live ui

* big needs small

* no download

* actually

* send it

.github/workflows/sunnypilot-build-prebuilt.yaml

@@ -211,6 +211,8 @@ jobs:
     needs: [ prepare_strategy ]
     runs-on: ubuntu-24.04
     if: ${{ needs.prepare_strategy.outputs.include_big_model == 'true' }}
+    outputs:
+      onnx_sha256: ${{ steps.resolve.outputs.onnx_sha256 }}
     env:
       HF_REPO: sunnypilot/sunnypilot_models_v1
       HF_DEFAULTS_PATH: models/defaults/big
@@ -226,6 +228,7 @@ jobs:
         run: |
           ACTUAL_ONNX_HASH=$(sha256sum "openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx" | cut -d' ' -f1)
           echo "Repo ONNX hash: $ACTUAL_ONNX_HASH"
+          echo "onnx_sha256=$ACTUAL_ONNX_HASH" >> $GITHUB_OUTPUT
 
           JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
 
@@ -267,36 +270,6 @@ jobs:
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
 
-      - name: Download big model chunks
-        run: |
-          ACTUAL_ONNX_HASH=$(sha256sum "openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx" | cut -d' ' -f1)
-          JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
-          DEFAULTS=$(curl -fsSL "$JSON_URL")
-          BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ACTUAL_ONNX_HASH" '.bundles[] | select(.onnx_sha256 == $hash)')
-
-          mkdir -p big_model_chunks
-          ARTIFACT=$(echo "$BUNDLE" | jq -r '.models[0].artifact')
-          BASE_URL=$(echo "$ARTIFACT" | jq -r '.download_uri.url' | sed 's|/[^/]*$||')
-          NUM_CHUNKS=$(echo "$ARTIFACT" | jq -r '.chunks | length')
-
-          CANONICAL="big_driving_tinygrad.pkl"
-          echo "$ARTIFACT" | jq -r '.chunks[].file_name' | while read CHUNK_NAME; do
-            CHUNK_IDX=$(echo "$CHUNK_NAME" | grep -oP 'chunk\K[0-9]+of[0-9]+')
-            CANONICAL_CHUNK="${CANONICAL}.chunk${CHUNK_IDX}"
-            ENCODED_URL=$(python3 -c "import urllib.parse; print(urllib.parse.quote('${BASE_URL}/${CHUNK_NAME}', safe=':/'))")
-            echo "Downloading $CHUNK_NAME -> $CANONICAL_CHUNK"
-            curl -fsSL -o "big_model_chunks/${CANONICAL_CHUNK}" "$ENCODED_URL"
-          done
-
-          echo "$NUM_CHUNKS" > "big_model_chunks/${CANONICAL}.chunkmanifest"
-
-      - name: Upload big model chunks
-        uses: actions/upload-artifact@v4
-        with:
-          name: big-model-chunks
-          path: big_model_chunks/
-          compression-level: 0
-
       - name: Cancel run on failure
         if: failure()
         run: gh run cancel ${{ github.run_id }}
@@ -339,12 +312,32 @@ jobs:
           mkdir -p "${{ github.workspace }}/chestnut_output"
           tar xzf prebuilt.tar.gz -C "${{ github.workspace }}/chestnut_output"
 
-      - name: Download big model chunks
+      - name: Download big model chunks from HF
         if: ${{ needs.prepare_chestnut.result == 'success' }}
-        uses: actions/download-artifact@v4
-        with:
-          name: big-model-chunks
-          path: big_model_chunks
+        env:
+          HF_REPO: sunnypilot/sunnypilot_models_v1
+          HF_DEFAULTS_PATH: models/defaults/big
+        run: |
+          ONNX_HASH="${{ needs.prepare_chestnut.outputs.onnx_sha256 }}"
+          JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
+          DEFAULTS=$(curl -fsSL "$JSON_URL")
+          BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ONNX_HASH" '.bundles[] | select(.onnx_sha256 == $hash)')
+
+          mkdir -p big_model_chunks
+          ARTIFACT=$(echo "$BUNDLE" | jq -r '.models[0].artifact')
+          BASE_URL=$(echo "$ARTIFACT" | jq -r '.download_uri.url' | sed 's|/[^/]*$||')
+          NUM_CHUNKS=$(echo "$ARTIFACT" | jq -r '.chunks | length')
+
+          CANONICAL="big_driving_tinygrad.pkl"
+          echo "$ARTIFACT" | jq -r '.chunks[].file_name' | while read CHUNK_NAME; do
+            CHUNK_IDX=$(echo "$CHUNK_NAME" | grep -oP 'chunk\K[0-9]+of[0-9]+')
+            CANONICAL_CHUNK="${CANONICAL}.chunk${CHUNK_IDX}"
+            ENCODED_URL=$(python3 -c "import urllib.parse; print(urllib.parse.quote('${BASE_URL}/${CHUNK_NAME}', safe=':/'))")
+            echo "Downloading $CHUNK_NAME -> $CANONICAL_CHUNK"
+            curl -fsSL -o "big_model_chunks/${CANONICAL_CHUNK}" "$ENCODED_URL"
+          done
+
+          echo "$NUM_CHUNKS" > "big_model_chunks/${CANONICAL}.chunkmanifest"
 
