : models) {
+      const QString key = modelNameToFileMap.value(modelName, modelName);
+      const QString date = modelReleasedDates.value(key, QStringLiteral("1970-01-01"));
+      if (!hasDate) {
+        newestDate = date;
+        oldestDate = date;
+        hasDate = true;
+      } else {
+        if (date > newestDate) {
+          newestDate = date;
+        }
+        if (date < oldestDate) {
+          oldestDate = date;
+        }
+      }
+    }
+
+    if (!hasDate) {
+      oldestDate = QStringLiteral("1970-01-01");
+    }
+
+    seriesInfos.push_back({series, models, newestDate, oldestDate});
+    newSeriesToModels.insert(series, models);
+  }
+
+  if (sortByDate) {
+    std::sort(seriesInfos.begin(), seriesInfos.end(), [sortDateNewestFirst](const SeriesInfo &a, const SeriesInfo &b) {
+      if (sortDateNewestFirst) {
+        if (a.newestDate == b.newestDate) {
+          return a.name < b.name;
+        }
+        return a.newestDate > b.newestDate;
+      } else {
+        if (a.oldestDate == b.oldestDate) {
+          return a.name < b.name;
+        }
+        return a.oldestDate < b.oldestDate;
+      }
+    });
+  } else {
+    std::sort(seriesInfos.begin(), seriesInfos.end(), [](const SeriesInfo &a, const SeriesInfo &b) {
+      return a.name < b.name;
+    });
+  }
+
+  for (const SeriesInfo &info : seriesInfos) {
+    orderedSeries.append(info.name);
+    validSeries.insert(info.name);
+  }
+
+  for (auto it = seriesExpanded.begin(); it != seriesExpanded.end(); ) {
+    if (!validSeries.contains(it.key())) {
+      it = seriesExpanded.erase(it);
+    } else {
+      ++it;
+    }
+  }
+
+  rebuildModelList(orderedSeries, newSeriesToModels);
+  refreshFavoriteIcons();
+}
+
+void ExpandableMultiOptionDialog::rebuildModelList(const QStringList &orderedSeries, const QMap<QString, QStringList> &newSeriesToModels) {
+  if (!listLayout) return;
+
+  stopActiveScroll();
+
+  while (QLayoutItem *item = listLayout->takeAt(0)) {
+    if (QWidget *w = item->widget()) {
+      delete w;
+    } else if (QLayout *layout = item->layout()) {
+      delete layout;
+    }
+    delete item;
+  }
+
+  seriesWidgets.clear();
+  modelButtons.clear();
+  favoriteButtons.clear();
+  currentSelectionButton = nullptr;
+
+  for (const QString &series : orderedSeries) {
+    const QStringList models = newSeriesToModels.value(series);
+    if (models.isEmpty()) {
+      continue;
+    }
+
+    QPushButton *seriesHeader = new QPushButton("▶ " + series);
+    seriesHeader->setProperty("class", "series-header");
+    seriesHeader->setCheckable(false);
+
+    bool expanded = seriesExpanded.value(series, false);
+    seriesExpanded.insert(series, expanded);
+
+    QObject::connect(seriesHeader, &QPushButton::clicked, [this, series, seriesHeader]() {
+      toggleSeries(series, seriesHeader);
+    });
+
+    QWidget *seriesContainer = new QWidget();
+    QVBoxLayout *seriesLayout = new QVBoxLayout(seriesContainer);
+    seriesLayout->setContentsMargins(20, 0, 0, 0);
+    seriesLayout->setSpacing(10);
+
+    for (const QString &modelName : models) {
+      QString modelKey = modelNameToFileMap.value(modelName, modelName);
+      if (!modelFileToNameMap.contains(modelKey)) {
+        modelFileToNameMap.insert(modelKey, modelName);
+      }
+      QString displayName = displayOverrides.value(modelKey, modelName);
+      createModelButton(modelKey, modelName, displayName, seriesLayout);
+    }
+
+    if (expanded) {
+      seriesContainer->show();
+      seriesHeader->setText("▼ " + series);
+    } else {
+      seriesContainer->hide();
+      seriesHeader->setText("▶ " + series);
+    }
+
+    seriesWidgets.insert(series, seriesContainer);
+
+    listLayout->addWidget(seriesHeader);
+    listLayout->addWidget(seriesContainer);
+  }
+
+  listLayout->addStretch(1);
+
+  seriesToModels = newSeriesToModels;
+
+  listWidgetContainer->updateGeometry();
+  listWidgetContainer->adjustSize();
+  if (scrollView && scrollView->widget()) {
+    scrollView->widget()->updateGeometry();
+    scrollView->widget()->adjustSize();
+  }
+
+  updateButtonStyles();
+}
+
+void ExpandableMultiOptionDialog::refreshFavoriteIcons() {
+  for (auto it = favoriteButtons.begin(); it != favoriteButtons.end(); ++it) {
+    const QString &modelKey = it.key();
+    const QList<QPushButton*> &buttons = it.value();
+    bool isCommunityFav = communityFavorites.contains(modelKey);
+    bool isUserFav = userFavorites.contains(modelKey);
+    bool isFavorite = isCommunityFav || isUserFav;
+
+    for (QPushButton *button : buttons) {
+      if (!button) continue;
+      button->setChecked(isFavorite);
+      button->setText(isFavorite ? QString::fromUtf16(u"\u2665") : QString::fromUtf16(u"\u2661"));
+    }
+  }
+
+  if (confirmButton && !selectionKey.isEmpty()) {
+    confirmButton->setEnabled(true);
+  }
+
+  updateButtonStyles();
+}
+
+void ExpandableMultiOptionDialog::updateButtonStyles() {
+  const QString selectedKey = selectionKey;
+  const QString selectedStyle = QStringLiteral(
+      "QPushButton {"
+      "background-color: #465BEA;"
+      "border: 3px solid #FFFFFF;"
+      "color: white;"
+      "font-weight: 500;"
+      "height: 135;"
+      "padding: 0px 50px;"
+      "text-align: left;"
+      "font-size: 55px;"
+      "border-radius: 10px;"
+      "}");
+
+  if (selectedKey.isEmpty()) {
+    currentSelectionButton = nullptr;
+  }
+
+  QPushButton *explicitButton = currentSelectionButton.data();
+  if (explicitButton && explicitButton->property("modelKey").toString() != selectedKey) {
+    explicitButton = nullptr;
+  }
+
+  for (auto it = modelButtons.begin(); it != modelButtons.end(); ++it) {
+    const QString &modelKey = it.key();
+    const QList<QPushButton*> &buttons = it.value();
+    const bool keyMatches = (!selectedKey.isEmpty() && modelKey == selectedKey);
+    bool activatedForKey = false;
+
+    for (QPushButton *button : buttons) {
+      if (!button) continue;
+
+      bool isActive = false;
+      if (explicitButton) {
+        isActive = (button == explicitButton);
+      } else if (keyMatches && !activatedForKey) {
+        isActive = true;
+        activatedForKey = true;
+        currentSelectionButton = button;
+      }
+
+      QSignalBlocker blocker(button);
+      button->setChecked(isActive);
+      button->setStyleSheet(isActive ? selectedStyle : QString());
+    }
+  }
+}

frogpilot/ui/qt/offroad/expandable_multi_option_dialog.h

@@ -0,0 +1,76 @@
+#pragma once
+
+#include <QDialog>
+#include <QLabel>
+#include <QVBoxLayout>
+#include <QWidget>
+#include <QMap>
+#include <QList>
+#include <QPointer>
+#include <QComboBox>
+#include <QMenu>
+
+#include "selfdrive/ui/qt/widgets/input.h"
+#include "selfdrive/ui/qt/widgets/scrollview.h"
+
+class QPushButton;
+class ExpandableMultiOptionDialog : public DialogBase {
+  Q_OBJECT
+
+public:
+  explicit ExpandableMultiOptionDialog(const QString &prompt_text, const QMap<QString, QStringList> &seriesToModels,
+                                         const QString &current, QWidget *parent,
+                                         const QStringList &userFavorites = QStringList(),
+                                         const QStringList &communityFavorites = QStringList(),
+                                         const QMap<QString, QString> &modelReleasedDates = QMap<QString, QString>(),
+                                         const QMap<QString, QString> &modelFileToNameMap = QMap<QString, QString>(),
+                                         const QString &initialSortMode = "alphabetical");
+  static QString getSelection(const QString &prompt_text, const QMap<QString, QStringList> &seriesToModels,
+                                const QString &current, QWidget *parent,
+                                const QStringList &userFavorites = QStringList(),
+                                const QStringList &communityFavorites = QStringList(),
+                                const QMap<QString, QString> &modelReleasedDates = QMap<QString, QString>(),
+                                const QMap<QString, QString> &modelFileToNameMap = QMap<QString, QString>(),
+                                const QString &initialSortMode = QString());
+  QString selection;
+
+  QString getCurrentSortMode() const { return currentSortMode; }
+  QStringList getUserFavorites() const;
+
+private:
+  void toggleSeries(const QString &series, QPushButton *headerButton);
+  void toggleFavorite(const QString &modelKey);
+  void updateSorting();
+  void rebuildModelList(const QStringList &orderedSeries, const QMap<QString, QStringList> &newSeriesToModels);
+  void createModelButton(const QString &modelKey, const QString &modelName, const QString &displayName,
+                         QVBoxLayout *layout);
+  void refreshFavoriteIcons();
+  void updateButtonStyles();
+  void stopActiveScroll();
+  void stopActiveScrollForInteraction();
+
+  QMap<QString, QStringList> seriesToModels;
+  QMap<QString, QStringList> baseSeriesToModels;
+  QMap<QString, QWidget*> seriesWidgets;
+  QMap<QString, bool> seriesExpanded;
+  QMap<QString, QList<QPushButton*>> modelButtons;
+  QMap<QString, QList<QPushButton*>> favoriteButtons;
+
+  QStringList userFavorites;
+  QStringList communityFavorites;
+  QMap<QString, QString> modelReleasedDates;
+  QMap<QString, QString> modelFileToNameMap;
+  QMap<QString, QString> modelNameToFileMap;
+  QMap<QString, QString> displayOverrides;
+
+  QString currentSortMode;
+  QString currentSelection;
+  QString currentSelectionKey;
+  QString selectionKey;
+
+  ScrollView *scrollView = nullptr;
+  QVBoxLayout *listLayout = nullptr;
+  QPushButton *confirmButton = nullptr;
+  QWidget *listWidgetContainer = nullptr;
+  QPointer<QPushButton> currentSelectionButton;
+};

frogpilot/ui/qt/offroad/frogpilot_settings.cc

@@ -269,6 +269,7 @@ void FrogPilotSettingsWindow::updateVariables() {
     hasPedal = CP.getEnableGasInterceptor();
     hasRadar = !CP.getRadarUnavailable();
     hasSDSU = frogpilot_toggles.value("has_sdsu").toBool();
+    hasSASCM = frogpilot_toggles.value("has_sascm").toBool();
     hasSNG = hasOpenpilotLongitudinal && CP.getAutoResumeSng();
     hasZSS = frogpilot_toggles.value("has_zss").toBool();
     isAngleCar = CP.getSteerControlType() == cereal::CarParams::SteerControlType::ANGLE;
@@ -277,20 +278,27 @@ void FrogPilotSettingsWindow::updateVariables() {
     isHKG = carMake == "hyundai";
     isHKGCanFd = isHKG && safetyModel == cereal::CarParams::SafetyModel::HYUNDAI_CANFD;
     isSubaru = carMake == "subaru";
+    isTorqueCar = CP.getLateralTuning().which() == cereal::CarParams::LateralTuning::TORQUE;
     isToyota = carMake == "toyota";
     isTSK = CP.getSecOcRequired();
-    isVolt = carFingerprint == "CHEVROLET_VOLT";
+    isVolt = carFingerprint.find("CHEVROLET_VOLT") == 0;
+    if (isVolt) hasSNG = false;
     longitudinalActuatorDelay = CP.getLongitudinalActuatorDelay();
     startAccel = CP.getStartAccel();
     steerActuatorDelay = CP.getSteerActuatorDelay();
+    steerOffset = 0.0f;
+    steerKp = CP.getLateralTuning().which() == cereal::CarParams::LateralTuning::PID ? CP.getLateralTuning().getPid().getKpV()[0] : 0.6;
     steerRatio = CP.getSteerRatio();
     stopAccel = CP.getStopAccel();
     stoppingDecelRate = CP.getStoppingDecelRate();
     vEgoStarting = CP.getVEgoStarting();
     vEgoStopping = CP.getVEgoStopping();
+    friction = CP.getLateralTuning().getTorque().getFriction();
+    latAccelFactor = CP.getLateralTuning().getTorque().getLatAccelFactor();
 
     float currentDelayStock = params.getFloat("SteerDelayStock");
     float currentFrictionStock = params.getFloat("SteerFrictionStock");
+    float currentSteerOffsetStock = params.getFloat("SteerOffsetStock");
     float currentKPStock = params.getFloat("SteerKPStock");
     float currentLatAccelStock = params.getFloat("SteerLatAccelStock");
     float currentLongDelayStock = params.getFloat("LongitudinalActuatorDelayStock");
@@ -315,6 +323,13 @@ void FrogPilotSettingsWindow::updateVariables() {
       params.putFloat("SteerFrictionStock", friction);
     }
 
+    if (currentSteerOffsetStock != steerOffset) {
+      if (params.getFloat("SteerOffset") == currentSteerOffsetStock) {
+        params.putFloat("SteerOffset", steerOffset);
+      }
+      params.putFloat("SteerOffsetStock", steerOffset);
+    }
+
     if (currentKPStock != steerKp && steerKp != 0) {
       if (params.getFloat("SteerKP") == currentKPStock || currentKPStock == 0) {
         params.putFloat("SteerKP", steerKp);
@@ -387,12 +402,18 @@ void FrogPilotSettingsWindow::updateVariables() {
 
     canUsePedal = FPCP.getCanUsePedal();
     canUseSDSU = FPCP.getCanUseSDSU();
-    friction = FPCP.getLateralTuning().getTorque().getFriction();
-    hasAutoTune = (carMake == "hyundai" || carMake == "toyota") && FPCP.getLateralTuning().which() == cereal::FrogPilotCarParams::LateralTuning::TORQUE;
-    isTorqueCar = FPCP.getLateralTuning().which() == cereal::FrogPilotCarParams::LateralTuning::TORQUE;
-    latAccelFactor = FPCP.getLateralTuning().getTorque().getLatAccelFactor();
+    canUseSASCM = FPCP.getCanUseSASCM();
     openpilotLongitudinalControlDisabled = FPCP.getOpenpilotLongitudinalControlDisabled();
-    steerKp = FPCP.getLateralTuning().getTorque().getKp();
+  }
+
+  std::string liveTorqueParameters = params.get("LiveTorqueParameters");
+  if (!liveTorqueParameters.empty()) {
+    AlignedBuffer aligned_buf;
+    capnp::FlatArrayMessageReader reader(aligned_buf.align(liveTorqueParameters.data(), liveTorqueParameters.size()));
+    cereal::Event::Reader event = reader.getRoot<cereal::Event>();
+    cereal::LiveTorqueParametersData::Reader LTP = event.getLiveTorqueParameters();
+
+    hasAutoTune = LTP.getUseParams();
   }
 
   isC3 = util::read_file("/sys/firmware/devicetree/base/model").find("tici") != std::string::npos;

frogpilot/ui/qt/offroad/frogpilot_settings.h

@@ -13,6 +13,7 @@ public:
 
   bool canUsePedal = false;
   bool canUseSDSU = false;
+  bool canUseSASCM = false;
   bool forceOpenDescriptions = false;
   bool hasAutoTune = true;
   bool hasBSM = true;
@@ -24,6 +25,7 @@ public:
   bool hasPedal = false;
   bool hasRadar = true;
   bool hasSDSU = false;
+  bool hasSASCM = false;
   bool hasSNG = false;
   bool hasZSS = false;
   bool isAngleCar = false;
@@ -45,6 +47,7 @@ public:
   float longitudinalActuatorDelay;
   float startAccel;
   float steerActuatorDelay;
+  float steerOffset;
   float steerKp;
   float steerRatio;
   float stopAccel;

frogpilot/ui/qt/offroad/lateral_settings.cc

@@ -39,11 +39,12 @@ FrogPilotLateralPanel::FrogPilotLateralPanel(FrogPilotSettingsWindow *parent) :
 
   const std::vector<std::tuple<QString, QString, QString, QString>> lateralToggles {
     {"AdvancedLateralTune", tr("Advanced Lateral Tuning"), tr("<b>Advanced steering control changes to fine-tune how openpilot drives.</b>"), "../../frogpilot/assets/toggle_icons/icon_advanced_lateral_tune.png"},
-    {"SteerDelay", steerActuatorDelay != 0 ? QString(tr("Actuator Delay (Default: %1)")).arg(QString::number(steerActuatorDelay, 'f', 2)) : tr("Actuator Delay"), tr("<b>The time between openpilot's steering command and the vehicle's response.</b> Increase if the vehicle reacts late; decrease if it feels jumpy. Auto-learned by default."), ""},
-    {"SteerFriction", friction != 0 ? QString(tr("Friction (Default: %1)")).arg(QString::number(friction, 'f', 2)) : tr("Friction"), tr("<b>Compensates for steering friction.</b> Increase if the wheel sticks near center; decrease if it jitters. Auto-learned by default."), ""},
-    {"SteerKP", steerKp != 0 ? QString(tr("Kp Factor (Default: %1)")).arg(QString::number(steerKp, 'f', 2)) : tr("Kp Factor"), tr("<b>How strongly openpilot corrects lane position.</b> Higher is tighter but twitchier; lower is smoother but slower. Auto-learned by default."), ""},
-    {"SteerLatAccel", latAccelFactor != 0 ? QString(tr("Lateral Acceleration (Default: %1)")).arg(QString::number(latAccelFactor, 'f', 2)) : tr("Lateral Acceleration"), tr("<b>Maps steering torque to turning response.</b> Increase for sharper turns; decrease for gentler steering. Auto-learned by default."), ""},
-    {"SteerRatio", steerRatio != 0 ? QString(tr("Steer Ratio (Default: %1)")).arg(QString::number(steerRatio, 'f', 2)) : tr("Steer Ratio"), tr("<b>The relationship between steering wheel rotation and road wheel angle.</b> Increase if steering feels too quick or twitchy; decrease if it feels too slow or weak. Auto-learned by default."), ""},
+    {"SteerDelay", parent->steerActuatorDelay != 0 ? QString(tr("Actuator Delay (Default: %1)")).arg(QString::number(parent->steerActuatorDelay, 'f', 2)) : tr("Actuator Delay"), tr("<b>The time between openpilot's steering command and the vehicle's response.</b> Increase if the vehicle reacts late; decrease if it feels jumpy. Auto-learned by default."), ""},
+    {"SteerFriction", parent->friction != 0 ? QString(tr("Friction (Default: %1)")).arg(QString::number(parent->friction, 'f', 2)) : tr("Friction"), tr("<b>Compensates for steering friction.</b> Increase if the wheel sticks near center; decrease if it jitters. Auto-learned by default."), ""},
+    {"SteerOffset", parent->steerOffset != 0 ? QString(tr("Steer Offset (Default: %1)")).arg(QString::number(parent->steerOffset, 'f', 3)) : tr("Steer Offset"), tr("<b>Offsets steering torque to help compensate for alignment or tire issues.</b> More negative pulls the car right; more positive pulls it left. Most users should not need to touch this."), ""},
+    {"SteerKP", parent->steerKp != 0 ? QString(tr("Kp Factor (Default: %1)")).arg(QString::number(parent->steerKp, 'f', 2)) : tr("Kp Factor"), tr("<b>How strongly openpilot corrects lane position.</b> Higher is tighter but twitchier; lower is smoother but slower. Auto-learned by default."), ""},
+    {"SteerLatAccel", parent->latAccelFactor != 0 ? QString(tr("Lateral Acceleration (Default: %1)")).arg(QString::number(parent->latAccelFactor, 'f', 2)) : tr("Lateral Acceleration"), tr("<b>Maps steering torque to turning response.</b> Increase for sharper turns; decrease for gentler steering. Auto-learned by default."), ""},
+    {"SteerRatio", parent->steerRatio != 0 ? QString(tr("Steer Ratio (Default: %1)")).arg(QString::number(parent->steerRatio, 'f', 2)) : tr("Steer Ratio"), tr("<b>The relationship between steering wheel rotation and road wheel angle.</b> Increase if steering feels too quick or twitchy; decrease if it feels too slow or weak. Auto-learned by default."), ""},
     {"ForceAutoTune", tr("Force Auto-Tune On"), tr("<b>Force-enable openpilot's live auto-tuning for \"Friction\" and \"Lateral Acceleration\".</b>"), ""},
     {"ForceAutoTuneOff", tr("Force Auto-Tune Off"), tr("<b>Force-disable openpilot's live auto-tuning for \"Friction\" and \"Lateral Acceleration\" and use the set value instead.</b>"), ""},
     {"ForceTorqueController", tr("Force Torque Controller"), tr("<b>Use torque-based steering control instead of angle-based control for smoother lane keeping, especially in curves.</b>"), ""},
@@ -87,15 +88,18 @@ FrogPilotLateralPanel::FrogPilotLateralPanel(FrogPilotSettingsWindow *parent) :
     } else if (param == "SteerFriction") {
       std::vector<QString> steerFrictionButton{"Reset"};
       lateralToggle = new FrogPilotParamValueButtonControl(param, title, desc, icon, 0, 0.5, QString(), std::map<float, QString>(), 0.01, false, {}, steerFrictionButton, false, false);
+    } else if (param == "SteerOffset") {
+      std::vector<QString> steerOffsetButton{"Reset"};
+      lateralToggle = new FrogPilotParamValueButtonControl(param, title, desc, icon, -0.2, 0.2, QString(), std::map<float, QString>(), 0.005, false, {}, steerOffsetButton, false, false);
     } else if (param == "SteerKP") {
       std::vector<QString> steerKPButton{"Reset"};
-      lateralToggle = new FrogPilotParamValueButtonControl(param, title, desc, icon, steerKp * 0.5, steerKp * 1.5, QString(), std::map<float, QString>(), 0.01, false, {}, steerKPButton, false, false);
+      lateralToggle = new FrogPilotParamValueButtonControl(param, title, desc, icon, parent->steerKp * 0.5, parent->steerKp * 1.5, QString(), std::map<float, QString>(), 0.01, false, {}, steerKPButton, false, false);
     } else if (param == "SteerLatAccel") {
       std::vector<QString> steerLatAccelButton{"Reset"};
-      lateralToggle = new FrogPilotParamValueButtonControl(param, title, desc, icon, latAccelFactor * 0.75, latAccelFactor * 1.25, QString(), std::map<float, QString>(), 0.01, false, {}, steerLatAccelButton, false, false);
+      lateralToggle = new FrogPilotParamValueButtonControl(param, title, desc, icon, parent->latAccelFactor * 0.75, parent->latAccelFactor * 1.25, QString(), std::map<float, QString>(), 0.01, false, {}, steerLatAccelButton, false, false);
     } else if (param == "SteerRatio") {
       std::vector<QString> steerRatioButton{"Reset"};
-      lateralToggle = new FrogPilotParamValueButtonControl(param, title, desc, icon, steerRatio * 0.5, steerRatio * 1.5, QString(), std::map<float, QString>(), 0.01, false, {}, steerRatioButton, false, false);
+      lateralToggle = new FrogPilotParamValueButtonControl(param, title, desc, icon, parent->steerRatio * 0.5, parent->steerRatio * 1.5, QString(), std::map<float, QString>(), 0.01, false, {}, steerRatioButton, false, false);
 
     } else if (param == "AlwaysOnLateral") {
       FrogPilotManageControl *aolToggle = new FrogPilotManageControl(param, title, desc, icon);
@@ -191,12 +195,6 @@ FrogPilotLateralPanel::FrogPilotLateralPanel(FrogPilotSettingsWindow *parent) :
           if (FrogPilotConfirmationDialog::toggleReboot(this)) {
             Hardware::reboot();
           }
-        } else if (key == "NNFF" || key == "NNFFLite") {
-          if (!isTorqueCar) {
-            if (FrogPilotConfirmationDialog::toggleReboot(this)) {
-              Hardware::reboot();
-            }
-          }
         } else if (key != "AlwaysOnLateral") {
           if (FrogPilotConfirmationDialog::toggleReboot(this)) {
             Hardware::reboot();
@@ -207,41 +205,49 @@ FrogPilotLateralPanel::FrogPilotLateralPanel(FrogPilotSettingsWindow *parent) :
   }
 
   steerDelayToggle = static_cast<FrogPilotParamValueButtonControl*>(toggles["SteerDelay"]);
-  QObject::connect(steerDelayToggle, &FrogPilotParamValueButtonControl::buttonClicked, [this]() {
+  QObject::connect(steerDelayToggle, &FrogPilotParamValueButtonControl::buttonClicked, [parent, this]() {
     if (FrogPilotConfirmationDialog::yesorno(tr("Reset <b>Actuator Delay</b> to its default value?"), this)) {
-      params.putFloat("SteerDelay", steerActuatorDelay);
+      params.putFloat("SteerDelay", parent->steerActuatorDelay);
       steerDelayToggle->refresh();
     }
   });
 
   steerFrictionToggle = static_cast<FrogPilotParamValueButtonControl*>(toggles["SteerFriction"]);
-  QObject::connect(steerFrictionToggle, &FrogPilotParamValueButtonControl::buttonClicked, [this]() {
+  QObject::connect(steerFrictionToggle, &FrogPilotParamValueButtonControl::buttonClicked, [parent, this]() {
     if (FrogPilotConfirmationDialog::yesorno(tr("Reset <b>Friction</b> to its default value?"), this)) {
-      params.putFloat("SteerFriction", friction);
+      params.putFloat("SteerFriction", parent->friction);
       steerFrictionToggle->refresh();
     }
   });
 
+  steerOffsetToggle = static_cast<FrogPilotParamValueButtonControl*>(toggles["SteerOffset"]);
+  QObject::connect(steerOffsetToggle, &FrogPilotParamValueButtonControl::buttonClicked, [parent, this]() {
+    if (FrogPilotConfirmationDialog::yesorno(tr("Reset <b>Steer Offset</b> to its default value?"), this)) {
+      params.putFloat("SteerOffset", parent->steerOffset);
+      steerOffsetToggle->refresh();
+    }
+  });
+
   steerKPToggle = static_cast<FrogPilotParamValueButtonControl*>(toggles["SteerKP"]);
-  QObject::connect(steerKPToggle, &FrogPilotParamValueButtonControl::buttonClicked, [this]() {
+  QObject::connect(steerKPToggle, &FrogPilotParamValueButtonControl::buttonClicked, [parent, this]() {
     if (FrogPilotConfirmationDialog::yesorno(tr("Reset <b>Kp Factor</b> to its default value?"), this)) {
-      params.putFloat("SteerKP", steerKp);
+      params.putFloat("SteerKP", parent->steerKp);
       steerKPToggle->refresh();
     }
   });
 
   steerLatAccelToggle = static_cast<FrogPilotParamValueButtonControl*>(toggles["SteerLatAccel"]);
-  QObject::connect(steerLatAccelToggle, &FrogPilotParamValueButtonControl::buttonClicked, [this]() {
+  QObject::connect(steerLatAccelToggle, &FrogPilotParamValueButtonControl::buttonClicked, [parent, this]() {
     if (FrogPilotConfirmationDialog::yesorno(tr("Reset <b>Lateral Accel</b> to its default value?"), this)) {
-      params.putFloat("SteerLatAccel", latAccelFactor);
+      params.putFloat("SteerLatAccel", parent->latAccelFactor);
       steerLatAccelToggle->refresh();
     }
   });
 
   steerRatioToggle = static_cast<FrogPilotParamValueButtonControl*>(toggles["SteerRatio"]);
-  QObject::connect(steerRatioToggle, &FrogPilotParamValueButtonControl::buttonClicked, [this]() {
+  QObject::connect(steerRatioToggle, &FrogPilotParamValueButtonControl::buttonClicked, [parent, this]() {
     if (FrogPilotConfirmationDialog::yesorno(tr("Reset <b>Steer Ratio</b> to its default value?"), this)) {
-      params.putFloat("SteerRatio", steerRatio);
+      params.putFloat("SteerRatio", parent->steerRatio);
       steerRatioToggle->refresh();
     }
   });
@@ -258,27 +264,16 @@ FrogPilotLateralPanel::FrogPilotLateralPanel(FrogPilotSettingsWindow *parent) :
 
 void FrogPilotLateralPanel::showEvent(QShowEvent *event) {
   frogpilotToggleLevels = parent->frogpilotToggleLevels;
-  friction = parent->friction;
-  hasAutoTune = parent->hasAutoTune;
-  hasNNFFLog = parent->hasNNFFLog;
-  hasOpenpilotLongitudinal = parent->hasOpenpilotLongitudinal;
-  isAngleCar = parent->isAngleCar;
-  isHKGCanFd = parent->isHKGCanFd;
-  isTorqueCar = parent->isTorqueCar;
-  latAccelFactor = parent->latAccelFactor;
-  steerActuatorDelay = parent->steerActuatorDelay;
-  steerKp = parent->steerKp;
-  steerRatio = parent->steerRatio;
-  tuningLevel = parent->tuningLevel;
 
-  steerDelayToggle->setTitle(QString(tr("Actuator Delay (Default: %1)")).arg(QString::number(steerActuatorDelay, 'f', 2)));
-  steerFrictionToggle->setTitle(QString(tr("Friction (Default: %1)")).arg(QString::number(friction, 'f', 2)));
-  steerKPToggle->setTitle(QString(tr("Kp Factor (Default: %1)")).arg(QString::number(steerKp, 'f', 2)));
-  steerKPToggle->updateControl(steerKp * 0.5, steerKp * 1.5);
-  steerLatAccelToggle->setTitle(QString(tr("Lateral Accel (Default: %1)")).arg(QString::number(latAccelFactor, 'f', 2)));
-  steerLatAccelToggle->updateControl(latAccelFactor * 0.75, latAccelFactor * 1.25);
-  steerRatioToggle->setTitle(QString(tr("Steer Ratio (Default: %1)")).arg(QString::number(steerRatio, 'f', 2)));
-  steerRatioToggle->updateControl(steerRatio * 0.5, steerRatio * 1.5);
+  steerDelayToggle->setTitle(QString(tr("Actuator Delay (Default: %1)")).arg(QString::number(parent->steerActuatorDelay, 'f', 2)));
+  steerFrictionToggle->setTitle(QString(tr("Friction (Default: %1)")).arg(QString::number(parent->friction, 'f', 2)));
+  steerOffsetToggle->setTitle(QString(tr("Steer Offset (Default: %1)")).arg(QString::number(parent->steerOffset, 'f', 3)));
+  steerKPToggle->setTitle(QString(tr("Kp Factor (Default: %1)")).arg(QString::number(parent->steerKp, 'f', 2)));
+  steerKPToggle->updateControl(parent->steerKp * 0.5, parent->steerKp * 1.5);
+  steerLatAccelToggle->setTitle(QString(tr("Lateral Accel (Default: %1)")).arg(QString::number(parent->latAccelFactor, 'f', 2)));
+  steerLatAccelToggle->updateControl(parent->latAccelFactor * 0.75, parent->latAccelFactor * 1.25);
+  steerRatioToggle->setTitle(QString(tr("Steer Ratio (Default: %1)")).arg(QString::number(parent->steerRatio, 'f', 2)));
+  steerRatioToggle->updateControl(parent->steerRatio * 0.5, parent->steerRatio * 1.5);
 
   updateToggles();
 }
@@ -358,41 +353,40 @@ void FrogPilotLateralPanel::updateToggles() {
     }
   }
 
-  bool forcingAutoTune = !hasAutoTune && params.getBool("ForceAutoTune");
-  bool forcingAutoTuneOff = hasAutoTune && params.getBool("ForceAutoTuneOff");
-  bool forcingTorqueController = !isAngleCar && params.getBool("ForceTorqueController");
-  bool usingNNFF = hasNNFFLog && params.getBool("LateralTune") && params.getBool("NNFF");
+  bool forcingAutoTuneOff = parent->hasAutoTune && params.getBool("ForceAutoTuneOff");
+  bool forcingTorqueController = !parent->isAngleCar && params.getBool("ForceTorqueController");
+  bool usingNNFF = parent->hasNNFFLog && params.getBool("LateralTune") && params.getBool("NNFF");
 
   for (auto &[key, toggle] : toggles) {
     if (parentKeys.contains(key)) {
       continue;
     }
 
-    bool setVisible = tuningLevel >= frogpilotToggleLevels[key].toDouble();
+    bool setVisible = parent->tuningLevel >= frogpilotToggleLevels[key].toDouble();
 
     if (key == "AlwaysOnLateralLKAS") {
-      setVisible &= isHKGCanFd;
-      setVisible &= !hasOpenpilotLongitudinal;
+      setVisible &= parent->isHKGCanFd;
+      setVisible &= !parent->hasOpenpilotLongitudinal;
     }
 
     else if (key == "AlwaysOnLateralMain") {
-      setVisible &= !isHKGCanFd;
-      setVisible |= hasOpenpilotLongitudinal;
+      setVisible &= !parent->isHKGCanFd;
+      setVisible |= parent->hasOpenpilotLongitudinal;
     }
 
     else if (key == "ForceAutoTune") {
-      setVisible &= !hasAutoTune;
-      setVisible &= !isAngleCar;
-      setVisible &= isTorqueCar || forcingTorqueController;
+      setVisible &= !parent->hasAutoTune;
+      setVisible &= !parent->isAngleCar;
+      setVisible &= parent->isTorqueCar || forcingTorqueController;
     }
 
     else if (key == "ForceAutoTuneOff") {
-      setVisible &= hasAutoTune;
+      setVisible &= parent->hasAutoTune;
     }
 
     else if (key == "ForceTorqueController") {
-      setVisible &= !isAngleCar;
-      setVisible &= !isTorqueCar;
+      setVisible &= !parent->isAngleCar;
+      setVisible &= !parent->isTorqueCar;
     }
 
     else if (key == "LaneChangeTime") {
@@ -404,42 +398,47 @@ void FrogPilotLateralPanel::updateToggles() {
     }
 
     else if (key == "NNFF") {
-      setVisible &= hasNNFFLog;
-      setVisible &= !isAngleCar;
+      setVisible &= parent->hasNNFFLog;
+      setVisible &= !parent->isAngleCar;
     }
 
     else if (key == "NNFFLite") {
       setVisible &= !usingNNFF;
-      setVisible &= !isAngleCar;
+      setVisible &= !parent->isAngleCar;
     }
 
     else if (key == "SteerDelay") {
-      setVisible &= steerActuatorDelay != 0;
+      setVisible &= parent->steerActuatorDelay != 0;
     }
 
     else if (key == "SteerFriction") {
-      setVisible &= friction != 0;
-      setVisible &= hasAutoTune ? forcingAutoTuneOff : !forcingAutoTune;
-      setVisible &= isTorqueCar || forcingTorqueController;
+      setVisible &= parent->friction != 0;
+      setVisible &= parent->hasAutoTune ? forcingAutoTuneOff : true;
+      setVisible &= parent->isTorqueCar || forcingTorqueController;
+      setVisible &= !usingNNFF;
+    }
+
+    else if (key == "SteerOffset") {
+      setVisible &= parent->isGM;
+      setVisible &= parent->isTorqueCar || forcingTorqueController;
       setVisible &= !usingNNFF;
     }
 
     else if (key == "SteerKP") {
-      setVisible &= steerKp != 0;
-      setVisible &= hasAutoTune ? forcingAutoTuneOff : !forcingAutoTune;
-      setVisible &= isTorqueCar || forcingTorqueController;
+      setVisible &= parent->steerKp != 0;
+      setVisible &= !parent->isAngleCar;
     }
 
     else if (key == "SteerLatAccel") {
-      setVisible &= latAccelFactor != 0;
-      setVisible &= hasAutoTune ? forcingAutoTuneOff : !forcingAutoTune;
-      setVisible &= isTorqueCar || forcingTorqueController;
+      setVisible &= parent->latAccelFactor != 0;
+      setVisible &= parent->hasAutoTune ? forcingAutoTuneOff : true;
+      setVisible &= parent->isTorqueCar || forcingTorqueController;
       setVisible &= !usingNNFF;
     }
 
     else if (key == "SteerRatio") {
-      setVisible &= steerRatio != 0;
-      setVisible &= hasAutoTune ? forcingAutoTuneOff : !forcingAutoTune;
+      setVisible &= parent->steerRatio != 0;
+      setVisible &= parent->hasAutoTune ? forcingAutoTuneOff : true;
     }
 
     toggle->setVisible(setVisible);

frogpilot/ui/qt/offroad/lateral_settings.h

@@ -31,6 +31,7 @@ private:
   float friction;
   float latAccelFactor;
   float steerActuatorDelay;
+  float steerOffset;
   float steerKp;
   float steerRatio;
 
@@ -38,7 +39,7 @@ private:
 
   std::map<QString, AbstractControl*> toggles;
 
-  QSet<QString> advancedLateralTuneKeys = {"ForceAutoTune", "ForceAutoTuneOff", "ForceTorqueController", "SteerDelay", "SteerFriction", "SteerLatAccel", "SteerKP", "SteerRatio"};
+  QSet<QString> advancedLateralTuneKeys = {"ForceAutoTune", "ForceAutoTuneOff", "ForceTorqueController", "SteerDelay", "SteerFriction", "SteerOffset", "SteerLatAccel", "SteerKP", "SteerRatio"};
   QSet<QString> aolKeys = {"AlwaysOnLateralLKAS", "AlwaysOnLateralMain", "PauseAOLOnBrake"};
   QSet<QString> laneChangeKeys = {"LaneChangeTime", "LaneDetectionWidth", "MinimumLaneChangeSpeed", "NudgelessLaneChange", "OneLaneChange"};
   QSet<QString> lateralTuneKeys = {"NNFF", "NNFFLite", "TurnDesires"};
@@ -48,6 +49,7 @@ private:
 
   FrogPilotParamValueButtonControl *steerDelayToggle;
   FrogPilotParamValueButtonControl *steerFrictionToggle;
+  FrogPilotParamValueButtonControl *steerOffsetToggle;
   FrogPilotParamValueButtonControl *steerLatAccelToggle;
   FrogPilotParamValueButtonControl *steerKPToggle;
   FrogPilotParamValueButtonControl *steerRatioToggle;

frogpilot/ui/qt/offroad/longitudinal_settings.h

@@ -40,19 +40,19 @@ private:
 
   std::map<QString, AbstractControl*> toggles;
 
-  QSet<QString> advancedLongitudinalTuneKeys = {"LongitudinalActuatorDelay", "StartAccel", "StopAccel", "StoppingDecelRate", "VEgoStarting", "VEgoStopping"};
-  QSet<QString> aggressivePersonalityKeys = {"AggressiveFollow", "AggressiveJerkAcceleration", "AggressiveJerkDeceleration", "AggressiveJerkDanger", "AggressiveJerkSpeed", "AggressiveJerkSpeedDecrease", "ResetAggressivePersonality"};
+  QSet<QString> advancedLongitudinalTuneKeys = {"EVTuning", "LongitudinalActuatorDelay", "StartAccel", "StopAccel", "StoppingDecelRate", "VEgoStarting", "VEgoStopping"};
+  QSet<QString> aggressivePersonalityKeys = {"AggressiveFollow", "AggressiveFollowHigh", "AggressiveJerkAcceleration", "AggressiveJerkDeceleration", "AggressiveJerkDanger", "AggressiveJerkSpeed", "AggressiveJerkSpeedDecrease", "ResetAggressivePersonality"};
   QSet<QString> conditionalExperimentalKeys = {"CESpeed", "CESpeedLead", "CECurves", "CELead", "CEModelStopTime", "CENavigation", "CESignalSpeed", "ShowCEMStatus"};
   QSet<QString> curveSpeedKeys = {"CalibratedLateralAcceleration", "CalibrationProgress", "ResetCurveData", "ShowCSCStatus"};
   QSet<QString> customDrivingPersonalityKeys = {"AggressivePersonalityProfile", "RelaxedPersonalityProfile", "StandardPersonalityProfile", "TrafficPersonalityProfile"};
-  QSet<QString> longitudinalTuneKeys = {"AccelerationProfile", "DecelerationProfile", "HumanAcceleration", "HumanFollowing", "LeadDetectionThreshold", "MaxDesiredAcceleration", "TacoTune"};
+  QSet<QString> longitudinalTuneKeys = {"AccelerationProfile", "DecelerationProfile", "HumanAcceleration", "HumanFollowing", "LeadDetectionThreshold", "MaxDesiredAcceleration", "TrailerLoad", "TacoTune"};
   QSet<QString> qolKeys = {"CustomCruise", "CustomCruiseLong", "ForceStops", "IncreasedStoppedDistance", "MapGears", "ReverseCruise", "SetSpeedOffset"};
-  QSet<QString> relaxedPersonalityKeys = {"RelaxedFollow", "RelaxedJerkAcceleration", "RelaxedJerkDeceleration", "RelaxedJerkDanger", "RelaxedJerkSpeed", "RelaxedJerkSpeedDecrease", "ResetRelaxedPersonality"};
+  QSet<QString> relaxedPersonalityKeys = {"RelaxedFollow", "RelaxedFollowHigh", "RelaxedJerkAcceleration", "RelaxedJerkDeceleration", "RelaxedJerkDanger", "RelaxedJerkSpeed", "RelaxedJerkSpeedDecrease", "ResetRelaxedPersonality"};
   QSet<QString> speedLimitControllerKeys = {"SLCOffsets", "SLCFallback", "SLCOverride", "SLCPriority", "SLCQOL", "SLCVisuals"};
   QSet<QString> speedLimitControllerOffsetsKeys = {"Offset1", "Offset2", "Offset3", "Offset4", "Offset5", "Offset6", "Offset7"};
   QSet<QString> speedLimitControllerQOLKeys = {"ForceMPHDashboard", "SetSpeedLimit", "SLCConfirmation", "SLCLookaheadHigher", "SLCLookaheadLower", "SLCMapboxFiller"};
   QSet<QString> speedLimitControllerVisualKeys = {"ShowSLCOffset", "SpeedLimitSources"};
-  QSet<QString> standardPersonalityKeys = {"StandardFollow", "StandardJerkAcceleration", "StandardJerkDeceleration", "StandardJerkDanger", "StandardJerkSpeed", "StandardJerkSpeedDecrease", "ResetStandardPersonality"};
+  QSet<QString> standardPersonalityKeys = {"StandardFollow", "StandardFollowHigh", "StandardJerkAcceleration", "StandardJerkDeceleration", "StandardJerkDanger", "StandardJerkSpeed", "StandardJerkSpeedDecrease", "ResetStandardPersonality"};
   QSet<QString> trafficPersonalityKeys = {"TrafficFollow", "TrafficJerkAcceleration", "TrafficJerkDeceleration", "TrafficJerkDanger", "TrafficJerkSpeed", "TrafficJerkSpeedDecrease", "ResetTrafficPersonality"};
 
   QSet<QString> parentKeys;

frogpilot/ui/qt/offroad/model_settings.cc

@@ -1,39 +1,15 @@
 #include "frogpilot/ui/qt/offroad/model_settings.h"
-
-bool hasAllTinygradFiles(const QDir &modelDir, const QString &modelKey) {
-  QStringList tinygradSuffixes = {
-    "_driving_policy_metadata.pkl",
-    "_driving_policy_tinygrad.pkl",
-    "_driving_vision_metadata.pkl",
-    "_driving_vision_tinygrad.pkl"
-  };
-
-  for (const QString &suffix : tinygradSuffixes) {
-    if (!modelDir.exists(modelKey + suffix)) {
-      return false;
-    }
-  }
-  return true;
-}
-
-QString normalizeModelKey(QString key) {
-  key = key.toLower();
-  if (key.endsWith("_default")) {
-    key.chop(QString("_default").size());
-  }
-  return key;
-}
+#include "frogpilot/ui/qt/offroad/expandable_multi_option_dialog.h"
+#include <QFile>
+#include <QFileInfo>
+#include <QJsonDocument>
+#include <QJsonObject>
+#include <QDoubleSpinBox>
+#include <QPushButton>
+#include <QDialog>
+#include <algorithm>
 
 FrogPilotModelPanel::FrogPilotModelPanel(FrogPilotSettingsWindow *parent) : FrogPilotListWidget(parent), parent(parent) {
-  QJsonObject shownDescriptions = QJsonDocument::fromJson(QString::fromStdString(params.get("ShownToggleDescriptions")).toUtf8()).object();
-  QString className = this->metaObject()->className();
-
-  if (!shownDescriptions.value(className).toBool(false)) {
-    forceOpenDescriptions = true;
-    shownDescriptions.insert(className, true);
-    params.put("ShownToggleDescriptions", QJsonDocument(shownDescriptions).toJson(QJsonDocument::Compact).toStdString());
-  }
-
   QStackedLayout *modelLayout = new QStackedLayout();
   addItem(modelLayout);
 
@@ -50,58 +26,92 @@ FrogPilotModelPanel::FrogPilotModelPanel(FrogPilotSettingsWindow *parent) : Frog
   modelLayout->addWidget(modelLabelsPanel);
 
   const std::vector<std::tuple<QString, QString, QString, QString>> modelToggles {
-    {"AutomaticallyDownloadModels", tr("Automatically Download New Models"), tr("<b>Automatically download new driving models</b> as they become available."), ""},
-    {"DeleteModel", tr("Delete Driving Models"), tr("<b>Delete downloaded driving models</b> to free up storage space."), ""},
-    {"DownloadModel", tr("Download Driving Models"), tr("<b>Manually download driving models</b> to the device."), ""},
-    {"ModelRandomizer", tr("Model Randomizer"), tr("<b>Select a random driving model each drive</b> and use feedback prompts at the end of the drive to help find the model that best suits you!"), ""},
-    {"ManageBlacklistedModels", tr("Manage Model Blacklist"), tr("<b>Add or remove driving models from the \"Model Randomizer\" blacklist.</b>"), ""},
-    {"ManageScores", tr("Manage Model Ratings"), tr("<b>View or reset saved model ratings</b> used by the \"Model Randomizer\"."), ""},
-    {"SelectModel", tr("Select Driving Model"), tr("<b>Choose which driving model openpilot uses.</b>"), ""},
-    {"UpdateTinygrad", tr("Update Model Manager"), tr("<b>Update the \"Model Manager\"</b> to support the latest models."), ""}
+    {"AutomaticallyDownloadModels", tr("Automatically Download New Models"), tr("Automatically download new driving models as they become available."), ""},
+    {"DeleteModel", tr("Delete Driving Models"), tr("Delete driving models from the device."), ""},
+    {"DownloadModel", tr("Download Driving Models"), tr("Download driving models to the device."), ""},
+    {"ModelRandomizer", tr("Model Randomizer"), tr("Driving models are chosen at random each drive and feedback prompts are used to find the model that best suits your needs."), ""},
+    {"RecoveryPower", tr("Recovery Power"), tr("Adjust the strength of planplus lane recovery corrections (0.5 to 2.0)."), ""},
+    {"StopDistance", tr("Stop Distance"), tr("Adjust the model's stopping distance in meters (minimum 4 for safety). Most users prefer 6."), ""},
+    {"ManageBlacklistedModels", tr("Manage Model Blacklist"), tr("Add or remove models from the <b>Model Randomizer</b>'s blacklist list."), ""},
+    {"ManageScores", tr("Manage Model Ratings"), tr("Reset or view the saved ratings for the driving models."), ""},
+    {"SelectModel", tr("Select Driving Model"), tr("Select the active driving model."), ""},
   };
 
+  FrogPilotParamValueButtonControl *recoveryPowerToggle = nullptr;
+  FrogPilotParamValueButtonControl *stopDistanceToggle = nullptr;
+
   for (const auto &[param, title, desc, icon] : modelToggles) {
     AbstractControl *modelToggle;
 
     if (param == "DeleteModel") {
       deleteModelButton = new FrogPilotButtonsControl(title, desc, icon, {tr("DELETE"), tr("DELETE ALL")});
       QObject::connect(deleteModelButton, &FrogPilotButtonsControl::buttonClicked, [this](int id) {
-        QStringList deletableModels;
-        for (const QString &file : modelDir.entryList(QDir::Files)) {
-          QString base = QFileInfo(file).baseName();
-          for (const QString &modelKey : modelFileToNameMapProcessed.keys()) {
-            if (base.startsWith(modelKey)) {
-              QString modelName = modelFileToNameMapProcessed.value(modelKey);
-              if (!deletableModels.contains(modelName)) {
-                deletableModels.append(modelName);
-              }
-            }
-          }
+        QMap<QString, QString> deletableModelsMap = getDeletableModelDisplayNames();
+        noModelsDownloaded = deletableModelsMap.isEmpty();
+
+        if (noModelsDownloaded) {
+          return;
         }
-        deletableModels.removeAll(processModelName(currentModel));
-        deletableModels.removeAll(modelFileToNameMapProcessed.value(normalizeModelKey(QString::fromStdString(params_default.get("Model")))));
-        noModelsDownloaded = deletableModels.isEmpty();
 
         if (id == 0) {
-          QString modelToDelete = MultiOptionDialog::getSelection(tr("Select a driving model to delete"), deletableModels, "", this);
-          if (!modelToDelete.isEmpty() && ConfirmationDialog::confirm(tr("Are you sure you want to delete the \"%1\" model?").arg(modelToDelete), tr("Delete"), this)) {
-            QString modelFile = modelFileToNameMapProcessed.key(modelToDelete);
-            for (const QString &file : modelDir.entryList(QDir::Files)) {
-              QString base = QFileInfo(file).baseName();
-              if (base.startsWith(modelFile)) {
-                QFile::remove(modelDir.filePath(file));
+          // Group deletable models by series and keep a lookup for selected names
+          QMap<QString, QStringList> deletableSeriesToModels;
+          QMap<QString, QString> displayNameToKey;
+          QMap<QString, QString> deletableFileToNameMap;
+          for (auto it = deletableModelsMap.constBegin(); it != deletableModelsMap.constEnd(); ++it) {
+            const QString &modelKey = it.key();
+            const QString &displayName = it.value();
+            QString series = modelSeriesMap.value(modelKey, tr("Custom Series"));
+            deletableSeriesToModels[series].append(displayName);
+            displayNameToKey.insert(displayName, modelKey);
+            deletableFileToNameMap.insert(modelKey, displayName);
+          }
+
+          // Sort models within each series
+          for (QString &series : deletableSeriesToModels.keys()) {
+            QStringList &models = deletableSeriesToModels[series];
+            models.removeDuplicates();
+            std::sort(models.begin(), models.end());
+          }
+
+          QString savedSortMode = QString::fromStdString(params.get("ModelSortMode"));
+          if (savedSortMode.isEmpty()) savedSortMode = "alphabetical";
+
+          QString modelToDelete = ExpandableMultiOptionDialog::getSelection(tr("Select a driving model to delete"), deletableSeriesToModels, "", this,
+                                                                           QStringList(), QStringList(), QMap<QString, QString>(),
+                                                                           deletableFileToNameMap, savedSortMode);
+          if (!modelToDelete.isEmpty()) {
+            QString modelKey = displayNameToKey.value(modelToDelete);
+            if (modelKey.isEmpty()) {
+              QString processedName = processModelName(modelToDelete);
+              for (auto it = deletableModelsMap.constBegin(); it != deletableModelsMap.constEnd(); ++it) {
+                if (processModelName(it.value()) == processedName) {
+                  modelKey = it.key();
+                  break;
+                }
               }
             }
 
-            allModelsDownloaded = false;
+            if (!modelKey.isEmpty() && ConfirmationDialog::confirm(tr("Are you sure you want to delete the \"%1\" model?").arg(modelToDelete), tr("Delete"), this)) {
+              for (const QString &file : modelDir.entryList(QDir::Files)) {
+                QString base = QFileInfo(file).baseName();
+                if (base.startsWith(modelKey)) {
+                  QFile::remove(modelDir.filePath(file));
+                }
+              }
+
+              allModelsDownloaded = false;
+              noModelsDownloaded = getDeletableModelDisplayNames().isEmpty();
+              deleteModelButton->setEnabled(!(allModelsDownloading || modelDownloading || noModelsDownloaded));
+            }
           }
         } else if (id == 1) {
           if (ConfirmationDialog::confirm(tr("Are you sure you want to delete all of your downloaded driving models?"), tr("Delete"), this)) {
+            const QList<QString> deletableKeys = deletableModelsMap.keys();
             for (const QString &file : modelDir.entryList(QDir::Files)) {
               QString base = QFileInfo(file).baseName();
-              for (const QString &modelKey : modelFileToNameMapProcessed.keys()) {
-                QString modelName = modelFileToNameMapProcessed.value(modelKey);
-                if (deletableModels.contains(modelName) && base.startsWith(modelKey)) {
+              for (const QString &modelKey : deletableKeys) {
+                if (base.startsWith(modelKey)) {
                   QFile::remove(modelDir.filePath(file));
                   break;
                 }
@@ -110,6 +120,7 @@ FrogPilotModelPanel::FrogPilotModelPanel(FrogPilotSettingsWindow *parent) : Frog
 
             allModelsDownloaded = false;
             noModelsDownloaded = true;
+            deleteModelButton->setEnabled(false);
           }
         }
       });
@@ -117,45 +128,96 @@ FrogPilotModelPanel::FrogPilotModelPanel(FrogPilotSettingsWindow *parent) : Frog
     } else if (param == "DownloadModel") {
       downloadModelButton = new FrogPilotButtonsControl(title, desc, icon, {tr("DOWNLOAD"), tr("DOWNLOAD ALL")});
       QObject::connect(downloadModelButton, &FrogPilotButtonsControl::buttonClicked, [this](int id) {
-        if (tinygradUpdate) {
-          if (FrogPilotConfirmationDialog::yesorno(tr("Tinygrad is out of date and must be updated before you can download new models. Update now?"), this)) {
-            if (FrogPilotConfirmationDialog::yesorno(tr("Updating Tinygrad will delete all existing Tinygrad-based models which will need to be re-downloaded. Proceed?"), this)) {
-              params_memory.putBool("UpdateTinygrad", true);
-              params_memory.put("ModelDownloadProgress", "Downloading...");
-
-              updateTinygradButton->setText(0, tr("CANCEL"));
-              updateTinygradButton->setValue(tr("Updating..."));
-
-              updatingTinygrad = true;
-            }
-          }
-        } else if (id == 0) {
+        if (id == 0) {
           if (modelDownloading) {
             params_memory.putBool("CancelModelDownload", true);
 
             cancellingDownload = true;
-          } else {
-            QStringList downloadableModels = availableModelNames;
-            for (const QString &modelKey : modelFileToNameMap.keys()) {
-              QString modelName = modelFileToNameMap.value(modelKey);
-              if (modelDir.exists(modelKey + ".thneed") || hasAllTinygradFiles(modelDir, modelKey)) {
-                downloadableModels.removeAll(modelName);
-              }
+        } else {
+          QMap<QString, QStringList> downloadableSeriesToModels;
+          QStringList downloadableModelNames;
+
+          for (auto it = modelFileToNameMap.constBegin(); it != modelFileToNameMap.constEnd(); ++it) {
+            const QString &modelKey = it.key();
+            const QString &modelName = it.value();
+            if (modelName.isEmpty() || isModelInstalled(modelKey)) {
+              continue;
             }
-            allModelsDownloaded = downloadableModels.isEmpty();
 
-            QString modelToDownload = MultiOptionDialog::getSelection(tr("Select a driving model to download"), downloadableModels, "", this);
+            QString series = modelSeriesMap.value(modelKey, tr("Custom Series"));
+            downloadableSeriesToModels[series].append(modelName);
+            if (!downloadableModelNames.contains(modelName)) {
+              downloadableModelNames.append(modelName);
+            }
+          }
+
+          allModelsDownloaded = downloadableModelNames.isEmpty();
+          if (allModelsDownloaded) {
+            return;
+          }
+
+          for (QString &series : downloadableSeriesToModels.keys()) {
+            QStringList &models = downloadableSeriesToModels[series];
+            models.removeDuplicates();
+            std::sort(models.begin(), models.end());
+          }
+
+          QStringList userFavorites = QString::fromStdString(params.get("UserFavorites")).split(",");
+          userFavorites.removeAll("");
+
+          QStringList communityFavorites = QString::fromStdString(params.get("CommunityFavorites")).split(",");
+          communityFavorites.removeAll("");
+
+          QString savedSortMode = QString::fromStdString(params.get("ModelSortMode"));
+          if (savedSortMode.isEmpty()) savedSortMode = "alphabetical";
+
+          ExpandableMultiOptionDialog dialog(
+              tr("Select a driving model to download"),
+              downloadableSeriesToModels,
+              "",
+              this,
+              userFavorites,
+              communityFavorites,
+              modelReleasedDates,
+              modelFileToNameMap,
+              savedSortMode);
+
+          int dialogResult = dialog.exec();
+
+          QString sortMode = dialog.getCurrentSortMode();
+          QStringList newUserFavs = dialog.getUserFavorites();
+          params.put("ModelSortMode", sortMode.toStdString());
+          params.put("UserFavorites", newUserFavs.join(",").toStdString());
+          userFavorites = newUserFavs;
+
+          if (dialogResult == QDialog::Accepted) {
+            QString modelToDownload = dialog.selection;
             if (!modelToDownload.isEmpty()) {
-              params_memory.put("ModelToDownload", modelFileToNameMap.key(modelToDownload).toStdString());
-              params_memory.put("ModelDownloadProgress", "Downloading...");
+              QString modelKey = modelFileToNameMap.key(modelToDownload);
+              params_memory.put("ModelToDownload", modelKey.toStdString());
+              // Also persist the version for this downloaded model if known
+              {
+                QFile vf("/data/models/.model_versions.json");
+                if (vf.open(QIODevice::ReadOnly)) {
+                  auto doc = QJsonDocument::fromJson(vf.readAll());
+                  if (doc.isObject()) {
+                    auto obj = doc.object();
+                    if (obj.contains(modelKey)) {
+                      params.put("ModelVersion", obj.value(modelKey).toString().toStdString());
+                    }
+                  }
+                }
+              }
+                params_memory.put("ModelDownloadProgress", "Downloading...");
 
-              downloadModelButton->setText(0, tr("CANCEL"));
+                downloadModelButton->setText(0, tr("CANCEL"));
 
-              downloadModelButton->setValue("Downloading...");
+                downloadModelButton->setValue("Downloading...");
 
-              downloadModelButton->setVisibleButton(1, false);
+                downloadModelButton->setVisibleButton(1, false);
 
-              modelDownloading = true;
+                modelDownloading = true;
+              }
             }
           }
         } else if (id == 1) {
@@ -179,8 +241,8 @@ FrogPilotModelPanel::FrogPilotModelPanel(FrogPilotSettingsWindow *parent) : Frog
       });
       modelToggle = downloadModelButton;
     } else if (param == "ManageBlacklistedModels") {
-      FrogPilotButtonsControl *blacklistButton = new FrogPilotButtonsControl(title, desc, icon, {tr("ADD"), tr("REMOVE"), tr("REMOVE ALL")});
-      QObject::connect(blacklistButton, &FrogPilotButtonsControl::buttonClicked, [this](int id) {
+      FrogPilotButtonsControl *blacklistBtn = new FrogPilotButtonsControl(title, desc, icon, {tr("ADD"), tr("REMOVE"), tr("REMOVE ALL")});
+      QObject::connect(blacklistBtn, &FrogPilotButtonsControl::buttonClicked, [this](int id) {
         QStringList blacklistedModels = QString::fromStdString(params.get("BlacklistedModels")).split(",");
         blacklistedModels.removeAll("");
 
@@ -193,9 +255,22 @@ FrogPilotModelPanel::FrogPilotModelPanel(FrogPilotSettingsWindow *parent) : Frog
           }
 
           if (blacklistableModels.size() <= 1) {
-            ConfirmationDialog::alert(tr("There are no more driving models to blacklist. The only available model is \"%1\"!").arg(blacklistableModels.first()), this);
+            ConfirmationDialog::alert(tr("There are no more models to blacklist! The only available model is \"%1\"!").arg(blacklistableModels.first()), this);
           } else {
-            QString modelToBlacklist = MultiOptionDialog::getSelection(tr("Select a driving model to add to the blacklist"), blacklistableModels, "", this);
+            // Group blacklistable models by series
+            QMap<QString, QStringList> blacklistableSeriesToModels;
+            for (const QString &modelName : blacklistableModels) {
+              QString modelKey = modelFileToNameMapProcessed.key(modelName);
+              QString series = modelSeriesMap.value(modelKey, "Custom Series");
+              blacklistableSeriesToModels[series].append(modelName);
+            }
+
+            // Sort models within each series
+            for (QString &series : blacklistableSeriesToModels.keys()) {
+              blacklistableSeriesToModels[series].sort();
+            }
+
+            QString modelToBlacklist = ExpandableMultiOptionDialog::getSelection(tr("Select a model to add to the blacklist"), blacklistableSeriesToModels, "", this);
             if (!modelToBlacklist.isEmpty()) {
               if (ConfirmationDialog::confirm(tr("Are you sure you want to add the \"%1\" model to the blacklist?").arg(modelToBlacklist), tr("Add"), this)) {
                 blacklistedModels.append(modelFileToNameMapProcessed.key(modelToBlacklist));
@@ -210,9 +285,21 @@ FrogPilotModelPanel::FrogPilotModelPanel(FrogPilotSettingsWindow *parent) : Frog
             QString modelName = modelFileToNameMapProcessed.value(model);
             whitelistableModels.append(modelName);
           }
-          whitelistableModels.sort();
 
-          QString modelToWhitelist = MultiOptionDialog::getSelection(tr("Select a driving model to remove from the blacklist"), whitelistableModels, "", this);
+          // Group whitelistable models by series
+          QMap<QString, QStringList> whitelistableSeriesToModels;
+          for (const QString &modelName : whitelistableModels) {
+            QString modelKey = modelFileToNameMapProcessed.key(modelName);
+            QString series = modelSeriesMap.value(modelKey, "Custom Series");
+            whitelistableSeriesToModels[series].append(modelName);
+          }
+
+          // Sort models within each series
+          for (QString &series : whitelistableSeriesToModels.keys()) {
+            whitelistableSeriesToModels[series].sort();
+          }
+
+          QString modelToWhitelist = ExpandableMultiOptionDialog::getSelection(tr("Select a model to remove from the blacklist"), whitelistableSeriesToModels, "", this);
           if (!modelToWhitelist.isEmpty()) {
             if (ConfirmationDialog::confirm(tr("Are you sure you want to remove the \"%1\" model from the blacklist?").arg(modelToWhitelist), tr("Remove"), this)) {
               blacklistedModels.removeAll(modelFileToNameMapProcessed.key(modelToWhitelist));
@@ -221,18 +308,18 @@ FrogPilotModelPanel::FrogPilotModelPanel(FrogPilotSettingsWindow *parent) : Frog
             }
           }
         } else if (id == 2) {
-          if (FrogPilotConfirmationDialog::yesorno(tr("Are you sure you want to remove all of your blacklisted driving models?"), this)) {
+          if (FrogPilotConfirmationDialog::yesorno(tr("Are you sure you want to remove all of your blacklisted models?"), this)) {
             params.remove("BlacklistedModels");
             params_cache.remove("BlacklistedModels");
           }
         }
       });
-      modelToggle = blacklistButton;
+      modelToggle = blacklistBtn;
     } else if (param == "ManageScores") {
-      FrogPilotButtonsControl *manageScoresButton = new FrogPilotButtonsControl(title, desc, icon, {tr("RESET"), tr("VIEW")});
-      QObject::connect(manageScoresButton, &FrogPilotButtonsControl::buttonClicked, [modelLayout, modelLabelsList, modelLabelsPanel, this](int id) {
+      FrogPilotButtonsControl *manageScoresBtn = new FrogPilotButtonsControl(title, desc, icon, {tr("RESET"), tr("VIEW")});
+      QObject::connect(manageScoresBtn, &FrogPilotButtonsControl::buttonClicked, [this, modelLayout, modelLabelsList, modelLabelsPanel](int id) {
         if (id == 0) {
-          if (FrogPilotConfirmationDialog::yesorno(tr("Reset all model drives and ratings? This clears your drive history and collected feedback!"), this)) {
+          if (FrogPilotConfirmationDialog::yesorno(tr("Are you sure you want to reset all of your model drives and scores?"), this)) {
             params.remove("ModelDrivesAndScores");
             params_cache.remove("ModelDrivesAndScores");
           }
@@ -244,82 +331,116 @@ FrogPilotModelPanel::FrogPilotModelPanel(FrogPilotSettingsWindow *parent) : Frog
           modelLayout->setCurrentWidget(modelLabelsPanel);
         }
       });
-      modelToggle = manageScoresButton;
+      modelToggle = manageScoresBtn;
     } else if (param == "SelectModel") {
       selectModelButton = new ButtonControl(title, tr("SELECT"), desc);
       QObject::connect(selectModelButton, &ButtonControl::clicked, [this]() {
-        QStringList selectableModels;
+        // Group models by series for the enhanced dialog
+        QMap<QString, QStringList> seriesToModels;
+        QMap<QString, QString> installedModelFileToNameMap;
+        QMap<QString, QString> installedReleasedDates;
+
+        // Add all available models by series
         for (const QString &modelKey : modelFileToNameMap.keys()) {
+          if (!isModelInstalled(modelKey)) {
+            continue;
+          }
+
           QString modelName = modelFileToNameMap.value(modelKey);
           if (modelName.contains("(Default)")) {
             continue;
           }
 
-          if (modelDir.exists(modelKey + ".thneed") || hasAllTinygradFiles(modelDir, modelKey)) {
-            selectableModels.append(modelName);
+          installedModelFileToNameMap.insert(modelKey, modelName);
+          if (modelReleasedDates.contains(modelKey)) {
+            installedReleasedDates.insert(modelKey, modelReleasedDates.value(modelKey));
           }
+
+          QString series = modelSeriesMap.value(modelKey, "Custom Series");
+          seriesToModels[series].append(modelName);
         }
-        selectableModels.sort();
-        selectableModels.prepend(modelFileToNameMap.value(normalizeModelKey(QString::fromStdString(params_default.get("Model")))));
 
-        QString modelToSelect = MultiOptionDialog::getSelection(tr("Select a Model — 🗺️ = Navigation | 📡 = Radar | 👀 = VOACC"), selectableModels, currentModel, this);
-        if (!modelToSelect.isEmpty()) {
-          currentModel = modelToSelect;
+        // Sort models alphabetically within each series
+        for (QString &series : seriesToModels.keys()) {
+          seriesToModels[series].sort();
+        }
 
-          params.put("Model", modelFileToNameMap.key(modelToSelect).toStdString());
+        // Add default model to the beginning of its series
+        QString defaultModelName = modelFileToNameMap.value(QString::fromStdString(params_default.get("Model")));
+        QString defaultSeries = modelSeriesMap.value(QString::fromStdString(params_default.get("Model")), "Custom Series");
+        if (seriesToModels.contains(defaultSeries) && seriesToModels[defaultSeries].contains(defaultModelName)) {
+          seriesToModels[defaultSeries].removeAll(defaultModelName);
+          seriesToModels[defaultSeries].prepend(defaultModelName);
+        }
 
-          updateFrogPilotToggles();
+        // Prepare favorites and dates for the enhanced dialog
+        QStringList userFavs = QString::fromStdString(params.get("UserFavorites")).split(",");
+        userFavs.removeAll("");
 
-          if (started) {
-            if (FrogPilotConfirmationDialog::toggleReboot(this)) {
-              Hardware::reboot();
-            }
-          }
-          selectModelButton->setValue(modelToSelect);
+        QStringList communityFavs = QString::fromStdString(params.get("CommunityFavorites")).split(",");
+        communityFavs.removeAll("");
 
-          QStringList deletableModels;
-          for (const QString &file : modelDir.entryList(QDir::Files)) {
-            QString base = QFileInfo(file).baseName();
-            for (const QString &modelKey : modelFileToNameMapProcessed.keys()) {
-              if (base.startsWith(modelKey)) {
-                QString modelName = modelFileToNameMapProcessed.value(modelKey);
-                if (!deletableModels.contains(modelName)) {
-                  deletableModels.append(modelName);
+        // Create dialog instance to access sort mode and favorites after selection
+        QString savedSortMode = QString::fromStdString(params.get("ModelSortMode"));
+        if (savedSortMode.isEmpty()) savedSortMode = "alphabetical";
+
+        ExpandableMultiOptionDialog dialog(tr("Select a model - 🗺️ = Navigation | 📡 = Radar | 👀 = VOACC"),
+                                          seriesToModels, currentModel, this,
+                                          userFavs, communityFavs, installedReleasedDates, installedModelFileToNameMap, savedSortMode);
+
+        int dialogResult = dialog.exec();
+
+        // Persist sort mode and user favorites even if no selection was made
+        QString sortMode = dialog.getCurrentSortMode();
+        QStringList newUserFavs = dialog.getUserFavorites();
+        params.put("ModelSortMode", sortMode.toStdString());
+        params.put("UserFavorites", newUserFavs.join(",").toStdString());
+
+        if (dialogResult == QDialog::Accepted) {
+          QString modelToSelect = dialog.selection;
+          if (!modelToSelect.isEmpty()) {
+            currentModel = modelToSelect;
+
+            params.put("Model", modelFileToNameMap.key(modelToSelect).toStdString());
+            // Sync ModelVersion with the selected model if known
+            {
+              QString modelKey = modelFileToNameMap.key(modelToSelect);
+              QFile vf("/data/models/.model_versions.json");
+              if (vf.open(QIODevice::ReadOnly)) {
+                auto doc = QJsonDocument::fromJson(vf.readAll());
+                if (doc.isObject()) {
+                  auto obj = doc.object();
+                  if (obj.contains(modelKey)) {
+                    params.put("ModelVersion", obj.value(modelKey).toString().toStdString());
+                  }
                 }
               }
             }
+
+            updateFrogPilotToggles();
+
+            if (started) {
+              if (FrogPilotConfirmationDialog::toggleReboot(this)) {
+                Hardware::reboot();
+              }
+            }
+            selectModelButton->setValue(modelToSelect);
+
+            noModelsDownloaded = getDeletableModelDisplayNames().isEmpty();
+            deleteModelButton->setEnabled(!(allModelsDownloading || modelDownloading || noModelsDownloaded));
           }
-          deletableModels.removeAll(processModelName(currentModel));
-          deletableModels.removeAll(modelFileToNameMapProcessed.value(normalizeModelKey(QString::fromStdString(params_default.get("Model")))));
-          noModelsDownloaded = deletableModels.isEmpty();
         }
       });
       modelToggle = selectModelButton;
 
-    } else if (param == "UpdateTinygrad") {
-      updateTinygradButton = new FrogPilotButtonsControl(title, desc, icon, {tr("UPDATE")});
-      QObject::connect(updateTinygradButton, &FrogPilotButtonsControl::buttonClicked, [this]() {
-        if (updatingTinygrad) {
-          params_memory.putBool("CancelModelDownload", true);
-
-          updateTinygradButton->setEnabled(false);
-          updateTinygradButton->setValue(tr("Cancelling..."));
-
-          cancellingDownload = true;
-        } else {
-          if (FrogPilotConfirmationDialog::yesorno(tr("Updating Tinygrad will delete existing Tinygrad-based driving models and need to be re-downloaded. Proceed?"), this)) {
-            params_memory.putBool("UpdateTinygrad", true);
-            params_memory.put("ModelDownloadProgress", "Downloading...");
-
-            updateTinygradButton->setText(0, tr("CANCEL"));
-            updateTinygradButton->setValue(tr("Updating..."));
-
-            updatingTinygrad = true;
-          }
-        }
-      });
-      modelToggle = updateTinygradButton;
-
+    } else if (param == "RecoveryPower") {
+      std::vector<QString> recoveryPowerButton{"Reset"};
+      modelToggle = new FrogPilotParamValueButtonControl(param, title, desc, icon, 0.5, 2.0, QString(), std::map<float, QString>(), 0.1, false, {}, recoveryPowerButton, false, false);
+      recoveryPowerToggle = static_cast<FrogPilotParamValueButtonControl*>(modelToggle);
+    } else if (param == "StopDistance") {
+      std::vector<QString> stopDistanceButton{"Reset"};
+      modelToggle = new FrogPilotParamValueButtonControl(param, title, desc, icon, 4.0, 10.0, QString(), std::map<float, QString>(), 0.1, false, {}, stopDistanceButton, false, false);
+      stopDistanceToggle = static_cast<FrogPilotParamValueButtonControl*>(modelToggle);
     } else {
       modelToggle = new ParamControl(param, title, desc, icon);
     }
@@ -328,21 +449,16 @@ FrogPilotModelPanel::FrogPilotModelPanel(FrogPilotSettingsWindow *parent) : Frog
 
     modelList->addItem(modelToggle);
 
-    QObject::connect(modelToggle, &AbstractControl::hideDescriptionEvent, [this]() {
-      update();
-    });
     QObject::connect(modelToggle, &AbstractControl::showDescriptionEvent, [this]() {
       update();
     });
   }
 
-  openDescriptions(forceOpenDescriptions, toggles);
-
   QObject::connect(static_cast<ToggleControl*>(toggles["ModelRandomizer"]), &ToggleControl::toggleFlipped, [this](bool state) {
     updateToggles();
 
     if (state && !allModelsDownloaded) {
-      if (FrogPilotConfirmationDialog::yesorno(tr("The \"Model Randomizer\" works only with downloaded models. Download all models now?"), this)) {
+      if (FrogPilotConfirmationDialog::yesorno(tr("The \"Model Randomizer\" only works with downloaded models. Do you want to download all the driving models?"), this)) {
         params_memory.putBool("DownloadAllModels", true);
         params_memory.put("ModelDownloadProgress", "Downloading...");
 
@@ -353,13 +469,120 @@ FrogPilotModelPanel::FrogPilotModelPanel(FrogPilotSettingsWindow *parent) : Frog
     }
   });
 
-  QObject::connect(parent, &FrogPilotSettingsWindow::closeSubPanel, [modelLayout, modelPanel, this] {
-    openDescriptions(forceOpenDescriptions, toggles);
-    modelLayout->setCurrentWidget(modelPanel);
-  });
+  if (recoveryPowerToggle) {
+    QObject::connect(recoveryPowerToggle, &FrogPilotParamValueButtonControl::buttonClicked, [this, recoveryPowerToggle]() {
+      if (ConfirmationDialog::confirm(tr("Are you sure you want to reset your <b>Recovery Power</b> to the default of 1.0?"), tr("Reset"), this)) {
+        params.putFloat("RecoveryPower", 1.0);
+        recoveryPowerToggle->refresh();
+        updateFrogPilotToggles();
+      }
+    });
+  }
+
+  if (stopDistanceToggle) {
+    QObject::connect(stopDistanceToggle, &FrogPilotParamValueButtonControl::buttonClicked, [this, stopDistanceToggle]() {
+      if (ConfirmationDialog::confirm(tr("Are you sure you want to reset your <b>Stop Distance</b> to the default of 6 meters?"), tr("Reset"), this)) {
+        params.putFloat("StopDistance", 6.0);
+        stopDistanceToggle->refresh();
+        updateFrogPilotToggles();
+      }
+    });
+  }
+
+  QObject::connect(parent, &FrogPilotSettingsWindow::closeSubPanel, [modelLayout, modelPanel] {modelLayout->setCurrentWidget(modelPanel);});
   QObject::connect(uiState(), &UIState::uiUpdate, this, &FrogPilotModelPanel::updateState);
 }
 
+bool FrogPilotModelPanel::isModelInstalled(const QString &key) const {
+  if (key.isEmpty()) {
+    return false;
+  }
+
+  bool has_thneed = false;
+  bool has_policy_meta = false;
+  bool has_policy_tg = false;
+  bool has_vision_meta = false;
+  bool has_vision_tg = false;
+  bool has_off_policy_meta = false;
+  bool has_off_policy_tg = false;
+  bool foundAny = false;
+
+  for (const QString &file : modelDir.entryList(QDir::Files)) {
+    QFileInfo fi(modelDir.filePath(file));
+    const QString base = fi.baseName();
+    const QString ext = fi.suffix();
+
+    if (!(base.startsWith(key) || base.startsWith(key + "_"))) continue;
+
+    foundAny = true;
+
+    if (ext == "thneed") {
+      has_thneed = true;
+    } else if (ext == "pkl") {
+      if (base.contains("_driving_policy_metadata")) {
+        has_policy_meta = true;
+      } else if (base.contains("_driving_policy_tinygrad")) {
+        has_policy_tg = true;
+      } else if (base.contains("_driving_off_policy_metadata")) {
+        has_off_policy_meta = true;
+      } else if (base.contains("_driving_off_policy_tinygrad")) {
+        has_off_policy_tg = true;
+      } else if (base.contains("_driving_vision_metadata")) {
+        has_vision_meta = true;
+      } else if (base.contains("_driving_vision_tinygrad")) {
+        has_vision_tg = true;
+      }
+    }
+  }
+
+  if (has_thneed) {
+    return true;
+  }
+
+  if (has_policy_meta && has_policy_tg && has_vision_meta && has_vision_tg) {
+    if (has_off_policy_meta || has_off_policy_tg) {
+      return has_off_policy_meta && has_off_policy_tg;
+    }
+    return true;
+  }
+
+  return foundAny;
+}
+
+QMap<QString, QString> FrogPilotModelPanel::getDeletableModelDisplayNames() {
+  QMap<QString, QString> deletable;
+
+  QString defaultModelKey = QString::fromStdString(params_default.get("Model"));
+  QString defaultModelName = modelFileToNameMap.value(defaultModelKey);
+  QString processedDefault = processModelName(defaultModelName);
+  QString processedCurrent = processModelName(currentModel);
+
+  for (auto it = modelFileToNameMap.constBegin(); it != modelFileToNameMap.constEnd(); ++it) {
+    const QString &modelKey = it.key();
+    const QString &displayName = it.value();
+    if (displayName.isEmpty()) {
+      continue;
+    }
+
+    if (!isModelInstalled(modelKey)) {
+      continue;
+    }
+
+    QString processedName = processModelName(displayName);
+    if (!processedCurrent.isEmpty() && processedName == processedCurrent) {
+      continue;
+    }
+
+    if (!processedDefault.isEmpty() && processedName == processedDefault) {
+      continue;
+    }
+
+    deletable.insert(modelKey, displayName);
+  }
+
+  return deletable;
+}
+
 void FrogPilotModelPanel::showEvent(QShowEvent *event) {
   FrogPilotUIState &fs = *frogpilotUIState();
   UIState &s = *uiState();
@@ -368,68 +591,90 @@ void FrogPilotModelPanel::showEvent(QShowEvent *event) {
   tuningLevel = parent->tuningLevel;
 
   allModelsDownloading = params_memory.getBool("DownloadAllModels");
-  modelDownloading = !params_memory.get("ModelDownloadProgress").empty();
-  tinygradUpdate = params.getBool("TinygradUpdateAvailable");
-  updatingTinygrad = params_memory.getBool("UpdateTinygrad");
-
-  modelDownloading &= !updatingTinygrad;
+  modelDownloading = !params_memory.get("ModelToDownload").empty();
 
   QStringList availableModels = QString::fromStdString(params.get("AvailableModels")).split(",");
-  availableModels.sort();
   availableModelNames = QString::fromStdString(params.get("AvailableModelNames")).split(",");
-  availableModelNames.sort();
+  availableModelSeries = QString::fromStdString(params.get("AvailableModelSeries")).split(",");
+  QStringList releasedDatesParam = QString::fromStdString(params.get("ModelReleasedDates")).split(",");
+  QStringList communityFavsParam = QString::fromStdString(params.get("CommunityFavorites")).split(",");
+  QStringList userFavsParam = QString::fromStdString(params.get("UserFavorites")).split(",");
+
+  // Build a simple model->version map for quick lookups elsewhere
+  {
+    QStringList versionList = QString::fromStdString(params.get("ModelVersions")).split(",");
+    QJsonObject versionObj;
+    int verCount = qMin(availableModels.size(), versionList.size());
+    for (int i = 0; i < verCount; ++i) {
+      versionObj.insert(availableModels[i], versionList[i]);
+    }
+    QFile out("/data/models/.model_versions.json");
+    if (out.open(QIODevice::WriteOnly)) {
+      out.write(QJsonDocument(versionObj).toJson());
+      out.close();
+    }
+  }
 
   modelFileToNameMap.clear();
   modelFileToNameMapProcessed.clear();
-  for (int i = 0; i < qMin(availableModels.size(), availableModelNames.size()); ++i) {
-    modelFileToNameMap.insert(availableModels[i], availableModelNames[i]);
-    modelFileToNameMapProcessed.insert(availableModels[i], processModelName(availableModelNames[i]));
-  }
-
-  QStringList downloadableModels = availableModelNames;
-  for (const QString &modelKey : modelFileToNameMap.keys()) {
-    QString modelName = modelFileToNameMap.value(modelKey);
-    if (modelDir.exists(modelKey + ".thneed") || hasAllTinygradFiles(modelDir, modelKey)) {
-      downloadableModels.removeAll(modelName);
+  modelSeriesMap.clear();
+  modelReleasedDates.clear();
+  int size = qMin(availableModels.size(), availableModelNames.size());
+  for (int i = 0; i < size; ++i) {
+    const QString modelKey = availableModels[i].trimmed();
+    const QString modelName = availableModelNames[i].trimmed();
+    if (modelKey.isEmpty() || modelName.isEmpty()) {
+      continue;
     }
-  }
-  allModelsDownloaded = downloadableModels.isEmpty();
 
-  QStringList deletableModels;
-  for (const QString &file : modelDir.entryList(QDir::Files)) {
-    QString base = QFileInfo(file).baseName();
-    for (const QString &modelKey : modelFileToNameMapProcessed.keys()) {
-      if (base.startsWith(modelKey)) {
-        QString modelName = modelFileToNameMapProcessed.value(modelKey);
-        if (!deletableModels.contains(modelName)) {
-          deletableModels.append(modelName);
-        }
+    QString series;
+    if (i < availableModelSeries.size()) {
+      series = availableModelSeries[i].trimmed();
+    }
+    if (series.isEmpty()) {
+      series = tr("Custom Series");
+    }
+
+    modelFileToNameMap.insert(modelKey, modelName);
+    modelFileToNameMapProcessed.insert(modelKey, processModelName(modelName));
+    modelSeriesMap.insert(modelKey, series);
+
+    if (i < releasedDatesParam.size()) {
+      const QString released = releasedDatesParam[i].trimmed();
+      if (!released.isEmpty()) {
+        this->modelReleasedDates.insert(modelKey, released);
       }
     }
   }
-  deletableModels.removeAll(processModelName(currentModel));
-  deletableModels.removeAll(modelFileToNameMapProcessed.value(normalizeModelKey(QString::fromStdString(params_default.get("Model")))));
-  noModelsDownloaded = deletableModels.isEmpty();
+  allModelsDownloaded = true;
+  for (auto it = modelFileToNameMap.constBegin(); it != modelFileToNameMap.constEnd(); ++it) {
+    if (it.value().isEmpty()) {
+      continue;
+    }
+    if (!isModelInstalled(it.key())) {
+      allModelsDownloaded = false;
+      break;
+    }
+  }
 
-  QString modelKey = normalizeModelKey(QString::fromStdString(params.get("Model")));
-  if (!modelDir.exists(modelKey + ".thneed") && !hasAllTinygradFiles(modelDir, modelKey)) {
-    modelKey = normalizeModelKey(QString::fromStdString(params_default.get("Model")));
+  QString modelKey = QString::fromStdString(params.get("Model"));
+  if (!isModelInstalled(modelKey)) {
+    modelKey = QString::fromStdString(params_default.get("Model"));
   }
   currentModel = modelFileToNameMap.value(modelKey);
   selectModelButton->setValue(currentModel);
 
+  noModelsDownloaded = getDeletableModelDisplayNames().isEmpty();
+
   bool parked = !s.scene.started || fs.frogpilot_scene.parked || fs.frogpilot_toggles.value("frogs_go_moo").toBool();
 
   deleteModelButton->setEnabled(!(allModelsDownloading || modelDownloading || noModelsDownloaded));
 
-  downloadModelButton->setEnabledButtons(0, !allModelsDownloaded && !allModelsDownloading && !cancellingDownload && !updatingTinygrad && fs.frogpilot_scene.online && parked);
-  downloadModelButton->setEnabledButtons(1, !allModelsDownloaded && !modelDownloading && !cancellingDownload && !updatingTinygrad && fs.frogpilot_scene.online && parked);
+  downloadModelButton->setEnabledButtons(0, !allModelsDownloaded && !allModelsDownloading && !cancellingDownload && fs.frogpilot_scene.online && parked);
+  downloadModelButton->setEnabledButtons(1, !allModelsDownloaded && !modelDownloading && !cancellingDownload && fs.frogpilot_scene.online && parked);
 
   downloadModelButton->setValue(fs.frogpilot_scene.online ? (parked ? "" : "Not parked") : tr("Offline..."));
 
-  updateTinygradButton->setEnabled(!modelDownloading && !cancellingDownload && fs.frogpilot_scene.online && parked && tinygradUpdate);
-  updateTinygradButton->setValue(tinygradUpdate ? tr("Update available!") : tr("Up to date!"));
-
   started = s.scene.started;
 
   updateToggles();
@@ -444,32 +689,27 @@ void FrogPilotModelPanel::updateState(const UIState &s, const FrogPilotUIState &
 
   if (allModelsDownloading || modelDownloading) {
     QString progress = QString::fromStdString(params_memory.get("ModelDownloadProgress"));
-    bool downloadFailed = progress.contains(QRegularExpression("cancelled|exists|failed|missing|offline", QRegularExpression::CaseInsensitiveOption));
+    bool downloadFailed = progress.contains(QRegularExpression("cancelled|exists|failed|offline", QRegularExpression::CaseInsensitiveOption));
 
     if (progress != "Downloading...") {
       downloadModelButton->setValue(progress);
     }
 
-    if (progress == "All models downloaded!" || progress == "Downloaded!" && !allModelsDownloading || downloadFailed) {
+    if (progress == "All models downloaded!" && allModelsDownloading || progress == "Downloaded!" && modelDownloading || downloadFailed) {
       finalizingDownload = true;
 
-      QTimer::singleShot(2500, [progress, this]() {
+      QTimer::singleShot(2500, [this, progress]() {
+        allModelsDownloaded = progress == "All models downloaded!";
         allModelsDownloading = false;
         cancellingDownload = false;
         finalizingDownload = false;
         modelDownloading = false;
         noModelsDownloaded = false;
 
-        QStringList downloadableModels = availableModelNames;
-        for (const QString &modelKey : modelFileToNameMap.keys()) {
-          QString modelName = modelFileToNameMap.value(modelKey);
-          if (modelDir.exists(modelKey + ".thneed") || hasAllTinygradFiles(modelDir, modelKey)) {
-            downloadableModels.removeAll(modelName);
-          }
-        }
-        allModelsDownloaded = downloadableModels.isEmpty();
-
+        params_memory.remove("CancelModelDownload");
+        params_memory.remove("DownloadAllModels");
         params_memory.remove("ModelDownloadProgress");
+        params_memory.remove("ModelToDownload");
 
         downloadModelButton->setEnabled(true);
         downloadModelButton->setValue("");
@@ -479,58 +719,20 @@ void FrogPilotModelPanel::updateState(const UIState &s, const FrogPilotUIState &
     downloadModelButton->setValue(fs.frogpilot_scene.online ? (parked ? "" : "Not parked") : tr("Offline..."));
   }
 
-  if (updatingTinygrad) {
-    QString progress = QString::fromStdString(params_memory.get("ModelDownloadProgress"));
-    bool downloadFailed = progress.contains(QRegularExpression("cancelled|exists|failed|missing|offline", QRegularExpression::CaseInsensitiveOption));
-
-    if (progress != "Downloading...") {
-      updateTinygradButton->setValue(progress);
-    }
-
-    if (progress == "Updated!" && updatingTinygrad || downloadFailed) {
-      finalizingDownload = true;
-
-      QTimer::singleShot(2500, [progress, this]() {
-        modelDownloading = !params_memory.get("ModelDownloadProgress").empty();
-
-        if (modelDownloading) {
-          downloadModelButton->setText(1, tr("CANCEL"));
-
-          downloadModelButton->setValue("Downloading...");
-
-          downloadModelButton->setVisibleButton(0, false);
-        } else {
-          cancellingDownload = false;
-        }
-
-        tinygradUpdate = params.getBool("TinygradUpdateAvailable");
-
-        finalizingDownload = false;
-        updatingTinygrad = false;
-
-        updateTinygradButton->setEnabled(tinygradUpdate);
-        updateTinygradButton->setText(0, tr("UPDATE"));
-        updateTinygradButton->setValue(tinygradUpdate ? tr("Update available!") : tr("Up to date!"));
-      });
-    }
-  }
-
   deleteModelButton->setEnabled(!(allModelsDownloading || modelDownloading || noModelsDownloaded));
 
   downloadModelButton->setText(0, modelDownloading ? tr("CANCEL") : tr("DOWNLOAD"));
   downloadModelButton->setText(1, allModelsDownloading ? tr("CANCEL") : tr("DOWNLOAD ALL"));
 
-  downloadModelButton->setEnabledButtons(0, !allModelsDownloaded && !allModelsDownloading && !cancellingDownload && !finalizingDownload && !updatingTinygrad && fs.frogpilot_scene.online && parked);
-  downloadModelButton->setEnabledButtons(1, !allModelsDownloaded && !modelDownloading && !cancellingDownload && !finalizingDownload && !updatingTinygrad && fs.frogpilot_scene.online && parked);
+  downloadModelButton->setEnabledButtons(0, !allModelsDownloaded && !allModelsDownloading && !cancellingDownload && fs.frogpilot_scene.online && parked);
+  downloadModelButton->setEnabledButtons(1, !allModelsDownloaded && !modelDownloading && !cancellingDownload && fs.frogpilot_scene.online && parked);
 
   downloadModelButton->setVisibleButton(0, !allModelsDownloading);
   downloadModelButton->setVisibleButton(1, !modelDownloading);
 
-  updateTinygradButton->setEnabled(!modelDownloading && !cancellingDownload && !cancellingDownload && !finalizingDownload && fs.frogpilot_scene.online && parked && tinygradUpdate);
-
   started = s.scene.started;
 
-  parent->keepScreenOn = allModelsDownloading || modelDownloading || updatingTinygrad;
+  parent->keepScreenOn = allModelsDownloading || modelDownloading;
 }
 
 void FrogPilotModelPanel::updateModelLabels(FrogPilotListWidget *labelsList) {
@@ -561,16 +763,16 @@ void FrogPilotModelPanel::updateToggles() {
 
     if (key == "ManageBlacklistedModels" || key == "ManageScores") {
       setVisible &= params.getBool("ModelRandomizer");
-    }
-
-    else if (key == "SelectModel") {
+    } else if (key == "SelectModel") {
       setVisible &= !params.getBool("ModelRandomizer");
+    } else if (key == "RecoveryPower") {
+      setVisible &= (tuningLevel == 3); // Only visible in developer tuning level
+    } else if (key == "StopDistance") {
+      setVisible &= (tuningLevel == 3); // Only visible in developer tuning level
     }
 
     toggle->setVisible(setVisible);
   }
 
-  openDescriptions(forceOpenDescriptions, toggles);
-
   update();
 }

frogpilot/ui/qt/offroad/model_settings.h

@@ -20,6 +20,8 @@ private:
   void updateModelLabels(FrogPilotListWidget *labelsList);
   void updateState(const UIState &s, const FrogPilotUIState &fs);
   void updateToggles();
+  bool isModelInstalled(const QString &key) const;
+  QMap<QString, QString> getDeletableModelDisplayNames();
 
   bool allModelsDownloaded;
   bool allModelsDownloading;
@@ -55,8 +57,12 @@ private:
 
   QMap<QString, QString> modelFileToNameMap;
   QMap<QString, QString> modelFileToNameMapProcessed;
+  QMap<QString, QString> modelReleasedDates;
+  QMap<QString, QString> modelSeriesMap;
 
   QString currentModel;
 
+
   QStringList availableModelNames;
+  QStringList availableModelSeries;
 };

frogpilot/ui/qt/offroad/vehicle_settings.cc

@@ -168,6 +168,7 @@ FrogPilotVehiclesPanel::FrogPilotVehiclesPanel(FrogPilotSettingsWindow *parent)
   std::vector<std::tuple<QString, QString, QString, QString>> vehicleToggles {
     {"GMToggles", tr("General Motors Settings"), tr("<b>FrogPilot features for General Motors vehicles.</b>"), ""},
     {"ExperimentalGMTune", tr("FrogsGoMoo's Experimental Tune"), tr("<b>Experimental GM tune by FrogsGoMoo</b> that attempts to smoothen stopping and takeoff control. Use at your own risk!"), ""},
+    {"GMPedalLongitudinal", tr("Use Pedal for Longitudinal Control"), tr("<b>Use the pedal interceptor for longitudinal control</b> instead of camera ACC/Redneck when available."), ""},
     {"LongPitch", tr("Smooth Pedal Response on Hills"), tr("<b>Smoothen acceleration and braking</b> when driving downhill/uphill."), ""},
     {"VoltSNG", tr("Stop-and-Go Hack"), tr("<b>Force stop-and-go</b> on the 2017 Chevy Volt."), ""},
 
@@ -188,6 +189,7 @@ FrogPilotVehiclesPanel::FrogPilotVehiclesPanel(FrogPilotSettingsWindow *parent)
     {"PedalSupport", tr("comma Pedal Support"), tr("<b>Does your vehicle support the \"comma pedal\"?</b>"), ""},
     {"OpenpilotLongitudinal", tr("openpilot Longitudinal Support"), tr("<b>Can openpilot control the vehicle's acceleration and braking?</b>"), ""},
     {"RadarSupport", tr("Radar Support"), tr("<b>Does openpilot use the vehicle's radar data</b> alongside the device's camera for tracking lead vehicles?"), ""},
+    {"SASCMSupport", tr("SASCM Support"), tr("<b>Does your vehicle support \"SASCMs\"?</b>"), ""},
     {"SDSUSupport", tr("SDSU Support"), tr("<b>Does your vehicle support \"SDSUs\"?</b>"), ""},
     {"SNGSupport", tr("Stop-and-Go Support"), tr("<b>Does your vehicle support stop-and-go driving?</b>"), ""}
   };
@@ -341,6 +343,7 @@ void FrogPilotVehiclesPanel::showEvent(QShowEvent *event) {
 
   QStringList detected;
   if (hasPedal) detected << "comma Pedal";
+  if (parent->hasSASCM) detected << "SASCM";
   if (parent->hasSDSU) detected << "SDSU";
   if (parent->hasZSS) detected << "ZSS";
   static_cast<LabelControl*>(toggles["HardwareDetected"])->setText(detected.isEmpty() ? tr("None") : detected.join(", "));
@@ -349,6 +352,7 @@ void FrogPilotVehiclesPanel::showEvent(QShowEvent *event) {
   static_cast<LabelControl*>(toggles["OpenpilotLongitudinal"])->setText(hasOpenpilotLongitudinal ? tr("Yes") : tr("No"));
   static_cast<LabelControl*>(toggles["PedalSupport"])->setText(parent->canUsePedal ? tr("Yes") : tr("No"));
   static_cast<LabelControl*>(toggles["RadarSupport"])->setText(parent->hasRadar ? tr("Yes") : tr("No"));
+  static_cast<LabelControl*>(toggles["SASCMSupport"])->setText(parent->canUseSASCM ? tr("Yes") : tr("No"));
   static_cast<LabelControl*>(toggles["SDSUSupport"])->setText(parent->canUseSDSU ? tr("Yes") : tr("No"));
   static_cast<LabelControl*>(toggles["SNGSupport"])->setText(hasSNG ? tr("Yes") : tr("No"));
 
@@ -403,6 +407,10 @@ void FrogPilotVehiclesPanel::updateToggles() {
       setVisible &= isHKGCanFd;
     }
 
+    else if (key == "GMPedalLongitudinal") {
+      setVisible &= hasPedal;
+    }
+
     else if (key == "VoltSNG") {
       setVisible &= isVolt && !hasSNG;
     }

frogpilot/ui/qt/offroad/vehicle_settings.h

@@ -36,11 +36,11 @@ private:
 
   std::map<QString, AbstractControl*> toggles;
 
-  QSet<QString> gmKeys = {"ExperimentalGMTune", "LongPitch", "VoltSNG"};
+  QSet<QString> gmKeys = {"ExperimentalGMTune", "GMPedalLongitudinal", "LongPitch", "VoltSNG"};
   QSet<QString> hkgKeys = {"NewLongAPI", "TacoTuneHacks"};
   QSet<QString> longitudinalKeys = {"ExperimentalGMTune", "FrogsGoMoosTweak", "LongPitch", "NewLongAPI", "SNGHack", "VoltSNG"};
   QSet<QString> toyotaKeys = {"ClusterOffset", "FrogsGoMoosTweak", "LockDoorsTimer", "SNGHack", "ToyotaDoors"};
-  QSet<QString> vehicleInfoKeys = {"BlindSpotSupport", "HardwareDetected", "OpenpilotLongitudinal", "PedalSupport", "RadarSupport", "SDSUSupport", "SNGSupport"};
+  QSet<QString> vehicleInfoKeys = {"BlindSpotSupport", "HardwareDetected", "OpenpilotLongitudinal", "PedalSupport", "RadarSupport", "SASCMSupport", "SDSUSupport", "SNGSupport"};
 
   QSet<QString> parentKeys;
 

frogpilot/ui/qt/offroad/visual_settings.cc

@@ -214,6 +214,7 @@ FrogPilotVisualsPanel::FrogPilotVisualsPanel(FrogPilotSettingsWindow *parent) :
         {13, tr("Longitudinal MPC Jerk: Acceleration")},
         {14, tr("Longitudinal MPC Jerk: Danger Zone")},
         {15, tr("Longitudinal MPC Jerk: Speed Control")},
+        {16, tr("Driving Model: Current")},
       };
 
       ButtonControl *metricToggle = new ButtonControl(title, tr("SELECT"), desc);

launch_chffrplus.sh

@@ -8,7 +8,114 @@ source "$BASEDIR/launch_env.sh"
 
 DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null && pwd )"
 
+ # --- BEGIN: auto-fix persist from squashfs -> ext4 (one-time, preserves identity) ---
+function persist_convert_if_needed {
+  LOG="/tmp/persist_fix.log"
+  {
+    echo "[persist-fix] ----- start $(date) -----"
+
+    # Guard: if we've already converted on this device, skip
+    if [ -f /data/.persist_converted ] || [ -f /persist/.converted_to_ext4 ]; then
+      echo "[persist-fix] Marker exists; skipping."
+      return 0
+    fi
+
+    # Discover persist device
+    DEV="$(blkid -t LABEL=persist -o device 2>/dev/null || true)"
+    if [ -z "$DEV" ] && [ -e /dev/disk/by-partlabel/persist ]; then
+      DEV="$(realpath /dev/disk/by-partlabel/persist)"
+    fi
+    if [ -z "$DEV" ]; then
+      # Fallback commonly used path
+      if lsblk -no PATH,LABEL | grep -E "persist$" >/dev/null 2>&1; then
+        DEV="$(lsblk -no PATH,LABEL | awk '$2=="persist"{print $1; exit}')"
+      else
+        DEV="/dev/sda2"
+      fi
+    fi
+    echo "[persist-fix] Using device: ${DEV}"
+
+    # Detect device filesystem type
+    FSTYPE="$(blkid -o value -s TYPE "$DEV" 2>/dev/null || true)"
+    echo "[persist-fix] Detected $DEV fstype='$FSTYPE'"
+    UNSQS="$DIR/third_party/bin/unsquashfs"
+
+    # Detect current /persist mount status & fstype
+    CUR_MNT_TYPE="$(mount | awk '$3==\"/persist\"{print $5}' | head -n1)"
+    if mountpoint -q /persist; then
+      echo "[persist-fix] /persist currently mounted as type='${CUR_MNT_TYPE}'"
+    else
+      echo "[persist-fix] /persist is not a mountpoint (empty dir)."
+    fi
+
+    # Only proceed on NEW devices: either /persist is not mounted OR is squashfs,
+    # AND the underlying persist partition is squashfs (factory RO image).
+    if { ! mountpoint -q /persist || [ "${CUR_MNT_TYPE}" = "squashfs" ]; } && [ "${FSTYPE}" = "squashfs" ]; then
+      echo "[persist-fix] NEW device detected (squashfs persist). Converting to ext4."
+
+      # Stream identity files using unsquashfs -cat directly
+      for f in id_rsa id_rsa.pub color_cal dongle_id; do
+        if sudo "$UNSQS" -cat "$DEV" "comma/$f" > "/data/$f" 2>/dev/null; then
+          echo "[persist-fix] Preserved $f"
+        else
+          echo "[persist-fix] $f not found in squashfs (ok, may not exist)."
+        fi
+      done
+
+      # (Optional) raw backup of the original partition image (once)
+      if [ ! -f /data/persist_backup.img ]; then
+        echo "[persist-fix] Creating raw backup of ${DEV} to /data/persist_backup.img"
+        sudo dd if="$DEV" of=/data/persist_backup.img bs=1M status=none || true
+        sync
+      fi
+
+      # Reformat persist as ext4 and label it
+      echo "[persist-fix] Formatting ${DEV} as ext4..."
+      if ! sudo mkfs.ext4 -F "$DEV"; then
+        echo "[persist-fix][ERROR] mkfs.ext4 failed on ${DEV}. Aborting."
+        return 0
+      fi
+      sudo e2label "$DEV" persist || true
+
+      # Mount the new ext4 persist RW
+      if ! sudo mount -t ext4 -o rw,discard "$DEV" /persist; then
+        echo "[persist-fix][ERROR] Failed to mount new ext4 persist. Aborting."
+        return 0
+      fi
+
+      # Recreate expected structure and restore identity
+      sudo mkdir -p /persist/{comma,params,tracking}
+      sudo chmod 755 /persist /persist/{comma,params,tracking}
+      for f in id_rsa id_rsa.pub color_cal dongle_id; do
+        if [ -f "/data/$f" ]; then
+          sudo cp -p "/data/$f" "/persist/comma/$f"
+        fi
+      done
+      if [ -f /persist/comma/id_rsa ]; then sudo chmod 600 /persist/comma/id_rsa; fi
+      sudo chown -R comma:comma /persist/ /persist/comma /persist/params /persist/tracking || true
+      sudo touch /persist/tracking/.lock
+
+      # Seed minimal params (only if not present)
+      [ -f /persist/params/HasAcceptedTerms ] || echo -n 1 | sudo tee /persist/params/HasAcceptedTerms >/dev/null
+      [ -f /persist/params/AlwaysOnDM ]      || echo -n 1 | sudo tee /persist/params/AlwaysOnDM      >/dev/null
+
+      # Mark complete so we don't run again; reboot once
+      echo "ext4" | sudo tee /persist/.converted_to_ext4 >/dev/null
+      sudo touch /data/.persist_converted
+      sync
+      echo "[persist-fix] Conversion complete. Rebooting once to finalize..."
+      sudo reboot
+    else
+      echo "[persist-fix] Device is not NEW/squashfs (persist already ext4 or mounted). Skipping."
+    fi
+
+    echo "[persist-fix] ----- end $(date) -----"
+  } >>"$LOG" 2>&1
+}
+# --- END: auto-fix persist from squashfs -> ext4 ---
+
 function agnos_init {
+  persist_convert_if_needed
   # TODO: move this to agnos
   sudo rm -f /data/etc/NetworkManager/system-connections/*.nmmeta
 

launch_env.sh

@@ -7,7 +7,7 @@ export OPENBLAS_NUM_THREADS=1
 export VECLIB_MAXIMUM_THREADS=1
 
 if [ -z "$AGNOS_VERSION" ]; then
-  export AGNOS_VERSION="10.1"
+  export AGNOS_VERSION="10.1.1"
 fi
 
 export STAGING_ROOT="/data/safe_staging"

opendbc/gm_global_a_powertrain_generated.dbc

@@ -82,6 +82,12 @@ VAL_TABLE_ HandsOffSWDetectionMode 2 "Failed" 1 "Enabled" 0 "Disabled" ;
 
 BO_ 189 EBCMRegenPaddle: 7 K17_EBCM
  SG_ RegenPaddle : 7|4@0+ (1,0) [0|0] ""  NEO
+ SG_ Byte1 : 8|8@1+ (1,0) [0|255] "" NEO
+ SG_ Byte2 : 16|8@1+ (1,0) [0|255] "" NEO
+ SG_ Byte3 : 24|8@1+ (1,0) [0|255] "" NEO
+ SG_ Byte4 : 32|8@1+ (1,0) [0|255] "" NEO
+ SG_ Byte5 : 40|8@1+ (1,0) [0|255] "" NEO
+ SG_ Byte6 : 48|8@1+ (1,0) [0|255] "" NEO
 
 BO_ 190 ECMAcceleratorPos: 6 K20_ECM
  SG_ BrakePedalPos : 15|8@0+ (1,0) [0|0] "sticky"  NEO
@@ -165,6 +171,7 @@ BO_ 481 ASCMSteeringButton: 7 K124_ASCM
  SG_ DistanceButton : 22|1@0+ (1,0) [0|0] ""  NEO
  SG_ LKAButton : 23|1@0+ (1,0) [0|0] ""  NEO
  SG_ ACCAlwaysOne : 24|1@0+ (1,0) [0|1] "" XXX
+ SG_ ACCHiddenBit : 30|1@0+ (1,0) [0|1] "" XXX
  SG_ ACCButtons : 46|3@0+ (1,0) [0|0] ""  NEO
  SG_ DriveModeButton : 39|1@0+ (1,0) [0|1] "" XXX
  SG_ RollingCounter : 33|2@0+ (1,0) [0|3] "" NEO
@@ -192,10 +199,15 @@ BO_ 500 SportMode: 6 XXX
  SG_ SportMode : 15|1@0+ (1,0) [0|1] "" XXX
 
 BO_ 501 ECMPRDNL2: 8 K20_ECM
- SG_ TransmissionState : 48|4@1+ (1,0) [0|7] "" NEO
+ SG_ Byte0 : 0|8@1+ (1,0) [0|255] "" NEO
+ SG_ Byte1 : 8|8@1+ (1,0) [0|255] "" NEO
+ SG_ Byte2 : 16|8@1+ (1,0) [0|255] "" NEO
  SG_ PRNDL2 : 27|4@0+ (1,0) [0|255] "" NEO
+ SG_ Byte4 : 32|8@1+ (1,0) [0|255] "" NEO
  SG_ ManualMode : 41|1@0+ (1,0) [0|1] "" NEO
-
+ SG_ TransmissionState : 48|4@1+ (1,0) [0|7] "" NEO
+ SG_ Byte7 : 56|8@1+ (1,0) [0|255] "" NEO
+ 
 BO_ 532 BRAKE_RELATED: 6 XXX
  SG_ UserBrakePressure : 0|9@0+ (1,0) [0|511] "" XXX
 
@@ -222,7 +234,7 @@ BO_ 715 ASCMGasRegenCmd: 8 K124_ASCM
  SG_ GasRegenCmdActive : 0|1@0+ (1,0) [0|0] ""  NEO
  SG_ RollingCounter : 7|2@0+ (1,0) [0|0] ""  NEO
  SG_ GasRegenAlwaysOne3 : 23|1@0+ (1,0) [0|1] ""  NEO
- SG_ GasRegenCmd : 22|12@0+ (1,0) [0|0] ""  NEO
+ SG_ GasRegenCmd : 8|14@0+ (1,0) [0|0] "" NEO
 
 BO_ 717 ASCM_2CD: 5 K124_ASCM
 
@@ -370,6 +382,6 @@ VAL_ 715 GasRegenCmdActive 1 "Active" 0 "Inactive" ;
 VAL_ 320 Intellibeam 1 "Active" 0 "Inactive" ;
 VAL_ 320 HighBeamsActive 1 "Active" 0 "Inactive" ;
 VAL_ 320 HighBeamsTemporary 1 "Active" 0 "Inactive" ;
-VAL_ 501 PRNDL2 6 "L" 4 "D" 3 "N" 2 "R" 1 "P" 0 "Shifting";
+VAL_ 501 PRNDL2 7 "L2" 6 "L" 5 "L3" 4 "D" 3 "N" 2 "R" 1 "P" 0 "Shifting";
 VAL_ 501 TransmissionState 11 "Shifting" 10 "Reverse" 9 "Forward" 8 "Disengaged";
 VAL_ 501 ManualMode 1 "Active" 0 "Inactive"

opendbc/gm_global_a_powertrain_volt.dbc

@@ -165,6 +165,7 @@ BO_ 481 ASCMSteeringButton: 7 K124_ASCM
  SG_ DistanceButton : 22|1@0+ (1,0) [0|0] ""  NEO
  SG_ LKAButton : 23|1@0+ (1,0) [0|0] ""  NEO
  SG_ ACCAlwaysOne : 24|1@0+ (1,0) [0|1] "" XXX
+ SG_ ACCHiddenBit : 30|1@0+ (1,0) [0|1] "" XXX
  SG_ ACCButtons : 46|3@0+ (1,0) [0|0] ""  NEO
  SG_ DriveModeButton : 39|1@0+ (1,0) [0|1] "" XXX
  SG_ RollingCounter : 33|2@0+ (1,0) [0|3] "" NEO

panda/board/drivers/can_common.h

@@ -200,11 +200,11 @@ void ignition_can_hook(CANPacket_t *to_push) {
   if (bus == 0) {
     int addr = GET_ADDR(to_push);
     int len = GET_LEN(to_push);
-    
+
     // GM exception
-    if ((addr == 0x1F1) && (len == 8)) {
-      // SystemPowerMode (2=Run, 3=Crank Request)
-      ignition_can = (GET_BYTE(to_push, 0) & 0x2U) != 0U;
+    if ((addr == 0xC9) && (len == 8)) {
+      // Matches SystemPowerMode (1=Run, 0=Off)
+      ignition_can = (GET_BYTE(to_push, 6) & 0x10U) != 0U;
       ignition_can_cnt = 0U;
     }
 
@@ -220,16 +220,6 @@ void ignition_can_hook(CANPacket_t *to_push) {
       ignition_can = (GET_BYTE(to_push, 0) >> 5) == 0x6U;
       ignition_can_cnt = 0U;
     }
-
-  } else if (bus == 2) {
-    int addr = GET_ADDR(to_push);
-    int len = GET_LEN(to_push);
-    // GM exception, SDGM cars have this message on bus 2
-    if ((addr == 0x1F1) && (len == 8)) {
-      // SystemPowerMode (2=Run, 3=Crank Request)
-      ignition_can = (GET_BYTE(to_push, 0) & 0x2U) != 0U;
-      ignition_can_cnt = 0U;
-    }
   }
 }
 

panda/board/safety.h

@@ -88,7 +88,7 @@ int safety_fwd_hook(int bus_num, int addr) {
 }
 
 bool get_longitudinal_allowed(void) {
-  return controls_allowed && !gas_pressed_prev;
+  return controls_allowed && !gas_pressed;
 }
 
 // Given a CRC-8 poly, generate a static lookup table to use with a fast CRC-8

panda/board/safety/safety_gm.h

@@ -10,16 +10,16 @@ const SteeringLimits GM_STEERING_LIMITS = {
 };
 
 const LongitudinalLimits GM_ASCM_LONG_LIMITS = {
-  .max_gas = 3072,
-  .min_gas = 1404,
-  .inactive_gas = 1404,
+  .max_gas = 8191,
+  .min_gas = 5500,
+  .inactive_gas = 5500,
   .max_brake = 400,
 };
 
 const LongitudinalLimits GM_CAM_LONG_LIMITS = {
-  .max_gas = 3400,
-  .min_gas = 1514,
-  .inactive_gas = 1554,
+  .max_gas = 8848,
+  .min_gas = 5610,
+  .inactive_gas = 5650,
   .max_brake = 400,
 };
 
@@ -29,46 +29,43 @@ const int GM_STANDSTILL_THRSLD = 10;  // 0.311kph
 
 // panda interceptor threshold needs to be equivalent to openpilot threshold to avoid controls mismatches
 // If thresholds are mismatched then it is possible for panda to see the gas fall and rise while openpilot is in the pre-enabled state
-const int GM_GAS_INTERCEPTOR_THRESHOLD = 515; // (675 + 355) / 2 ratio between offset and gain from dbc file
+const int GM_GAS_INTERCEPTOR_THRESHOLD = 595; // (675 + 355) / 2 ratio between offset and gain from dbc file
 #define GM_GET_INTERCEPTOR(msg) (((GET_BYTE((msg), 0) << 8) + GET_BYTE((msg), 1) + (GET_BYTE((msg), 2) << 8) + GET_BYTE((msg), 3)) / 2U) // avg between 2 tracks
 
-const CanMsg GM_ASCM_TX_MSGS[] = {{0x180, 0, 4}, {0x409, 0, 7}, {0x40A, 0, 7}, {0x2CB, 0, 8}, {0x370, 0, 6}, {0x200, 0, 6},  // pt bus
+const CanMsg GM_ASCM_TX_MSGS[] = {{0x180, 0, 4}, {0x409, 0, 7}, {0x40A, 0, 7}, {0x2CB, 0, 8}, {0x370, 0, 6}, {0x200, 0, 6}, {0xBD, 0, 7}, {0x1F5, 0, 8}, // pt bus
                                   {0xA1, 1, 7}, {0x306, 1, 8}, {0x308, 1, 7}, {0x310, 1, 2},   // obs bus
                                   {0x315, 2, 5}};  // ch bus
 
-const CanMsg GM_CAM_TX_MSGS[] = {{0x180, 0, 4}, {0x200, 0, 6}, {0x1E1, 0, 7},  // pt bus
+const CanMsg GM_CAM_TX_MSGS[] = {{0x180, 0, 4}, {0x200, 0, 6}, {0x1E1, 0, 7}, {0xBD, 0, 7}, {0x1F5, 0, 8}, // pt bus
                                  {0x1E1, 2, 7}, {0x184, 2, 8}};  // camera bus
 
-const CanMsg GM_CAM_LONG_TX_MSGS[] = {{0x180, 0, 4}, {0x315, 0, 5}, {0x2CB, 0, 8}, {0x370, 0, 6}, {0x200, 0, 6},  // pt bus
-                                      {0x1E1, 2, 7}, {0x184, 2, 8}};  // camera bus
+const CanMsg GM_CAM_LONG_TX_MSGS[] = {{0x180, 0, 4}, {0x315, 0, 5}, {0x2CB, 0, 8}, {0x370, 0, 6}, {0x200, 0, 6}, {0xBD, 0, 7}, {0x1F5, 0, 8},   // pt bus
+                                      {0x315, 2, 5}, {0x1E1, 2, 7}, {0x184, 2, 8}};  // camera bus
 
-const CanMsg GM_SDGM_TX_MSGS[] = {{0x180, 0, 4}, {0x1E1, 0, 7},  // pt bus
-                                  {0x184, 2, 8}};  // camera bus
-
-const CanMsg GM_CC_LONG_TX_MSGS[] = {{0x180, 0, 4}, {0x1E1, 0, 7},  // pt bus
+const CanMsg GM_CC_LONG_TX_MSGS[] = {{0x180, 0, 4}, {0x1E1, 0, 7}, {0xBD, 0, 7}, {0x1F5, 0, 8}, // pt bus
                                      {0x184, 2, 8}, {0x1E1, 2, 7}};  // camera bus
 
 // TODO: do checksum and counter checks. Add correct timestep, 0.1s for now.
 RxCheck gm_rx_checks[] = {
   {.msg = {{0x184, 0, 8, .frequency = 10U}, { 0 }, { 0 }}},
   {.msg = {{0x34A, 0, 5, .frequency = 10U}, { 0 }, { 0 }}},
-  {.msg = {{0x1E1, 0, 7, .frequency = 10U},   // Non-SDGM Car
-           {0x1E1, 2, 7, .frequency = 100000U}}}, // SDGM Car
-  {.msg = {{0xF1, 0, 6, .frequency = 10U},   // Non-SDGM Car
-           {0xF1, 2, 6, .frequency = 100000U}}}, // SDGM Car
+  {.msg = {{0x1E1, 0, 7, .frequency = 10U}, { 0 }, { 0 }}},
+  {.msg = {{0xF1, 0, 6, .frequency = 10U}, { 0 }, { 0 }}},
   {.msg = {{0x1C4, 0, 8, .frequency = 10U}, { 0 }, { 0 }}},
   {.msg = {{0xC9, 0, 8, .frequency = 10U}, { 0 }, { 0 }}},
 };
 
 const uint16_t GM_PARAM_HW_CAM = 1;
 const uint16_t GM_PARAM_HW_CAM_LONG = 2;
-const uint16_t GM_PARAM_HW_SDGM = 4;
-const uint16_t GM_PARAM_CC_LONG = 8;
-const uint16_t GM_PARAM_HW_ASCM_LONG = 16;
-const uint16_t GM_PARAM_NO_CAMERA = 32;
-const uint16_t GM_PARAM_NO_ACC = 64;
-const uint16_t GM_PARAM_PEDAL_LONG = 128;  // TODO: this can be inferred
-const uint16_t GM_PARAM_PEDAL_INTERCEPTOR = 256;
+const uint16_t GM_PARAM_CC_LONG = 4;
+const uint16_t GM_PARAM_HW_ASCM_LONG = 8;
+const uint16_t GM_PARAM_NO_CAMERA = 16;
+const uint16_t GM_PARAM_NO_ACC = 32;
+const uint16_t GM_PARAM_PEDAL_LONG = 64;  // TODO: this can be inferred
+const uint16_t GM_PARAM_PEDAL_INTERCEPTOR = 128;
+const uint16_t GM_PARAM_ASCM_INT = 256;
+const uint16_t GM_PARAM_FORCE_BRAKE_C9 = 512;
+const uint16_t GM_PARAM_HW_SDGM = 1024;
 
 enum {
   GM_BTN_UNPRESS = 1,
@@ -90,30 +87,9 @@ bool gm_pedal_long = false;
 bool gm_cc_long = false;
 bool gm_skip_relay_check = false;
 bool gm_force_ascm = false;
-
-static void handle_gm_wheel_buttons(const CANPacket_t *to_push) {
-  int button = (GET_BYTE(to_push, 5) & 0x70U) >> 4;
-
-  // enter controls on falling edge of set or rising edge of resume (avoids fault)
-  bool set = (button != GM_BTN_SET) && (cruise_button_prev == GM_BTN_SET);
-  bool res = (button == GM_BTN_RESUME) && (cruise_button_prev != GM_BTN_RESUME);
-  if (set || res) {
-    controls_allowed = true;
-  }
-
-  // exit controls on cancel press
-  if (button == GM_BTN_CANCEL) {
-    controls_allowed = false;
-  }
-
-  cruise_button_prev = button;
-}
+bool gm_force_brake_c9 = false;
 
 static void gm_rx_hook(const CANPacket_t *to_push) {
-  if ((GET_BUS(to_push) == 2U) && (GET_ADDR(to_push) == 0x1E1) && (gm_hw == GM_SDGM)) {
-    // SDGM buttons are on bus 2
-    handle_gm_wheel_buttons(to_push);
-  }
   if (GET_BUS(to_push) == 0U) {
     int addr = GET_ADDR(to_push);
 
@@ -131,19 +107,35 @@ static void gm_rx_hook(const CANPacket_t *to_push) {
       vehicle_moving = (left_rear_speed > GM_STANDSTILL_THRSLD) || (right_rear_speed > GM_STANDSTILL_THRSLD);
     }
 
-    // ACC steering wheel buttons (GM_CAM and GM_SDGM are tied to the PCM)
-    if ((addr == 0x1E1) && (!gm_pcm_cruise || gm_cc_long) && (gm_hw != GM_SDGM)) {
-      handle_gm_wheel_buttons(to_push);
+    // ACC steering wheel buttons (GM_CAM is tied to the PCM)
+    if ((addr == 0x1E1) && (!gm_pcm_cruise || gm_cc_long)) {
+      int button = (GET_BYTE(to_push, 5) & 0x70U) >> 4;
+
+      // enter controls on falling edge of set or rising edge of resume (avoids fault)
+      bool set = (button != GM_BTN_SET) && (cruise_button_prev == GM_BTN_SET);
+      bool res = (button == GM_BTN_RESUME) && (cruise_button_prev != GM_BTN_RESUME);
+      if (set || res) {
+        controls_allowed = true;
+      }
+
+      // exit controls on cancel press
+      if (button == GM_BTN_CANCEL) {
+        controls_allowed = false;
+      }
+
+      cruise_button_prev = button;
     }
 
     // Reference for brake pressed signals:
     // https://github.com/commaai/openpilot/blob/master/selfdrive/car/gm/carstate.py
-    if ((addr == 0xBE) && (gm_hw == GM_ASCM)) {
+    // Prefer 0xC9 (ECMEngineStatus) when gm_force_brake_c9 is set, otherwise keep legacy behavior.
+    // This allows SDGM/Traverse variants without 0xBE (ECMAcceleratorPos) to report brake correctly.
+    if ((addr == 0xC9) && gm_force_brake_c9) {
+      brake_pressed = GET_BIT(to_push, 40U) != 0U;
+    } else if ((addr == 0xBE) && ((gm_hw == GM_ASCM) || (gm_hw == GM_SDGM))) {
       brake_pressed = GET_BYTE(to_push, 1) >= 8U;
-    }
-
-    if ((addr == 0xC9) && ((gm_hw == GM_CAM) || (gm_hw == GM_SDGM))) {
-      brake_pressed = GET_BIT(to_push, 40U);
+    } else if ((addr == 0xC9) && (gm_hw == GM_CAM)) {
+      brake_pressed = GET_BIT(to_push, 40U) != 0U;
     }
 
     if (addr == 0xC9) {
@@ -192,6 +184,18 @@ static void gm_rx_hook(const CANPacket_t *to_push) {
     }
     generic_rx_checks(stock_ecu_detected);
   }
+  // Cruise check for Gen2 Bolt (ASCMActiveCruiseControlStatus on bus 2)
+  int addr = GET_ADDR(to_push);
+  if ((addr == 0x370) && (GET_BUS(to_push) == 2U)) {
+    bool cruise_engaged = (GET_BYTE(to_push, 2) >> 7) != 0U;  // ACCCmdActive
+    // Align SDGM/camera PCM cruise behavior with ASCM path: when using stock PCM cruise,
+    // drive controls_allowed via pcm_cruise_check on ACC engaged edges.
+    if (gm_pcm_cruise && gm_has_acc) {
+      pcm_cruise_check(cruise_engaged);
+    } else {
+      cruise_engaged_prev = cruise_engaged;
+    }
+  }
 }
 
 static bool gm_tx_hook(const CANPacket_t *to_send) {
@@ -229,7 +233,7 @@ static bool gm_tx_hook(const CANPacket_t *to_send) {
   // GAS/REGEN: safety check
   if (addr == 0x2CB) {
     bool apply = GET_BIT(to_send, 0U);
-    int gas_regen = ((GET_BYTE(to_send, 2) & 0x7FU) << 5) + ((GET_BYTE(to_send, 3) & 0xF8U) >> 3);
+    int gas_regen = ((GET_BYTE(to_send, 1) & 0x1U) << 13) + ((GET_BYTE(to_send, 2) & 0xFFU) << 5) + ((GET_BYTE(to_send, 3) & 0xF8U) >> 3);
 
     bool violation = false;
     // Allow apply bit in pre-enabled and overriding states
@@ -246,8 +250,8 @@ static bool gm_tx_hook(const CANPacket_t *to_send) {
     int button = (GET_BYTE(to_send, 5) >> 4) & 0x7U;
 
     bool allowed_btn = (button == GM_BTN_CANCEL) && cruise_engaged_prev;
-    // For standard CC, allow spamming of SET / RESUME
-    if (gm_cc_long) {
+    // For CC_LONG or PCM cruise vehicles, allow SET/RESUME when cruise is engaged
+    if (gm_cc_long || gm_pcm_cruise) {
       allowed_btn |= cruise_engaged_prev && (button == GM_BTN_SET || button == GM_BTN_RESUME || button == GM_BTN_UNPRESS);
     }
 
@@ -255,7 +259,6 @@ static bool gm_tx_hook(const CANPacket_t *to_send) {
       tx = false;
     }
   }
-
   return tx;
 }
 
@@ -286,9 +289,10 @@ static int gm_fwd_hook(int bus_num, int addr) {
 }
 
 static safety_config gm_init(uint16_t param) {
-  if GET_FLAG(param, GM_PARAM_HW_CAM) {
+  const bool gm_ascm_int = GET_FLAG(param, GM_PARAM_ASCM_INT);
+  if (GET_FLAG(param, GM_PARAM_HW_CAM)) {
     gm_hw = GM_CAM;
-  } else if GET_FLAG(param, GM_PARAM_HW_SDGM) {
+  } else if (GET_FLAG(param, GM_PARAM_HW_SDGM)) {
     gm_hw = GM_SDGM;
   } else {
     gm_hw = GM_ASCM;
@@ -296,7 +300,7 @@ static safety_config gm_init(uint16_t param) {
 
   gm_force_ascm = GET_FLAG(param, GM_PARAM_HW_ASCM_LONG);
 
-  if (gm_hw == GM_ASCM || gm_force_ascm) {
+  if (gm_hw == GM_ASCM || gm_force_ascm || gm_ascm_int) {
     gm_long_limits = &GM_ASCM_LONG_LIMITS;
   } else if ((gm_hw == GM_CAM) || (gm_hw == GM_SDGM)) {
     gm_long_limits = &GM_CAM_LONG_LIMITS;
@@ -306,10 +310,11 @@ static safety_config gm_init(uint16_t param) {
   gm_pedal_long = GET_FLAG(param, GM_PARAM_PEDAL_LONG);
   gm_cc_long = GET_FLAG(param, GM_PARAM_CC_LONG);
   gm_cam_long = GET_FLAG(param, GM_PARAM_HW_CAM_LONG) && !gm_cc_long;
-  gm_pcm_cruise = ((gm_hw == GM_CAM) && (!gm_cam_long || gm_cc_long) && !gm_force_ascm && !gm_pedal_long) || (gm_hw == GM_SDGM);
+  gm_pcm_cruise = (((gm_hw == GM_CAM) || (gm_hw == GM_SDGM)) && (!gm_cam_long || gm_cc_long) && !gm_force_ascm && !gm_pedal_long);
   gm_skip_relay_check = GET_FLAG(param, GM_PARAM_NO_CAMERA);
   gm_has_acc = !GET_FLAG(param, GM_PARAM_NO_ACC);
   enable_gas_interceptor = GET_FLAG(param, GM_PARAM_PEDAL_INTERCEPTOR);
+  gm_force_brake_c9 = GET_FLAG(param, GM_PARAM_FORCE_BRAKE_C9);
 
   safety_config ret = BUILD_SAFETY_CFG(gm_rx_checks, GM_ASCM_TX_MSGS);
   if (gm_hw == GM_CAM) {
@@ -320,8 +325,6 @@ static safety_config gm_init(uint16_t param) {
     } else {
       ret = BUILD_SAFETY_CFG(gm_rx_checks, GM_CAM_TX_MSGS);
     }
-  } else if (gm_hw == GM_SDGM) {
-    ret = BUILD_SAFETY_CFG(gm_rx_checks, GM_SDGM_TX_MSGS);
   }
   return ret;
 }

panda/python/__init__.py

@@ -211,7 +211,6 @@ class Panda:
   FLAG_HYUNDAI_ALT_LIMITS = 64
   FLAG_HYUNDAI_CANFD_HDA2_ALT_STEERING = 128
   FLAG_HYUNDAI_LFA_BTN = 256
-  FLAG_HYUNDAI_TACO_TUNE_HACK = 512
 
   FLAG_TESLA_POWERTRAIN = 1
   FLAG_TESLA_LONG_CONTROL = 2
@@ -231,13 +230,15 @@ class Panda:
 
   FLAG_GM_HW_CAM = 1
   FLAG_GM_HW_CAM_LONG = 2
-  FLAG_GM_HW_SDGM = 4
-  FLAG_GM_CC_LONG = 8
-  FLAG_GM_HW_ASCM_LONG = 16
-  FLAG_GM_NO_CAMERA = 32
-  FLAG_GM_NO_ACC = 64
-  FLAG_GM_PEDAL_LONG = 128  # TODO: This can be inferred
-  FLAG_GM_GAS_INTERCEPTOR = 256
+  FLAG_GM_CC_LONG = 4
+  FLAG_GM_HW_ASCM_LONG = 8
+  FLAG_GM_NO_CAMERA = 16
+  FLAG_GM_NO_ACC = 32
+  FLAG_GM_PEDAL_LONG = 64  # TODO: This can be inferred
+  FLAG_GM_GAS_INTERCEPTOR = 128
+  FLAG_GM_ASCM_INT = 256
+  FLAG_GM_FORCE_BRAKE_C9 = 512
+  FLAG_GM_HW_SDGM = 1024
 
   FLAG_FORD_LONG_CONTROL = 1
   FLAG_FORD_CANFD = 2
@@ -804,7 +805,8 @@ class Panda:
   # The panda will NAK CAN writes when there is CAN congestion.
   # libusb will try to send it again, with a max timeout.
   # Timeout is in ms. If set to 0, the timeout is infinite.
-  CAN_SEND_TIMEOUT_MS = 10
+  CAN_SEND_TIMEOUT_MS = 5
+  CAN_MAX_RETRIES = 3
 
   def can_reset_communications(self):
     self._handle.controlWrite(Panda.REQUEST_OUT, 0xc0, 0, 0, b'')
@@ -812,18 +814,18 @@ class Panda:
   @ensure_can_packet_version
   def can_send_many(self, arr, timeout=CAN_SEND_TIMEOUT_MS):
     snds = pack_can_buffer(arr)
-    while True:
-      try:
-        for tx in snds:
-          while True:
-            bs = self._handle.bulkWrite(3, tx, timeout=timeout)
-            tx = tx[bs:]
-            if len(tx) == 0:
-              break
-            logging.error("CAN: PARTIAL SEND MANY, RETRYING")
-        break
-      except (usb1.USBErrorIO, usb1.USBErrorOverflow):
-        logging.error("CAN: BAD SEND MANY, RETRYING")
+    for tx in snds:
+      retries = 0
+      while len(tx) > 0:
+        bs = self._handle.bulkWrite(3, tx, timeout=timeout)
+        if bs == 0:
+          retries += 1
+          if retries > self.CAN_MAX_RETRIES:
+            logging.warning("CAN send: no progress after retries, dropping")
+            break
+        else:
+          retries = 0
+        tx = tx[bs:]
 
   def can_send(self, addr, dat, bus, timeout=CAN_SEND_TIMEOUT_MS):
     self.can_send_many([[addr, None, dat, bus]], timeout=timeout)
@@ -831,13 +833,16 @@ class Panda:
   @ensure_can_packet_version
   def can_recv(self):
     dat = bytearray()
-    while True:
+    for _ in range(self.CAN_MAX_RETRIES):
       try:
         dat = self._handle.bulkRead(1, 16384) # Max receive batch size + 2 extra reserve frames
         break
       except (usb1.USBErrorIO, usb1.USBErrorOverflow):
         logging.error("CAN: BAD RECV, RETRYING")
-        time.sleep(0.1)
+        time.sleep(0.01)
+    else:
+      logging.error("CAN: recv failed after retries")
+      return []
     msgs, self.can_rx_overflow_buffer = unpack_can_buffer(self.can_rx_overflow_buffer + dat)
     return msgs
 

panda/python/spi.py

@@ -27,7 +27,10 @@ NACK = 0x1F
 CHECKSUM_START = 0xAB
 
 MIN_ACK_TIMEOUT_MS = 100
+MAX_ACK_TIMEOUT_MS = 500  # like C++ SPI_ACK_TIMEOUT
+DEFAULT_TIMEOUT_MS = 500  # default when timeout=0
 MAX_XFER_RETRY_COUNT = 5
+MAX_TIMEOUT_RETRIES = 5  # like C++
 
 XFER_SIZE = 0x40*31
 
@@ -152,6 +155,8 @@ class PandaSpiHandle(BaseHandle):
     return cksum
 
   def _wait_for_ack(self, spi, ack_val: int, timeout: int, tx: int, length: int = 1) -> bytes:
+    # Original behavior preserved - timeout=0 means wait forever within this function
+    # The caller (_transfer) handles the overall timeout
     timeout_s = max(MIN_ACK_TIMEOUT_MS, timeout) * 1e-3
 
     start = time.monotonic()
@@ -225,10 +230,15 @@ class PandaSpiHandle(BaseHandle):
     logging.debug("starting transfer: endpoint=%d, max_rx_len=%d", endpoint, max_rx_len)
     logging.debug("==============================================")
 
+    # Fix timeout=0 infinite loop: default to DEFAULT_TIMEOUT_MS
+    if timeout == 0:
+      timeout = DEFAULT_TIMEOUT_MS
+
     n = 0
     start_time = time.monotonic()
     exc = PandaSpiException()
-    while (timeout == 0) or (time.monotonic() - start_time) < timeout*1e-3:
+    # Use the timeout for the overall loop, matching original behavior but with timeout=0 fixed
+    while (time.monotonic() - start_time) < timeout * 1e-3:
       n += 1
       logging.debug("\ntry #%d", n)
       with self.dev.acquire() as spi:
@@ -238,6 +248,7 @@ class PandaSpiHandle(BaseHandle):
           exc = e
           logging.debug("SPI transfer failed, retrying", exc_info=True)
 
+    logging.error("SPI transfer failed after %d tries, %.2fms", n, (time.monotonic() - start_time) * 1000)
     raise exc
 
   def get_protocol_version(self) -> bytes:

selfdrive/car/gm/carcontroller.py

@@ -1,3 +1,5 @@
+import math
+
 from cereal import car
 from openpilot.common.conversions import Conversions as CV
 from openpilot.common.filter_simple import FirstOrderFilter
@@ -7,7 +9,7 @@ from openpilot.common.params_pyx import Params
 from opendbc.can.packer import CANPacker
 from openpilot.selfdrive.car import apply_driver_steer_torque_limits, create_gas_interceptor_command
 from openpilot.selfdrive.car.gm import gmcan
-from openpilot.selfdrive.car.gm.values import DBC, AccState, CanBus, CarControllerParams, CruiseButtons, GMFlags, CC_ONLY_CAR, SDGM_CAR, EV_CAR
+from openpilot.selfdrive.car.gm.values import DBC, AccState, CanBus, CarControllerParams, CruiseButtons, GMFlags, CC_ONLY_CAR, SDGM_CAR, EV_CAR, CAR
 from openpilot.selfdrive.car.interfaces import CarControllerBase
 from openpilot.selfdrive.controls.lib.drive_helpers import apply_deadzone
 from openpilot.selfdrive.controls.lib.vehicle_model import ACCELERATION_DUE_TO_GRAVITY
@@ -46,7 +48,18 @@ class CarController(CarControllerBase):
     self.lka_icon_status_last = (False, False)
 
     self.params = CarControllerParams(self.CP)
+    self.is_volt = self.CP.carFingerprint in (CAR.CHEVROLET_VOLT, CAR.CHEVROLET_VOLT_2019, CAR.CHEVROLET_VOLT_ASCM, CAR.CHEVROLET_VOLT_CAMERA, CAR.CHEVROLET_VOLT_CC)
+    self.pedal_scale = 1.0
+    self.mass = CP.mass
+    self.tireRadius = 0.075 * CP.wheelbase + 0.1453
+    self.frontalArea = 1.05 * CP.wheelbase + 0.0679
+    self.coeffDrag = 0.30
+    self.airDensity = 1.225
     self.params_ = Params()
+    self.malibu_cancel_phase = 0
+    self.malibu_cancel_last_ts = 0.0
+    self.malibu_cancel_frame = 0
+    self.malibu_button_phase = 0
 
     self.packer_pt = CANPacker(DBC[self.CP.carFingerprint]['pt'])
     self.packer_obj = CANPacker(DBC[self.CP.carFingerprint]['radar'])
@@ -54,8 +67,8 @@ class CarController(CarControllerBase):
 
     # FrogPilot variables
     self.accel_g = 0.0
-
     self.pitch = FirstOrderFilter(0., 0.09 * 4, DT_CTRL * 4)  # runs at 25 Hz
+    self.accel_g = 0.0
 
   @staticmethod
   def calc_pedal_command(accel: float, long_active: bool) -> float:
@@ -80,10 +93,18 @@ class CarController(CarControllerBase):
     hud_v_cruise = hud_control.setSpeed
     if hud_v_cruise > 70:
       hud_v_cruise = 0
+    now_sec = now_nanos * 1e-9
 
     # Send CAN commands.
     can_sends = []
 
+    if self.CP.carFingerprint == CAR.CHEVROLET_MALIBU_HYBRID_CC:
+      phase_map = gmcan.malibu_phase_map_for_acc(CS.cruise_buttons)
+      if phase_map and CS.steering_button_checksum in phase_map:
+        phase = (phase_map[CS.steering_button_checksum] + 1) % 4
+        self.malibu_cancel_phase = phase
+        self.malibu_button_phase = phase
+
     # Steering (Active: 50Hz, inactive: 10Hz)
     steer_step = self.params.STEER_STEP if CC.latActive else self.params.INACTIVE_STEER_STEP
 
@@ -112,6 +133,9 @@ class CarController(CarControllerBase):
       else:
         apply_steer = 0
 
+      if (self.CP.flags & GMFlags.CC_LONG.value) and CC.enabled and not CS.out.cruiseState.enabled: # Send 0 so Panda doesn't error
+        apply_steer = 0
+
       self.last_steer_frame = self.frame
       self.apply_steer_last = apply_steer
       idx = self.lka_steering_cmd_counter % 4
@@ -124,7 +148,7 @@ class CarController(CarControllerBase):
 
         # Pitch compensated acceleration;
         # TODO: include future pitch (sm['modelDataV2'].orientation.y) to account for long actuator delay
-        if frogpilot_toggles.long_pitch and len(CC.orientationNED) > 1:
+        if frogpilot_toggles.long_pitch and len(CC.orientationNED) > 1 and not self.is_volt:
           self.pitch.update(CC.orientationNED[1])
           self.accel_g = ACCELERATION_DUE_TO_GRAVITY * apply_deadzone(self.pitch.x, PITCH_DEADZONE) # driving uphill is positive pitch
           accel += self.accel_g
@@ -142,13 +166,58 @@ class CarController(CarControllerBase):
           self.apply_brake = int(min(-100 * frogpilot_toggles.stopAccel, self.params.MAX_BRAKE))
         else:
           # Normal operation
-          if self.CP.carFingerprint in EV_CAR:
-            self.params.update_ev_gas_brake_threshold(CS.out.vEgo)
-            self.apply_gas = int(round(interp(accel, self.params.EV_GAS_LOOKUP_BP, self.params.GAS_LOOKUP_V)))
-            self.apply_brake = int(round(interp(brake_accel, self.params.EV_BRAKE_LOOKUP_BP, self.params.BRAKE_LOOKUP_V)))
+          if self.is_volt:
+            if len(CC.orientationNED) == 3 and CS.out.vEgo > self.CP.vEgoStopping:
+              volt_pitch_accel = math.sin(CC.orientationNED[1]) * ACCELERATION_DUE_TO_GRAVITY
+            else:
+              volt_pitch_accel = 0.0
+
+            aero_drag_accel = (0.5 * self.coeffDrag * self.frontalArea * self.airDensity * CS.out.vEgo ** 2) / self.mass
+            accel += aero_drag_accel + volt_pitch_accel
+            brake_accel = actuators.accel + aero_drag_accel + volt_pitch_accel * interp(CS.out.vEgo, BRAKE_PITCH_FACTOR_BP, BRAKE_PITCH_FACTOR_V)
+            accel = clip(accel, self.params.ACCEL_MIN, self.params.ACCEL_MAX)
+            brake_accel = clip(brake_accel, self.params.ACCEL_MIN, self.params.ACCEL_MAX)
+
+            if self.CP.carFingerprint in EV_CAR:
+              self.params.update_ev_gas_brake_threshold(CS.out.vEgo)
+              self.apply_gas = int(round(interp(accel, self.params.EV_GAS_LOOKUP_BP, self.params.GAS_LOOKUP_V)))
+              self.apply_brake = int(round(interp(brake_accel, self.params.EV_BRAKE_LOOKUP_BP, self.params.BRAKE_LOOKUP_V)))
+            else:
+              self.apply_gas = int(round(interp(accel, self.params.GAS_LOOKUP_BP, self.params.GAS_LOOKUP_V)))
+              self.apply_brake = int(round(interp(brake_accel, self.params.BRAKE_LOOKUP_BP, self.params.BRAKE_LOOKUP_V)))
+
+            # Clamp within message-valid ranges to avoid ASCM faults from overshoot or rounding
+            self.apply_gas = int(round(clip(self.apply_gas, self.params.MAX_ACC_REGEN, self.params.MAX_GAS)))
+            self.apply_brake = int(round(clip(self.apply_brake, 0, self.params.MAX_BRAKE)))
+
+            if self.apply_brake > 0:
+              # Volt should never present positive torque alongside friction braking
+              self.apply_gas = self.params.INACTIVE_REGEN
           else:
-            self.apply_gas = int(round(interp(accel, self.params.GAS_LOOKUP_BP, self.params.GAS_LOOKUP_V)))
+            if len(CC.orientationNED) == 3 and CS.out.vEgo > self.CP.vEgoStopping:
+              accel_due_to_pitch = math.sin(CC.orientationNED[1]) * ACCELERATION_DUE_TO_GRAVITY
+            else:
+              accel_due_to_pitch = 0.0
+
+            gas_max = self.params.MAX_GAS
+            accel_max = self.params.ACCEL_MAX
+
+            accel = clip(actuators.accel + accel_due_to_pitch, self.params.ACCEL_MIN, accel_max)
+            torque = self.tireRadius * ((self.mass * accel) + (0.5 * self.coeffDrag * self.frontalArea * self.airDensity * CS.out.vEgo ** 2))
+
+            scaled_torque = torque + self.params.ZERO_GAS
+            apply_gas_torque = clip(scaled_torque, self.params.MAX_ACC_REGEN, gas_max)
+            BRAKE_SWITCH = int(round(interp(CS.out.vEgo, self.params.BRAKE_SWITCH_LOOKUP_BP, self.params.BRAKE_SWITCH_LOOKUP_V)))
+            brake_accel = min((scaled_torque - BRAKE_SWITCH) / (self.tireRadius * self.mass), 0)
+            self.apply_gas = int(round(apply_gas_torque))
             self.apply_brake = int(round(interp(brake_accel, self.params.BRAKE_LOOKUP_BP, self.params.BRAKE_LOOKUP_V)))
+
+            # Clamp within message-valid ranges to avoid ASCM faults from overshoot or rounding
+            self.apply_gas = int(round(clip(self.apply_gas, self.params.MAX_ACC_REGEN, self.params.MAX_GAS)))
+            self.apply_brake = int(round(clip(self.apply_brake, 0, self.params.MAX_BRAKE)))
+
+            if self.apply_brake > 0 and self.apply_gas > self.params.INACTIVE_REGEN:
+              self.apply_gas = self.params.INACTIVE_REGEN
           # Don't allow any gas above inactive regen while stopping
           # FIXME: brakes aren't applied immediately when enabling at a stop
           if stopping:
@@ -156,6 +225,7 @@ class CarController(CarControllerBase):
           if self.CP.carFingerprint in CC_ONLY_CAR:
             # gas interceptor only used for full long control on cars without ACC
             interceptor_gas_cmd = self.calc_pedal_command(actuators.accel, CC.longActive)
+            interceptor_gas_cmd = clip(interceptor_gas_cmd * self.pedal_scale, 0., 1.)
 
         if self.CP.enableGasInterceptor and self.apply_gas > self.params.INACTIVE_REGEN and CS.out.cruiseState.standstill:
           # "Tap" the accelerator pedal to re-engage ACC
@@ -168,7 +238,16 @@ class CarController(CarControllerBase):
         if self.CP.flags & GMFlags.CC_LONG.value:
           if CC.longActive and CS.out.vEgo > self.CP.minEnableSpeed:
             # Using extend instead of append since the message is only sent intermittently
-            can_sends.extend(gmcan.create_gm_cc_spam_command(self.packer_pt, self, CS, actuators))
+            can_sends.extend(gmcan.create_gm_cc_spam_command(self.packer_pt, self, CS, actuators, frogpilot_toggles))
+          elif (CS.out.cruiseState.enabled and CC.enabled and self.frame % 52 == 0 and
+                CS.cruise_buttons == CruiseButtons.UNPRESS and CS.out.gasPressed and CS.out.cruiseState.speed < CS.out.vEgo < hud_v_cruise):
+            if self.CP.carFingerprint == CAR.CHEVROLET_MALIBU_HYBRID_CC:
+              can_sends.append(gmcan.create_buttons_malibu(
+                self.packer_pt, CanBus.POWERTRAIN, CruiseButtons.DECEL_SET,
+                self.malibu_button_phase, CS.steering_button_prefix))
+              self.malibu_button_phase = (self.malibu_button_phase + 1) % 4
+            else:
+              can_sends.append(gmcan.create_buttons(self.packer_pt, CanBus.POWERTRAIN, (CS.buttons_counter + 1) % 4, CruiseButtons.DECEL_SET))
         if self.CP.enableGasInterceptor:
           can_sends.append(create_gas_interceptor_command(self.packer_pt, interceptor_gas_cmd, idx))
         if self.CP.carFingerprint not in CC_ONLY_CAR:
@@ -178,6 +257,8 @@ class CarController(CarControllerBase):
           if self.CP.networkLocation == NetworkLocation.fwdCamera and self.CP.carFingerprint not in CC_ONLY_CAR:
             at_full_stop = at_full_stop and stopping
             friction_brake_bus = CanBus.POWERTRAIN
+            if self.CP.carFingerprint in SDGM_CAR:
+              friction_brake_bus = CanBus.CAMERA
 
           if self.CP.autoResumeSng:
             resume = actuators.longControlState != LongCtrlState.starting or CC.cruiseControl.resume
@@ -203,7 +284,7 @@ class CarController(CarControllerBase):
 
       # Radar needs to know current speed and yaw rate (50hz),
       # and that ADAS is alive (10hz)
-      if not self.CP.radarUnavailable:
+      if not self.CP.radarUnavailable and self.CP.networkLocation != NetworkLocation.fwdCamera and self.CP.carFingerprint not in SDGM_CAR:
         tt = self.frame * DT_CTRL
         time_and_headlights_step = 10
         if self.frame % time_and_headlights_step == 0:
@@ -225,9 +306,17 @@ class CarController(CarControllerBase):
           (self.CP.flags & GMFlags.PEDAL_LONG.value)  # Always cancel stock CC when using pedal interceptor
           or (self.CP.flags & GMFlags.CC_LONG.value and not CC.enabled)  # Cancel stock CC if OP is not active
       ) and CS.out.cruiseState.enabled:
-        if (self.frame - self.last_button_frame) * DT_CTRL > 0.04:
-          self.last_button_frame = self.frame
-          can_sends.append(gmcan.create_buttons(self.packer_pt, CanBus.POWERTRAIN, (CS.buttons_counter + 1) % 4, CruiseButtons.CANCEL))
+        if self.CP.carFingerprint == CAR.CHEVROLET_MALIBU_HYBRID_CC:
+          # Match 33 Hz cadence (every 3 frames) and align phase to the last seen checksum.
+          if self.malibu_cancel_frame % 3 == 0:
+            can_sends.append(gmcan.create_buttons_malibu_cancel(
+              CanBus.POWERTRAIN, self.malibu_cancel_phase, CS.steering_button_prefix))
+            self.malibu_cancel_phase = (self.malibu_cancel_phase + 1) % 4
+          self.malibu_cancel_frame += 1
+        else:
+          if (self.frame - self.last_button_frame) * DT_CTRL > 0.04:
+            self.last_button_frame = self.frame
+            can_sends.append(gmcan.create_buttons(self.packer_pt, CanBus.POWERTRAIN, (CS.buttons_counter + 1) % 4, CruiseButtons.CANCEL))
 
     else:
       # While car is braking, cancel button causes ECM to enter a soft disable state with a fault status.
@@ -235,12 +324,16 @@ class CarController(CarControllerBase):
       self.cancel_counter = self.cancel_counter + 1 if CC.cruiseControl.cancel else 0
 
       # Stock longitudinal, integrated at camera
-      if (self.frame - self.last_button_frame) * DT_CTRL > 0.04:
-        if self.cancel_counter > CAMERA_CANCEL_DELAY_FRAMES:
-          self.last_button_frame = self.frame
-          if self.CP.carFingerprint in SDGM_CAR:
-            can_sends.append(gmcan.create_buttons(self.packer_pt, CanBus.POWERTRAIN, CS.buttons_counter, CruiseButtons.CANCEL))
-          else:
+      if self.cancel_counter > CAMERA_CANCEL_DELAY_FRAMES:
+        if self.CP.carFingerprint == CAR.CHEVROLET_MALIBU_HYBRID_CC:
+          if self.malibu_cancel_frame % 3 == 0:
+            can_sends.append(gmcan.create_buttons_malibu_cancel(
+              CanBus.POWERTRAIN, self.malibu_cancel_phase, CS.steering_button_prefix))
+            self.malibu_cancel_phase = (self.malibu_cancel_phase + 1) % 4
+          self.malibu_cancel_frame += 1
+        else:
+          if (self.frame - self.last_button_frame) * DT_CTRL > 0.04:
+            self.last_button_frame = self.frame
             can_sends.append(gmcan.create_buttons(self.packer_pt, CanBus.CAMERA, CS.buttons_counter, CruiseButtons.CANCEL))
 
     if self.CP.networkLocation == NetworkLocation.fwdCamera:

selfdrive/car/gm/carstate.py

@@ -5,7 +5,7 @@ from openpilot.common.numpy_fast import mean
 from opendbc.can.can_define import CANDefine
 from opendbc.can.parser import CANParser
 from openpilot.selfdrive.car.interfaces import CarStateBase
-from openpilot.selfdrive.car.gm.values import DBC, AccState, CanBus, STEER_THRESHOLD, GMFlags, CC_ONLY_CAR, CAMERA_ACC_CAR, SDGM_CAR
+from openpilot.selfdrive.car.gm.values import DBC, AccState, CanBus, STEER_THRESHOLD, GMFlags, CC_ONLY_CAR, CAMERA_ACC_CAR, SDGM_CAR, ASCM_INT, CAR
 
 TransmissionType = car.CarParams.TransmissionType
 NetworkLocation = car.CarParams.NetworkLocation
@@ -26,6 +26,8 @@ class CarState(CarStateBase):
     self.pt_lka_steering_cmd_counter = 0
     self.cam_lka_steering_cmd_counter = 0
     self.buttons_counter = 0
+    self.steering_button_checksum = 0
+    self.steering_button_prefix = 0x01
 
     self.prev_distance_button = 0
     self.distance_button = 0
@@ -39,14 +41,13 @@ class CarState(CarStateBase):
 
     self.prev_cruise_buttons = self.cruise_buttons
     self.prev_distance_button = self.distance_button
-    if self.CP.carFingerprint not in SDGM_CAR:
-      self.cruise_buttons = pt_cp.vl["ASCMSteeringButton"]["ACCButtons"]
-      self.distance_button = pt_cp.vl["ASCMSteeringButton"]["DistanceButton"]
-      self.buttons_counter = pt_cp.vl["ASCMSteeringButton"]["RollingCounter"]
-    else:
-      self.cruise_buttons = cam_cp.vl["ASCMSteeringButton"]["ACCButtons"]
-      self.distance_button = cam_cp.vl["ASCMSteeringButton"]["DistanceButton"]
-      self.buttons_counter = cam_cp.vl["ASCMSteeringButton"]["RollingCounter"]
+    self.cruise_buttons = pt_cp.vl["ASCMSteeringButton"]["ACCButtons"]
+    self.distance_button = pt_cp.vl["ASCMSteeringButton"]["DistanceButton"]
+    self.buttons_counter = pt_cp.vl["ASCMSteeringButton"]["RollingCounter"]
+    self.steering_button_checksum = pt_cp.vl["ASCMSteeringButton"]["SteeringButtonChecksum"]
+    acc_always_one = pt_cp.vl["ASCMSteeringButton"]["ACCAlwaysOne"]
+    acc_hidden_bit = pt_cp.vl["ASCMSteeringButton"].get("ACCHiddenBit", 0)
+    self.steering_button_prefix = (int(acc_always_one) & 1) | ((int(acc_hidden_bit) & 1) << 6)
     self.pscm_status = copy.copy(pt_cp.vl["PSCMStatus"])
     # This is to avoid a fault where you engage while still moving backwards after shifting to D.
     # An Equinox has been seen with an unsupported status (3), so only check if either wheel is in reverse (2)
@@ -77,26 +78,28 @@ class CarState(CarStateBase):
       ret.gearShifter = self.parse_gear_shifter(self.shifter_values.get(pt_cp.vl["ECMPRDNL2"]["PRNDL2"], None))
 
     if self.CP.flags & GMFlags.NO_ACCELERATOR_POS_MSG.value:
-      ret.brake = pt_cp.vl["EBCMBrakePedalPosition"]["BrakePedalPosition"] / 0xd0
+      ret.brake = pt_cp.vl.get("EBCMBrakePedalPosition", {}).get("BrakePedalPosition", 0) / 0xd0
     else:
-      ret.brake = pt_cp.vl["ECMAcceleratorPos"]["BrakePedalPos"]
-    if self.CP.networkLocation == NetworkLocation.fwdCamera:
+      ret.brake = pt_cp.vl.get("ECMAcceleratorPos", {}).get("BrakePedalPos", 0)
+
+    if (self.CP.flags & GMFlags.FORCE_BRAKE_C9.value) or ((self.CP.networkLocation == NetworkLocation.fwdCamera) and (self.CP.carFingerprint != CAR.CHEVROLET_BLAZER)):
       ret.brakePressed = pt_cp.vl["ECMEngineStatus"]["BrakePressed"] != 0
     else:
       # Some Volt 2016-17 have loose brake pedal push rod retainers which causes the ECM to believe
       # that the brake is being intermittently pressed without user interaction.
       # To avoid a cruise fault we need to use a conservative brake position threshold
       # https://static.nhtsa.gov/odi/tsbs/2017/MC-10137629-9999.pdf
-      ret.brakePressed = ret.brake >= 8
+      analog_thresh = 0.10 if (self.CP.flags & GMFlags.NO_ACCELERATOR_POS_MSG.value) else 8
+      ret.brakePressed = ret.brake >= analog_thresh
 
     # Regen braking is braking
     if self.CP.transmissionType == TransmissionType.direct:
       ret.regenBraking = pt_cp.vl["EBCMRegenPaddle"]["RegenPaddle"] != 0
-      self.single_pedal_mode = ret.gearShifter == GearShifter.low or pt_cp.vl["EVDriveMode"]["SinglePedalModeActive"] == 1 or (ret.regenBraking and GearShifter.manumatic)
+      self.single_pedal_mode = ret.gearShifter == GearShifter.low or pt_cp.vl["EVDriveMode"]["SinglePedalModeActive"] == 1 or (ret.regenBraking and GearShifter.manumatic) or (self.CP.carFingerprint in [CAR.CHEVROLET_BOLT_EUV, CAR.CHEVROLET_BOLT_CC] and self.CP.enableGasInterceptor)
 
     if self.CP.enableGasInterceptor:
       ret.gas = (pt_cp.vl["GAS_SENSOR"]["INTERCEPTOR_GAS"] + pt_cp.vl["GAS_SENSOR"]["INTERCEPTOR_GAS2"]) / 2.
-      threshold = 10 if self.CP.carFingerprint in CAMERA_ACC_CAR else 4 # Panda 515 threshold = 10.88. Set lower to avoid panda blocking messages and GasInterceptor faulting.
+      threshold = 21 if self.CP.carFingerprint in CAMERA_ACC_CAR else 4 # Panda 595 threshold = 23.65. Set lower to avoid panda blocking messages and GasInterceptor faulting.
       ret.gasPressed = ret.gas > threshold
     else:
       ret.gas = pt_cp.vl["AcceleratorPedal2"]["AcceleratorPedal2"] / 254.
@@ -113,32 +116,19 @@ class CarState(CarStateBase):
     ret.steerFaultTemporary = self.lkas_status == 2
     ret.steerFaultPermanent = self.lkas_status == 3
 
-    if self.CP.carFingerprint not in SDGM_CAR:
-      # 1 - open, 0 - closed
-      ret.doorOpen = (pt_cp.vl["BCMDoorBeltStatus"]["FrontLeftDoor"] == 1 or
-                      pt_cp.vl["BCMDoorBeltStatus"]["FrontRightDoor"] == 1 or
-                      pt_cp.vl["BCMDoorBeltStatus"]["RearLeftDoor"] == 1 or
-                      pt_cp.vl["BCMDoorBeltStatus"]["RearRightDoor"] == 1)
 
-      # 1 - latched
-      ret.seatbeltUnlatched = pt_cp.vl["BCMDoorBeltStatus"]["LeftSeatBelt"] == 0
-      ret.leftBlinker = pt_cp.vl["BCMTurnSignals"]["TurnSignals"] == 1
-      ret.rightBlinker = pt_cp.vl["BCMTurnSignals"]["TurnSignals"] == 2
+    # 1 - open, 0 - closed
+    ret.doorOpen = (pt_cp.vl["BCMDoorBeltStatus"]["FrontLeftDoor"] == 1 or
+                    pt_cp.vl["BCMDoorBeltStatus"]["FrontRightDoor"] == 1 or
+                    pt_cp.vl["BCMDoorBeltStatus"]["RearLeftDoor"] == 1 or
+                    pt_cp.vl["BCMDoorBeltStatus"]["RearRightDoor"] == 1)
 
-      ret.parkingBrake = pt_cp.vl["BCMGeneralPlatformStatus"]["ParkBrakeSwActive"] == 1
-    else:
-      # 1 - open, 0 - closed
-      ret.doorOpen = (cam_cp.vl["BCMDoorBeltStatus"]["FrontLeftDoor"] == 1 or
-                      cam_cp.vl["BCMDoorBeltStatus"]["FrontRightDoor"] == 1 or
-                      cam_cp.vl["BCMDoorBeltStatus"]["RearLeftDoor"] == 1 or
-                      cam_cp.vl["BCMDoorBeltStatus"]["RearRightDoor"] == 1)
+    # 1 - latched
+    ret.seatbeltUnlatched = pt_cp.vl["BCMDoorBeltStatus"]["LeftSeatBelt"] == 0
+    ret.leftBlinker = pt_cp.vl["BCMTurnSignals"]["TurnSignals"] == 1
+    ret.rightBlinker = pt_cp.vl["BCMTurnSignals"]["TurnSignals"] == 2
 
-      # 1 - latched
-      ret.seatbeltUnlatched = cam_cp.vl["BCMDoorBeltStatus"]["LeftSeatBelt"] == 0
-      ret.leftBlinker = cam_cp.vl["BCMTurnSignals"]["TurnSignals"] == 1
-      ret.rightBlinker = cam_cp.vl["BCMTurnSignals"]["TurnSignals"] == 2
-
-      ret.parkingBrake = cam_cp.vl["BCMGeneralPlatformStatus"]["ParkBrakeSwActive"] == 1
+    ret.parkingBrake = pt_cp.vl["BCMGeneralPlatformStatus"]["ParkBrakeSwActive"] == 1
     ret.cruiseState.available = pt_cp.vl["ECMEngineStatus"]["CruiseMainOn"] != 0
     ret.espDisabled = pt_cp.vl["ESPStatus"]["TractionControlOn"] != 1
     ret.accFaulted = (pt_cp.vl["AcceleratorPedal2"]["CruiseState"] == AccState.FAULTED or
@@ -149,12 +139,11 @@ class CarState(CarStateBase):
     if self.CP.networkLocation == NetworkLocation.fwdCamera and not self.CP.flags & GMFlags.NO_CAMERA.value:
       if self.CP.carFingerprint not in CC_ONLY_CAR:
         ret.cruiseState.speed = cam_cp.vl["ASCMActiveCruiseControlStatus"]["ACCSpeedSetpoint"] * CV.KPH_TO_MS
-      if self.CP.carFingerprint not in SDGM_CAR:
+      if self.CP.carFingerprint not in (SDGM_CAR|ASCM_INT):
         ret.stockAeb = cam_cp.vl["AEBCmd"]["AEBCmdActive"] != 0
-      else:
-        ret.stockAeb = False
       # openpilot controls nonAdaptive when not pcmCruise
-      if self.CP.pcmCruise:
+      # 2016-2018 Volt won't identify non-adaptive cruise state since switchable cruise state was not introduced till 2019 model year / SDGM Global AAdd commentMore actions
+      if self.CP.pcmCruise and self.CP.carFingerprint not in ASCM_INT:
         ret.cruiseState.nonAdaptive = cam_cp.vl["ASCMActiveCruiseControlStatus"]["ACCCruiseState"] not in (2, 3)
     if self.CP.carFingerprint in CC_ONLY_CAR:
       ret.accFaulted = False
@@ -162,19 +151,11 @@ class CarState(CarStateBase):
       ret.cruiseState.enabled = pt_cp.vl["ECMCruiseControl"]["CruiseActive"] != 0
 
     if self.CP.enableBsm:
-      if self.CP.carFingerprint not in SDGM_CAR:
-        ret.leftBlindspot = pt_cp.vl["BCMBlindSpotMonitor"]["LeftBSM"] == 1
-        ret.rightBlindspot = pt_cp.vl["BCMBlindSpotMonitor"]["RightBSM"] == 1
-      else:
-        ret.leftBlindspot = cam_cp.vl["BCMBlindSpotMonitor"]["LeftBSM"] == 1
-        ret.rightBlindspot = cam_cp.vl["BCMBlindSpotMonitor"]["RightBSM"] == 1
+      ret.leftBlindspot = pt_cp.vl["BCMBlindSpotMonitor"]["LeftBSM"] == 1
+      ret.rightBlindspot = pt_cp.vl["BCMBlindSpotMonitor"]["RightBSM"] == 1
 
-    # FrogPilot CarState functions
     self.lkas_previously_enabled = self.lkas_enabled
-    if self.CP.carFingerprint in SDGM_CAR:
-      self.lkas_enabled = cam_cp.vl["ASCMSteeringButton"]["LKAButton"]
-    else:
-      self.lkas_enabled = pt_cp.vl["ASCMSteeringButton"]["LKAButton"]
+    self.lkas_enabled = pt_cp.vl["ASCMSteeringButton"]["LKAButton"]
 
     self.pcm_acc_status = pt_cp.vl["AcceleratorPedal2"]["CruiseState"]
 
@@ -189,16 +170,7 @@ class CarState(CarStateBase):
       messages += [
         ("ASCMLKASteeringCmd", 10),
       ]
-      if CP.carFingerprint in SDGM_CAR:
-        messages += [
-          ("BCMTurnSignals", 1),
-          ("BCMDoorBeltStatus", 10),
-          ("BCMGeneralPlatformStatus", 10),
-          ("ASCMSteeringButton", 33),
-        ]
-        if CP.enableBsm:
-          messages.append(("BCMBlindSpotMonitor", 10))
-      else:
+      if CP.carFingerprint not in (SDGM_CAR|ASCM_INT):
         messages += [
           ("AEBCmd", 10),
         ]
@@ -212,34 +184,25 @@ class CarState(CarStateBase):
   @staticmethod
   def get_can_parser(CP, FPCP):
     messages = [
+      ("BCMTurnSignals", 1),
+      ("ECMPRDNL2", 10),
       ("PSCMStatus", 10),
       ("ESPStatus", 10),
+      ("BCMDoorBeltStatus", 10),
+      ("BCMGeneralPlatformStatus", 10),
       ("EBCMWheelSpdFront", 20),
       ("EBCMWheelSpdRear", 20),
       ("EBCMFrictionBrakeStatus", 20),
+      ("AcceleratorPedal2", 33),
+      ("ASCMSteeringButton", 33),
+      ("ECMEngineStatus", 100),
       ("PSCMSteeringAngle", 100),
       ("ECMAcceleratorPos", 80),
       ("SportMode", 0),
     ]
 
-    if CP.carFingerprint in SDGM_CAR:
-      messages += [
-        ("ECMPRDNL2", 40),
-        ("AcceleratorPedal2", 40),
-        ("ECMEngineStatus", 80),
-      ]
-    else:
-      messages += [
-        ("ECMPRDNL2", 10),
-        ("AcceleratorPedal2", 33),
-        ("ECMEngineStatus", 100),
-        ("BCMTurnSignals", 1),
-        ("BCMDoorBeltStatus", 10),
-        ("BCMGeneralPlatformStatus", 10),
-        ("ASCMSteeringButton", 33),
-      ]
-      if CP.enableBsm:
-        messages.append(("BCMBlindSpotMonitor", 10))
+    if CP.enableBsm:
+      messages.append(("BCMBlindSpotMonitor", 10))
 
     # Used to read back last counter sent to PT by camera
     if CP.networkLocation == NetworkLocation.fwdCamera:
@@ -266,6 +229,7 @@ class CarState(CarStateBase):
         ("GAS_SENSOR", 50),
       ]
 
+
     return CANParser(DBC[CP.carFingerprint]["pt"], messages, CanBus.POWERTRAIN)
 
   @staticmethod

selfdrive/car/gm/fingerprints.py

@@ -26,6 +26,20 @@ FINGERPRINTS = {
   {
     170: 8, 171: 8, 189: 7, 190: 6, 193: 8, 197: 8, 199: 4, 201: 8, 209: 7, 211: 2, 241: 6, 288: 5, 298: 8, 304: 1, 308: 4, 309: 8, 311: 8, 313: 8, 320: 3, 328: 1, 352: 5, 381: 6, 384: 4, 386: 8, 388: 8, 389: 2, 390: 7, 417: 7, 419: 1, 426: 7, 451: 8, 452: 8, 453: 6, 454: 8, 456: 8, 479: 3, 481: 7, 485: 8, 489: 8, 493: 8, 495: 4, 497: 8, 499: 3, 500: 6, 501: 8, 508: 8, 528: 4, 532: 6, 546: 7, 550: 8, 554: 3, 558: 8, 560: 8, 562: 8, 563: 5, 564: 5, 565: 5, 566: 5, 567: 3, 568: 1, 573: 1, 577: 8, 608: 8, 609: 6, 610: 6, 611: 6, 612: 8, 613: 8, 647: 3, 707: 8, 711: 6, 717: 5, 761: 7, 800: 6, 810: 8, 840: 5, 842: 5, 844: 8, 866: 4, 869: 4, 961: 8, 967: 4, 969: 8, 977: 8, 979: 7, 988: 6, 989: 8, 995: 7, 1001: 8, 1005: 6, 1009: 8, 1017: 8, 1019: 2, 1020: 8, 1033: 7, 1034: 7, 1105: 6, 1187: 4, 1217: 8, 1221: 5, 1223: 3, 1225: 7, 1227: 4, 1233: 8, 1249: 8, 1257: 6, 1265: 8, 1267: 1, 1273: 3, 1275: 3, 1280: 4, 1300: 8, 1322: 6, 1323: 4, 1328: 4, 1417: 8, 1601: 8, 1905: 7, 1906: 7, 1907: 7, 1910: 7, 1912: 7, 1922: 7, 1927: 7, 1930: 7, 2017: 8, 2020: 8, 2025: 8, 2028: 8
   }],
+  CAR.CHEVROLET_VOLT_ASCM: [
+  # Causes errors with normal OBD install
+  #   {
+  #   189: 7, 193: 8, 197: 8, 201: 8, 209: 7, 211: 2, 241: 6, 288: 5, 298: 8, 304: 1, 308: 4, 309: 8, 311: 8, 313: 8, 320: 3, 328: 1, 352: 5, 381: 6, 384: 4, 386: 8, 388: 8, 451: 8, 452: 8, 453: 6, 479: 3, 481: 7, 485: 8, 489: 8, 493: 8, 497: 8, 500: 6, 501: 8, 528: 4, 532: 6, 560: 8, 562: 8, 563: 5, 565: 5, 566: 5, 608: 8, 609: 6, 610: 6, 611: 6, 612: 8, 613: 8, 707: 8, 715: 8, 717: 5, 761: 7, 767: 4, 810: 8, 840: 5, 842: 5, 844: 8, 869: 4, 880: 6, 977: 8, 1001: 8, 1017: 8, 1020: 8, 1033: 7, 1034: 7, 1217: 8, 1221: 5, 1233: 8, 1249: 8, 1265: 8, 1267: 1, 1280: 4, 1296: 4, 1300: 8, 1922: 7, 1930: 7
+  # }
+  ],
+  CAR.CHEVROLET_VOLT_CAMERA: [
+  # Volt Premier 2017 w/ flashed firmware, cam harness + pedal (no 0x170/0x171 on PT bus)
+  {
+  #  189: 7, 193: 8, 197: 8, 201: 8, 209: 7, 211: 2, 241: 6, 298: 8, 304: 1, 308: 4, 309: 8, 311: 8, 313: 8, 320: 3, 328: 1, 352: 5, 381: 6, 386: 8, 388: 8, 451: 8, 452: 8, 453: 6, 479: 3, 481: 7, 485: 8, 489: 8, 493: 8, 497: 8, 500: 6, 501: 8, 513: 6, 528: 4, 532: 6, 560: 8, 562: 8, 563: 5, 565: 5, 566: 5, 608: 8, 609: 6, 610: 6, 611: 6, 612: 8, 613: 8, 707: 8, 761: 7, 810: 8, 840: 5, 842: 5, 844: 8, 977: 8, 1001: 8, 1017: 8, 1020: 8, 1217: 8, 1221: 5, 1233: 8, 1249: 8, 1265: 8, 1267: 1, 1280: 4, 1300: 8, 1922: 7
+  }],
+  CAR.GMC_ACADIA_ASCM: [
+  # Causes errors with normal OBD install
+  ],
   CAR.BUICK_LACROSSE: [{
     190: 6, 193: 8, 197: 8, 199: 4, 201: 8, 209: 7, 211: 2, 241: 6, 249: 8, 288: 5, 298: 8, 304: 1, 309: 8, 311: 8, 313: 8, 320: 3, 322: 7, 328: 1, 352: 5, 353: 3, 381: 6, 386: 8, 388: 8, 393: 7, 398: 8, 407: 7, 413: 8, 417: 7, 419: 1, 422: 4, 426: 7, 431: 8, 442: 8, 451: 8, 452: 8, 453: 6, 455: 7, 456: 8, 463: 3, 479: 3, 481: 7, 485: 8, 487: 8, 489: 8, 495: 4, 497: 8, 499: 3, 500: 6, 501: 8, 503: 1, 508: 8, 510: 8, 528: 5, 532: 6, 534: 2, 554: 3, 560: 8, 562: 8, 563: 5, 564: 5, 565: 5, 567: 5, 573: 1, 608: 8, 609: 6, 610: 6, 611: 6, 612: 8, 613: 8, 647: 5, 707: 8, 753: 5, 761: 7, 801: 8, 804: 3, 810: 8, 840: 5, 842: 5, 844: 8, 866: 4, 872: 1, 882: 8, 890: 1, 892: 2, 893: 1, 894: 1, 961: 8, 967: 4, 969: 8, 977: 8, 979: 8, 985: 5, 1001: 8, 1005: 6, 1009: 8, 1011: 6, 1013: 3, 1017: 8, 1019: 2, 1020: 8, 1022: 1, 1105: 6, 1217: 8, 1221: 5, 1223: 2, 1225: 7, 1233: 8, 1243: 3, 1249: 8, 1257: 6, 1259: 8, 1261: 7, 1263: 4, 1265: 8, 1267: 1, 1280: 4, 1300: 8, 1322: 6, 1328: 4, 1417: 8, 1609: 8, 1613: 8, 1649: 8, 1792: 8, 1798: 8, 1824: 8, 1825: 8, 1840: 8, 1842: 8, 1858: 8, 1860: 8, 1863: 8, 1872: 8, 1875: 8, 1882: 8, 1888: 8, 1889: 8, 1892: 8, 1904: 7, 1906: 7, 1907: 7, 1912: 7, 1913: 7, 1914: 7, 1916: 7, 1918: 7, 1919: 7, 1937: 8, 1953: 8, 1968: 8, 2001: 8, 2017: 8, 2018: 8, 2020: 8, 2026: 8
   }],
@@ -52,6 +66,9 @@ FINGERPRINTS = {
   CAR.CHEVROLET_MALIBU: [{
     190: 6, 193: 8, 197: 8, 199: 4, 201: 8, 209: 7, 211: 2, 241: 6, 249: 8, 288: 5, 298: 8, 304: 1, 309: 8, 311: 8, 313: 8, 320: 3, 328: 1, 352: 5, 381: 6, 384: 4, 386: 8, 388: 8, 393: 7, 398: 8, 407: 7, 413: 8, 417: 7, 419: 1, 422: 4, 426: 7, 431: 8, 442: 8, 451: 8, 452: 8, 453: 6, 455: 7, 456: 8, 479: 3, 481: 7, 485: 8, 487: 8, 489: 8, 495: 4, 497: 8, 499: 3, 500: 6, 501: 8, 508: 8, 510: 8, 528: 5, 532: 6, 554: 3, 560: 8, 562: 8, 563: 5, 564: 5, 565: 5, 567: 5, 573: 1, 577: 8, 608: 8, 609: 6, 610: 6, 611: 6, 612: 8, 613: 8, 647: 6, 707: 8, 715: 8, 717: 5, 753: 5, 761: 7, 810: 8, 840: 5, 842: 5, 844: 8, 866: 4, 869: 4, 880: 6, 961: 8, 969: 8, 977: 8, 979: 8, 985: 5, 1001: 8, 1005: 6, 1009: 8, 1013: 3, 1017: 8, 1019: 2, 1020: 8, 1033: 7, 1034: 7, 1105: 6, 1217: 8, 1221: 5, 1223: 2, 1225: 7, 1233: 8, 1249: 8, 1257: 6, 1265: 8, 1267: 1, 1280: 4, 1296: 4, 1300: 8, 1322: 6, 1323: 4, 1328: 4, 1417: 8, 1601: 8, 1906: 7, 1907: 7, 1912: 7, 1919: 7, 1930: 7, 2016: 8, 2024: 8
   }],
+  CAR.CHEVROLET_MALIBU_ASCM: [{
+    190: 6, 193: 8, 197: 8, 199: 4, 201: 8, 209: 7, 211: 2, 241: 6, 249: 8, 288: 5, 298: 8, 304: 1, 309: 8, 311: 8, 313: 8, 320: 3, 328: 1, 352: 5, 381: 6, 384: 4, 386: 8, 388: 8, 393: 7, 398: 8, 407: 7, 413: 8, 417: 7, 419: 1, 422: 4, 426: 7, 431: 8, 442: 8, 451: 8, 452: 8, 453: 6, 455: 7, 456: 8, 479: 3, 481: 7, 485: 8, 487: 8, 489: 8, 495: 4, 497: 8, 499: 3, 500: 6, 501: 8, 508: 8, 510: 8, 528: 5, 532: 6, 554: 3, 560: 8, 562: 8, 563: 5, 564: 5, 565: 5, 567: 5, 573: 1, 577: 8, 608: 8, 609: 6, 610: 6, 611: 6, 612: 8, 613: 8, 647: 6, 707: 8, 715: 8, 717: 5, 753: 5, 761: 7, 810: 8, 840: 5, 842: 5, 844: 8, 866: 4, 869: 4, 880: 6, 961: 8, 969: 8, 977: 8, 979: 8, 985: 5, 1001: 8, 1005: 6, 1009: 8, 1013: 3, 1017: 8, 1019: 2, 1020: 8, 1033: 7, 1034: 7, 1105: 6, 1217: 8, 1221: 5, 1223: 2, 1225: 7, 1233: 8, 1249: 8, 1257: 6, 1265: 8, 1267: 1, 1280: 4, 1296: 4, 1300: 8, 1322: 6, 1323: 4, 1328: 4, 1417: 8, 1601: 8, 1906: 7, 1907: 7, 1912: 7, 1919: 7, 1930: 7, 2016: 8, 2024: 8
+  }],
   CAR.GMC_ACADIA: [{
     190: 6, 192: 5, 193: 8, 197: 8, 199: 4, 201: 6, 208: 8, 209: 7, 211: 2, 241: 6, 249: 8, 288: 5, 289: 1, 290: 1, 298: 8, 304: 8, 309: 8, 313: 8, 320: 8, 322: 7, 328: 1, 352: 7, 368: 8, 381: 8, 384: 8, 386: 8, 388: 8, 393: 8, 398: 8, 413: 8, 417: 7, 419: 1, 422: 4, 426: 7, 431: 8, 442: 8, 451: 8, 452: 8, 453: 6, 454: 8, 455: 7, 458: 8, 460: 4, 462: 4, 463: 3, 479: 3, 481: 7, 485: 8, 489: 5, 497: 8, 499: 3, 500: 6, 501: 8, 508: 8, 510: 8, 512: 3, 530: 8, 532: 6, 534: 2, 554: 3, 560: 8, 562: 8, 563: 5, 564: 5, 567: 5, 568: 2, 573: 1, 608: 8, 609: 6, 610: 6, 611: 6, 612: 8, 613: 8, 647: 6, 707: 8, 715: 8, 717: 5, 753: 5, 761: 7, 789: 5, 800: 6, 801: 8, 803: 8, 804: 3, 805: 8, 832: 8, 840: 5, 842: 5, 844: 8, 866: 4, 869: 4, 880: 6, 961: 8, 969: 8, 977: 8, 979: 8, 985: 5, 1001: 8, 1003: 5, 1005: 6, 1009: 8, 1017: 8, 1020: 8, 1033: 7, 1034: 7, 1105: 6, 1217: 8, 1221: 5, 1225: 8, 1233: 8, 1249: 8, 1257: 6, 1265: 8, 1267: 1, 1280: 4, 1296: 4, 1300: 8, 1322: 6, 1328: 4, 1417: 8, 1906: 7, 1907: 7, 1912: 7, 1914: 7, 1918: 7, 1919: 7, 1920: 7, 1930: 7
   },
@@ -178,31 +195,50 @@ FINGERPRINTS = {
   CAR.CADILLAC_XT4: [
   # Cadillac XT4 w/ ACC 2023
   {
-    190: 6, 193: 8, 197: 8, 199: 4, 201: 8, 209: 7, 211: 2, 241: 6, 249: 8, 257: 8, 288: 5, 289: 8, 292: 2, 298: 8, 304: 3, 309: 8, 313: 8, 320: 4, 322: 7, 328: 1, 331: 3, 352: 5, 353: 3, 368: 3, 381: 8, 384: 4, 386: 8, 388: 8, 393: 7, 398: 8, 401: 8, 407: 7, 413: 8, 417: 7, 419: 1, 422: 4, 426: 7, 431: 8, 442: 8, 451: 8, 452: 8, 453: 6, 455: 7, 479: 3, 481: 7, 485: 8, 489: 8, 497: 8, 499: 3, 500: 6, 501: 8, 503: 2, 508: 8, 532: 6, 554: 3, 560: 8, 562: 8, 563: 5, 564: 5, 565: 5, 567: 5, 573: 1, 577: 8, 608: 8, 609: 6, 610: 6, 611: 6, 612: 8, 613: 8, 647: 6, 707: 8, 715: 8, 717: 5, 719: 5, 761: 7, 806: 1, 840: 5, 842: 5, 844: 8, 866: 4, 869: 4, 872: 1, 880: 6, 961: 8, 969: 8, 975: 2, 977: 8, 979: 8, 985: 5, 1001: 8, 1005: 6, 1009: 8, 1011: 6, 1013: 5, 1017: 8, 1020: 8, 1033: 7, 1034: 7, 1037: 5, 1105: 5, 1187: 5, 1195: 3, 1217: 8, 1221: 5, 1223: 2, 1225: 7, 1233: 8, 1236: 8, 1249: 8, 1257: 6, 1259: 8, 1261: 7, 1263: 4, 1265: 8, 1267: 1, 1268: 2, 1271: 8, 1273: 3, 1276: 2, 1277: 7, 1278: 4, 1279: 4, 1280: 4, 1296: 4, 1300: 8, 1322: 6, 1323: 4, 1328: 4, 1345: 8, 1417: 8, 1512: 8, 1517: 8, 1601: 8, 1609: 8, 1613: 8, 1649: 8, 1792: 8, 1793: 8, 1798: 8, 1824: 8, 1825: 8, 1840: 8, 1842: 8, 1858: 8, 1860: 8, 1863: 8, 1872: 8, 1875: 8, 1882: 8, 1888: 8, 1889: 8, 1892: 8, 1906: 7, 1907: 7, 1912: 7, 1919: 7, 1920: 8, 1924: 8, 1930: 7, 1937: 8, 1953: 8, 1968: 8, 1969: 8, 1971: 8, 1975: 8, 1984: 8, 1988: 8, 2000: 8, 2001: 8, 2002: 8, 2016: 8, 2017: 8, 2018: 8, 2020: 8, 2021: 8, 2024: 8, 2026: 8
-  }],
+    190: 6, 193: 8, 197: 8, 199: 4, 201: 8, 209: 7, 211: 2, 241: 6, 249: 8, 257: 8, 288: 5, 289: 8, 292: 2, 298: 8, 304: 3, 309: 8, 313: 8, 320: 4, 322: 7, 328: 1, 331: 3, 352: 5, 353: 3, 368: 3, 381: 8, 384: 4, 386: 8, 388: 8, 393: 7, 398: 8, 401: 8, 407: 7, 413: 8, 417: 7, 419: 1, 422: 4, 426: 7, 431: 8, 442: 8, 451: 8, 452: 8, 453: 6, 455: 7, 479: 3, 481: 7, 485: 8, 489: 8, 497: 8, 499: 3, 500: 6, 501: 8, 503: 2, 508: 8, 532: 6, 554: 3, 560: 8, 562: 8, 563: 5, 564: 5, 565: 5, 567: 5, 573: 1, 577: 8, 608: 8, 609: 6, 610: 6, 611: 6, 612: 8, 613: 8, 647: 6, 707: 8, 715: 8, 717: 5, 719: 5, 761: 7, 767: 4, 806: 1, 840: 5, 842: 5, 844: 8, 866: 4, 869: 4, 872: 1, 880: 6, 961: 8, 969: 8, 975: 2, 977: 8, 979: 8, 985: 5, 1001: 8, 1005: 6, 1009: 8, 1011: 6, 1013: 5, 1017: 8, 1020: 8, 1033: 7, 1034: 7, 1037: 5, 1105: 5, 1187: 5, 1195: 3, 1217: 8, 1221: 5, 1223: 2, 1225: 7, 1233: 8, 1236: 8, 1249: 8, 1257: 6, 1259: 8, 1261: 7, 1263: 4, 1265: 8, 1267: 1, 1268: 2, 1271: 8, 1273: 3, 1276: 2, 1277: 7, 1278: 4, 1279: 4, 1280: 4, 1296: 4, 1300: 8, 1322: 6, 1323: 4, 1328: 4, 1345: 8, 1417: 8, 1512: 8, 1517: 8, 1601: 8, 1609: 8, 1613: 8, 1649: 8, 1792: 8, 1793: 8, 1798: 8, 1824: 8, 1825: 8, 1840: 8, 1842: 8, 1858: 8, 1860: 8, 1863: 8, 1872: 8, 1875: 8, 1882: 8, 1888: 8, 1889: 8, 1892: 8, 1906: 7, 1907: 7, 1912: 7, 1919: 7, 1920: 8, 1924: 8, 1930: 7, 1937: 8, 1953: 8, 1968: 8, 1969: 8, 1971: 8, 1975: 8, 1984: 8, 1988: 8, 2000: 8, 2001: 8, 2002: 8, 2016: 8, 2017: 8, 2018: 8, 2020: 8, 2021: 8, 2024: 8, 2026: 8  }],
   CAR.CADILLAC_XT5_CC: [
   # TRain's 2017 XT5
   {
     190: 6, 193: 8, 197: 8, 199: 4, 201: 8, 208: 8, 209: 7, 211: 2, 241: 6, 249: 8, 288: 5, 298: 8, 304: 1, 309: 8, 313: 8, 320: 3, 322: 7, 328: 1, 352: 5, 353: 3, 381: 6, 384: 4, 386: 8, 388: 8, 393: 7, 398: 8, 407: 7, 413: 8, 417: 7, 419: 1, 422: 4, 426: 7, 431: 8, 442: 8, 451: 8, 452: 8, 453: 6, 454: 8, 455: 7, 462: 4, 463: 3, 479: 3, 481: 7, 485: 8, 487: 8, 489: 8, 495: 4, 497: 8, 499: 3, 500: 6, 501: 8, 503: 1, 508: 8, 510: 8, 532: 6, 554: 3, 560: 8, 562: 8, 563: 5, 564: 5, 567: 5, 647: 3, 707: 8, 717: 5, 723: 2, 753: 5, 761: 7, 800: 6, 840: 5, 842: 5, 844: 8, 866: 4, 869: 4, 872: 1, 961: 8, 967: 4, 969: 8, 977: 8, 979: 8, 985: 5, 1001: 8, 1005: 6, 1009: 8, 1011: 6, 1013: 3, 1017: 8, 1019: 2, 1020: 8, 1022: 1, 1105: 6, 1217: 8, 1221: 5, 1223: 3, 1225: 7, 1233: 8, 1243: 3, 1249: 8, 1257: 6, 1259: 8, 1261: 7, 1263: 4, 1265: 8, 1267: 1, 1280: 4, 1300: 8, 1322: 6, 1328: 4, 1417: 8, 1904: 7, 1906: 7, 1907: 7, 1912: 7, 1913: 7, 1914: 7, 1919: 7, 1920: 7
   }],
+  CAR.CADILLAC_XT6: [
+  #{}
+  ],
+  CAR.CHEVROLET_BLAZER: [{
+    190: 6, 193: 8, 197: 8, 201: 8, 208: 8, 209: 7, 211: 2, 241: 6, 249: 8, 289: 8, 298: 8, 304: 3, 309: 8, 313: 8, 322: 7, 352: 5, 381: 8, 384: 4, 386: 8, 388: 8, 413: 8, 451: 8, 452: 8, 453: 6, 455: 7, 479: 3, 481: 7, 485: 8, 489: 8, 497: 8, 500: 6, 501: 8, 510: 8, 532: 6, 560: 8, 562: 8, 608: 8, 609: 6, 610: 6, 611: 6, 612: 8, 613: 8, 707: 8, 715: 8, 717: 5, 753: 5, 761: 7, 767: 4, 840: 5, 842: 5, 844: 8, 869: 4, 880: 6, 977: 8, 1001: 8, 1011: 6, 1017: 8, 1020: 8, 1033: 7, 1034: 7, 1217: 8, 1233: 8, 1249: 8, 1259: 8, 1261: 7, 1263: 4, 1265: 8, 1296: 4
+  }],
   CAR.CHEVROLET_TRAVERSE: [
   # Chevy Traverse w/ ACC 2023
   {
-    190: 6, 193: 8, 197: 8, 199: 4, 201: 8, 208: 8, 209: 7, 211: 2, 241: 6, 249: 8, 257: 8, 288: 5, 289: 8, 292: 2, 298: 8, 304: 3, 309: 8, 313: 8, 320: 4, 322: 7, 328: 1, 331: 3, 352: 5, 368: 3, 381: 8, 384: 4, 386: 8, 388: 8, 393: 7, 398: 8, 401: 8, 407: 7, 413: 8, 417: 7, 419: 1, 422: 4, 426: 7, 431: 8, 442: 8, 451: 8, 452: 8, 453: 6, 454: 8, 455: 7, 479: 3, 481: 7, 485: 8, 489: 8, 497: 8, 499: 3, 500: 6, 501: 8, 508: 8, 510: 8, 532: 6, 554: 3, 560: 8, 562: 8, 563: 5, 564: 5, 567: 5, 573: 1, 577: 8, 578: 8, 579: 8, 587: 8, 603: 8, 608: 8, 609: 6, 610: 6, 611: 6, 612: 8, 613: 8, 647: 6, 707: 8, 715: 8, 717: 5, 723: 4, 730: 4, 753: 5, 761: 7, 840: 5, 842: 5, 844: 8, 866: 4, 869: 4, 880: 6, 961: 8, 969: 8, 975: 2, 977: 8, 979: 8, 985: 5, 1001: 8, 1005: 6, 1009: 8, 1011: 6, 1013: 5, 1017: 8, 1020: 8, 1033: 7, 1034: 7, 1105: 5, 1217: 8, 1221: 5, 1223: 3, 1225: 7, 1233: 8, 1236: 8, 1249: 8, 1257: 6, 1259: 8, 1261: 7, 1263: 4, 1265: 8, 1267: 1, 1268: 2, 1271: 8, 1279: 4, 1280: 4, 1296: 4, 1300: 8, 1322: 6, 1323: 4, 1328: 4, 1345: 8, 1346: 8, 1347: 8, 1355: 8, 1362: 8, 1417: 8, 1512: 8, 1514: 8, 1601: 8, 1602: 8, 1603: 7, 1609: 8, 1611: 8, 1613: 8, 1618: 8, 1649: 8, 1792: 8, 1793: 8, 1798: 8, 1799: 8, 1810: 8, 1813: 8, 1824: 8, 1825: 8, 1840: 8, 1842: 8, 1856: 8, 1858: 8, 1859: 8, 1860: 8, 1862: 8, 1863: 8, 1871: 8, 1872: 8, 1875: 8, 1879: 8, 1882: 8, 1888: 8, 1889: 8, 1892: 8, 1906: 7, 1907: 7, 1912: 7, 1919: 7, 1920: 7, 1927: 8, 1930: 7, 1937: 8, 1953: 8, 1954: 8, 1955: 8, 1968: 8, 1969: 8, 1971: 8, 1975: 8, 1988: 8, 1990: 8, 2000: 8, 2001: 8, 2004: 8, 2016: 8, 2017: 8, 2018: 8, 2019: 8, 2020: 8, 2024: 8, 2026: 8
+    190: 6, 193: 8, 197: 8, 199: 4, 201: 8, 208: 8, 209: 7, 211: 2, 241: 6, 249: 8, 257: 8, 288: 5, 289: 8, 292: 2, 298: 8, 304: 3, 309: 8, 313: 8, 320: 4, 322: 7, 328: 1, 331: 3, 352: 5, 368: 3, 381: 8, 384: 4, 386: 8, 388: 8, 393: 7, 398: 8, 401: 8, 407: 7, 413: 8, 417: 7, 419: 1, 422: 4, 426: 7, 431: 8, 442: 8, 451: 8, 452: 8, 453: 6, 454: 8, 455: 7, 479: 3, 481: 7, 485: 8, 489: 8, 497: 8, 499: 3, 500: 6, 501: 8, 508: 8, 510: 8, 532: 6, 554: 3, 560: 8, 562: 8, 563: 5, 564: 5, 567: 5, 573: 1, 577: 8, 578: 8, 579: 8, 587: 8, 603: 8, 608: 8, 609: 6, 610: 6, 611: 6, 612: 8, 613: 8, 647: 6, 707: 8, 715: 8, 717: 5, 723: 4, 730: 4, 753: 5, 761: 7, 767: 4, 840: 5, 842: 5, 844: 8, 866: 4, 869: 4, 880: 6, 961: 8, 969: 8, 975: 2, 977: 8, 979: 8, 985: 5, 1001: 8, 1005: 6, 1009: 8, 1011: 6, 1013: 5, 1017: 8, 1020: 8, 1033: 7, 1034: 7, 1105: 5, 1217: 8, 1221: 5, 1223: 3, 1225: 7, 1233: 8, 1236: 8, 1249: 8, 1257: 6, 1259: 8, 1261: 7, 1263: 4, 1265: 8, 1267: 1, 1268: 2, 1271: 8, 1279: 4, 1280: 4, 1296: 4, 1300: 8, 1322: 6, 1323: 4, 1328: 4, 1345: 8, 1346: 8, 1347: 8, 1355: 8, 1362: 8, 1417: 8, 1512: 8, 1514: 8, 1601: 8, 1602: 8, 1603: 7, 1609: 8, 1611: 8, 1613: 8, 1618: 8, 1649: 8, 1792: 8, 1793: 8, 1798: 8, 1799: 8, 1810: 8, 1813: 8, 1824: 8, 1825: 8, 1840: 8, 1842: 8, 1856: 8, 1858: 8, 1859: 8, 1860: 8, 1862: 8, 1863: 8, 1871: 8, 1872: 8, 1875: 8, 1879: 8, 1882: 8, 1888: 8, 1889: 8, 1892: 8, 1906: 7, 1907: 7, 1912: 7, 1919: 7, 1920: 7, 1927: 8, 1930: 7, 1937: 8, 1953: 8, 1954: 8, 1955: 8, 1968: 8, 1969: 8, 1971: 8, 1975: 8, 1988: 8, 1990: 8, 2000: 8, 2001: 8, 2004: 8, 2016: 8, 2017: 8, 2018: 8, 2019: 8, 2020: 8, 2024: 8, 2026: 8
+  }],
+  CAR.CHEVROLET_MALIBU_SDGM: [
+  # Chevy Malibu w/ SDGM Harness 2019
+  {
+    190: 6, 193: 8, 197: 8, 201: 8, 209: 7, 211: 2, 241: 6, 249: 8, 257: 5, 288: 5, 289: 8, 298: 8, 304: 1, 309: 8, 311: 8, 313: 8, 320: 3, 328: 1, 352: 5, 381: 8, 384: 4, 386: 8, 388: 8, 413: 8, 451: 8, 452: 8, 453: 6, 455: 7, 479: 3, 481: 7, 485: 8, 489: 8, 497: 8, 500: 6, 501: 8, 532: 6, 560: 8, 562: 8, 563: 5, 565: 5, 587: 8, 707: 8, 715: 8, 717: 5, 761: 7, 767: 4, 810: 8, 840: 5, 842: 5, 844: 8, 869: 4, 880: 6, 882: 8, 890: 1, 892: 2, 893: 2, 894: 1, 977: 8, 1001: 8, 1011: 6, 1017: 8, 1020: 8, 1217: 8, 1221: 5, 1233: 8, 1249: 8, 1259: 8, 1261: 7, 1263: 4, 1265: 8, 1267: 1, 1271: 8, 1280: 4, 1296: 4, 1300: 8, 1353: 8, 1355: 8, 1611: 8, 1792: 8, 1793: 8, 1798: 8, 1799: 8, 1810: 8, 1813: 8, 1824: 8, 1825: 8, 1840: 8, 1842: 8, 1843: 8, 1856: 8, 1858: 8, 1859: 8, 1860: 8, 1862: 8, 1863: 8, 1871: 8, 1872: 8, 1875: 8, 1879: 8, 1882: 8, 1888: 8, 1889: 8, 1892: 8, 1916: 7, 1920: 8, 1927: 8, 1930: 7, 1937: 8, 1953: 8, 1954: 8, 1955: 8, 1968: 8, 1969: 8, 1971: 8, 1975: 8, 1988: 8, 1990: 8, 2000: 8, 2001: 8, 2002: 8, 2004: 8, 2017: 8, 2018: 8, 2020: 8
   }],
   CAR.BUICK_BABYENCLAVE: [
   # Buick Baby Enclave w/ ACC 2020-23
   {
-    190: 6, 193: 8, 197: 8, 199: 4, 201: 8, 208: 8, 209: 7, 211: 2, 241: 6, 249: 8, 257: 8, 288: 5, 289: 8, 292: 2, 298: 8, 304: 3, 309: 8, 311: 8, 313: 8, 320: 4, 322: 7, 328: 1, 331: 3, 352: 5, 353: 3, 368: 3, 381: 8, 384: 4, 386: 8, 388: 8, 394: 7, 398: 8, 401: 8, 405: 8, 407: 7, 413: 8, 417: 7, 419: 1, 422: 4, 426: 7, 431: 8, 442: 8, 450: 4, 451: 8, 452: 8, 453: 6, 454: 8, 455: 7, 456: 8, 457: 6, 462: 4, 463: 3, 479: 3, 481: 7, 485: 8, 489: 8, 497: 8, 499: 3, 500: 6, 501: 8, 503: 2, 508: 8, 528: 5, 532: 6, 554: 3, 560: 8, 562: 8, 563: 5, 564: 5, 565: 5, 567: 5, 569: 3, 573: 1, 577: 8, 608: 8, 609: 6, 610: 6, 611: 6, 612: 8, 613: 8, 647: 6, 707: 8, 715: 8, 717: 5, 723: 4, 730: 4, 761: 7, 810: 8, 840: 5, 842: 5, 844: 8, 869: 4, 872: 1, 880: 6, 882: 8, 890: 1, 892: 2, 893: 2, 894: 1, 961: 8, 969: 8, 975: 2, 977: 8, 979: 8, 985: 5, 1001: 8, 1005: 6, 1009: 8, 1011: 6, 1013: 6, 1017: 8, 1020: 8, 1033: 7, 1034: 7, 1037: 5, 1105: 5, 1187: 5, 1195: 3, 1201: 3, 1217: 8, 1218: 3, 1221: 5, 1223: 3, 1225: 7, 1233: 8, 1236: 8, 1249: 8, 1257: 6, 1259: 8, 1261: 7, 1263: 4, 1265: 8, 1267: 1, 1268: 2, 1271: 8, 1273: 3, 1276: 2, 1277: 7, 1278: 4, 1279: 4, 1280: 4, 1296: 4, 1300: 8, 1322: 6, 1323: 4, 1328: 4, 1345: 8, 1417: 8, 1512: 8, 1514: 8, 1517: 8, 1601: 8, 1906: 7, 1907: 7, 1910: 7, 1912: 7, 1914: 7, 1916: 7, 1919: 7, 1927: 7, 1930: 7, 2018: 8, 2020: 8, 2021: 8, 2028: 8
+    190: 6, 193: 8, 197: 8, 199: 4, 201: 8, 208: 8, 209: 7, 211: 2, 241: 6, 249: 8, 257: 8, 288: 5, 289: 8, 292: 2, 298: 8, 304: 3, 309: 8, 311: 8, 313: 8, 320: 4, 322: 7, 328: 1, 331: 3, 352: 5, 353: 3, 368: 3, 381: 8, 384: 4, 386: 8, 388: 8, 394: 7, 398: 8, 401: 8, 405: 8, 407: 7, 413: 8, 417: 7, 419: 1, 422: 4, 426: 7, 431: 8, 442: 8, 450: 4, 451: 8, 452: 8, 453: 6, 454: 8, 455: 7, 456: 8, 457: 6, 462: 4, 463: 3, 479: 3, 481: 7, 485: 8, 489: 8, 497: 8, 499: 3, 500: 6, 501: 8, 503: 2, 508: 8, 528: 5, 532: 6, 554: 3, 560: 8, 562: 8, 563: 5, 564: 5, 565: 5, 567: 5, 569: 3, 573: 1, 577: 8, 608: 8, 609: 6, 610: 6, 611: 6, 612: 8, 613: 8, 647: 6, 707: 8, 715: 8, 717: 5, 723: 4, 730: 4, 761: 7, 767: 4, 810: 8, 840: 5, 842: 5, 844: 8, 869: 4, 872: 1, 880: 6, 882: 8, 890: 1, 892: 2, 893: 2, 894: 1, 961: 8, 969: 8, 975: 2, 977: 8, 979: 8, 985: 5, 1001: 8, 1005: 6, 1009: 8, 1011: 6, 1013: 6, 1017: 8, 1020: 8, 1033: 7, 1034: 7, 1037: 5, 1105: 5, 1187: 5, 1195: 3, 1201: 3, 1217: 8, 1218: 3, 1221: 5, 1223: 3, 1225: 7, 1233: 8, 1236: 8, 1249: 8, 1257: 6, 1259: 8, 1261: 7, 1263: 4, 1265: 8, 1267: 1, 1268: 2, 1271: 8, 1273: 3, 1276: 2, 1277: 7, 1278: 4, 1279: 4, 1280: 4, 1296: 4, 1300: 8, 1322: 6, 1323: 4, 1328: 4, 1345: 8, 1417: 8, 1512: 8, 1514: 8, 1517: 8, 1601: 8, 1906: 7, 1907: 7, 1910: 7, 1912: 7, 1914: 7, 1916: 7, 1919: 7, 1927: 7, 1930: 7, 2018: 8, 2020: 8, 2021: 8, 2028: 8
   }],
   CAR.CHEVROLET_MALIBU_CC: [
   {
     190: 6, 193: 8, 197: 8, 199: 4, 201: 8, 209: 7, 211: 2, 241: 6, 249: 8, 257: 8, 288: 5, 298: 8, 304: 3, 309: 8, 311: 8, 313: 8, 320: 4, 328: 1, 352: 5, 368: 3, 381: 8, 384: 4, 386: 8, 388: 8, 393: 7, 398: 8, 401: 8, 407: 7, 409: 8, 413: 8, 417: 7, 419: 1, 422: 4, 426: 7, 431: 8, 442: 8, 451: 8, 452: 8, 453: 6, 455: 7, 479: 3, 481: 7, 485: 8, 489: 8, 497: 8, 499: 3, 500: 6, 501: 8, 508: 8, 532: 6, 554: 3, 560: 8, 562: 8, 563: 5, 564: 5, 565: 5, 567: 5, 573: 1, 577: 8, 608: 8, 609: 6, 610: 6, 611: 6, 612: 8, 613: 8, 647: 6, 707: 8, 717: 5, 730: 4, 761: 7, 800: 6, 810: 8, 840: 5, 842: 5, 844: 8, 866: 4, 869: 4, 961: 8, 969: 8, 975: 2, 977: 8, 979: 8, 985: 5, 1001: 8, 1005: 6, 1009: 8, 1011: 6, 1013: 6, 1017: 8, 1020: 8, 1037: 5, 1105: 5, 1187: 6, 1189: 1, 1195: 3, 1217: 8, 1221: 5, 1223: 3, 1225: 7, 1233: 8, 1236: 8, 1249: 8, 1257: 6, 1259: 8, 1261: 7, 1263: 4, 1265: 8, 1267: 1, 1268: 2, 1271: 8, 1273: 3, 1279: 4, 1280: 4, 1300: 8, 1322: 6, 1323: 4, 1328: 4, 1417: 8, 1601: 8, 1906: 7, 1907: 7, 1912: 7, 1919: 7
   }],
+  CAR.CHEVROLET_MALIBU_HYBRID_CC: [
+  {
+    193:8, 197:8, 201:8, 209:7, 211:2, 241:6, 249:8, 352:5, 386:8, 451:8, 452:8, 453:6, 481:7, 485:8, 489:8, 493:8, 500:6, 560:8, 562:8, 566:6, 609:6, 610:6, 611:6, 612:8, 613:8, 707:8, 717:5, 761:7, 810:8, 840:5, 842:5, 844:8, 869:4
+  }],
   CAR.CHEVROLET_TRAX: [
   {
     190: 6, 193: 8, 197: 8, 201: 8, 209: 7, 211: 2, 241: 6, 249: 8, 288: 5, 298: 8, 304: 3, 309: 8, 311: 8, 313: 8, 320: 4, 322: 7, 328: 1, 352: 5, 381: 8, 384: 4, 386: 8, 388: 8, 413: 8, 451: 8, 452: 8, 453: 6, 455: 7, 479: 3, 481: 7, 485: 8, 489: 8, 497: 8, 500: 6, 501: 8, 532: 6, 560: 8, 562: 8, 563: 5, 565: 5, 608: 8, 609: 6, 610: 6, 611: 6, 612: 8, 613: 8, 707: 8, 715: 8, 717: 5, 761: 7, 789: 5, 800: 6, 810: 8, 840: 5, 842: 5, 844: 8, 869: 4, 880: 6, 977: 8, 1001: 8, 1011: 6, 1017: 8, 1020: 8, 1217: 8, 1221: 5, 1233: 8, 1249: 8, 1259: 8, 1261: 7, 1263: 4, 1265: 8, 1267: 1, 1271: 8, 1280: 4, 1296: 4, 1300: 8, 1930: 7
   }],
+  CAR.CHEVROLET_VOLT_2019: [
+  # Chevy Volt w/ ACC 2019
+  {
+    170: 8, 189: 7, 190: 6, 193: 8, 197: 8, 199: 4, 201: 8, 209: 7, 211: 2, 241: 6, 257: 8, 288: 5, 289: 8, 292: 2, 298: 8, 304: 1, 308: 4, 309: 8, 311: 8, 313: 8, 320: 3, 328: 1, 331: 3, 352: 5, 368: 3, 381: 8, 384: 4, 386: 8, 388: 8, 390: 7, 417: 7, 419: 1, 426: 7, 451: 8, 452: 8, 453: 6, 454: 8, 456: 8, 479: 3, 481: 7, 485: 8, 489: 8, 493: 8, 495: 4, 497: 8, 499: 3, 500: 6, 501: 8, 508: 8, 528: 5, 532: 6, 546: 7, 550: 8, 554: 3, 558: 8, 560: 8, 562: 8, 563: 5, 564: 5, 565: 5, 566: 7, 567: 5, 573: 1, 577: 8, 587: 8, 608: 8, 609: 6, 610: 6, 611: 6, 612: 8, 613: 8, 647: 3, 707: 8, 711: 6, 715: 8, 717: 5, 761: 7, 767: 4, 810: 8, 840: 5, 842: 5, 844: 8, 866: 4, 869: 4, 880: 6, 961: 8, 967: 4, 969: 8, 975: 2, 977: 8, 979: 7, 988: 6, 989: 8, 995: 7, 1001: 8, 1005: 6, 1009: 8, 1017: 8, 1019: 2, 1020: 8, 1033: 7, 1034: 7, 1105: 5, 1187: 4, 1217: 8, 1221: 5, 1223: 3, 1225: 7, 1227: 4, 1233: 8, 1236: 8, 1249: 8, 1257: 6, 1265: 8, 1267: 1, 1268: 2, 1273: 3, 1275: 3, 1279: 4, 1280: 4, 1296: 4, 1300: 8, 1322: 6, 1328: 4, 1345: 8, 1417: 8, 1512: 8, 1513: 8, 1516: 8, 1517: 8, 1601: 8, 1609: 8, 1611: 8, 1618: 8, 1613: 8, 1649: 8, 1792: 8, 1793: 8, 1798: 8, 1799: 8, 1810: 8, 1813: 8, 1824: 8, 1825: 8, 1840: 8, 1842: 8, 1856: 8, 1858: 8, 1859: 8, 1860: 8, 1862: 8, 1863: 8, 1871: 8, 1872: 8, 1875: 8, 1879: 8, 1882: 8, 1888: 8, 1889: 8, 1892: 8, 1905: 7, 1906: 7, 1907: 7, 1910: 7, 1912: 7, 1920: 8, 1922: 7, 1927: 7, 1930: 7, 1937: 8, 1953: 8, 1954: 8, 1955: 8, 1968: 8, 1969: 8, 1971: 8, 1975: 8, 1988: 8, 1990: 8, 2000: 8, 2001: 8, 2004: 8, 2017: 8, 2018: 8, 2020: 8, 2021: 8, 2023: 8, 2025: 8, 2028: 8, 2031: 8
+  }],
 }
 
 FW_VERSIONS: dict[str, dict[tuple, list[bytes]]] = {

selfdrive/car/gm/gmcan.py

@@ -7,6 +7,58 @@ from openpilot.selfdrive.car import make_can_msg
 from openpilot.selfdrive.car.gm.values import CAR, CruiseButtons, CanBus
 
 
+MALIBU_BUTTON_TABLE = {
+  0: [0x2FBC, 0x25DE, 0x15EE, 0x1FCC],
+  1: [0x55AE, 0x5F8C, 0x6F7C, 0x659E],
+  4: [0x2ACD, 0x20EF, 0x1ADD, 0x10FF],
+  5: [0x50BF, 0x5A9D, 0x60AF, 0x6A8D],
+}
+
+MALIBU_BUTTON_MAP = {
+  CruiseButtons.UNPRESS: 0,
+  CruiseButtons.RES_ACCEL: 1,
+  CruiseButtons.MAIN: 4,
+  CruiseButtons.CANCEL: 5,
+}
+
+
+def malibu_phase_map_for_button(button):
+  key = MALIBU_BUTTON_MAP.get(button, None)
+  if key is None or key not in MALIBU_BUTTON_TABLE:
+    return None
+  return {v: i for i, v in enumerate(MALIBU_BUTTON_TABLE[key])}
+
+
+def malibu_phase_map_for_acc(acc_value):
+  seq = MALIBU_BUTTON_TABLE.get(acc_value)
+  if not seq:
+    return None
+  return {v: i for i, v in enumerate(seq)}
+
+
+def create_buttons_malibu(packer, bus, button, phase, prefix=0x41):
+  key = MALIBU_BUTTON_MAP.get(button, None)
+  if key is None or key not in MALIBU_BUTTON_TABLE:
+    # fallback to standard checksum for unsupported buttons
+    return create_buttons(packer, bus, 0, button)
+
+  values = {
+    "ACCButtons": button,
+    "RollingCounter": 0,
+    "ACCAlwaysOne": 1,
+    "DistanceButton": 0,
+  }
+  dat = packer.make_can_msg("ASCMSteeringButton", bus, values)[2]
+  data = bytearray(dat)
+  data[3] = prefix & 0xFF
+
+  seq = MALIBU_BUTTON_TABLE[key]
+  val = seq[phase % len(seq)]
+  data[5] = (val >> 8) & 0xFF
+  data[6] = val & 0xFF
+  return make_can_msg(0x1e1, bytes(data), bus)
+
+
 def create_buttons(packer, bus, idx, button):
   values = {
     "ACCButtons": button,
@@ -24,6 +76,18 @@ def create_buttons(packer, bus, idx, button):
   return packer.make_can_msg("ASCMSteeringButton", bus, values)
 
 
+def create_buttons_malibu_cancel(bus, phase, prefix=0x41):
+  # Malibu Hybrid CC cancel frames use a 4-value pattern in the last 2 bytes.
+  data = bytearray(7)
+  data[3] = prefix & 0xFF
+  data[4] = 0x00
+  cancel_bytes = (0x60, 0xAF, 0x65, 0x9E, 0x6A, 0x8D, 0x6F, 0x7C)
+  idx = ((phase + 2) % 4) * 2
+  data[5] = cancel_bytes[idx]
+  data[6] = cancel_bytes[idx + 1]
+  return make_can_msg(0x1e1, bytes(data), bus)
+
+
 def create_pscm_status(packer, bus, pscm_status):
   values = {s: pscm_status[s] for s in [
     "HandsOffSWDetectionMode",
@@ -178,46 +242,50 @@ def create_lka_icon_command(bus, active, critical, steer):
   return make_can_msg(0x104c006c, dat, bus)
 
 
-def create_gm_cc_spam_command(packer, controller, CS, actuators):
-  if controller.params_.get_bool("IsMetric"):
-    _CV = CV.MS_TO_KPH
-    RATE_UP_MAX = 0.04
-    RATE_DOWN_MAX = 0.04
-  else:
-    _CV = CV.MS_TO_MPH
-    RATE_UP_MAX = 0.2
-    RATE_DOWN_MAX = 0.2
-
-  accel = actuators.accel * _CV  # m/s/s to mph/s
-  speedSetPoint = int(round(CS.out.cruiseState.speed * _CV))
+def create_gm_cc_spam_command(packer, controller, CS, actuators, frogpilot_toggles):
+  accel = actuators.accel
+  Vego = CS.out.vEgo
 
   cruiseBtn = CruiseButtons.INIT
-  if speedSetPoint == CS.CP.minEnableSpeed and accel < -1:
+  if abs(accel) <= 0.15:
+    rate = 1
+  else:
+    rate = 0.2
+
+  MS_CONVERT = CV.MS_TO_KPH if frogpilot_toggles.is_metric else CV.MS_TO_MPH
+
+  speedSetPoint = int(round(CS.out.cruiseState.speed * MS_CONVERT))
+
+  if accel > 0:
+    DesiredSetPoint = int(round((Vego * 1.01 + 3 * accel) * MS_CONVERT)) # 1.01 factor to match cluster speed better
+  else: # accel <= 0
+    DesiredSetPoint = int(round((Vego * 1.01 + 3 * accel) * MS_CONVERT))
+
+  if CS.CP.minEnableSpeed - (DesiredSetPoint /  MS_CONVERT) > 3.25:
     cruiseBtn = CruiseButtons.CANCEL
     controller.apply_speed = 0
-    rate = 0.04
-  elif accel < 0:
+  elif DesiredSetPoint < speedSetPoint and speedSetPoint > CS.CP.minEnableSpeed * MS_CONVERT + 1:
     cruiseBtn = CruiseButtons.DECEL_SET
-    if speedSetPoint > (CS.out.vEgo * _CV) + 3.0:  # If accel is changing directions, bring set speed to current speed as fast as possible
-      rate = RATE_DOWN_MAX
-    else:
-      rate = max(-1 / accel, RATE_DOWN_MAX)
     controller.apply_speed = speedSetPoint - 1
-  elif accel > 0:
+  elif DesiredSetPoint > speedSetPoint:
     cruiseBtn = CruiseButtons.RES_ACCEL
-    if speedSetPoint < (CS.out.vEgo * _CV) - 3.0:
-      rate = RATE_UP_MAX
-    else:
-      rate = max(1 / accel, RATE_UP_MAX)
     controller.apply_speed = speedSetPoint + 1
   else:
+    cruiseBtn = CruiseButtons.INIT
     controller.apply_speed = speedSetPoint
-    rate = float('inf')
 
   # Check rlogs closely - our message shouldn't show up on the pt bus for us
   # Or bus 2, since we're forwarding... but I think it does
+  # TODO: Cleanup the timing - normal is every 30ms...
   if (cruiseBtn != CruiseButtons.INIT) and ((controller.frame - controller.last_button_frame) * DT_CTRL > rate):
     controller.last_button_frame = controller.frame
+    if CS.CP.carFingerprint == CAR.CHEVROLET_MALIBU_HYBRID_CC:
+      phase_map = malibu_phase_map_for_button(cruiseBtn)
+      if phase_map:
+        msgs = [create_buttons_malibu(packer, CanBus.POWERTRAIN, cruiseBtn, controller.malibu_button_phase,
+                                      CS.steering_button_prefix)]
+        controller.malibu_button_phase = (controller.malibu_button_phase + 1) % 4
+        return msgs
     idx = (CS.buttons_counter + 1) % 4  # Need to predict the next idx for '22-23 EUV
     return [create_buttons(packer, CanBus.POWERTRAIN, idx, cruiseBtn)]
   else:

selfdrive/car/gm/interface.py

@@ -7,10 +7,12 @@ from panda import Panda
 from openpilot.common.conversions import Conversions as CV
 from openpilot.selfdrive.car import create_button_events, get_safety_config
 from openpilot.selfdrive.car.gm.radar_interface import RADAR_HEADER_MSG
-from openpilot.selfdrive.car.gm.values import CAR, CruiseButtons, CarControllerParams, EV_CAR, CAMERA_ACC_CAR, CanBus, GMFlags, CC_ONLY_CAR, SDGM_CAR
-from openpilot.selfdrive.car.interfaces import CarInterfaceBase, TorqueFromLateralAccelCallbackType, FRICTION_THRESHOLD, LateralAccelFromTorqueCallbackType
+from openpilot.selfdrive.car.gm.values import CAR, CruiseButtons, CarControllerParams, EV_CAR, CAMERA_ACC_CAR, CanBus, GMFlags, CC_ONLY_CAR, SDGM_CAR, ASCM_INT
+from openpilot.selfdrive.car.interfaces import CarInterfaceBase, TorqueFromLateralAccelCallbackType, FRICTION_THRESHOLD, LateralAccelFromTorqueCallbackType, get_friction_threshold
 from openpilot.selfdrive.controls.lib.drive_helpers import get_friction
 
+
+
 ButtonType = car.CarState.ButtonEvent.Type
 FrogPilotButtonType = custom.FrogPilotCarState.ButtonEvent.Type
 EventName = car.CarEvent.EventName
@@ -26,15 +28,33 @@ CAM_MSG = 0x320  # AEBCmd
                  # TODO: Is this always linked to camera presence?
 ACCELERATOR_POS_MSG = 0xbe
 
+VOLT_LIKE_CARS = (
+  CAR.CHEVROLET_VOLT,
+  CAR.CHEVROLET_VOLT_2019,
+  CAR.CHEVROLET_VOLT_CC,
+  CAR.CHEVROLET_VOLT_CAMERA,
+  CAR.CHEVROLET_VOLT_ASCM,
+  CAR.CHEVROLET_MALIBU,
+  CAR.CHEVROLET_MALIBU_ASCM,
+  CAR.CHEVROLET_MALIBU_SDGM,
+  CAR.CHEVROLET_MALIBU_CC,
+  CAR.CHEVROLET_MALIBU_HYBRID_CC,
+)
+
 NON_LINEAR_TORQUE_PARAMS = {
   CAR.CHEVROLET_BOLT_EUV: [2.6531724862969748, 1.0, 0.1919764879840985, 0.009054123646805178],
   CAR.CHEVROLET_BOLT_CC: [2.6531724862969748, 1.0, 0.1919764879840985, 0.009054123646805178],
   CAR.GMC_ACADIA: [4.78003305, 1.0, 0.3122, 0.05591772],
+  CAR.GMC_ACADIA_ASCM: [4.78003305, 1.0, 0.3122, 0.05591772],
   CAR.CHEVROLET_SILVERADO: [3.29974374, 1.0, 0.25571356, 0.0465122]
 }
 
 
 class CarInterface(CarInterfaceBase):
+  def __init__(self, CP, FPCP, CarController, CarState):
+    super().__init__(CP, FPCP, CarController, CarState)
+    self.steer_offset = 0.0
+
   @staticmethod
   def get_pid_accel_limits(CP, current_speed, cruise_speed):
     return CarControllerParams.ACCEL_MIN, CarControllerParams.ACCEL_MAX
@@ -47,7 +67,7 @@ class CarInterface(CarInterfaceBase):
     return 0.10006696 * sigmoid * (v_ego + 3.12485927)
 
   def get_steer_feedforward_function(self):
-    if self.CP.carFingerprint in (CAR.CHEVROLET_VOLT, CAR.CHEVROLET_VOLT_CC):
+    if self.CP.carFingerprint in VOLT_LIKE_CARS:
       return self.get_steer_feedforward_volt
     else:
       return CarInterfaceBase.get_steer_feedforward_default
@@ -60,10 +80,10 @@ class CarInterface(CarInterfaceBase):
       # This has big effect on the stability about 0 (noise when going straight)
       non_linear_torque_params = NON_LINEAR_TORQUE_PARAMS.get(self.CP.carFingerprint)
       assert non_linear_torque_params, "The params are not defined"
-      a, b, c, _ = non_linear_torque_params
+      a, b, c, d = non_linear_torque_params
       sig_input = a * lateral_acceleration
       sig = np.sign(sig_input) * (1 / (1 + exp(-fabs(sig_input))) - 0.5)
-      steer_torque = (sig * b) + (lateral_acceleration * c)
+      steer_torque = (sig * b) + (lateral_acceleration * c) + d
       return float(steer_torque)
 
     lataccel_values = np.arange(-5.0, 5.0, 0.01)
@@ -76,20 +96,28 @@ class CarInterface(CarInterfaceBase):
       torque_values, lataccel_values = self.get_lataccel_torque_siglin()
 
       def torque_from_lateral_accel_siglin(lateral_acceleration: float, torque_params: car.CarParams.LateralTorqueTuning):
-        return np.interp(lateral_acceleration, lataccel_values, torque_values)
+        return float(np.interp(lateral_acceleration, lataccel_values, torque_values) + self.steer_offset)
       return torque_from_lateral_accel_siglin
     else:
-      return self.torque_from_lateral_accel_linear
+      def torque_from_lateral_accel_linear(lateral_acceleration: float, torque_params: car.CarParams.LateralTorqueTuning):
+        return self.torque_from_lateral_accel_linear(lateral_acceleration, torque_params) + self.steer_offset
+      return torque_from_lateral_accel_linear
 
   def lateral_accel_from_torque(self) -> LateralAccelFromTorqueCallbackType:
     if self.CP.carFingerprint in NON_LINEAR_TORQUE_PARAMS:
       torque_values, lataccel_values = self.get_lataccel_torque_siglin()
 
       def lateral_accel_from_torque_siglin(torque: float, torque_params: car.CarParams.LateralTorqueTuning):
-        return np.interp(torque, torque_values, lataccel_values)
+        return np.interp(torque - self.steer_offset, torque_values, lataccel_values)
       return lateral_accel_from_torque_siglin
     else:
-      return self.lateral_accel_from_torque_linear
+      def lateral_accel_from_torque_linear(torque: float, torque_params: car.CarParams.LateralTorqueTuning):
+        return self.lateral_accel_from_torque_linear(torque - self.steer_offset, torque_params)
+      return lateral_accel_from_torque_linear
+
+  def update(self, c: car.CarControl, can_strings: list[bytes], frogpilot_toggles) -> car.CarState:
+    self.steer_offset = float(getattr(frogpilot_toggles, "steer_offset", 0.0))
+    return super().update(c, can_strings, frogpilot_toggles)
 
   @staticmethod
   def _get_params(ret, candidate, fingerprint, car_fw, experimental_long, docs, frogpilot_toggles):
@@ -97,9 +125,16 @@ class CarInterface(CarInterfaceBase):
     ret.safetyConfigs = [get_safety_config(car.CarParams.SafetyModel.gm)]
     ret.autoResumeSng = False
     ret.enableBsm = 0x142 in fingerprint[CanBus.POWERTRAIN]
+
+    # Detect Beartech SASCM allows openpilot longitudinal control on SDGM and ASCM_INT vehicles
+    if 0x2FF in fingerprint[0]:
+      ret.flags |= GMFlags.SASCM.value
+
     if PEDAL_MSG in fingerprint[0]:
       ret.enableGasInterceptor = True
       ret.safetyConfigs[0].safetyParam |= Panda.FLAG_GM_GAS_INTERCEPTOR
+      # When a pedal interceptor is present, always use normal longitudinal (block stock cruise)
+      experimental_long = False
 
     if candidate in EV_CAR:
       ret.transmissionType = TransmissionType.direct
@@ -108,39 +143,41 @@ class CarInterface(CarInterfaceBase):
 
     ret.longitudinalTuning.kiBP = [5., 35.]
 
-    if candidate in CAMERA_ACC_CAR:
-      ret.experimentalLongitudinalAvailable = candidate not in CC_ONLY_CAR
+    if candidate in (CAMERA_ACC_CAR | SDGM_CAR | ASCM_INT) or candidate == CAR.CHEVROLET_VOLT_CAMERA:
+      ret.experimentalLongitudinalAvailable = candidate not in (CC_ONLY_CAR | ASCM_INT | SDGM_CAR) or 0x2FF in fingerprint[CanBus.POWERTRAIN]
       ret.networkLocation = NetworkLocation.fwdCamera
-      ret.radarUnavailable = True  # no radar
+      ret.radarUnavailable = 0x460 not in fingerprint[CanBus.OBSTACLE]
       ret.pcmCruise = True
-      ret.safetyConfigs[0].safetyParam |= Panda.FLAG_GM_HW_CAM
       ret.minEnableSpeed = 5 * CV.KPH_TO_MS
       ret.minSteerSpeed = 10 * CV.KPH_TO_MS
+      if candidate in SDGM_CAR:
+        ret.safetyConfigs[0].safetyParam |= Panda.FLAG_GM_HW_SDGM
+        # Use C9 brake bit only on SDGM variants that lack 0xBE (ECMAcceleratorPos)
+        if ACCELERATOR_POS_MSG not in fingerprint[CanBus.POWERTRAIN]:
+          ret.safetyConfigs[0].safetyParam |= Panda.FLAG_GM_FORCE_BRAKE_C9
+          ret.flags |= GMFlags.FORCE_BRAKE_C9.value
+        ret.minEnableSpeed = -1.  # engage speed is decided by pcm
+        ret.minSteerSpeed = 7 * CV.MPH_TO_MS
+      elif candidate in ASCM_INT:
+        ret.safetyConfigs[0].safetyParam |= Panda.FLAG_GM_HW_CAM
+        ret.minSteerSpeed = 7 * CV.MPH_TO_MS
+        ret.safetyConfigs[0].safetyParam |= Panda.FLAG_GM_ASCM_INT
+      else:
+        ret.safetyConfigs[0].safetyParam |= Panda.FLAG_GM_HW_CAM
 
       # Tuning for experimental long
-      ret.longitudinalTuning.kiV = [2.0, 1.5]
-      ret.vEgoStopping = 0.1
-      ret.vEgoStarting = 0.1
+      ret.longitudinalTuning.kiV = [0.5, 0.5]
 
-      ret.stoppingDecelRate = 2.0  # reach brake quickly after enabling
+      ret.stoppingDecelRate = 1.0  # reach brake quickly after enabling
       ret.vEgoStopping = 0.25
       ret.vEgoStarting = 0.25
+      ret.stopAccel = -0.25
 
       if ret.experimentalLongitudinalAvailable and experimental_long:
         ret.pcmCruise = False
         ret.openpilotLongitudinalControl = True
         ret.safetyConfigs[0].safetyParam |= Panda.FLAG_GM_HW_CAM_LONG
 
-    elif candidate in SDGM_CAR:
-      ret.longitudinalTuning.kiV = [0., 0.]  # TODO: tuning
-      ret.experimentalLongitudinalAvailable = False
-      ret.networkLocation = NetworkLocation.fwdCamera
-      ret.pcmCruise = True
-      ret.radarUnavailable = True
-      ret.minEnableSpeed = -1.  # engage speed is decided by ASCM
-      ret.minSteerSpeed = 30 * CV.MPH_TO_MS
-      ret.safetyConfigs[0].safetyParam |= Panda.FLAG_GM_HW_SDGM
-
     else:  # ASCM, OBD-II harness
       ret.openpilotLongitudinalControl = not frogpilot_toggles.disable_openpilot_long
       ret.networkLocation = NetworkLocation.gateway
@@ -151,7 +188,11 @@ class CarInterface(CarInterfaceBase):
       ret.minSteerSpeed = 7 * CV.MPH_TO_MS
 
       # Tuning
-      ret.longitudinalTuning.kiV = [2.4, 1.5]
+      ret.longitudinalTuning.kiV = [0.5, 0.5]
+      ret.stoppingDecelRate = 3
+      ret.vEgoStopping = 0.75
+      ret.vEgoStarting = 0.75
+      ret.stopAccel = -1.5
 
       if ret.enableGasInterceptor:
         # Need to set ASCM long limits when using pedal interceptor, instead of camera ACC long limits
@@ -162,25 +203,35 @@ class CarInterface(CarInterfaceBase):
     ret.lateralTuning.pid.kpV, ret.lateralTuning.pid.kiV = [[0.2], [0.00]]
     ret.lateralTuning.pid.kf = 0.00004   # full torque for 20 deg at 80mph means 0.00007818594
     ret.steerActuatorDelay = 0.1  # Default delay, not measured yet
+    ret.longitudinalTuning.deadzoneBP = [0.]
+    ret.longitudinalTuning.deadzoneV  = [0.]
 
     ret.steerLimitTimer = 0.4
     ret.radarTimeStep = 0.0667  # GM radar runs at 15Hz instead of standard 20Hz
     ret.longitudinalActuatorDelay = 0.5  # large delay to initially start braking
 
-    if candidate in (CAR.CHEVROLET_VOLT, CAR.CHEVROLET_VOLT_CC):
+    if candidate in (CAR.CHEVROLET_VOLT, CAR.CHEVROLET_VOLT_CC, CAR.CHEVROLET_VOLT_CAMERA):
       ret.minEnableSpeed = -1
-      ret.lateralTuning.pid.kpBP = [0., 40.]
-      ret.lateralTuning.pid.kpV = [0., 0.17]
-      ret.lateralTuning.pid.kiBP = [0.]
-      ret.lateralTuning.pid.kiV = [0.]
-      ret.lateralTuning.pid.kf = 1.  # get_steer_feedforward_volt()
+
+    if candidate == CAR.CHEVROLET_VOLT_2019 and not ret.openpilotLongitudinalControl:
+      ret.minEnableSpeed = -1
+
+    if candidate in VOLT_LIKE_CARS:
+      CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
       ret.steerActuatorDelay = 0.2
+      if candidate == CAR.CHEVROLET_MALIBU_HYBRID_CC and ret.enableGasInterceptor:
+        ret.flags |= GMFlags.PEDAL_LONG.value
 
     elif candidate == CAR.GMC_ACADIA:
       ret.minEnableSpeed = -1.  # engage speed is decided by pcm
       ret.steerActuatorDelay = 0.2
       CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
 
+    elif candidate == CAR.GMC_ACADIA_ASCM:
+      ret.minEnableSpeed = -1.  # engage speed is decided by pcm
+      ret.steerActuatorDelay = 0.2
+      CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
+
     elif candidate == CAR.BUICK_LACROSSE:
       CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
 
@@ -230,35 +281,44 @@ class CarInterface(CarInterfaceBase):
       ret.steerActuatorDelay = 0.2
       CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
 
+    elif candidate == CAR.CADILLAC_XT6:
+      ret.steerActuatorDelay = 0.2
+      ret.minSteerSpeed = 7 * CV.MPH_TO_MS
+      CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
+
     elif candidate == CAR.CADILLAC_XT4:
       ret.steerActuatorDelay = 0.2
+      if not ret.openpilotLongitudinalControl:
+        ret.minEnableSpeed = -1.  # engage speed is decided by pcm
+      ret.minSteerSpeed = 30 * CV.MPH_TO_MS
       CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
 
     elif candidate == CAR.CADILLAC_XT5_CC:
       ret.steerActuatorDelay = 0.2
       CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
 
-    elif candidate == CAR.CHEVROLET_TRAVERSE:
+    elif candidate in (CAR.CHEVROLET_TRAVERSE, CAR.CHEVROLET_BLAZER):
       ret.steerActuatorDelay = 0.2
-      ret.minSteerSpeed = 10 * CV.KPH_TO_MS
+      if not ret.openpilotLongitudinalControl:
+        ret.minEnableSpeed = -1.  # engage speed is decided by pcm
       CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
 
+    elif candidate == CAR.CHEVROLET_BLAZER:
+      ret.minEnableSpeed = 5 * CV.KPH_TO_MS
+
     elif candidate == CAR.BUICK_BABYENCLAVE:
       ret.steerActuatorDelay = 0.2
-      ret.minSteerSpeed = 10 * CV.KPH_TO_MS
+      if not ret.openpilotLongitudinalControl:
+        ret.minEnableSpeed = -1.  # engage speed is decided by pcm
       CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
 
     elif candidate == CAR.CADILLAC_CT6_CC:
       CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
-
-    elif candidate == CAR.CHEVROLET_MALIBU_CC:
-      ret.steerActuatorDelay = 0.2
-      CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
-
+ 
     elif candidate == CAR.CHEVROLET_TRAX:
       CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
 
-    if ret.enableGasInterceptor:
+    if ret.enableGasInterceptor and frogpilot_toggles.gm_pedal_longitudinal:
       ret.networkLocation = NetworkLocation.fwdCamera
       ret.safetyConfigs[0].safetyParam |= Panda.FLAG_GM_HW_CAM
       ret.minEnableSpeed = -1
@@ -273,14 +333,29 @@ class CarInterface(CarInterfaceBase):
         # Note: Low speed, stop and go not tested. Should be fairly smooth on highway
         ret.longitudinalTuning.kiBP = [0.0, 5., 35.]
         ret.longitudinalTuning.kiV = [0.0, 0.35, 0.5]
-        ret.longitudinalTuning.kf = 0.15
+        ret.longitudinalTuning.kfDEPRECATED = 0.15
         ret.stoppingDecelRate = 0.8
+        ret.minEnableSpeed = -1
+        ret.pcmCruise = False
+        ret.openpilotLongitudinalControl = not frogpilot_toggles.disable_openpilot_long
       else:  # Pedal used for SNG, ACC for longitudinal control otherwise
         ret.safetyConfigs[0].safetyParam |= Panda.FLAG_GM_HW_CAM_LONG
         ret.startingState = True
         ret.vEgoStopping = 0.25
         ret.vEgoStarting = 0.25
 
+    if ret.enableGasInterceptor and candidate == CAR.CHEVROLET_MALIBU_HYBRID_CC:
+      ret.flags |= GMFlags.PEDAL_LONG.value
+      ret.safetyConfigs[0].safetyParam |= Panda.FLAG_GM_PEDAL_LONG
+      ret.longitudinalTuning.kiBP = [0.0, 5., 35.]
+      ret.longitudinalTuning.kiV = [0.0, 0.18, 0.25]
+      ret.longitudinalTuning.kfDEPRECATED = 0.15
+      ret.stoppingDecelRate = 0.8
+      ret.minEnableSpeed = -1
+      ret.pcmCruise = False
+      ret.openpilotLongitudinalControl = not frogpilot_toggles.disable_openpilot_long
+
+
     elif candidate in CC_ONLY_CAR:
       ret.flags |= GMFlags.CC_LONG.value
       ret.safetyConfigs[0].safetyParam |= Panda.FLAG_GM_CC_LONG
@@ -290,22 +365,25 @@ class CarInterface(CarInterfaceBase):
       ret.openpilotLongitudinalControl = not frogpilot_toggles.disable_openpilot_long
       ret.pcmCruise = False
 
-      ret.stoppingDecelRate = 11.18  # == 25 mph/s (.04 rate)
+      ret.stoppingDecelRate = 11.18
 
-      ret.longitudinalTuning.deadzoneBP = [0.]
-      ret.longitudinalTuning.deadzoneV = [0.56]  # == 2 km/h/s, 1.25 mph/s
-      ret.longitudinalActuatorDelay = 1.  # TODO: measure this
+      if candidate not in (CAR.CHEVROLET_BOLT_CC, CAR.CHEVROLET_MALIBU_HYBRID_CC):
+        ret.longitudinalTuning.kpBP = [10.7, 10.8, 28.]  # 10.7 m/s == 24 mph
+        ret.longitudinalTuning.kpV = [0., 5., 2.]  # set lower end to 0 since we can't drive below that speed
+        ret.longitudinalTuning.deadzoneBP = [0., 1.]
+        ret.longitudinalTuning.deadzoneV = [0.9, 0.9]  # == 2 km/h/s, 1.25 mph/s
+        ret.longitudinalActuatorDelay = 1.  # TODO: measure this
 
-      ret.longitudinalTuning.kpBP = [10.7, 10.8, 28.]  # 10.7 m/s == 24 mph
-      ret.longitudinalTuning.kpV = [0., 20., 20.]  # set lower end to 0 since we can't drive below that speed
-      ret.longitudinalTuning.kiBP = [0.]
-      ret.longitudinalTuning.kiV = [0.1]
+        ret.longitudinalTuning.kpBP = [10.7, 10.8, 28.]  # 10.7 m/s == 24 mph
+        ret.longitudinalTuning.kpV = [0., 20., 20.]  # set lower end to 0 since we can't drive below that speed
+        ret.longitudinalTuning.kiBP = [0.]
+        ret.longitudinalTuning.kiV = [0.1]
 
     if candidate in CC_ONLY_CAR:
       ret.safetyConfigs[0].safetyParam |= Panda.FLAG_GM_NO_ACC
 
     # Exception for flashed cars, or cars whose camera was removed
-    if (ret.networkLocation == NetworkLocation.fwdCamera or candidate in CC_ONLY_CAR) and CAM_MSG not in fingerprint[CanBus.CAMERA] and not candidate in SDGM_CAR:
+    if (ret.networkLocation == NetworkLocation.fwdCamera or candidate in CC_ONLY_CAR) and CAM_MSG not in fingerprint[CanBus.CAMERA] and not candidate in (SDGM_CAR | ASCM_INT):
       ret.flags |= GMFlags.NO_CAMERA.value
       ret.safetyConfigs[0].safetyParam |= Panda.FLAG_GM_NO_CAMERA
 
@@ -341,18 +419,21 @@ class CarInterface(CarInterfaceBase):
     # TODO: verify 17 Volt can enable for the first time at a stop and allow for all GMs
     below_min_enable_speed = ret.vEgo < self.CP.minEnableSpeed or self.CS.moving_backward
     if below_min_enable_speed and not (ret.standstill and ret.brake >= 20 and
-                                       (self.CP.networkLocation == NetworkLocation.fwdCamera and not self.CP.carFingerprint in SDGM_CAR)):
+                                       self.CP.networkLocation == NetworkLocation.fwdCamera):
       events.add(EventName.belowEngageSpeed)
     if ret.cruiseState.standstill and not self.CP.autoResumeSng:
       events.add(EventName.resumeRequired)
+
     if ret.vEgo < self.CP.minSteerSpeed:
       events.add(EventName.belowSteerSpeed)
 
-    if (self.CP.flags & GMFlags.CC_LONG.value) and ret.vEgo < self.CP.minEnableSpeed and ret.cruiseState.enabled:
-      events.add(EventName.speedTooLow)
+    if (self.CP.flags & GMFlags.CC_LONG.value) and ret.vEgo < self.CP.minEnableSpeed:
+      if ret.cruiseState.enabled or self.CS.out.cruiseState.enabled:
+        events.add(EventName.speedTooLow)
 
     if (self.CP.flags & GMFlags.PEDAL_LONG.value) and \
       self.CP.transmissionType == TransmissionType.direct and \
+      self.CP.carFingerprint != CAR.CHEVROLET_MALIBU_HYBRID_CC and \
       not self.CS.single_pedal_mode and \
       c.longActive:
       events.add(FrogPilotEventName.pedalInterceptorNoBrake)

selfdrive/car/gm/values.py

@@ -33,40 +33,48 @@ class CarControllerParams:
   # Our controller should still keep the 2 second average above
   # -3.5 m/s^2 as per planner limits
   ACCEL_MAX = 2.  # m/s^2
+  ACCEL_MAX_PLUS = 4.  # m/s^2
   ACCEL_MIN = -4.  # m/s^2
 
   def __init__(self, CP):
     # Gas/brake lookups
-    self.ZERO_GAS = 2048  # Coasting
+    self.ZERO_GAS = 6150  # Coasting
     self.MAX_BRAKE = 400  # ~ -4.0 m/s^2 with regen
+    self.BRAKE_SWITCH_MAX = self.ZERO_GAS
 
-    if CP.carFingerprint in CAMERA_ACC_CAR and CP.carFingerprint not in CC_ONLY_CAR:
-      self.MAX_GAS = 3400
-      self.MAX_ACC_REGEN = 1514
-      self.INACTIVE_REGEN = 1554
+    if CP.carFingerprint in (CAMERA_ACC_CAR | SDGM_CAR) and CP.carFingerprint not in CC_ONLY_CAR and CP.carFingerprint != CAR.CHEVROLET_BOLT_EUV:
+      self.MAX_GAS = 8848
+      self.MAX_GAS_PLUS = 8848
+      self.MAX_ACC_REGEN = 5610
+      self.INACTIVE_REGEN = 5650
       # Camera ACC vehicles have no regen while enabled.
       # Camera transitions to MAX_ACC_REGEN from ZERO_GAS and uses friction brakes instantly
-      max_regen_acceleration = 0.
-
-    elif CP.carFingerprint in SDGM_CAR:
-      self.MAX_GAS = 3400
-      self.MAX_ACC_REGEN = 1514
-      self.INACTIVE_REGEN = 1554
-      max_regen_acceleration = 0.
+      self.max_regen_acceleration = 0.
 
     else:
-      self.MAX_GAS = 3072  # Safety limit, not ACC max. Stock ACC >4096 from standstill.
-      self.MAX_ACC_REGEN = 1404  # Max ACC regen is slightly less than max paddle regen
-      self.INACTIVE_REGEN = 1404
+      self.MAX_GAS = 8191  # Safety limit, not ACC max. Stock ACC >8192 from standstill.
+      self.MAX_GAS_PLUS = 8191
+      self.MAX_ACC_REGEN = 5500  # Max ACC regen is slightly less than max paddle regen
+      self.INACTIVE_REGEN = 5500
       # ICE has much less engine braking force compared to regen in EVs,
       # lower threshold removes some braking deadzone
-      max_regen_acceleration = -1. if CP.carFingerprint in EV_CAR else -0.1
+      self.max_regen_acceleration = -1. if CP.carFingerprint in EV_CAR else -0.1
 
-    self.GAS_LOOKUP_BP = [max_regen_acceleration, 0., self.ACCEL_MAX]
+    if CP.carFingerprint in (CAR.CHEVROLET_VOLT, CAR.CHEVROLET_VOLT_ASCM, CAR.CHEVROLET_VOLT_CAMERA, CAR.CHEVROLET_VOLT_CC):
+      self.ZERO_GAS = 6150
+      self.BRAKE_SWITCH_MAX = self.MAX_ACC_REGEN if CP.carFingerprint in EV_CAR else self.ZERO_GAS
+      self.BRAKE_LOOKUP_BP = [self.ACCEL_MIN, 0.]
+    else:
+      self.BRAKE_LOOKUP_BP = [self.ACCEL_MIN, self.max_regen_acceleration]
+
+    self.GAS_LOOKUP_BP = [self.max_regen_acceleration, 0., self.ACCEL_MAX]
+    self.GAS_LOOKUP_BP_PLUS = [self.max_regen_acceleration, 0., self.ACCEL_MAX_PLUS]
     self.GAS_LOOKUP_V = [self.MAX_ACC_REGEN, self.ZERO_GAS, self.MAX_GAS]
+    self.GAS_LOOKUP_V_PLUS = [self.MAX_ACC_REGEN, self.ZERO_GAS, self.MAX_GAS_PLUS]
 
-    self.BRAKE_LOOKUP_BP = [self.ACCEL_MIN, max_regen_acceleration]
     self.BRAKE_LOOKUP_V = [self.MAX_BRAKE, 0.]
+    self.BRAKE_SWITCH_LOOKUP_BP = [0.5, 10]
+    self.BRAKE_SWITCH_LOOKUP_V = [self.ZERO_GAS, self.BRAKE_SWITCH_MAX]
 
   # determined by letting Volt regen to a stop in L gear from 89mph,
   # and by letting off gas and allowing car to creep, for determining
@@ -76,10 +84,11 @@ class CarControllerParams:
 
   def update_ev_gas_brake_threshold(self, v_ego):
     gas_brake_threshold = interp(v_ego, self.EV_GAS_BRAKE_THRESHOLD_BP, self.EV_GAS_BRAKE_THRESHOLD_V)
+    self.GAS_LOOKUP_BP_PLUS = [self.max_regen_acceleration, 0., self.ACCEL_MAX_PLUS]
     self.EV_GAS_LOOKUP_BP = [gas_brake_threshold, max(0., gas_brake_threshold), self.ACCEL_MAX]
+    self.EV_GAS_LOOKUP_BP_PLUS = [gas_brake_threshold, max(0., gas_brake_threshold), self.ACCEL_MAX_PLUS]
     self.EV_BRAKE_LOOKUP_BP = [self.ACCEL_MIN, gas_brake_threshold]
 
-
 @dataclass
 class GMCarDocs(CarDocs):
   package: str = "Adaptive Cruise Control (ACC)"
@@ -104,8 +113,7 @@ class GMPlatformConfig(PlatformConfig):
 @dataclass
 class GMASCMPlatformConfig(GMPlatformConfig):
   def init(self):
-    # ASCM is supported, but due to a janky install and hardware configuration, we are not showing in the car docs
-    self.car_docs = []
+    pass
 
 
 class CAR(Platforms):
@@ -118,6 +126,16 @@ class CAR(Platforms):
     GMCarSpecs(mass=1607, wheelbase=2.69, steerRatio=17.7, centerToFrontRatio=0.45, tireStiffnessFactor=0.469, minEnableSpeed=-1),
     dbc_dict=dbc_dict('gm_global_a_powertrain_volt', 'gm_global_a_object', chassis_dbc='gm_global_a_chassis')
   )
+  CHEVROLET_VOLT_ASCM = GMPlatformConfig(
+    [GMCarDocs("Chevrolet Volt 2017-18 ASCM Harness", min_enable_speed=0, video_link="https://youtu.be/QeMCN_4TFfQ")],
+    GMCarSpecs(mass=1607, wheelbase=2.69, steerRatio=17.7, centerToFrontRatio=0.45, tireStiffnessFactor=0.469, minEnableSpeed=-1),
+    dbc_dict=dbc_dict('gm_global_a_powertrain_volt', 'gm_global_a_object', chassis_dbc='gm_global_a_chassis')
+  )
+  CHEVROLET_VOLT_CAMERA = GMPlatformConfig(
+    [GMCarDocs("Chevrolet Volt 2017-18 Camera Harness", "Flashed camera-forward integration with ACC")],
+    CHEVROLET_VOLT.specs,
+    dbc_dict=dbc_dict('gm_global_a_powertrain_volt', 'gm_global_a_object', chassis_dbc='gm_global_a_chassis')
+  )
   CADILLAC_ATS = GMASCMPlatformConfig(
     [GMCarDocs("Cadillac ATS Premium Performance 2018")],
     GMCarSpecs(mass=1601, wheelbase=2.78, steerRatio=15.3),
@@ -126,10 +144,19 @@ class CAR(Platforms):
     [GMCarDocs("Chevrolet Malibu Premier 2017")],
     GMCarSpecs(mass=1496, wheelbase=2.83, steerRatio=15.8, centerToFrontRatio=0.4),
   )
+  CHEVROLET_MALIBU_ASCM = GMPlatformConfig(
+    [GMCarDocs("Chevrolet Malibu 2017-19 ASCM Harness")],
+    CHEVROLET_MALIBU.specs,
+  )
   GMC_ACADIA = GMASCMPlatformConfig(
     [GMCarDocs("GMC Acadia 2018", video_link="https://www.youtube.com/watch?v=0ZN6DdsBUZo")],
     GMCarSpecs(mass=1975, wheelbase=2.86, steerRatio=14.4, centerToFrontRatio=0.4),
   )
+  GMC_ACADIA_ASCM = GMPlatformConfig(
+    [GMCarDocs("GMC Acadia 2018 ASCM Harness", video_link="https://www.youtube.com/watch?v=0ZN6DdsBUZo")],
+    GMCarSpecs(mass=1975, wheelbase=2.86, steerRatio=14.4, centerToFrontRatio=0.4),
+    dbc_dict=dbc_dict('gm_global_a_powertrain_generated', 'gm_global_a_object', chassis_dbc='gm_global_a_chassis')
+  )
   BUICK_LACROSSE = GMASCMPlatformConfig(
     [GMCarDocs("Buick LaCrosse 2017-19", "Driver Confidence Package 2")],
     GMCarSpecs(mass=1712, wheelbase=2.91, steerRatio=15.8, centerToFrontRatio=0.4),
@@ -217,22 +244,42 @@ class CAR(Platforms):
     [GMCarDocs("Cadillac XT5 - No-ACC")],
     CarSpecs(mass=1810, wheelbase=2.86, steerRatio=16.34, centerToFrontRatio=0.5),
   )
+  CHEVROLET_BLAZER = GMPlatformConfig(
+    [GMCarDocs("Chevrolet Blazer 2019-2025", "Driver Assist Package")],
+    CarSpecs(mass=1850, wheelbase=3.10, steerRatio=17.9, centerToFrontRatio=0.4),
+  )
   CHEVROLET_TRAVERSE = GMPlatformConfig(
     [GMCarDocs("Chevrolet Traverse 2023", "Driver Assist Package")],
     CarSpecs(mass=1955, wheelbase=3.07, steerRatio=17.9, centerToFrontRatio=0.4),
   )
+  CHEVROLET_MALIBU_SDGM = GMPlatformConfig(
+    [GMCarDocs("Chevrolet Malibu 2019", "SDGM Harness (Optional SASCM)")],
+    CHEVROLET_MALIBU.specs,
+  )
   BUICK_BABYENCLAVE = GMPlatformConfig(
     [GMCarDocs("Buick Baby Enclave 2020-23", "Driver Assist Package")],
     CarSpecs(mass=2050, wheelbase=2.86, steerRatio=16.0, centerToFrontRatio=0.5),
   )
   CHEVROLET_MALIBU_CC = GMPlatformConfig(
     [GMCarDocs("Chevrolet Malibu 2023 - No-ACC")],
+    CarSpecs(mass=1450, wheelbase=2.8, steerRatio=18.25, centerToFrontRatio=0.4, tireStiffnessFactor=0.997),
+  )
+  CHEVROLET_MALIBU_HYBRID_CC = GMPlatformConfig(
+    [GMCarDocs("Chevrolet Malibu Hybrid 2017 - No-ACC")],
     CarSpecs(mass=1450, wheelbase=2.8, steerRatio=15.8, centerToFrontRatio=0.4),
   )
   CHEVROLET_TRAX = GMPlatformConfig(
     [GMCarDocs("Chevrolet TRAX 2024")],
     CarSpecs(mass=1365, wheelbase=2.7, steerRatio=16.4, centerToFrontRatio=0.4),
   )
+  CHEVROLET_VOLT_2019 = GMPlatformConfig(
+    [GMCarDocs("Chevrolet Volt 2019")],
+    GMCarSpecs(mass=1607, wheelbase=2.69, steerRatio=15.7, centerToFrontRatio=0.45),
+  )
+  CADILLAC_XT6 = GMPlatformConfig(
+    [GMCarDocs("Cadillac XT6 2020", "Driver Assist Package")],
+    GMCarSpecs(mass=2050, wheelbase=2.86, steerRatio=16.5, centerToFrontRatio=0.4),
+  )
 
 
 class CruiseButtons:
@@ -262,6 +309,8 @@ class GMFlags(IntFlag):
   CC_LONG = 2
   NO_CAMERA = 4
   NO_ACCELERATOR_POS_MSG = 8
+  FORCE_BRAKE_C9 = 16
+  SASCM = 32
 
 
 # In a Data Module, an identifier is a string used to recognize an object,
@@ -313,16 +362,18 @@ FW_QUERY_CONFIG = FwQueryConfig(
   extra_ecus=[(Ecu.fwdCamera, 0x24b, None)],
 )
 
-EV_CAR = {CAR.CHEVROLET_VOLT, CAR.CHEVROLET_BOLT_EUV, CAR.CHEVROLET_VOLT_CC, CAR.CHEVROLET_BOLT_CC}
-CC_ONLY_CAR = {CAR.CHEVROLET_VOLT_CC, CAR.CHEVROLET_BOLT_CC, CAR.CHEVROLET_EQUINOX_CC, CAR.CHEVROLET_SUBURBAN_CC, CAR.GMC_YUKON_CC, CAR.CADILLAC_CT6_CC, CAR.CHEVROLET_TRAILBLAZER_CC, CAR.CADILLAC_XT5_CC, CAR.CHEVROLET_MALIBU_CC}
+EV_CAR = {CAR.CHEVROLET_VOLT, CAR.CHEVROLET_VOLT_2019, CAR.CHEVROLET_BOLT_EUV, CAR.CHEVROLET_VOLT_CC, CAR.CHEVROLET_VOLT_CAMERA, CAR.CHEVROLET_BOLT_CC, CAR.CHEVROLET_VOLT_ASCM, CAR.CHEVROLET_MALIBU_HYBRID_CC}
+CC_ONLY_CAR = {CAR.CHEVROLET_VOLT_CC, CAR.CHEVROLET_BOLT_CC, CAR.CHEVROLET_EQUINOX_CC, CAR.CHEVROLET_SUBURBAN_CC, CAR.GMC_YUKON_CC, CAR.CADILLAC_CT6_CC, CAR.CHEVROLET_TRAILBLAZER_CC, CAR.CADILLAC_XT5_CC, CAR.CHEVROLET_MALIBU_CC, CAR.CHEVROLET_MALIBU_HYBRID_CC}
 # CC_ONLY_CAR = set(c for c in CAR if str(c).endswith('_CC'))
 
 # We're integrated at the Safety Data Gateway Module on these cars
-SDGM_CAR = {CAR.CADILLAC_XT4, CAR.CHEVROLET_TRAVERSE, CAR.BUICK_BABYENCLAVE}
+SDGM_CAR = {CAR.CADILLAC_XT4, CAR.CADILLAC_XT6, CAR.CHEVROLET_TRAVERSE, CAR.CHEVROLET_BLAZER, CAR.CHEVROLET_MALIBU_SDGM, CAR.BUICK_BABYENCLAVE, CAR.CHEVROLET_VOLT_2019}
+
+ASCM_INT = {CAR.CHEVROLET_VOLT_ASCM, CAR.GMC_ACADIA_ASCM, CAR.CHEVROLET_MALIBU_ASCM}
 
 # We're integrated at the camera with VOACC on these cars (instead of ASCM w/ OBD-II harness)
-CAMERA_ACC_CAR = {CAR.CHEVROLET_BOLT_EUV, CAR.CHEVROLET_SILVERADO, CAR.CHEVROLET_EQUINOX, CAR.CHEVROLET_TRAILBLAZER, CAR.CHEVROLET_TRAX}
-CAMERA_ACC_CAR.update({CAR.CHEVROLET_VOLT_CC, CAR.CHEVROLET_BOLT_CC, CAR.CHEVROLET_EQUINOX_CC, CAR.GMC_YUKON_CC, CAR.CADILLAC_CT6_CC, CAR.CHEVROLET_TRAILBLAZER_CC, CAR.CADILLAC_XT5_CC, CAR.CHEVROLET_MALIBU_CC})
+CAMERA_ACC_CAR = {CAR.CHEVROLET_BOLT_EUV, CAR.CHEVROLET_SILVERADO, CAR.CHEVROLET_EQUINOX, CAR.CHEVROLET_TRAILBLAZER, CAR.CHEVROLET_TRAX, CAR.CHEVROLET_VOLT_CAMERA, CAR.CHEVROLET_BLAZER}
+CAMERA_ACC_CAR.update({CAR.CHEVROLET_VOLT_CC, CAR.CHEVROLET_BOLT_CC, CAR.CHEVROLET_EQUINOX_CC, CAR.GMC_YUKON_CC, CAR.CADILLAC_CT6_CC, CAR.CHEVROLET_TRAILBLAZER_CC, CAR.CADILLAC_XT5_CC, CAR.CHEVROLET_MALIBU_CC, CAR.CHEVROLET_MALIBU_HYBRID_CC})
 # CAMERA_ACC_CAR.update(CC_ONLY_CAR)
 
 STEER_THRESHOLD = 1.0

selfdrive/car/honda/carcontroller.py

@@ -1,3 +1,4 @@
+import math
 from collections import namedtuple
 
 from cereal import car
@@ -5,10 +6,12 @@ from openpilot.common.numpy_fast import clip, interp
 from openpilot.common.realtime import DT_CTRL
 from opendbc.can.packer import CANPacker
 from openpilot.selfdrive.car import create_gas_interceptor_command
+from openpilot.selfdrive.controls.lib.vehicle_model import ACCELERATION_DUE_TO_GRAVITY
 from openpilot.selfdrive.car.honda import hondacan
 from openpilot.selfdrive.car.honda.values import CruiseButtons, VISUAL_HUD, HONDA_BOSCH, HONDA_BOSCH_RADARLESS, HONDA_NIDEC_ALT_PCM_ACCEL, CarControllerParams
 from openpilot.selfdrive.car.interfaces import CarControllerBase
 from openpilot.selfdrive.controls.lib.drive_helpers import rate_limit
+from openpilot.selfdrive.controls.lib.pid import PIDController
 
 VisualAlert = car.CarControl.HUDControl.VisualAlert
 LongCtrlState = car.CarControl.Actuators.LongControlState
@@ -125,6 +128,10 @@ class CarController(CarControllerBase):
     self.gas = 0.0
     self.brake = 0.0
     self.last_steer = 0.0
+    self.pitch = 0.0
+    self.gasonly_pid = PIDController(k_p=([0,], [0,]),
+                                      k_i=([0., 5., 35.], [1.2, 0.8, 0.5]),
+                                      rate=1 / DT_CTRL / 2)
 
   def update(self, CC, CS, now_nanos, frogpilot_toggles):
     actuators = CC.actuators
@@ -133,6 +140,9 @@ class CarController(CarControllerBase):
     hud_v_cruise = hud_control.setSpeed / conversion if hud_control.speedVisible else 255
     pcm_cancel_cmd = CC.cruiseControl.cancel
 
+    if len(CC.orientationNED) == 3:
+      self.pitch = CC.orientationNED[1]
+
     if CC.longActive:
       accel = actuators.accel
       gas, brake = compute_gas_brake(actuators.accel, CS.out.vEgo, self.CP.carFingerprint)
@@ -173,8 +183,11 @@ class CarController(CarControllerBase):
                                                       CS.CP.openpilotLongitudinalControl))
 
     # wind brake from air resistance decel at high speed
-    wind_brake = interp(CS.out.vEgo, [0.0, 2.3, 35.0], [0.001, 0.002, 0.15])
+    wind_brake_ms2 = interp(CS.out.vEgo, [0.0, 13.4, 22.4, 31.3, 40.2], [0.000, 0.049, 0.136, 0.267, 0.441]) # in m/s2 units
+    hill_brake = math.sin(self.pitch) * ACCELERATION_DUE_TO_GRAVITY
+
     # all of this is only relevant for HONDA NIDEC
+    wind_brake = interp(CS.out.vEgo, [0.0, 2.3, 35.0], [0.001, 0.002, 0.15]) # not in m/s2 units
     max_accel = interp(CS.out.vEgo, self.params.NIDEC_MAX_ACCEL_BP, self.params.NIDEC_MAX_ACCEL_V)
     # TODO this 1.44 is just to maintain previous behavior
     pcm_speed_BP = [-wind_brake,
@@ -217,12 +230,25 @@ class CarController(CarControllerBase):
 
         if self.CP.carFingerprint in HONDA_BOSCH:
           self.accel = clip(accel, self.params.BOSCH_ACCEL_MIN, self.params.BOSCH_ACCEL_MAX)
-          self.gas = interp(accel, self.params.BOSCH_GAS_LOOKUP_BP, self.params.BOSCH_GAS_LOOKUP_V)
+
+          if self.CP.carFingerprint in HONDA_BOSCH_RADARLESS:
+            gas_pedal_force = self.accel # radarless does not need a pid
+          elif (actuators.longControlState == LongCtrlState.pid) and not CS.out.gasPressed: # perform a gas-only pid
+            gas_error = self.accel - CS.out.aEgo
+            self.gasonly_pid.neg_limit = self.params.BOSCH_ACCEL_MIN
+            self.gasonly_pid.pos_limit = self.params.BOSCH_ACCEL_MAX
+            gas_pedal_force = self.gasonly_pid.update(gas_error, speed=CS.out.vEgo, feedforward=self.accel)
+            gas_pedal_force += wind_brake_ms2 + hill_brake
+          else:
+            gas_pedal_force = self.accel
+            self.gasonly_pid.reset()
+            gas_pedal_force += wind_brake_ms2 + hill_brake
+          self.gas = interp(gas_pedal_force, self.params.BOSCH_GAS_LOOKUP_BP, self.params.BOSCH_GAS_LOOKUP_V)
 
           stopping = actuators.longControlState == LongCtrlState.stopping
           self.stopping_counter = self.stopping_counter + 1 if stopping else 0
           can_sends.extend(hondacan.create_acc_commands(self.packer, self.CAN, CC.enabled, CC.longActive, self.accel, self.gas,
-                                                        self.stopping_counter, self.CP.carFingerprint))
+                                                        self.stopping_counter, self.CP.carFingerprint, accel + wind_brake_ms2 + hill_brake))
         else:
           apply_brake = clip(self.brake_last - wind_brake, 0.0, 1.0)
           apply_brake = int(clip(apply_brake * self.params.NIDEC_BRAKE_MAX, 0, self.params.NIDEC_BRAKE_MAX - 1))

selfdrive/car/interfaces.py

@@ -37,7 +37,12 @@ EventName = car.CarEvent.EventName
 MAX_CTRL_SPEED = (V_CRUISE_MAX + 4) * CV.KPH_TO_MS
 ACCEL_MAX = 2.0
 ACCEL_MIN = -3.5
-FRICTION_THRESHOLD = 0.3
+FRICTION_THRESHOLD = 0.09
+
+def get_friction_threshold(v_ego):
+  # Interpolate friction threshold from 0.09 at 50 mph to 0.15 at 75 mph
+  from openpilot.common.numpy_fast import interp
+  return interp(v_ego, [1 * CV.MPH_TO_MS, 75 * CV.MPH_TO_MS], [0.12, 0.25])
 
 TORQUE_PARAMS_PATH = os.path.join(BASEDIR, 'selfdrive/car/torque_data/params.toml')
 TORQUE_OVERRIDE_PATH = os.path.join(BASEDIR, 'selfdrive/car/torque_data/override.toml')
@@ -52,6 +57,7 @@ GEAR_SHIFTER_MAP: dict[str, car.CarState.GearShifter] = {
   'D': GearShifter.drive, 'DRIVE': GearShifter.drive,
   'S': GearShifter.sport, 'SPORT': GearShifter.sport,
   'L': GearShifter.low, 'LOW': GearShifter.low,
+  'L2': GearShifter.low, 'L3': GearShifter.low,
   'B': GearShifter.brake, 'BRAKE': GearShifter.brake,
 }
 
@@ -146,14 +152,22 @@ class CarInterfaceBase(ABC):
 
     ret = cls._get_params(ret, candidate, fingerprint, car_fw, experimental_long, docs, frogpilot_toggles)
 
+    trailer_load_kg = getattr(frogpilot_toggles, "trailer_load_kg", 0)
+
     # Vehicle mass is published curb weight plus assumed payload such as a human driver; notCars have no assumed payload
     if not ret.notCar:
+      ret.mass = ret.mass + trailer_load_kg
       ret.mass = ret.mass + STD_CARGO_KG
 
     # Set params dependent on values set by the car interface
     ret.rotationalInertia = scale_rot_inertia(ret.mass, ret.wheelbase)
     ret.tireStiffnessFront, ret.tireStiffnessRear = scale_tire_stiffness(ret.mass, ret.wheelbase, ret.centerToFront, ret.tireStiffnessFactor)
 
+    # FrogPilot variables
+    toggles_to_check = ("force_torque_controller", "nnff", "nnff_lite")
+    if ret.steerControlType != car.CarParams.SteerControlType.angle and any(getattr(frogpilot_toggles, toggle, False) for toggle in toggles_to_check):
+      CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
+
     return ret
 
   @classmethod
@@ -173,6 +187,7 @@ class CarInterfaceBase(ABC):
 
       elif platform in GMCAR:
         fp_ret.canUsePedal = True
+        fp_ret.canUseSASCM = True
 
       elif platform in HondaCAR:
         if candidate == HondaCAR.HONDA_CLARITY:
@@ -216,14 +231,6 @@ class CarInterfaceBase(ABC):
         fp_ret.canUsePedal = not CP.autoResumeSng
         fp_ret.canUseSDSU = not CP.enableDsu and candidate not in UNSUPPORTED_DSU_CAR and candidate not in TSS2_CAR
 
-      if CP.steerControlType != car.CarParams.SteerControlType.angle:
-        if CP.lateralTuning.which() == "pid" and (frogpilot_toggles.force_torque_controller or frogpilot_toggles.nnff or frogpilot_toggles.nnff_lite):
-          CarInterfaceBase.configure_torque_tune(candidate, fp_ret.lateralTuning)
-        elif CP.lateralTuning.which() == "torque":
-          CarInterfaceBase.configure_torque_tune(candidate, fp_ret.lateralTuning)
-        else:
-          fp_ret.lateralTuning.init("pid")
-
       fp_ret.openpilotLongitudinalControlDisabled = frogpilot_toggles.disable_openpilot_long
 
     return fp_ret
@@ -285,7 +292,7 @@ class CarInterfaceBase(ABC):
     ret.vEgoStopping = 0.5
     ret.vEgoStarting = 0.5
     ret.stoppingControl = True
-    ret.longitudinalTuning.kf = 1.
+    ret.longitudinalTuning.kfDEPRECATED = 1.
     ret.longitudinalTuning.kpBP = [0.]
     ret.longitudinalTuning.kpV = [0.]
     ret.longitudinalTuning.kiBP = [0.]
@@ -301,9 +308,9 @@ class CarInterfaceBase(ABC):
 
     tune.init('torque')
     tune.torque.useSteeringAngle = use_steering_angle
-    tune.torque.kf = 1.0
-    tune.torque.kp = 1.0
+    tune.torque.kp = 0.6
     tune.torque.ki = 0.3
+    tune.torque.kd = 0.0
     tune.torque.friction = params['FRICTION']
     tune.torque.latAccelFactor = params['LAT_ACCEL_FACTOR']
     tune.torque.latAccelOffset = 0.0

selfdrive/car/torque_data/override.toml

@@ -43,9 +43,11 @@ legend = ["LAT_ACCEL_FACTOR", "MAX_LAT_ACCEL_MEASURED", "FRICTION"]
 "CADILLAC_ESCALADE" = [1.899999976158142, 1.842270016670227, 0.1120000034570694]
 "CADILLAC_ESCALADE_ESV_2019" = [1.15, 1.3, 0.2]
 "CADILLAC_XT4" = [1.45, 1.6, 0.2]
-"CHEVROLET_BOLT_EUV" = [2.0, 2.0, 0.05]
-"CHEVROLET_MALIBU_CC" = [1.85, 1.85, 0.075]
+"CADILLAC_XT6" = [1.33, 1.9, 0.16]
+"CHEVROLET_BOLT_EUV" = [1.0, 2.0, 0.175]
+"CHEVROLET_MALIBU_CC" = [1.58, 1.8422651988094612, 0.205]
 "CHEVROLET_SILVERADO" = [1.9, 1.9, 0.112]
+"CHEVROLET_BLAZER" = [1.33, 1.33, 0.18]
 "CHEVROLET_TRAILBLAZER" = [1.33, 1.9, 0.16]
 "CHEVROLET_TRAVERSE" = [1.33, 1.33, 0.18]
 "CHEVROLET_EQUINOX" = [2.5, 2.5, 0.05]

selfdrive/car/torque_data/params.toml

@@ -5,6 +5,7 @@ legend = ["LAT_ACCEL_FACTOR", "MAX_LAT_ACCEL_MEASURED", "FRICTION"]
 "AUDI_A3_MK3" = [1.5122414863077502, 1.7443517531719404, 0.15194151892450905]
 "AUDI_Q3_MK2" = [1.4439223359448605, 1.2254955789112076, 0.1413798895978097]
 "CHEVROLET_VOLT" = [1.5961527626411784, 1.8422651988094612, 0.1572393918005158]
+"CHEVROLET_MALIBU_HYBRID_CC" = [1.5961527626411784, 1.8422651988094612, 0.1572393918005158]
 "CHRYSLER_PACIFICA_2018" = [2.07140, 1.3366521181047952, 0.13776367250652022]
 "CHRYSLER_PACIFICA_2020" = [1.86206, 1.509076559398423, 0.14328246159386085]
 "CHRYSLER_PACIFICA_2017_HYBRID" = [1.79422, 1.06831764583744, 0.116237]

selfdrive/car/torque_data/substitute.toml

@@ -56,8 +56,14 @@ legend = ["LAT_ACCEL_FACTOR", "MAX_LAT_ACCEL_MEASURED", "FRICTION"]
 "CADILLAC_ESCALADE_ESV" = "CHEVROLET_VOLT"
 "CADILLAC_ATS" = "CHEVROLET_VOLT"
 "CHEVROLET_MALIBU" = "CHEVROLET_VOLT"
+"CHEVROLET_MALIBU_ASCM" = "CHEVROLET_VOLT"
+"CHEVROLET_MALIBU_SDGM" = "CHEVROLET_VOLT"
 "HOLDEN_ASTRA" = "CHEVROLET_VOLT"
 "CHEVROLET_VOLT_CC" = "CHEVROLET_VOLT"
+"CHEVROLET_VOLT_CAMERA" = "CHEVROLET_VOLT"
+"CHEVROLET_VOLT_ASCM" = "CHEVROLET_VOLT"
+"GMC_ACADIA_ASCM" = "GMC_ACADIA"
+"CHEVROLET_VOLT_2019" = "CHEVROLET_VOLT"
 "CHEVROLET_BOLT_CC" = "CHEVROLET_BOLT_EUV"
 "CHEVROLET_EQUINOX_CC" = "CHEVROLET_EQUINOX"
 "CHEVROLET_SUBURBAN" = "CHEVROLET_SILVERADO"
@@ -66,7 +72,6 @@ legend = ["LAT_ACCEL_FACTOR", "MAX_LAT_ACCEL_MEASURED", "FRICTION"]
 "CHEVROLET_TRAX" = "CHEVROLET_VOLT"
 "CADILLAC_CT6_CC" = "CHEVROLET_VOLT"
 "CADILLAC_XT5_CC" = "GMC_ACADIA"
-
 "SKODA_FABIA_MK4" = "VOLKSWAGEN_GOLF_MK7"
 "SKODA_OCTAVIA_MK3" = "SKODA_SUPERB_MK3"
 "SKODA_KODIAQ_MK1" = "SKODA_SUPERB_MK3"

selfdrive/car/toyota/carcontroller.py

@@ -53,7 +53,7 @@ def get_long_tune(CP, params):
   kiBP = [2., 5.]
   kiV = [0.5, 0.25]
 
-  return PIDController(0.0, (kiBP, kiV), k_f=1.0,
+  return PIDController(0.0, (kiBP, kiV),
                        pos_limit=params.ACCEL_MAX, neg_limit=params.ACCEL_MIN,
                        rate=1 / (DT_CTRL * 3))
 

selfdrive/controls/controlsd.py

@@ -29,10 +29,12 @@ from openpilot.selfdrive.controls.lib.latcontrol_angle import LatControlAngle, S
 from openpilot.selfdrive.controls.lib.latcontrol_torque import LatControlTorque
 from openpilot.selfdrive.controls.lib.longcontrol import LongControl
 from openpilot.selfdrive.controls.lib.vehicle_model import VehicleModel
+from openpilot.frogpilot.tinygrad_modeld.tinygrad_modeld import LAT_SMOOTH_SECONDS
 
 from openpilot.system.hardware import HARDWARE
 
 from openpilot.frogpilot.common.frogpilot_variables import get_frogpilot_toggles, params_memory
+from openpilot.frogpilot.controls.lib.neural_network_feedforward import LatControlNNFF
 
 SOFT_DISABLE_TIME = 3  # seconds
 LDW_MIN_SPEED = 31 * CV.MPH_TO_MS
@@ -135,11 +137,11 @@ class Controls:
 
     self.LaC: LatControl
     if self.CP.steerControlType == car.CarParams.SteerControlType.angle:
-      self.LaC = LatControlAngle(self.CP, self.CI)
-    elif self.FPCP.lateralTuning.which() == 'pid':
-      self.LaC = LatControlPID(self.CP, self.CI)
-    elif self.FPCP.lateralTuning.which() == 'torque':
-      self.LaC = LatControlTorque(self.CP, self.FPCP, self.CI)
+      self.LaC = LatControlAngle(self.CP, self.CI, DT_CTRL)
+    elif self.CP.lateralTuning.which() == 'pid':
+      self.LaC = LatControlPID(self.CP, self.CI, DT_CTRL)
+    elif self.CP.lateralTuning.which() == 'torque':
+      self.LaC = LatControlTorque(self.CP, self.CI, DT_CTRL)
 
     self.initialized = False
     self.state = State.disabled
@@ -204,6 +206,12 @@ class Controls:
 
     self.frogpilot_toggles = get_frogpilot_toggles()
 
+    if self.CP.lateralTuning.which() == "torque" and (self.frogpilot_toggles.nnff or self.frogpilot_toggles.nnff_lite):
+      self.LaC = LatControlNNFF(self.CP, self.CI, DT_CTRL)
+
+
+    self.frogpilot_toggles.is_metric = self.is_metric
+
   def set_initial_state(self):
     if REPLAY:
       controls_state = self.params.get("ReplayControlsState")
@@ -613,14 +621,36 @@ class Controls:
     self.curvature = -self.VM.calc_curvature(steer_angle_without_offset, CS.vEgo, lp.roll)
 
     # Update Torque Params
-    if self.FPCP.lateralTuning.which() == 'torque':
+    if self.CP.lateralTuning.which() == 'torque':
       torque_params = self.sm['liveTorqueParameters']
-      if self.sm.all_checks(['liveTorqueParameters']) and (torque_params.useParams or self.frogpilot_toggles.force_auto_tune):
-        self.LaC.update_live_torque_params(torque_params.latAccelFactorFiltered, torque_params.latAccelOffsetFiltered,
-                                           torque_params.frictionCoefficientFiltered)
 
-      if self.sm.updated['liveDelay'] and (self.frogpilot_toggles.nnff or self.frogpilot_toggles.nnff_lite):
-        self.LaC.nnff.update_live_delay(self.sm['liveDelay'].lateralDelay)
+      allow_lat_accel_learning = self.CP.carName in ['toyota', 'hyundai']
+      allow_friction_learning = (allow_lat_accel_learning or self.CP.carName in ['gm'])
+      use_live_params = self.sm.all_checks(['liveTorqueParameters']) and (torque_params.useParams or self.frogpilot_toggles.force_auto_tune)
+
+      # Defaults pulled from manual tuning values
+      lat_accel_factor = self.params.get_float("SteerLatAccel")
+      friction = self.params.get_float("SteerFriction")
+      lat_accel_offset = self.CP.lateralTuning.torque.latAccelOffset
+
+      # Apply user overrides first
+      if self.frogpilot_toggles.use_custom_latAccelFactor:
+        lat_accel_factor = self.frogpilot_toggles.latAccelFactor
+      if self.frogpilot_toggles.use_custom_friction:
+        friction = self.frogpilot_toggles.friction
+
+      # Layer in live values only for parameters the platform allows to learn and only when not overridden
+      if use_live_params:
+        if allow_lat_accel_learning and not self.frogpilot_toggles.use_custom_latAccelFactor:
+          lat_accel_factor = torque_params.latAccelFactorFiltered
+          lat_accel_offset = torque_params.latAccelOffsetFiltered
+        if allow_friction_learning and not self.frogpilot_toggles.use_custom_friction:
+          friction = torque_params.frictionCoefficientFiltered
+
+      self.LaC.update_live_torque_params(lat_accel_factor, lat_accel_offset, friction)
+
+      if self.sm.updated['liveDelay'] and hasattr(self.LaC, "update_live_delay"):
+        self.LaC.update_live_delay(self.sm['liveDelay'].lateralDelay)
 
     long_plan = self.sm['longitudinalPlan']
     model_v2 = self.sm['modelV2']
@@ -671,11 +701,12 @@ class Controls:
       # Reset desired curvature to current to avoid violating the limits on engage
       new_desired_curvature = model_v2.action.desiredCurvature if CC.latActive else self.curvature
       self.desired_curvature, curvature_limited = clip_curvature(CS.vEgo, self.desired_curvature, new_desired_curvature, lp.roll)
+      lat_delay = self.sm["liveDelay"].lateralDelay + LAT_SMOOTH_SECONDS
 
       actuators.curvature = self.desired_curvature
       steer, steeringAngleDeg, lac_log = self.LaC.update(CC.latActive, CS, self.VM, lp,
                                                          self.steer_limited_by_safety, self.desired_curvature,
-                                                         curvature_limited,
+                                                         curvature_limited, lat_delay,
                                                          self.sm['liveLocationKalman'],
                                                          self.sm['modelV2'],
                                                          self.frogpilot_toggles)
@@ -715,8 +746,8 @@ class Controls:
       desired_lateral_accel = model_v2.action.desiredCurvature * (clipped_speed**2)
       undershooting = abs(desired_lateral_accel) / abs(1e-3 + actual_lateral_accel) > 1.2
       turning = abs(desired_lateral_accel) > 1.0
-      # TODO: lac.saturated includes speed and other checks, should be pulled out
-      if undershooting and turning and lac_log.saturated:
+      commanded_torque_at_max = abs(lac_log.output) > 0.99
+      if undershooting and turning and (lac_log.saturated or commanded_torque_at_max):
         if self.frogpilot_toggles.goat_scream_alert:
           self.frogpilot_events.add(FrogPilotEventName.goatSteerSaturated)
         else:
@@ -764,7 +795,7 @@ class Controls:
     if self.frogpilot_toggles.conditional_experimental_mode or self.frogpilot_toggles.slc_fallback_experimental_mode:
       self.experimental_mode = self.sm['frogpilotPlan'].experimentalMode
 
-    if hasattr(self.LaC, "pid"):
+    if hasattr(self.LaC, "pid") and self.CP.lateralTuning.which() != "pid":
       self.LaC.pid._k_p = self.frogpilot_toggles.steerKp
 
     # Update FrogPilot variables
@@ -888,7 +919,7 @@ class Controls:
     controlsState.experimentalMode = self.experimental_mode
     controlsState.personality = self.personality
 
-    lat_tuning = self.FPCP.lateralTuning.which()
+    lat_tuning = self.CP.lateralTuning.which()
     if self.joystick_mode:
       controlsState.lateralControlState.debugState = lac_log
     elif self.CP.steerControlType == car.CarParams.SteerControlType.angle:

selfdrive/controls/lib/drive_helpers.py

@@ -189,7 +189,7 @@ def smooth_value(val, prev_val, tau, dt=DT_MDL):
   alpha = 1 - np.exp(-dt/tau) if tau > 0 else 1
   return alpha * val + (1 - alpha) * prev_val
 
-def clip_curvature(v_ego, prev_curvature, new_curvature, roll):
+def clip_curvature(v_ego, prev_curvature, new_curvature, roll) -> tuple[float, bool]:
   # This function respects ISO lateral jerk and acceleration limits + a max curvature
   v_ego = max(v_ego, MIN_SPEED)
   max_curvature_rate = MAX_LATERAL_JERK / (v_ego ** 2)  # inexact calculation, check https://github.com/commaai/openpilot/pull/24755
@@ -225,7 +225,7 @@ def get_speed_error(modelV2: log.ModelDataV2, v_ego: float) -> float:
   return 0.0
 
 
-def get_accel_from_plan(speeds, accels, t_idxs, action_t=DT_MDL, vEgoStopping=0.05):
+def get_accel_from_plan_tomb_raider(speeds, accels, t_idxs, action_t=DT_MDL, vEgoStopping=0.05):
   if len(speeds) == len(t_idxs):
     v_now = speeds[0]
     a_now = accels[0]

selfdrive/controls/lib/latcontrol.py

@@ -1,33 +1,31 @@
 import numpy as np
 from abc import abstractmethod, ABC
 
-from openpilot.common.realtime import DT_CTRL
-
 MIN_LATERAL_CONTROL_SPEED = 0.3  # m/s
 
 
 class LatControl(ABC):
-  def __init__(self, CP, CI):
-    self.sat_count_rate = 1.0 * DT_CTRL
+  def __init__(self, CP, CI, dt):
+    self.dt = dt
     self.sat_limit = CP.steerLimitTimer
-    self.sat_count = 0.
+    self.sat_time = 0.
     self.sat_check_min_speed = 10.
 
     # we define the steer torque scale as [-1.0...1.0]
     self.steer_max = 1.0
 
   @abstractmethod
-  def update(self, active, CS, VM, params, steer_limited_by_safety, desired_curvature, curvature_limited, llk, model_data, frogpilot_toggles):
+  def update(self, active: bool, CS, VM, params, steer_limited_by_safety: bool, desired_curvature: float, curvature_limited: bool, lat_delay: float, llk, model_data, frogpilot_toggles):
     pass
 
   def reset(self):
-    self.sat_count = 0.
+    self.sat_time = 0.
 
   def _check_saturation(self, saturated, CS, steer_limited_by_safety, curvature_limited):
     # Saturated only if control output is not being limited by car torque/angle rate limits
     if (saturated or curvature_limited) and CS.vEgo > self.sat_check_min_speed and not steer_limited_by_safety and not CS.steeringPressed:
-      self.sat_count += self.sat_count_rate
+      self.sat_time += self.dt
     else:
-      self.sat_count -= self.sat_count_rate
-    self.sat_count = np.clip(self.sat_count, 0.0, self.sat_limit)
-    return self.sat_count > (self.sat_limit - 1e-3)
+      self.sat_time -= self.dt
+    self.sat_time = np.clip(self.sat_time, 0.0, self.sat_limit)
+    return self.sat_time > (self.sat_limit - 1e-3)

selfdrive/controls/lib/latcontrol_angle.py

@@ -8,12 +8,12 @@ STEER_ANGLE_SATURATION_THRESHOLD = 2.5  # Degrees
 
 
 class LatControlAngle(LatControl):
-  def __init__(self, CP, CI):
-    super().__init__(CP, CI)
+  def __init__(self, CP, CI, dt):
+    super().__init__(CP, CI, dt)
     self.sat_check_min_speed = 5.
     self.use_steer_limited_by_safety = CP.carName == "tesla"
 
-  def update(self, active, CS, VM, params, steer_limited_by_safety, desired_curvature, curvature_limited, llk, model_data, frogpilot_toggles):
+  def update(self, active, CS, VM, params, steer_limited_by_safety, desired_curvature, curvature_limited, lat_delay, llk, model_data, frogpilot_toggles):
     angle_log = log.ControlsState.LateralAngleState.new_message()
 
     if not active:

selfdrive/controls/lib/latcontrol_pid.py

@@ -1,19 +1,23 @@
 import math
 
 from cereal import log
-from openpilot.selfdrive.controls.lib.latcontrol import LatControl
+from openpilot.selfdrive.controls.lib.latcontrol import LatControl, MIN_LATERAL_CONTROL_SPEED
 from openpilot.selfdrive.controls.lib.pid import PIDController
 
 
 class LatControlPID(LatControl):
-  def __init__(self, CP, CI):
-    super().__init__(CP, CI)
+  def __init__(self, CP, CI, dt):
+    super().__init__(CP, CI, dt)
+    self.steer_release_i_decay = 0.8
+    self.prev_steering_pressed = False
     self.pid = PIDController((CP.lateralTuning.pid.kpBP, CP.lateralTuning.pid.kpV),
                              (CP.lateralTuning.pid.kiBP, CP.lateralTuning.pid.kiV),
-                             k_f=CP.lateralTuning.pid.kf, pos_limit=self.steer_max, neg_limit=-self.steer_max)
+                             pos_limit=self.steer_max, neg_limit=-self.steer_max)
+    self.ff_factor = CP.lateralTuning.pid.kf
     self.get_steer_feedforward = CI.get_steer_feedforward_function()
+    self.low_speed_reset_threshold = max(CP.minSteerSpeed, MIN_LATERAL_CONTROL_SPEED)
 
-  def update(self, active, CS, VM, params, steer_limited_by_safety, desired_curvature, curvature_limited, llk, model_data, frogpilot_toggles):
+  def update(self, active, CS, VM, params, steer_limited_by_safety, desired_curvature, curvature_limited, lat_delay, llk, model_data, frogpilot_toggles):
     pid_log = log.ControlsState.LateralPIDState.new_message()
     pid_log.steeringAngleDeg = float(CS.steeringAngleDeg)
     pid_log.steeringRateDeg = float(CS.steeringRateDeg)
@@ -27,11 +31,17 @@ class LatControlPID(LatControl):
     if not active:
       output_torque = 0.0
       pid_log.active = False
+      self.pid.reset()
 
     else:
+      if self.prev_steering_pressed and not CS.steeringPressed:
+        self.pid.i *= self.steer_release_i_decay
+
       # offset does not contribute to resistive torque
-      ff = self.get_steer_feedforward(angle_steers_des_no_offset, CS.vEgo)
-      freeze_integrator = steer_limited_by_safety or CS.steeringPressed or CS.vEgo < 5
+      ff = self.ff_factor * self.get_steer_feedforward(angle_steers_des_no_offset, CS.vEgo)
+      if CS.vEgo < self.low_speed_reset_threshold:
+        self.pid.reset()
+      freeze_integrator = steer_limited_by_safety or CS.steeringPressed or CS.vEgo < self.low_speed_reset_threshold
 
       output_torque = self.pid.update(error,
                                 feedforward=ff,
@@ -45,4 +55,6 @@ class LatControlPID(LatControl):
       pid_log.output = float(output_torque)
       pid_log.saturated = bool(self._check_saturation(self.steer_max - abs(output_torque) < 1e-3, CS, steer_limited_by_safety, curvature_limited))
 
+    self.prev_steering_pressed = CS.steeringPressed
+
     return output_torque, angle_steers_des, pid_log

selfdrive/controls/lib/latcontrol_torque.py

@@ -1,45 +1,60 @@
 import math
 import numpy as np
+from collections import deque
 
 from cereal import log
-from openpilot.selfdrive.controls.lib.drive_helpers import get_friction
-from openpilot.selfdrive.car.interfaces import FRICTION_THRESHOLD
-from openpilot.selfdrive.controls.lib.latcontrol import LatControl
+from openpilot.selfdrive.car.interfaces import FRICTION_THRESHOLD, get_friction_threshold
+from openpilot.selfdrive.controls.lib.drive_helpers import MIN_SPEED, get_friction
+from openpilot.common.filter_simple import FirstOrderFilter
+from openpilot.selfdrive.controls.lib.latcontrol import LatControl, MIN_LATERAL_CONTROL_SPEED
 from openpilot.selfdrive.controls.lib.pid import PIDController
 from openpilot.selfdrive.controls.lib.vehicle_model import ACCELERATION_DUE_TO_GRAVITY
 
-from openpilot.frogpilot.controls.lib.neural_network_feedforward import LOW_SPEED_Y_NN, NeuralNetworkFeedforward
-
 # At higher speeds (25+mph) we can assume:
 # Lateral acceleration achieved by a specific car correlates to
 # torque applied to the steering rack. It does not correlate to
 # wheel slip, or to speed.
 
 # This controller applies torque to achieve desired lateral
-# accelerations. To compensate for the low speed effects we
-# use a LOW_SPEED_FACTOR in the error. Additionally, there is
-# friction in the steering wheel that needs to be overcome to
-# move it at all, this is compensated for too.
+# accelerations. To compensate for the low speed effects the
+# proportional gain is increased at low speeds by the PID controller.
+# Additionally, there is friction in the steering wheel that needs
+# to be overcome to move it at all, this is compensated for too.
+
+KP = 0.6
+KI = 0.3
+
+INTERP_SPEEDS = [1, 1.5, 2.0, 3.0, 5, 7.5, 10, 15, 30]
+KP_INTERP = [250, 120, 65, 30, 11.5, 5.5, 3.5, 2.0, KP]
 
 LOW_SPEED_X = [0, 10, 20, 30]
-LOW_SPEED_Y = [15, 13, 10, 5]
+LOW_SPEED_Y = [12, 10.5, 8, 5]
+MAX_LAT_JERK_UP = 2.5            # m/s^3
 
+LP_FILTER_CUTOFF_HZ = 1.2
+JERK_LOOKAHEAD_SECONDS = 0.19
+JERK_GAIN = 0.22
+LAT_ACCEL_REQUEST_BUFFER_SECONDS = 1.0
+VERSION = 2
 
 class LatControlTorque(LatControl):
-  def __init__(self, CP, FPCP, CI):
-    super().__init__(CP, CI)
-    self.torque_params = FPCP.lateralTuning.torque
+  def __init__(self, CP, CI, dt):
+    super().__init__(CP, CI, dt)
+    self.steer_release_i_decay = 0.8
+    self.prev_steering_pressed = False
+    self.torque_params = CP.lateralTuning.torque
     self.torque_from_lateral_accel = CI.torque_from_lateral_accel()
     self.lateral_accel_from_torque = CI.lateral_accel_from_torque()
-    self.pid = PIDController(self.torque_params.kp, self.torque_params.ki,
-                             k_f=self.torque_params.kf)
+    self.pid = PIDController([INTERP_SPEEDS, KP_INTERP], KI, rate=1/self.dt)
     self.update_limits()
     self.steering_angle_deadzone_deg = self.torque_params.steeringAngleDeadzoneDeg
-
-    # FrogPilot variables
-    self.nnff = NeuralNetworkFeedforward(CP, self)
-
-    self.nnff_loaded = self.nnff.lat_torque_nn_model != None
+    self.lat_accel_request_buffer_len = int(LAT_ACCEL_REQUEST_BUFFER_SECONDS / self.dt)
+    self.lat_accel_request_buffer = deque([0.] * self.lat_accel_request_buffer_len , maxlen=self.lat_accel_request_buffer_len)
+    self.lookahead_frames = int(JERK_LOOKAHEAD_SECONDS / self.dt)
+    self.jerk_filter = FirstOrderFilter(0.0, 1 / (2 * np.pi * LP_FILTER_CUTOFF_HZ), self.dt)
+    self.previous_measurement = 0.0
+    self.measurement_rate_filter = FirstOrderFilter(0.0, 1 / (2 * np.pi * (MAX_LAT_JERK_UP - 0.5)), self.dt)
+    self.low_speed_reset_threshold = max(CP.minSteerSpeed, MIN_LATERAL_CONTROL_SPEED)
 
   def update_live_torque_params(self, latAccelFactor, latAccelOffset, friction):
     self.torque_params.latAccelFactor = latAccelFactor
@@ -51,50 +66,57 @@ class LatControlTorque(LatControl):
     self.pid.set_limits(self.lateral_accel_from_torque(self.steer_max, self.torque_params),
                         self.lateral_accel_from_torque(-self.steer_max, self.torque_params))
 
-  def update(self, active, CS, VM, params, steer_limited_by_safety, desired_curvature, curvature_limited, llk, model_data, frogpilot_toggles):
+  def update(self, active, CS, VM, params, steer_limited_by_safety, desired_curvature, curvature_limited, lat_delay, llk, model_data, frogpilot_toggles):
     pid_log = log.ControlsState.LateralTorqueState.new_message()
+    pid_log.version = VERSION
     if not active:
       output_torque = 0.0
       pid_log.active = False
+      self.pid.reset()
+      self.previous_measurement = 0.0
+      self.measurement_rate_filter.x = 0.0
+      self.lat_accel_request_buffer = deque([0.] * self.lat_accel_request_buffer_len , maxlen=self.lat_accel_request_buffer_len)
     else:
-      actual_curvature = -VM.calc_curvature(math.radians(CS.steeringAngleDeg - params.angleOffsetDeg), CS.vEgo, params.roll)
+      if self.prev_steering_pressed and not CS.steeringPressed:
+        self.pid.i *= self.steer_release_i_decay
+
+      measured_curvature = -VM.calc_curvature(math.radians(CS.steeringAngleDeg - params.angleOffsetDeg), CS.vEgo, params.roll)
       roll_compensation = params.roll * ACCELERATION_DUE_TO_GRAVITY
       curvature_deadzone = abs(VM.calc_curvature(math.radians(self.steering_angle_deadzone_deg), CS.vEgo, 0.0))
-
-      desired_lateral_accel = desired_curvature * CS.vEgo ** 2
-      actual_lateral_accel = actual_curvature * CS.vEgo ** 2
       lateral_accel_deadzone = curvature_deadzone * CS.vEgo ** 2
 
-      low_speed_factor = np.interp(CS.vEgo, LOW_SPEED_X, LOW_SPEED_Y_NN if frogpilot_toggles.nnff else LOW_SPEED_Y)**2
-      setpoint = desired_lateral_accel + low_speed_factor * desired_curvature
-      measurement = actual_lateral_accel + low_speed_factor * actual_curvature
-      gravity_adjusted_lateral_accel = desired_lateral_accel - roll_compensation
+      delay_frames = int(np.clip(lat_delay / self.dt, 1, self.lat_accel_request_buffer_len))
+      expected_lateral_accel = self.lat_accel_request_buffer[-delay_frames]
+      future_desired_lateral_accel = desired_curvature * CS.vEgo ** 2
+      self.lat_accel_request_buffer.append(future_desired_lateral_accel)
+      raw_lateral_jerk = (future_desired_lateral_accel - expected_lateral_accel) / max(lat_delay, self.dt)
+      raw_lateral_jerk = np.clip(raw_lateral_jerk, -MAX_LAT_JERK_UP, MAX_LAT_JERK_UP)
+      desired_lateral_jerk = np.clip(self.jerk_filter.update(raw_lateral_jerk), -MAX_LAT_JERK_UP, MAX_LAT_JERK_UP)
+      gravity_adjusted_future_lateral_accel = future_desired_lateral_accel - roll_compensation
+      setpoint = expected_lateral_accel + desired_lateral_jerk * lat_delay
 
-      if self.nnff_loaded and frogpilot_toggles.nnff or frogpilot_toggles.nnff_lite:
-        pid_log, ff = self.nnff.compute_nnff(
-          CS, VM, actual_lateral_accel, desired_lateral_accel, gravity_adjusted_lateral_accel, lateral_accel_deadzone,
-          llk, measurement, model_data, params, pid_log, roll_compensation, setpoint, frogpilot_toggles
-        )
+      measurement = measured_curvature * CS.vEgo ** 2
+      measurement_rate = self.measurement_rate_filter.update((measurement - self.previous_measurement) / self.dt)
+      measurement_rate = np.clip(measurement_rate, -MAX_LAT_JERK_UP, MAX_LAT_JERK_UP)
+      self.previous_measurement = measurement
 
-        freeze_integrator = steer_limited_by_safety or CS.steeringPressed or CS.vEgo < 5
-        output_torque = self.pid.update(pid_log.error,
-                                        feedforward=ff,
-                                        speed=CS.vEgo,
-                                        freeze_integrator=freeze_integrator)
-      else:
-        # do error correction in lateral acceleration space, convert at end to handle non-linear torque responses correctly
-        pid_log.error = float(setpoint - measurement)
-        ff = gravity_adjusted_lateral_accel
-        # latAccelOffset corrects roll compensation bias from device roll misalignment relative to car roll
-        ff -= self.torque_params.latAccelOffset
-        ff += get_friction(desired_lateral_accel - actual_lateral_accel, lateral_accel_deadzone, FRICTION_THRESHOLD, self.torque_params)
+      low_speed_factor = (np.interp(CS.vEgo, LOW_SPEED_X, LOW_SPEED_Y) / max(CS.vEgo, MIN_SPEED)) ** 2
+      current_kp = np.interp(CS.vEgo, self.pid._k_p[0], self.pid._k_p[1])
+      error = setpoint - measurement
+      error_with_lsf = error * (1 + low_speed_factor / max(current_kp, 1e-3))
 
-        freeze_integrator = steer_limited_by_safety or CS.steeringPressed or CS.vEgo < 5
-        output_lataccel = self.pid.update(pid_log.error,
-                                        feedforward=ff,
-                                        speed=CS.vEgo,
-                                        freeze_integrator=freeze_integrator)
-        output_torque = self.torque_from_lateral_accel(output_lataccel, self.torque_params)
+      # do error correction in lateral acceleration space, convert at end to handle non-linear torque responses correctly
+      pid_log.error = float(error_with_lsf)
+      ff = gravity_adjusted_future_lateral_accel
+      # latAccelOffset corrects roll compensation bias from device roll misalignment relative to car roll
+      ff -= self.torque_params.latAccelOffset
+      ff += get_friction(error_with_lsf + JERK_GAIN * desired_lateral_jerk, lateral_accel_deadzone, get_friction_threshold(CS.vEgo), self.torque_params)
+
+      if CS.vEgo < self.low_speed_reset_threshold:
+        self.pid.reset()
+      freeze_integrator = steer_limited_by_safety or CS.steeringPressed or CS.vEgo < self.low_speed_reset_threshold
+      output_lataccel = self.pid.update(pid_log.error, error_rate=-measurement_rate, speed=CS.vEgo, feedforward=ff, freeze_integrator=freeze_integrator)
+      output_torque = self.torque_from_lateral_accel(output_lataccel, self.torque_params)
 
       pid_log.active = True
       pid_log.p = float(self.pid.p)
@@ -102,9 +124,12 @@ class LatControlTorque(LatControl):
       pid_log.d = float(self.pid.d)
       pid_log.f = float(self.pid.f)
       pid_log.output = float(-output_torque)  # TODO: log lat accel?
-      pid_log.actualLateralAccel = float(actual_lateral_accel)
-      pid_log.desiredLateralAccel = float(desired_lateral_accel)
+      pid_log.actualLateralAccel = float(measurement)
+      pid_log.desiredLateralAccel = float(setpoint)
+      pid_log.desiredLateralJerk = float(desired_lateral_jerk)
       pid_log.saturated = bool(self._check_saturation(self.steer_max - abs(output_torque) < 1e-3, CS, steer_limited_by_safety, curvature_limited))
 
+    self.prev_steering_pressed = CS.steeringPressed
+
     # TODO left is positive in this convention
     return -output_torque, 0.0, pid_log

selfdrive/controls/lib/longcontrol.py

@@ -4,6 +4,8 @@ from openpilot.common.realtime import DT_CTRL
 from openpilot.selfdrive.controls.lib.drive_helpers import CONTROL_N, apply_deadzone
 from openpilot.selfdrive.controls.lib.pid import PIDController
 from openpilot.selfdrive.modeld.constants import ModelConstants
+from openpilot.common.filter_simple import FirstOrderFilter
+from openpilot.selfdrive.car.gm.values import CarControllerParams
 
 CONTROL_N_T_IDX = ModelConstants.T_IDXS[:CONTROL_N]
 
@@ -85,17 +87,51 @@ def long_control_state_trans_old_long(CP, active, long_control_state, v_ego, v_t
 
   return long_control_state
 
-
 class LongControl:
   def __init__(self, CP):
     self.CP = CP
     self.long_control_state = LongCtrlState.off
+    self.experimental_mode = False
+    pos_p_limit = 0.0 # if params("NoPositivePResponse") else None # put parameter-based control here
     self.pid = PIDController((CP.longitudinalTuning.kpBP, CP.longitudinalTuning.kpV),
                              (CP.longitudinalTuning.kiBP, CP.longitudinalTuning.kiV),
-                             k_f=CP.longitudinalTuning.kf, rate=1 / DT_CTRL)
+                             rate=1 / DT_CTRL, pos_p_limit=pos_p_limit)
+    # Preserve legacy behaviour when no feedforward gain is provided (default of 0.0)
+    kf = getattr(CP.longitudinalTuning, 'kfDEPRECATED', 0.0)
+    self.feedforward_gain = kf if kf != 0.0 else 1.0
     self.v_pid = 0.0
+    self._mode_setup()
     self.last_output_accel = 0.0
 
+
+
+  def update_mpc_mode(self, experimental_mode):
+    new_mode = 'blended' if experimental_mode else 'acc'
+
+    if self.transitioning and self.prev_mode == 'blended' and self.current_mode == 'acc':
+      self.mode_transition_timer = 0.0
+
+    if new_mode != self.current_mode:
+      self.prev_mode = self.current_mode
+      self.transitioning = True
+      self.mode_transition_timer = 0.0
+      self.mode_transition_filter.x = self.last_output_accel
+
+      self.current_mode = new_mode
+
+    if self.transitioning:
+      self.mode_transition_timer += DT_CTRL
+      if self.mode_transition_timer >= self.mode_transition_duration:
+        self.transitioning = False
+
+  def _mode_setup(self):
+    self.prev_mode = 'acc'
+    self.current_mode = 'acc'
+    self.mode_transition_filter = FirstOrderFilter(0.0, 0.5, DT_CTRL)
+    self.mode_transition_timer = 0.0
+    self.mode_transition_duration = 1.0
+    self.transitioning = False
+
   def reset(self):
     self.pid.reset()
 
@@ -124,8 +160,44 @@ class LongControl:
 
     else:  # LongCtrlState.pid
       error = a_target - CS.aEgo
-      output_accel = self.pid.update(error, speed=CS.vEgo,
-                                     feedforward=a_target)
+      self.update_mpc_mode(self.experimental_mode)
+      feedforward = a_target * self.feedforward_gain
+      raw_output_accel = self.pid.update(error, speed=CS.vEgo, feedforward=feedforward)
+
+
+      if self.transitioning and self.prev_mode == 'acc' and self.current_mode == 'blended':
+        if raw_output_accel < 0 and raw_output_accel < self.last_output_accel:
+          progress = min(1.0, self.mode_transition_timer / self.mode_transition_duration)
+          # Soften transition at low urgency, but keep sharp for high decel
+          # 20% smoother for chill decel (lower exponent)
+          urgency = abs(raw_output_accel / CarControllerParams.ACCEL_MIN)
+          urgency_smooth = min(1.0, urgency ** 0.4)  # 20% smoother for chill decel
+          blend_factor = 1.0 - (1.0 - progress) * (1.0 - urgency_smooth)
+          output_accel = self.last_output_accel + (raw_output_accel - self.last_output_accel) * blend_factor
+        else:
+          output_accel = raw_output_accel
+      else:
+        output_accel = raw_output_accel
+
+    if self.long_control_state == LongCtrlState.pid:
+      # Smooth acceleration and deceleration with urgency-based rate limiting
+      base_rate = 1.0
+      
+      if output_accel < self.last_output_accel:  # Deceleration requested
+          decel_needed = self.last_output_accel - output_accel
+          # Use a safe default for ACCEL_MIN if not available, to prevent division by zero
+          max_decel = abs(CarControllerParams.ACCEL_MIN) if CarControllerParams.ACCEL_MIN != 0 else 4.0
+          urgency = min(1.0, decel_needed / max_decel)
+          
+          # Adjust rate based on urgency (1.0 m/s^3 for low urgency, up to 4.0 m/s^3 for high urgency)
+          max_rate = 1.0 + 3.0 * urgency
+      else:
+          max_rate = base_rate  # Acceleration is always smooth
+      
+      max_accel_change = max_rate * DT_CTRL
+      output_accel = clip(output_accel,
+                          self.last_output_accel - max_accel_change,
+                          self.last_output_accel + max_accel_change)
 
     self.last_output_accel = clip(output_accel, accel_limits[0], accel_limits[1])
     return self.last_output_accel
@@ -187,8 +259,9 @@ class LongControl:
 
       error = self.v_pid - CS.vEgo
       error_deadzone = apply_deadzone(error, deadzone)
+      feedforward = a_target * self.feedforward_gain
       output_accel = self.pid.update(error_deadzone, speed=CS.vEgo,
-                                     feedforward=a_target,
+                                     feedforward=feedforward,
                                      freeze_integrator=freeze_integrator)
 
     self.last_output_accel = clip(output_accel, accel_limits[0], accel_limits[1])

selfdrive/controls/lib/longitudinal_mpc_lib/long_mpc.py

@@ -3,11 +3,13 @@ import os
 import time
 import numpy as np
 from cereal import log
-from openpilot.selfdrive.car.interfaces import ACCEL_MIN, ACCEL_MAX
+from openpilot.common.numpy_fast import clip, interp
 from openpilot.common.realtime import DT_MDL
-from openpilot.common.swaglog import cloudlog
+from openpilot.common.filter_simple import FirstOrderFilter
+from openpilot.common.conversions import Conversions as CV
 # WARNING: imports outside of constants will not trigger a rebuild
 from openpilot.selfdrive.modeld.constants import index_function
+from openpilot.selfdrive.car.interfaces import ACCEL_MIN
 
 if __name__ == '__main__':  # generating code
   from openpilot.third_party.acados.acados_template import AcadosModel, AcadosOcp, AcadosOcpSolver
@@ -30,12 +32,54 @@ COST_E_DIM = 5
 COST_DIM = COST_E_DIM + 1
 CONSTR_DIM = 4
 
-X_EGO_OBSTACLE_COST = 3.
+# ===== VOACC SPEED-BASED TUNING PARAMETERS =====
+# City: Emergency-responsive | Highway: Rubber-banding prevention
+# Speed ranges: [0-35, 35-55, 55-70, 70+ mph]
+
+# SPEED BREAKPOINTS (mph)
+SPEED_BREAKPOINTS = [0, 35, 55, 70]  # 4 ranges: 0-35, 35-55, 55-70, 70+
+
+# ===== CHANGE THESE VALUES FOR DIFFERENT SPEEDS =====
+
+# RESPONSIVENESS TO LEAD CARS (Lower = More responsive, Higher = More stable)
+# [City Emergency, Urban Hwy, Rural Hwy, High Speed]
+X_EGO_OBSTACLE_COSTS = [3.0, 3.0, 2.5, 2.0]  # Less aggressive at low speeds, closer to original
+
+# JERK CONTROL (Lower = More jerky/responsive, Higher = Smoother/conservative)
+# [City Emergency, Urban Hwy, Rural Hwy, High Speed]
+J_EGO_COSTS = [5.0, 4.75, 4.5, 4.0]  # Reverted to original 5.0 at low speeds
+
+# ACCELERATION CHANGE PENALTIES (Lower = More responsive, Higher = Smoother)
+# [City Emergency, Urban Hwy, Rural Hwy, High Speed]
+A_CHANGE_COSTS = [200, 195, 180, 170]  # Reverted to original 200 at low speeds
+
+# SMOOTHING FILTERS - Speed-adaptive for optimal responsiveness
+# Lower = More responsive, Higher = Smoother
+LEAD_FILTER_TIME_LOW = 0.8   # Under 40 mph: Fast response for city emergency braking
+LEAD_FILTER_TIME_HIGH = 1.2  # Over 40 mph: Faster response to prevent highway gaps
+SPEED_FILTER_THRESHOLD = 40 * CV.MPH_TO_MS  # 40 mph threshold
+
+# DISTANCE ADAPTATION STRENGTH (How much penalties increase when close to lead)
+# [City, Urban Hwy, Rural Hwy, High Speed]
+DIST_ADAPTS = [0.04, 0.06, 0.06, 0.05]  # Balanced across speeds
+
+# ===== END TUNING PARAMETERS =====
+
+# Function to get parameter value based on current speed
+def get_speed_based_param(speed_mph, param_array):
+    """Get parameter value based on current speed using smooth interpolation"""
+    return np.interp(speed_mph, SPEED_BREAKPOINTS, param_array)
+
+# Current active values (set based on speed)
+X_EGO_OBSTACLE_COST = 2.75
+J_EGO_COST = 5.5
+A_CHANGE_COST = 250.0
+LEAD_FILTER_TIME = 2.0
+DIST_ADAPT = 0.06
+
 X_EGO_COST = 0.
 V_EGO_COST = 0.
 A_EGO_COST = 0.
-J_EGO_COST = 5.0
-A_CHANGE_COST = 200.
 DANGER_ZONE_COST = 100.
 CRASH_DISTANCE = .25
 LEAD_DANGER_FACTOR = 0.75
@@ -55,9 +99,6 @@ T_IDXS = np.array(T_IDXS_LST)
 FCW_IDXS = T_IDXS < 5.0
 T_DIFFS = np.diff(T_IDXS, prepend=[0.])
 COMFORT_BRAKE = 2.5
-STOP_DISTANCE = 6.0
-CRUISE_MIN_ACCEL = -1.2
-CRUISE_MAX_ACCEL = 1.6
 
 def get_jerk_factor(aggressive_jerk_acceleration=0.5, aggressive_jerk_danger=0.5, aggressive_jerk_speed=0.5,
                     standard_jerk_acceleration=1.0, standard_jerk_danger=1.0, standard_jerk_speed=1.0,
@@ -107,7 +148,11 @@ def get_stopped_equivalence_factor(v_lead):
   return (v_lead**2) / (2 * COMFORT_BRAKE)
 
 def get_safe_obstacle_distance(v_ego, t_follow):
-  return (v_ego**2) / (2 * COMFORT_BRAKE) + t_follow * v_ego + STOP_DISTANCE
+  from openpilot.common.params import Params
+  params = Params()
+  stop_str = params.get("StopDistance", encoding="utf8")
+  stop_distance = float(stop_str) if stop_str else 6.0
+  return (v_ego**2) / (2 * COMFORT_BRAKE) + t_follow * v_ego + stop_distance
 
 def desired_follow_distance(v_ego, v_lead, t_follow=None):
   if t_follow is None:
@@ -188,11 +233,12 @@ def gen_long_ocp():
   # from an obstacle at every timestep. This obstacle can be a lead car
   # or other object. In e2e mode we can use x_position targets as a cost
   # instead.
+  accel_change = a_ego - prev_a
   costs = [((x_obstacle - x_ego) - (desired_dist_comfort)) / (v_ego + 10.),
            x_ego,
            v_ego,
            a_ego,
-           a_ego - prev_a,
+           accel_change,
            j_ego]
   ocp.model.cost_y_expr = vertcat(*costs)
   ocp.model.cost_y_expr_e = vertcat(*costs[:-1])
@@ -250,8 +296,23 @@ class LongitudinalMpc:
     self.mode = mode
     self.dt = dt
     self.solver = AcadosOcpSolverCython(MODEL_NAME, ACADOS_SOLVER_TYPE, N)
-    self.reset()
     self.source = SOURCES[2]
+    # Initialize smoothing filters with default time constants
+    self.current_filter_time = LEAD_FILTER_TIME_LOW
+    self.lead_a_filter = FirstOrderFilter(0.0, self.current_filter_time, self.dt)
+    self.lead_v_filter = FirstOrderFilter(0.0, self.current_filter_time, self.dt)
+    # Slew-limited filter factor to avoid abrupt 0.50↔1.00 jumps
+    self.filter_time_factor = 1.0
+    self.slew_per_sec = 1.0
+    # Instance variables to avoid global modifications
+    self.current_x_ego_cost = X_EGO_OBSTACLE_COSTS[0]
+    self.current_j_ego_cost = J_EGO_COSTS[0]
+    self.current_a_change_cost = A_CHANGE_COSTS[0]
+    self.current_dist_adapt = DIST_ADAPTS[0]
+    # Initialize acceleration limits to prevent AttributeError
+    self.cruise_min_a = ACCEL_MIN
+    self.max_a = 1.2  # Default max acceleration
+    self.reset()
 
   def reset(self):
     # self.solver = AcadosOcpSolverCython(MODEL_NAME, ACADOS_SOLVER_TYPE, N)
@@ -298,10 +359,71 @@ class LongitudinalMpc:
     for i in range(N):
       self.solver.cost_set(i, 'Zl', Zl)
 
-  def set_weights(self, acceleration_jerk=1.0, danger_jerk=1.0, speed_jerk=1.0, prev_accel_constraint=True, personality=log.LongitudinalPersonality.standard):
+  def set_weights(self, acceleration_jerk=1.0, danger_jerk=1.0, speed_jerk=1.0, prev_accel_constraint=True,
+                  personality=log.LongitudinalPersonality.standard, v_ego=0.0, lead_dist=50.0,
+                  uncertainty=0.0, accel_reengage=False, panic_bypass=False):
+    # Update parameters based on current speed with interpolation for smooth scaling
+    speed_mph = v_ego * CV.MS_TO_MPH  # Convert m/s to mph
+
+    # Use speed-based parameters for smooth scaling across all breakpoints
+    self.current_x_ego_cost = get_speed_based_param(speed_mph, X_EGO_OBSTACLE_COSTS)
+    self.current_j_ego_cost = get_speed_based_param(speed_mph, J_EGO_COSTS)
+    self.current_a_change_cost = get_speed_based_param(speed_mph, A_CHANGE_COSTS)
+
+    # For dist_adapt, start from 0.0 under low speeds while enabling full smooth transitions
+    dist_adapt_array = [0.0, DIST_ADAPTS[1], DIST_ADAPTS[2], DIST_ADAPTS[3]]
+    self.current_dist_adapt = get_speed_based_param(speed_mph, dist_adapt_array)
+
+    # Update filter time constants with interp and recreate filters if needed
+    if speed_mph < 47:
+        self.current_filter_time = 0.0
+    else:
+        self.current_filter_time = interp(speed_mph, [47, 65], [0.0, LEAD_FILTER_TIME_HIGH])
+    if abs(self.current_filter_time - getattr(self, 'prev_filter_time', 0)) > 0.1:  # Only update if significant change
+      # Recreate filters with new time constant while preserving current values
+      current_a = self.lead_a_filter.x if hasattr(self.lead_a_filter, 'x') else 0.0
+      current_v = self.lead_v_filter.x if hasattr(self.lead_v_filter, 'x') else 0.0
+      self.lead_a_filter = FirstOrderFilter(current_a, self.current_filter_time, self.dt)
+      self.lead_v_filter = FirstOrderFilter(current_v, self.current_filter_time, self.dt)
+      self.prev_filter_time = self.current_filter_time
+
+    # Adaptive jerk factors for distance with interp scaling
+    dist_factor = 1.0 + self.current_dist_adapt * (20.0 / max(lead_dist, 5.0))
+    acceleration_jerk *= dist_factor
+    danger_jerk *= dist_factor
+    speed_jerk *= dist_factor
+
+    # Scene complexity adjustment based on model uncertainty
+    prev_filter_time_factor = getattr(self, 'prev_filter_time_factor', 1.0)
+    # Target factor from uncertainty
+    if uncertainty <= 0.45:
+      tgt_factor = 1.0
+    elif uncertainty >= 0.70:
+      tgt_factor = 0.0
+    else:
+      tgt_factor = float(np.interp(uncertainty, [0.45, 0.70], [1.0, 0.30]))
+
+    if accel_reengage:
+      tgt_factor = min(tgt_factor, 0.5)
+
+    # Hard bypass of smoothing when approaching fast or magnitude trips
+    if panic_bypass:
+      tgt_factor = 0.0
+
+    # Slew-limit changes to avoid step-wise filter jumps
+    max_step = self.slew_per_sec * self.dt
+    delta = np.clip(tgt_factor - self.filter_time_factor, -max_step, max_step)
+    self.filter_time_factor += float(delta)
+    filter_time_factor = float(self.filter_time_factor)
+
+    # When uncertainty is moderately elevated, allow accel but cap jerk by increasing jerk cost
+    if 0.45 <= uncertainty < 0.60:
+      scale = float(np.interp(uncertainty, [0.45, 0.60], [1.2, 1.5]))
+      speed_jerk *= scale
+
     if self.mode == 'acc':
       a_change_cost = acceleration_jerk if prev_accel_constraint else 0
-      cost_weights = [X_EGO_OBSTACLE_COST, X_EGO_COST, V_EGO_COST, A_EGO_COST, a_change_cost, speed_jerk]
+      cost_weights = [self.current_x_ego_cost, X_EGO_COST, V_EGO_COST, A_EGO_COST, a_change_cost, speed_jerk]
       constraint_cost_weights = [LIMIT_COST, LIMIT_COST, LIMIT_COST, danger_jerk]
     elif self.mode == 'blended':
       a_change_cost = 40.0 if prev_accel_constraint else 0
@@ -311,6 +433,15 @@ class LongitudinalMpc:
       raise NotImplementedError(f'Planner mode {self.mode} not recognized in planner cost set')
     self.set_cost_weights(cost_weights, constraint_cost_weights)
 
+    # Adjust filter time constants for complex scenes
+    if abs(filter_time_factor - getattr(self, 'prev_filter_time_factor', 1.0)) > 0.05:
+      current_a = self.lead_a_filter.x if hasattr(self.lead_a_filter, 'x') else 0.0
+      current_v = self.lead_v_filter.x if hasattr(self.lead_v_filter, 'x') else 0.0
+      new_filter_time = self.current_filter_time * filter_time_factor
+      self.lead_a_filter = FirstOrderFilter(current_a, new_filter_time, self.dt)
+      self.lead_v_filter = FirstOrderFilter(current_v, new_filter_time, self.dt)
+      self.prev_filter_time_factor = filter_time_factor
+
   def set_cur_state(self, v, a):
     v_prev = self.x0[1]
     self.x0[1] = v
@@ -320,16 +451,34 @@ class LongitudinalMpc:
         self.solver.set(i, 'x', self.x0)
 
   @staticmethod
-  def extrapolate_lead(x_lead, v_lead, a_lead, a_lead_tau):
-    a_lead_traj = a_lead * np.exp(-a_lead_tau * (T_IDXS**2)/2.)
-    v_lead_traj = np.clip(v_lead + np.cumsum(T_DIFFS * a_lead_traj), 0.0, 1e8)
-    x_lead_traj = x_lead + np.cumsum(T_DIFFS * v_lead_traj)
+  def extrapolate_lead(x_lead, v_lead, a_lead, a_lead_tau, v_ego=0.0):
+    speed_mph = v_ego * CV.MS_TO_MPH
+    bp = [0, 20, 35]
+    exp_weight = interp(speed_mph, bp, [1.0, 1.0, 0.0])  # Full exp at <20, blend to constant at 35
+
+    if exp_weight > 0:
+      # Exponential decay component
+      a_lead_traj_exp = a_lead * np.exp(-a_lead_tau * (T_IDXS**2)/2.)
+      v_lead_traj_exp = np.clip(v_lead + np.cumsum(T_DIFFS * a_lead_traj_exp), 0.0, 1e8)
+      x_lead_traj_exp = x_lead + np.cumsum(T_DIFFS * v_lead_traj_exp)
+    else:
+      x_lead_traj_exp = np.zeros_like(T_IDXS)
+      v_lead_traj_exp = np.zeros_like(T_IDXS)
+
+    # Constant acceleration component
+    v_lead_traj_const = np.clip(v_lead + a_lead * T_IDXS, 0.0, 1e8)
+    x_lead_traj_const = x_lead + v_lead * T_IDXS + 0.5 * a_lead * T_IDXS**2
+
+    # Blend based on weight
+    v_lead_traj = exp_weight * v_lead_traj_exp + (1 - exp_weight) * v_lead_traj_const
+    x_lead_traj = exp_weight * x_lead_traj_exp + (1 - exp_weight) * x_lead_traj_const
+
     lead_xv = np.column_stack((x_lead_traj, v_lead_traj))
     return lead_xv
 
-  def process_lead(self, lead):
+  def process_lead(self, lead, tracking_lead=True):
     v_ego = self.x0[1]
-    if lead is not None and lead.status:
+    if lead is not None and lead.status and tracking_lead:
       x_lead = lead.dRel
       v_lead = lead.vLead
       a_lead = lead.aLeadK
@@ -344,18 +493,29 @@ class LongitudinalMpc:
     # MPC will not converge if immediate crash is expected
     # Clip lead distance to what is still possible to brake for
     min_x_lead = ((v_ego + v_lead)/2) * (v_ego - v_lead) / (-ACCEL_MIN * 2)
-    x_lead = np.clip(x_lead, min_x_lead, 1e8)
-    v_lead = np.clip(v_lead, 0.0, 1e8)
-    a_lead = np.clip(a_lead, -10., 5.)
-    lead_xv = self.extrapolate_lead(x_lead, v_lead, a_lead, a_lead_tau)
+    x_lead = clip(x_lead, min_x_lead, 1e8)
+    v_lead = clip(v_lead, 0.0, 1e8)
+    a_lead = clip(a_lead, -10., 5.)
+    # Apply smoothing filters with interp scaling
+    self.lead_a_filter.update(a_lead)
+    self.lead_v_filter.update(v_lead)
+    a_lead = self.lead_a_filter.x
+    v_lead = self.lead_v_filter.x
+    lead_xv = self.extrapolate_lead(x_lead, v_lead, a_lead, a_lead_tau, v_ego)
     return lead_xv
 
-  def update(self, radarstate, v_cruise, x, v, a, j, t_follow, frogpilot_toggles, personality=log.LongitudinalPersonality.standard):
-    v_ego = self.x0[1]
-    self.status = radarstate.leadOne.status or radarstate.leadTwo.status
+  def set_accel_limits(self, min_a, max_a):
+    # TODO this sets a max accel limit, but the minimum limit is only for cruise decel
+    # needs refactor
+    self.cruise_min_a = min_a
+    self.max_a = max_a
 
-    lead_xv_0 = self.process_lead(radarstate.leadOne)
-    lead_xv_1 = self.process_lead(radarstate.leadTwo)
+  def update(self, lead_one, lead_two, v_cruise, x, v, a, j, t_follow, tracking_lead, personality=log.LongitudinalPersonality.standard):
+    v_ego = self.x0[1]
+    self.status = lead_one.status and tracking_lead or lead_two.status
+
+    lead_xv_0 = self.process_lead(lead_one, tracking_lead)
+    lead_xv_1 = self.process_lead(lead_two, v_ego)
 
     # To estimate a safe distance from a moving lead, we calculate how much stopping
     # distance that lead needs as a minimum. We can add that to the current distance
@@ -364,7 +524,8 @@ class LongitudinalMpc:
     lead_1_obstacle = lead_xv_1[:,0] + get_stopped_equivalence_factor(lead_xv_1[:,1])
 
     self.params[:,0] = ACCEL_MIN
-    self.params[:,1] = ACCEL_MAX
+    # negative accel constraint causes problems because negative speed is not allowed
+    self.params[:,1] = max(0.0, self.max_a)
 
     # Update in ACC mode or ACC/e2e blend
     if self.mode == 'acc':
@@ -372,9 +533,9 @@ class LongitudinalMpc:
 
       # Fake an obstacle for cruise, this ensures smooth acceleration to set speed
       # when the leads are no factor.
-      v_lower = v_ego + (T_IDXS * CRUISE_MIN_ACCEL * 1.05)
+      v_lower = v_ego + (T_IDXS * self.cruise_min_a * 1.05)
       # TODO does this make sense when max_a is negative?
-      v_upper = v_ego + (T_IDXS * CRUISE_MAX_ACCEL * 1.05)
+      v_upper = v_ego + (T_IDXS * self.max_a * 1.05)
       v_cruise_clipped = np.clip(v_cruise * np.ones(N+1),
                                  v_lower,
                                  v_upper)
@@ -415,8 +576,8 @@ class LongitudinalMpc:
     self.params[:,4] = t_follow
 
     self.run()
-    if (np.any(lead_xv_0[FCW_IDXS,0] - self.x_sol[FCW_IDXS,0] < CRASH_DISTANCE) and
-            radarstate.leadOne.modelProb > 0.9):
+    lead_probability = lead_one.modelProb
+    if (np.any(lead_xv_0[FCW_IDXS,0] - self.x_sol[FCW_IDXS,0] < CRASH_DISTANCE) and lead_probability > 0.9):
       self.crash_cnt += 1
     else:
       self.crash_cnt = 0
@@ -462,11 +623,7 @@ class LongitudinalMpc:
 
     self.prev_a = np.interp(T_IDXS + self.dt, T_IDXS, self.a_solution)
 
-    t = time.monotonic()
     if self.solution_status != 0:
-      if t > self.last_cloudlog_t + 5.0:
-        self.last_cloudlog_t = t
-        cloudlog.warning(f"Long mpc reset, solution_status: {self.solution_status}")
       self.reset()
       # reset = 1
     # print(f"long_mpc timings: total internal {self.solve_time:.2e}, external: {(time.monotonic() - t0):.2e} qp {self.time_qp_solution:.2e}, \

selfdrive/controls/lib/longitudinal_planner.py

@@ -1,6 +1,8 @@
 #!/usr/bin/env python3
 import math
 import numpy as np
+import time
+from openpilot.common.numpy_fast import clip, interp
 
 import cereal.messaging as messaging
 from openpilot.common.conversions import Conversions as CV
@@ -11,25 +13,28 @@ from openpilot.selfdrive.car.interfaces import ACCEL_MIN, ACCEL_MAX
 from openpilot.selfdrive.controls.lib.longcontrol import LongCtrlState
 from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import LongitudinalMpc
 from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import T_IDXS as T_IDXS_MPC
-from openpilot.selfdrive.controls.lib.drive_helpers import V_CRUISE_MAX, V_CRUISE_UNSET, CONTROL_N, get_accel_from_plan
+from openpilot.selfdrive.controls.lib.drive_helpers import V_CRUISE_UNSET, CONTROL_N, get_speed_error, get_accel_from_plan_tomb_raider
 from openpilot.common.swaglog import cloudlog
 
-from openpilot.frogpilot.common.frogpilot_variables import MINIMUM_LATERAL_ACCELERATION
-
 LON_MPC_STEP = 0.2  # first step is 0.2s
+A_CRUISE_MIN = -1.2
 A_CRUISE_MAX_VALS = [1.6, 1.2, 0.8, 0.6]
 A_CRUISE_MAX_BP = [0., 10.0, 25., 40.]
 CONTROL_N_T_IDX = ModelConstants.T_IDXS[:CONTROL_N]
-ALLOW_THROTTLE_THRESHOLD = 0.4
+ALLOW_THROTTLE_THRESHOLD = 0.5
 MIN_ALLOW_THROTTLE_SPEED = 2.5
 
+# Uncertainty-based filter disable thresholds
+UNCERT_SLOPE_TRIG = 0.12  # per second
+UNCERT_MAG_TRIG = 0.50
+
 # Lookup table for turns
 _A_TOTAL_MAX_V = [1.7, 3.2]
 _A_TOTAL_MAX_BP = [20., 40.]
 
 
 def get_max_accel(v_ego):
-  return float(np.interp(v_ego, A_CRUISE_MAX_BP, A_CRUISE_MAX_VALS))
+  return interp(v_ego, A_CRUISE_MAX_BP, A_CRUISE_MAX_VALS)
 
 def get_coast_accel(pitch):
   return np.sin(pitch) * -5.65 - 0.3  # fitted from data using xx/projects/allow_throttle/compute_coast_accel.py
@@ -42,45 +47,114 @@ def limit_accel_in_turns(v_ego, angle_steers, a_target, CP):
   """
   # FIXME: This function to calculate lateral accel is incorrect and should use the VehicleModel
   # The lookup table for turns should also be updated if we do this
-  a_total_max = np.interp(v_ego, _A_TOTAL_MAX_BP, _A_TOTAL_MAX_V)
+  a_total_max = interp(v_ego, _A_TOTAL_MAX_BP, _A_TOTAL_MAX_V)
   a_y = v_ego ** 2 * angle_steers * CV.DEG_TO_RAD / (CP.steerRatio * CP.wheelbase)
-
-  if abs(a_y) > MINIMUM_LATERAL_ACCELERATION:
-    a_x_allowed = math.sqrt(max(a_total_max ** 2 - a_y ** 2, 0.))
-  else:
-    a_x_allowed = a_target[1]
+  a_x_allowed = math.sqrt(max(a_total_max ** 2 - a_y ** 2, 0.))
 
   return [a_target[0], min(a_target[1], a_x_allowed)]
 
 
+def get_accel_from_plan_classic(CP, speeds, accels, vEgoStopping):
+  if len(speeds) == CONTROL_N:
+    v_target_now = interp(DT_MDL, CONTROL_N_T_IDX, speeds)
+    a_target_now = interp(DT_MDL, CONTROL_N_T_IDX, accels)
+
+    v_target = interp(CP.longitudinalActuatorDelay + DT_MDL, CONTROL_N_T_IDX, speeds)
+    if v_target != v_target_now:
+      a_target = 2 * (v_target - v_target_now) / CP.longitudinalActuatorDelay - a_target_now
+    else:
+      a_target = a_target_now
+
+    v_target_1sec = interp(CP.longitudinalActuatorDelay + DT_MDL + 1.0, CONTROL_N_T_IDX, speeds)
+  else:
+    v_target = 0.0
+    v_target_1sec = 0.0
+    a_target = 0.0
+  should_stop = (v_target < vEgoStopping and
+                 v_target_1sec < vEgoStopping)
+  return a_target, should_stop
+
+
+def get_accel_from_plan(speeds, accels, action_t=DT_MDL, vEgoStopping=0.05):
+  if len(speeds) == CONTROL_N:
+    v_now = speeds[0]
+    a_now = accels[0]
+
+    v_target = interp(action_t, CONTROL_N_T_IDX, speeds)
+    a_target = 2 * (v_target - v_now) / (action_t) - a_now
+    v_target_1sec = interp(action_t + 1.0, CONTROL_N_T_IDX, speeds)
+  else:
+    v_target = 0.0
+    v_target_1sec = 0.0
+    a_target = 0.0
+  should_stop = (v_target < vEgoStopping and
+                 v_target_1sec < vEgoStopping)
+  return a_target, should_stop
+
+
 class LongitudinalPlanner:
   def __init__(self, CP, init_v=0.0, init_a=0.0, dt=DT_MDL):
     self.CP = CP
     self.mpc = LongitudinalMpc(dt=dt)
-    # TODO remove mpc modes when TR released
-    self.mpc.mode = 'acc'
     self.fcw = False
     self.dt = dt
     self.allow_throttle = True
+    self.mode = 'acc'
+
+    self.generation = None
 
     self.a_desired = init_a
     self.v_desired_filter = FirstOrderFilter(init_v, 2.0, self.dt)
-    self.prev_accel_clip = [ACCEL_MIN, ACCEL_MAX]
-    self.output_a_target = 0.0
-    self.output_should_stop = False
+    self.v_model_error = 0.0
 
     self.v_desired_trajectory = np.zeros(CONTROL_N)
     self.a_desired_trajectory = np.zeros(CONTROL_N)
     self.j_desired_trajectory = np.zeros(CONTROL_N)
     self.solverExecutionTime = 0.0
 
+    # ---- Rubberband mitigation state ----
+    # Two uncertainty tracks (slow/fast) for asymmetric gating
+    self.uncert_slow = FirstOrderFilter(0.0, 1.6, self.dt)  # ~lam=0.6
+    self.uncert_fast = FirstOrderFilter(0.0, 0.9, self.dt)  # faster cool-down for accel decisions
+    # Lead stability tracking
+    self.prev_lead_dist = None
+    self.last_big_brake_t = 0.0
+    self.stable_lead = False
+    # Temporary accel nudge window
+    self.accel_nudge_until = 0.0
+
+    # Hysteresis gate + dwell for accel re-engage and smoothed lead distance
+    self.accel_gate = False
+    self._t_arm = 0.0
+    self._t_disarm = 0.0
+    self.lead_dist_f = None
+
+    # Uncertainty slope tracking
+    self._uncert_last = 0.0
+    self._uncert_last_t = None
+
+  @property
+  def mlsim(self):
+      return self.generation in ("v8", "v10", "v11", "v12")
+
+  def get_mpc_mode(self) -> str:
+      """
+      Determine the desired MPC mode: if not ML-SIM, MPC should follow self.mode;
+      otherwise leave MPC.mode unchanged.
+      """
+      # For non-ML-SIM generations, MPC mode tracks self.mode
+      if not self.mlsim:
+          return self.mode
+      # For ML-SIM (v8), preserve the existing MPC mode
+      return getattr(self.mpc, 'mode', 'acc')
+
   @staticmethod
-  def parse_model(model_msg, v_ego, taco_tune):
+  def parse_model(model_msg, model_error, v_ego, taco_tune):
     if (len(model_msg.position.x) == ModelConstants.IDX_N and
       len(model_msg.velocity.x) == ModelConstants.IDX_N and
       len(model_msg.acceleration.x) == ModelConstants.IDX_N):
-      x = np.interp(T_IDXS_MPC, ModelConstants.T_IDXS, model_msg.position.x)
-      v = np.interp(T_IDXS_MPC, ModelConstants.T_IDXS, model_msg.velocity.x)
+      x = np.interp(T_IDXS_MPC, ModelConstants.T_IDXS, model_msg.position.x) - model_error * T_IDXS_MPC
+      v = np.interp(T_IDXS_MPC, ModelConstants.T_IDXS, model_msg.velocity.x) - model_error
       a = np.interp(T_IDXS_MPC, ModelConstants.T_IDXS, model_msg.acceleration.x)
       j = np.zeros(len(T_IDXS_MPC))
     else:
@@ -90,7 +164,7 @@ class LongitudinalPlanner:
       j = np.zeros(len(T_IDXS_MPC))
 
     if taco_tune:
-      max_lat_accel = np.interp(v_ego, [5, 10, 20], [1.5, 2.0, 3.0])
+      max_lat_accel = interp(v_ego, [5, 10, 20], [1.5, 2.0, 3.0])
       curvatures = np.interp(T_IDXS_MPC, ModelConstants.T_IDXS, model_msg.orientationRate.z) / np.clip(v, 0.3, 100.0)
       max_v = np.sqrt(max_lat_accel / (np.abs(curvatures) + 1e-3)) - 2.0
       v = np.minimum(max_v, v)
@@ -101,17 +175,22 @@ class LongitudinalPlanner:
       throttle_prob = 1.0
     return x, v, a, j, throttle_prob
 
-  def update(self, sm, classic_longitudinal, frogpilot_toggles):
-    mode = 'blended' if sm['controlsState'].experimentalMode else 'acc'
-    if classic_longitudinal:
-      self.mpc.mode = mode
+  def update(self, tinygrad_model, sm, frogpilot_toggles):
+    self.generation = frogpilot_toggles.model_version
+    if tinygrad_model:
+      self.mpc.mode = 'acc'
+      self.mode = 'blended' if sm['controlsState'].experimentalMode else 'acc'
+    else:
+      self.mpc.mode = 'blended' if sm['controlsState'].experimentalMode else 'acc'
+    if not self.mlsim:
+      self.mpc.mode = self.mode
 
     if len(sm['carControl'].orientationNED) == 3:
       accel_coast = get_coast_accel(sm['carControl'].orientationNED[1])
     else:
       accel_coast = ACCEL_MAX
 
-    v_ego = sm['carState'].vEgo
+    v_ego = max(sm['carState'].vEgo, sm['carState'].vEgoCluster)
     v_cruise = sm['frogpilotPlan'].vCruise
     v_cruise_initialized = sm['controlsState'].vCruise != V_CRUISE_UNSET
 
@@ -126,36 +205,190 @@ class LongitudinalPlanner:
     # No change cost when user is controlling the speed, or when standstill
     prev_accel_constraint = not (reset_state or sm['carState'].standstill)
 
-    if mode == 'acc':
-      accel_clip = [sm['frogpilotPlan'].minAcceleration, sm['frogpilotPlan'].maxAcceleration]
+    if self.mpc.mode == 'acc':
+      accel_limits = [sm['frogpilotPlan'].minAcceleration, sm['frogpilotPlan'].maxAcceleration]
       steer_angle_without_offset = sm['carState'].steeringAngleDeg - sm['liveParameters'].angleOffsetDeg
-      if not sm['frogpilotPlan'].cscControllingSpeed:
-        accel_clip = limit_accel_in_turns(v_ego, steer_angle_without_offset, accel_clip, self.CP)
+      accel_limits_turns = limit_accel_in_turns(v_ego, steer_angle_without_offset, accel_limits, self.CP)
     else:
-      accel_clip = [ACCEL_MIN, ACCEL_MAX]
+      accel_limits = [ACCEL_MIN, ACCEL_MAX]
+      accel_limits_turns = [ACCEL_MIN, ACCEL_MAX]
 
     if reset_state:
       self.v_desired_filter.x = v_ego
       # Clip aEgo to cruise limits to prevent large accelerations when becoming active
-      self.a_desired = np.clip(sm['carState'].aEgo, accel_clip[0], accel_clip[1])
+      self.a_desired = clip(sm['carState'].aEgo, accel_limits[0], accel_limits[1])
 
     # Prevent divergence, smooth in current v_ego
     self.v_desired_filter.x = max(0.0, self.v_desired_filter.update(v_ego))
-    x, v, a, j, throttle_prob = self.parse_model(sm['modelV2'], v_ego, frogpilot_toggles.taco_tune)
+    # Compute model v_ego error
+    self.v_model_error = get_speed_error(sm['modelV2'], v_ego)
+    x, v, a, j, throttle_prob = self.parse_model(sm['modelV2'], self.v_model_error, v_ego, frogpilot_toggles.taco_tune)
     # Don't clip at low speeds since throttle_prob doesn't account for creep
     self.allow_throttle = throttle_prob > ALLOW_THROTTLE_THRESHOLD or v_ego <= MIN_ALLOW_THROTTLE_SPEED
+    self.allow_throttle &= not sm['frogpilotPlan'].disableThrottle
 
     if not self.allow_throttle:
-      clipped_accel_coast = max(accel_coast, accel_clip[0])
-      clipped_accel_coast_interp = np.interp(v_ego, [MIN_ALLOW_THROTTLE_SPEED, MIN_ALLOW_THROTTLE_SPEED*2], [accel_clip[1], clipped_accel_coast])
-      accel_clip[1] = min(accel_clip[1], clipped_accel_coast_interp)
+      clipped_accel_coast = max(accel_coast, accel_limits_turns[0])
+      clipped_accel_coast_interp = interp(v_ego, [MIN_ALLOW_THROTTLE_SPEED, MIN_ALLOW_THROTTLE_SPEED*2], [accel_limits_turns[1], clipped_accel_coast])
+      accel_limits_turns[1] = min(accel_limits_turns[1], clipped_accel_coast_interp)
 
     if force_slow_decel:
       v_cruise = 0.0
+    # clip limits, cannot init MPC outside of bounds
+    accel_limits_turns[0] = min(accel_limits_turns[0], self.a_desired + 0.05)
+    accel_limits_turns[1] = max(accel_limits_turns[1], self.a_desired - 0.05)
 
-    self.mpc.set_weights(sm['frogpilotPlan'].accelerationJerk, sm['frogpilotPlan'].dangerJerk, sm['frogpilotPlan'].speedJerk, prev_accel_constraint, personality=sm['controlsState'].personality)
+    self.lead_one = sm['radarState'].leadOne
+    self.lead_two = sm['radarState'].leadTwo
+
+    lead_dist = self.lead_one.dRel if self.lead_one.status else 50.0
+
+    # Smooth lead distance (EMA) to avoid chatter in thresholds
+    alpha = max(0.02, min(0.15, 0.05 + 0.002 * v_ego))
+    if self.lead_dist_f is None:
+      self.lead_dist_f = float(lead_dist)
+    else:
+      self.lead_dist_f += alpha * (float(lead_dist) - self.lead_dist_f)
+
+    # Lead stability estimation and recent-brake timer
+    now_t = time.monotonic()
+    # relative speed (ego - lead) positive when closing
+    v_rel = (v_ego - self.lead_one.vLead) if self.lead_one.status else 0.0
+    if self.prev_lead_dist is None:
+      d_rel_dot = 0.0
+    else:
+      d_rel_dot = (lead_dist - self.prev_lead_dist) / max(self.dt, 1e-3)
+    self.prev_lead_dist = lead_dist
+
+    # Remember time of last non-trivial model brake risk
+    if 'raw_brake_max' in locals() and raw_brake_max is not None and raw_brake_max > 0.02:
+      self.last_big_brake_t = now_t
+
+    # Stable lead heuristic (short window, cheap to compute)
+    recently_braked = (now_t - self.last_big_brake_t) < 0.7
+    self.stable_lead = (
+      self.lead_one.status and
+      abs(v_rel) < 0.5 and
+      abs(d_rel_dot) < 0.5 and
+      not recently_braked
+    )
+
+    # Calculate scene uncertainty from model desire prediction entropy and disengage predictions
+    uncertainty = 0.0
+    if hasattr(sm['modelV2'], 'meta'):
+      # Desire prediction entropy (maneuver uncertainty), normalized to [0, 1]
+      desire_entropy = 0.0
+      if hasattr(sm['modelV2'].meta, 'desirePrediction'):
+        desire_probs = sm['modelV2'].meta.desirePrediction
+        if len(desire_probs) > 1:
+          probs = np.asarray(desire_probs, dtype=float)
+          total = float(np.sum(probs))
+          if total > 1e-6:
+            p = probs / total
+            entropy = -np.sum(p * np.log(p + 1e-10))
+            max_entropy = np.log(len(p))
+            desire_entropy = float(entropy / max(max_entropy, 1e-6))  # normalized entropy in [0,1]
+          else:
+            desire_entropy = 0.0  # guard against all-zero vector
+
+      # Disengage prediction risk (intervention likelihood)
+      disengage_risk = 0.0
+      raw_brake_max = -1.0
+      lam = -1.0
+      if hasattr(sm['modelV2'].meta, 'disengagePredictions'):
+        # Use brake press probabilities as primary risk indicator
+        brake_probs = sm['modelV2'].meta.disengagePredictions.brakePressProbs
+        if len(brake_probs) > 0:
+          # Exponentially decayed max over the full horizon
+          probs = np.asarray(brake_probs, dtype=float)
+          # Clip tiny brake blips so they don't inflate uncertainty
+          if float(np.max(probs)) < 0.015:
+            probs = probs * 0.5
+          raw_brake_max = float(np.max(probs))
+          # Time vector assuming model horizon step = DT_MDL
+          t = np.arange(len(probs), dtype=float) * DT_MDL
+          lam = 0.6  # decay rate per second (tunable: 0.5–0.9 typical)
+          weights = np.exp(-lam * t)
+          disengage_risk = float(np.max(probs * weights))
+
+      # Combined uncertainty metric (range roughly 0..2), with dual-track filtering
+      raw_uncertainty = desire_entropy + disengage_risk
+      # Update filters
+      self.uncert_slow.update(raw_uncertainty)
+      self.uncert_fast.update(raw_uncertainty)
+      # Use a more permissive track for accel decisions
+      uncertainty = self.uncert_slow.x
+    uncertainty_accel = min(self.uncert_slow.x, self.uncert_fast.x)
+
+    # --- Slope-based panic bypass ---
+    if self._uncert_last_t is None:
+      uncert_slope = 0.0
+    else:
+      dt_u = max(1e-3, now_t - self._uncert_last_t)
+      uncert_slope = (uncertainty - self._uncert_last) / dt_u
+    self._uncert_last = uncertainty
+    self._uncert_last_t = now_t
+
+    closing_fast = (self.lead_one.status and (v_ego - self.lead_one.vLead) > 0.5)
+    # Trigger if either slope is high or magnitude is high; require a valid lead and closing
+    panic_bypass = closing_fast and (uncert_slope > UNCERT_SLOPE_TRIG or uncertainty >= UNCERT_MAG_TRIG)
+
+    if panic_bypass:
+      try:
+        cloudlog.error(f"LON_SLOPE; slope={uncert_slope:.3f}/s; uncertainty={uncertainty:.3f}; v_ego={v_ego:.2f}; v_rel={(v_ego - self.lead_one.vLead) if self.lead_one.status else 0.0:.2f}; lead_dist={self.lead_dist_f if self.lead_dist_f is not None else -1:.2f}; trigger=True")
+      except Exception:
+        pass
+
+    # now_t defined earlier
+    over = uncertainty > 1.0
+
+    # Asymmetric accel release with hysteresis + dwell to prevent on/off pulsing
+    rise_dwell_s, fall_dwell_s = 0.6, 0.4
+    good = (
+      (self.a_desired > 0.0) and
+      self.stable_lead and
+      (uncertainty <= 0.425) and
+      (desire_entropy < 0.41)
+    )
+
+    # dwell timers for robust gating
+    if good and not self.accel_gate:
+      if now_t - self._t_arm >= rise_dwell_s:
+        self.accel_gate = True
+    else:
+      self._t_arm = now_t
+
+    if (not good) and self.accel_gate:
+      if now_t - self._t_disarm >= fall_dwell_s:
+        self.accel_gate = False
+    else:
+      self._t_disarm = now_t
+
+    if self.accel_gate:
+      # Ensure some positive headroom for MPC to exit coasting
+      accel_limits_turns[1] = max(accel_limits_turns[1], 0.2)
+      # Short self-canceling nudge to unstick (applied post-MPC)
+      if now_t > self.accel_nudge_until:
+        self.accel_nudge_until = now_t + 0.45
+
+    self.mpc.set_weights(sm['frogpilotPlan'].accelerationJerk,
+                         sm['frogpilotPlan'].dangerJerk,
+                         sm['frogpilotPlan'].speedJerk,
+                         prev_accel_constraint,
+                         personality=sm['controlsState'].personality,
+                         v_ego=v_ego,
+                         lead_dist=self.lead_dist_f if self.lead_dist_f is not None else lead_dist,
+                         uncertainty=uncertainty,
+                         accel_reengage=self.accel_gate,
+                         panic_bypass=panic_bypass)
+    self.mpc.set_accel_limits(accel_limits_turns[0], accel_limits_turns[1])
     self.mpc.set_cur_state(self.v_desired_filter.x, self.a_desired)
-    self.mpc.update(sm['radarState'], v_cruise, x, v, a, j, sm['frogpilotPlan'].tFollow, frogpilot_toggles, personality=sm['controlsState'].personality)
+    # After deciding the MPC mode via get_mpc_mode(), ensure MPC uses that mode when not mlsim
+    dec_mpc_mode = self.get_mpc_mode()
+    if not self.mlsim:
+      self.mpc.mode = dec_mpc_mode
+    self.mpc.update(self.lead_one, self.lead_two, v_cruise, x, v, a, j, sm['frogpilotPlan'].tFollow,
+                    sm['frogpilotPlan'].trackingLead, personality=sm['controlsState'].personality)
 
     self.a_desired_trajectory_full = np.interp(CONTROL_N_T_IDX, T_IDXS_MPC, self.mpc.a_solution)
     self.v_desired_trajectory = np.interp(CONTROL_N_T_IDX, T_IDXS_MPC, self.mpc.v_solution)
@@ -167,30 +400,41 @@ class LongitudinalPlanner:
     if self.fcw:
       cloudlog.info("FCW triggered")
 
+    # Safety checks for rubber-banding mitigation
+    max_jerk = np.max(np.abs(self.mpc.j_solution))
+    max_accel_change = np.max(np.abs(np.diff(self.mpc.a_solution)))
+    if max_jerk > 5.0:  # m/s^3
+      cloudlog.warning(f"High jerk detected: {max_jerk:.2f} m/s^3")
+    if max_accel_change > 2.0:  # m/s^2
+      cloudlog.warning(f"High acceleration change: {max_accel_change:.2f} m/s^2")
+
     # Interpolate 0.05 seconds and save as starting point for next iteration
     a_prev = self.a_desired
-    self.a_desired = float(np.interp(self.dt, CONTROL_N_T_IDX, self.a_desired_trajectory))
+    self.a_desired = float(interp(self.dt, CONTROL_N_T_IDX, self.a_desired_trajectory))
     self.v_desired_filter.x = self.v_desired_filter.x + self.dt * (self.a_desired + a_prev) / 2.0
 
-    action_t = frogpilot_toggles.longitudinalActuatorDelay + DT_MDL
-    output_a_target_mpc, output_should_stop_mpc = get_accel_from_plan(self.v_desired_trajectory, self.a_desired_trajectory, CONTROL_N_T_IDX,
-                                                                        action_t=action_t, vEgoStopping=frogpilot_toggles.vEgoStopping)
-    output_a_target_e2e = sm['modelV2'].action.desiredAcceleration
-    output_should_stop_e2e = sm['modelV2'].action.shouldStop
+    # Anticipatory pre-brake to avoid "coming in hot" when closing on a lead
+    if self.lead_one.status:
+      rel_v = max(0.0, v_ego - self.lead_one.vLead)
+      # dynamic time headway adds a small buffer when uncertainty is elevated
+      base_th = 1.6
+      th = base_th + 0.6 * max(0.0, uncertainty - 0.42)
+      desired_gap = th * v_ego
+      if (self.lead_dist_f is not None and self.lead_dist_f < desired_gap and rel_v > 0.5):
+        k_rel, k_unc = 0.04, 0.20
+        pre_brake = k_rel * rel_v + k_unc * max(0.0, uncertainty - 0.42)
+        pre_brake = min(pre_brake, 0.06)
+        self.a_desired = float(self.a_desired - pre_brake)
 
-    if mode == 'acc':
-      output_a_target = output_a_target_mpc
-      self.output_should_stop = output_should_stop_mpc
-    else:
-      output_a_target = min(output_a_target_mpc, output_a_target_e2e)
-      self.output_should_stop = output_should_stop_e2e or output_should_stop_mpc
+    # Apply tiny feed-forward nudge when released and safe
+    if now_t < self.accel_nudge_until and self.a_desired > -0.1:
+      self.a_desired = float(min(self.a_desired + 0.12, get_max_accel(v_ego)))
 
-    for idx in range(2):
-      accel_clip[idx] = np.clip(accel_clip[idx], self.prev_accel_clip[idx] - 0.05, self.prev_accel_clip[idx] + 0.05)
-    self.output_a_target = np.clip(output_a_target, accel_clip[0], accel_clip[1])
-    self.prev_accel_clip = accel_clip
+    # Small deadzone around zero accel to kill micro-dithers
+    if -0.05 < self.a_desired < 0.05:
+      self.a_desired = 0.0
 
-  def publish(self, sm, pm):
+  def publish(self, classic_model, tinygrad_model, sm, pm, frogpilot_toggles):
     plan_send = messaging.new_message('longitudinalPlan')
 
     plan_send.valid = sm.all_checks(service_list=['carState', 'controlsState'])
@@ -204,13 +448,34 @@ class LongitudinalPlanner:
     longitudinalPlan.accels = self.a_desired_trajectory.tolist()
     longitudinalPlan.jerks = self.j_desired_trajectory.tolist()
 
-    longitudinalPlan.hasLead = sm['radarState'].leadOne.status
+    longitudinalPlan.hasLead = self.lead_one.status
     longitudinalPlan.longitudinalPlanSource = self.mpc.source
     longitudinalPlan.fcw = self.fcw
 
-    longitudinalPlan.aTarget = float(self.output_a_target)
-    longitudinalPlan.shouldStop = bool(self.output_should_stop)
+    if classic_model:
+      a_target, should_stop = get_accel_from_plan_classic(self.CP, longitudinalPlan.speeds,
+                                                          longitudinalPlan.accels, vEgoStopping=frogpilot_toggles.vEgoStopping)
+    elif tinygrad_model:
+      action_t =  self.CP.longitudinalActuatorDelay + DT_MDL
+      output_a_target_mpc, output_should_stop_mpc = get_accel_from_plan_tomb_raider(self.v_desired_trajectory, self.a_desired_trajectory, CONTROL_N_T_IDX,
+                                                                                    action_t=action_t, vEgoStopping=frogpilot_toggles.vEgoStopping)
+      output_a_target_e2e = sm['modelV2'].action.desiredAcceleration
+      output_should_stop_e2e = sm['modelV2'].action.shouldStop
+
+      # v9 uses a different longitudinal interface; keep MPC-only behavior even in blended mode
+      if self.mode == 'acc' or self.generation == 'v9':
+        a_target = output_a_target_mpc
+        should_stop = output_should_stop_mpc
+      else:
+        a_target = min(output_a_target_mpc, output_a_target_e2e)
+        should_stop = output_should_stop_e2e or output_should_stop_mpc
+    else:
+      action_t = self.CP.longitudinalActuatorDelay + DT_MDL
+      a_target, should_stop = get_accel_from_plan(longitudinalPlan.speeds, longitudinalPlan.accels,
+                                                  action_t=action_t, vEgoStopping=frogpilot_toggles.vEgoStopping)
+    longitudinalPlan.aTarget = float(a_target)
+    longitudinalPlan.shouldStop = bool(should_stop) or sm['frogpilotPlan'].forcingStopLength < 1
     longitudinalPlan.allowBrake = True
-    longitudinalPlan.allowThrottle = bool(self.allow_throttle)
+    longitudinalPlan.allowThrottle = self.allow_throttle
 
     pm.send('longitudinalPlan', plan_send)

selfdrive/controls/lib/pid.py

@@ -2,11 +2,10 @@ import numpy as np
 from numbers import Number
 
 class PIDController:
-  def __init__(self, k_p, k_i, k_f=0., k_d=0., pos_limit=1e308, neg_limit=-1e308, rate=100):
+  def __init__(self, k_p, k_i, k_d=0., pos_limit=1e308, neg_limit=-1e308, rate=100, pos_p_limit=None, neg_p_limit=None):
     self._k_p = k_p
     self._k_i = k_i
     self._k_d = k_d
-    self.k_f = k_f   # feedforward gain
     if isinstance(self._k_p, Number):
       self._k_p = [[0], [self._k_p]]
     if isinstance(self._k_i, Number):
@@ -16,7 +15,7 @@ class PIDController:
 
     self.set_limits(pos_limit, neg_limit)
 
-    self.i_rate = 1.0 / rate
+    self.i_dt = 1.0 / rate
     self.speed = 0.0
 
     self.reset()
@@ -46,12 +45,12 @@ class PIDController:
 
   def update(self, error, error_rate=0.0, speed=0.0, feedforward=0., freeze_integrator=False):
     self.speed = speed
-    self.p = float(error) * self.k_p
-    self.f = feedforward * self.k_f
-    self.d = error_rate * self.k_d
+    self.p = self.k_p * float(error)
+    self.d = self.k_d * error_rate
+    self.f = feedforward
 
     if not freeze_integrator:
-      i = self.i + error * self.k_i * self.i_rate
+      i = self.i + self.k_i * self.i_dt * error
 
       # Don't allow windup if already clipping
       test_control = self.p + i + self.d + self.f

selfdrive/controls/plannerd.py

@@ -37,13 +37,11 @@ def plannerd_thread():
   # FrogPilot variables
   frogpilot_toggles = get_frogpilot_toggles()
 
-  classic_longitudinal = frogpilot_toggles.classic_longitudinal
-
   while True:
     sm.update()
     if sm.updated['modelV2']:
-      longitudinal_planner.update(sm, classic_longitudinal, frogpilot_toggles)
-      longitudinal_planner.publish(sm, pm)
+      longitudinal_planner.update(False, sm, frogpilot_toggles)
+      longitudinal_planner.publish(False, False, sm, pm, frogpilot_toggles)
       publish_ui_plan(sm, pm, longitudinal_planner)
 
     # Update FrogPilot variables

selfdrive/controls/radard.py

@@ -16,9 +16,10 @@ from openpilot.common.swaglog import cloudlog
 from openpilot.common.simple_kalman import KF1D
 
 from openpilot.frogpilot.common.frogpilot_variables import THRESHOLD, get_frogpilot_toggles
+from openpilot.selfdrive.controls.controlsd import LaneChangeDirection, LaneChangeState
 
 # Default lead acceleration decay set to 50% at 1s
-_LEAD_ACCEL_TAU = 1.5
+_LEAD_ACCEL_TAU = 0.6
 
 # radar tracks
 SPEED, ACCEL = 0, 1     # Kalman filter states enum
@@ -84,7 +85,7 @@ class Track:
 
     # Learn if constant acceleration
     if abs(self.aLeadK) < 0.5:
-      self.aLeadTau.x = _LEAD_ACCEL_TAU
+      self.aLeadTau.x = min(max(self.aLeadTau.x, 1e-2) * 1.1, _LEAD_ACCEL_TAU)
     else:
       self.aLeadTau.update(0.0)
 
@@ -149,7 +150,15 @@ def laplacian_pdf(x: float, mu: float, b: float):
   return math.exp(-abs(x-mu)/b)
 
 
-def match_vision_to_track(v_ego: float, lead: capnp._DynamicStructReader, tracks: dict[int, Track]):
+def match_vision_to_track(v_ego: float, lead: capnp._DynamicStructReader, model_data: capnp._DynamicStructReader, tracks: dict[int, Track], frogpilot_toggles: SimpleNamespace):
+  if model_data.meta.laneChangeState == LaneChangeState.laneChangeStarting and getattr(frogpilot_toggles, "human_lane_changes", False):
+    direction = model_data.meta.laneChangeDirection
+
+    if direction == LaneChangeDirection.left:
+      tracks = {k: v for k, v in tracks.items() if v.yRel > 0}
+    elif direction == LaneChangeDirection.right:
+      tracks = {k: v for k, v in tracks.items() if v.yRel < 0}
+
   offset_vision_dist = lead.x[0] - RADAR_TO_CAMERA
 
   def prob(c):
@@ -173,14 +182,16 @@ def match_vision_to_track(v_ego: float, lead: capnp._DynamicStructReader, tracks
 
 
 def get_RadarState_from_vision(lead_msg: capnp._DynamicStructReader, v_ego: float, model_v_ego: float):
-  lead_v_rel_pred = lead_msg.v[0] - model_v_ego
+  prev_aLeadK = getattr(get_RadarState_from_vision, "prev_aLeadK", 0.0)
+  blended_aLeadK = 0.8 * float(lead_msg.a[0]) + 0.2 * prev_aLeadK
+  get_RadarState_from_vision.prev_aLeadK = blended_aLeadK
   return {
     "dRel": float(lead_msg.x[0] - RADAR_TO_CAMERA),
     "yRel": float(-lead_msg.y[0]),
-    "vRel": float(lead_v_rel_pred),
-    "vLead": float(v_ego + lead_v_rel_pred),
-    "vLeadK": float(v_ego + lead_v_rel_pred),
-    "aLeadK": float(lead_msg.a[0]),
+    "vRel": float(lead_msg.v[0] - model_v_ego),
+    "vLead": float(v_ego + (lead_msg.v[0] - model_v_ego)),
+    "vLeadK": float(v_ego + (lead_msg.v[0] - model_v_ego)),
+    "aLeadK": blended_aLeadK,
     "aLeadTau": 0.3,
     "fcw": False,
     "modelProb": float(lead_msg.prob),
@@ -192,11 +203,11 @@ def get_RadarState_from_vision(lead_msg: capnp._DynamicStructReader, v_ego: floa
 
 def get_lead(v_ego: float, ready: bool, tracks: dict[int, Track], lead_msg: capnp._DynamicStructReader,
              model_v_ego: float, model_data: capnp._DynamicStructReader, standstill: bool,
-             frogpilot_toggles: SimpleNamespace, frogpilotPlan: capnp._DynamicStructReader,
+             frogpilotPlan: capnp._DynamicStructReader, frogpilot_toggles: SimpleNamespace,
              low_speed_override: bool = True) -> dict[str, Any]:
   # Determine leads, this is where the essential logic happens
   if len(tracks) > 0 and ready and lead_msg.prob > frogpilot_toggles.lead_detection_probability:
-    track = match_vision_to_track(v_ego, lead_msg, tracks)
+    track = match_vision_to_track(v_ego, lead_msg, model_data, tracks, frogpilot_toggles)
   else:
     track = None
 
@@ -313,8 +324,8 @@ class RadarD:
       model_v_ego = self.v_ego
     leads_v3 = sm['modelV2'].leadsV3
     if len(leads_v3) > 1:
-      self.radar_state.leadOne = get_lead(self.v_ego, self.ready, self.tracks, leads_v3[0], model_v_ego, sm['modelV2'], sm['carState'].standstill, self.frogpilot_toggles, sm['frogpilotPlan'], low_speed_override=True)
-      self.radar_state.leadTwo = get_lead(self.v_ego, self.ready, self.tracks, leads_v3[1], model_v_ego, sm['modelV2'], sm['carState'].standstill, self.frogpilot_toggles, sm['frogpilotPlan'], low_speed_override=False)
+      self.radar_state.leadOne = get_lead(self.v_ego, self.ready, self.tracks, leads_v3[0], model_v_ego, sm['modelV2'], sm['carState'].standstill, sm['frogpilotPlan'], self.frogpilot_toggles, low_speed_override=True)
+      self.radar_state.leadTwo = get_lead(self.v_ego, self.ready, self.tracks, leads_v3[1], model_v_ego, sm['modelV2'], sm['carState'].standstill, sm['frogpilotPlan'], self.frogpilot_toggles, low_speed_override=False)
 
     if self.frogpilot_toggles.adjacent_lead_tracking and self.ready:
       self.frogpilot_radar_state.leadLeft = get_adjacent_lead(self.tracks, sm['carState'].standstill, sm['modelV2'], left=True)

selfdrive/locationd/paramsd.py

@@ -187,8 +187,6 @@ def main():
   # FrogPilot variables
   frogpilot_toggles = get_frogpilot_toggles()
 
-  with custom.FrogPilotCarParams.from_bytes(params_reader.get("FrogPilotCarParams", block=True)) as msg:
-    FPCP = msg
 
   while True:
     sm.update()
@@ -240,7 +238,7 @@ def main():
         0.2 <= liveParameters.stiffnessFactor <= 5.0,
         min_sr <= liveParameters.steerRatio <= max_sr,
       ))
-      if CP.carFingerprint == "RAM_HD" or CP.carName == "subaru" and FPCP.lateralTuning.which() == "torque":
+      if CP.carFingerprint == "RAM_HD" or CP.carName == "subaru" and CP.lateralTuning.which() == "torque":
         liveParameters.valid = True
       liveParameters.steerRatioStd = float(P[States.STEER_RATIO].item())
       liveParameters.stiffnessFactorStd = float(P[States.STIFFNESS].item())

selfdrive/locationd/torqued.py

@@ -34,7 +34,8 @@ MIN_BUCKET_POINTS = np.array([100, 300, 500, 500, 500, 500, 300, 100])
 MIN_ENGAGE_BUFFER = 2  # secs
 
 VERSION = 1  # bump this to invalidate old parameter caches
-ALLOWED_CARS = ['toyota', 'hyundai']
+FULL_AUTO_CARS = ['toyota', 'hyundai']
+FRICTION_ONLY_CARS = ['gm']
 
 
 def slope2rot(slope):
@@ -52,7 +53,7 @@ class TorqueBuckets(PointBuckets):
 
 
 class TorqueEstimator(ParameterEstimator):
-  def __init__(self, CP, FPCP, decimated=False):
+  def __init__(self, CP, decimated=False):
     self.hist_len = int(HISTORY / DT_MDL)
     self.lag = 0.0
     if decimated:
@@ -72,11 +73,14 @@ class TorqueEstimator(ParameterEstimator):
     self.offline_friction = 0.0
     self.offline_latAccelFactor = 0.0
     self.resets = 0.0
-    self.use_params = CP.carName in ALLOWED_CARS and FPCP.lateralTuning.which() == 'torque'
+    self.allow_lat_accel_learning = CP.carName in FULL_AUTO_CARS and CP.lateralTuning.which() == 'torque'
+    self.allow_friction_learning = (self.allow_lat_accel_learning or CP.carName in FRICTION_ONLY_CARS) \
+                                   and CP.lateralTuning.which() == 'torque'
+    self.use_params = self.allow_friction_learning
 
-    if FPCP.lateralTuning.which() == 'torque':
-      self.offline_friction = FPCP.lateralTuning.torque.friction
-      self.offline_latAccelFactor = FPCP.lateralTuning.torque.latAccelFactor
+    if CP.lateralTuning.which() == 'torque':
+      self.offline_friction = CP.lateralTuning.torque.friction
+      self.offline_latAccelFactor = CP.lateralTuning.torque.latAccelFactor
 
     self.reset()
 
@@ -102,13 +106,13 @@ class TorqueEstimator(ParameterEstimator):
           cache_ltp = log_evt.liveTorqueParameters
         with car.CarParams.from_bytes(params_cache) as msg:
           cache_CP = msg
-        if self.get_restore_key(cache_CP, FPCP, cache_ltp.version) == self.get_restore_key(CP, FPCP, VERSION):
+        if self.get_restore_key(cache_CP, cache_ltp.version) == self.get_restore_key(CP, VERSION):
           if cache_ltp.liveValid:
-            initial_params = {
-              'latAccelFactor': cache_ltp.latAccelFactorFiltered,
-              'latAccelOffset': cache_ltp.latAccelOffsetFiltered,
-              'frictionCoefficient': cache_ltp.frictionCoefficientFiltered
-            }
+            if self.allow_lat_accel_learning:
+              initial_params['latAccelFactor'] = cache_ltp.latAccelFactorFiltered
+              initial_params['latAccelOffset'] = cache_ltp.latAccelOffsetFiltered
+            if self.allow_friction_learning:
+              initial_params['frictionCoefficient'] = cache_ltp.frictionCoefficientFiltered
           initial_params['points'] = cache_ltp.points
           self.decay = cache_ltp.decay
           self.filtered_points.load_points(initial_params['points'])
@@ -121,12 +125,12 @@ class TorqueEstimator(ParameterEstimator):
     for param in initial_params:
       self.filtered_params[param] = FirstOrderFilter(initial_params[param], self.decay, DT_MDL)
 
-  def get_restore_key(self, CP, FPCP, version):
+  def get_restore_key(self, CP, version):
     a, b = None, None
-    if FPCP.lateralTuning.which() == 'torque':
-      a = FPCP.lateralTuning.torque.friction
-      b = FPCP.lateralTuning.torque.latAccelFactor
-    return (CP.carFingerprint, FPCP.lateralTuning.which(), a, b, version)
+    if CP.lateralTuning.which() == 'torque':
+      a = CP.lateralTuning.torque.friction
+      b = CP.lateralTuning.torque.latAccelFactor
+    return (CP.carFingerprint, CP.lateralTuning.which(), a, b, version)
 
   def reset(self):
     self.resets += 1.0
@@ -155,6 +159,10 @@ class TorqueEstimator(ParameterEstimator):
   def update_params(self, params):
     self.decay = min(self.decay + DT_MDL, MAX_FILTER_DECAY)
     for param, value in params.items():
+      if param.startswith('latAccel') and not self.allow_lat_accel_learning:
+        continue
+      if param == 'frictionCoefficient' and not self.allow_friction_learning:
+        continue
       self.filtered_params[param].update(value)
       self.filtered_params[param].update_alpha(self.decay)
 
@@ -227,14 +235,14 @@ def main(demo=False):
   sm = messaging.SubMaster(['carControl', 'carOutput', 'carState', 'liveLocationKalman', 'liveDelay', 'frogpilotPlan'], poll='liveLocationKalman')
 
   params = Params()
-  with car.CarParams.from_bytes(params.get("CarParams", block=True)) as CP, custom.FrogPilotCarParams.from_bytes(params.get("FrogPilotCarParams", block=True)) as FPCP:
-    estimator = TorqueEstimator(CP, FPCP)
+  with car.CarParams.from_bytes(params.get("CarParams", block=True)) as CP:
+    estimator = TorqueEstimator(CP)
 
   # FrogPilot variables
   frogpilot_toggles = get_frogpilot_toggles()
 
   if not frogpilot_toggles.liveValid:
-    estimator = TorqueEstimator(CP, FPCP, decimated=True)
+    estimator = TorqueEstimator(CP, decimated=True)
 
   while True:
     sm.update()