       - name: Inject big model into chestnut
         if: ${{ needs.prepare_chestnut.result == 'success' }}

.gitmodules

@@ -4,7 +4,6 @@
 [submodule "opendbc"]
   path = opendbc_repo
   url = https://github.com/sunnypilot/opendbc.git
-  branch = tn
 [submodule "msgq"]
   path = msgq_repo
   url = https://github.com/sunnypilot/msgq.git

openpilot/cereal/custom.capnp

@@ -203,16 +203,11 @@ struct LongitudinalPlanSP @0xf35cc4560bbf6ec2 {
   aTarget @5 :Float32;
   events @6 :List(OnroadEventSP.Event);
   e2eAlerts @7 :E2eAlerts;
-  accelController @8 :AccelController;
 
   struct DynamicExperimentalControl {
     state @0 :DynamicExperimentalControlState;
     enabled @1 :Bool;
     active @2 :Bool;
-    decelIntent @3 :Float32;
-    curveDetected @4 :Bool;
-    wantBlended @5 :Bool;
-    leadVeto @6 :Bool;
 
     enum DynamicExperimentalControlState {
       acc @0;
@@ -310,17 +305,6 @@ struct LongitudinalPlanSP @0xf35cc4560bbf6ec2 {
     greenLightAlert @0 :Bool;
     leadDepartAlert @1 :Bool;
   }
-
-  struct AccelController {
-    enabled @0 :Bool;
-    active @1 :Bool;
-    profile @2 :Profile;
-    enum Profile {
-      eco @0;
-      normal @1;
-      sport @2;
-    }
-  }
 }
 
 struct OnroadEventSP @0xda96579883444c35 {

openpilot/common/params_keys.h

@@ -187,12 +187,6 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"StandstillTimer", {PERSISTENT | BACKUP, BOOL, "0"}},
     {"TrueVEgoUI", {PERSISTENT | BACKUP, BOOL, "0"}},
 
-    // toyota specific params
-    {"ToyotaAutoHold", {PERSISTENT | BACKUP, BOOL, "0"}},
-    {"ToyotaEnhancedBsm", {PERSISTENT | BACKUP, BOOL, "0"}},
-    {"ToyotaTSS2Long", {PERSISTENT | BACKUP, BOOL, "0"}},
-    {"ToyotaDriveMode", {PERSISTENT | BACKUP, BOOL, "0"}},
-
     // MADS params
     {"Mads", {PERSISTENT | BACKUP, BOOL, "1"}},
     {"MadsMainCruiseAllowed", {PERSISTENT | BACKUP, BOOL, "1"}},
@@ -240,10 +234,6 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {
     {"DynamicExperimentalControl", {PERSISTENT | BACKUP, BOOL, "0"}},
     {"BlindSpot", {PERSISTENT | BACKUP, BOOL, "0"}},
 
-    // Accel Controller profiles (Eco / Normal / Sport)
-    {"AccelPersonalityEnabled", {PERSISTENT | BACKUP, BOOL, "0"}},
-    {"AccelPersonality", {PERSISTENT | BACKUP, INT, "1"}},
-
     // sunnypilot model params
     {"CameraOffset", {PERSISTENT | BACKUP, FLOAT, "0.0"}},
     {"LagdToggle", {PERSISTENT | BACKUP, BOOL, "1"}},

openpilot/common/tests/test_params.py

@@ -117,16 +117,12 @@ class TestParams(OpenpilotTestCase):
   def test_params_default_value(self):
     self.params.remove("LanguageSetting")
     self.params.remove("LongitudinalPersonality")
-    self.params.remove("AccelPersonalityEnabled")
-    self.params.remove("AccelPersonality")
     self.params.remove("LiveParametersV2")
 
     assert self.params.get("LanguageSetting") is None
     assert self.params.get("LanguageSetting", return_default=False) is None
     assert isinstance(self.params.get("LanguageSetting", return_default=True), str)
     assert isinstance(self.params.get("LongitudinalPersonality", return_default=True), int)
-    assert self.params.get("AccelPersonalityEnabled", return_default=True) is False
-    assert self.params.get("AccelPersonality", return_default=True) == 1
     assert self.params.get("LiveParametersV2") is None
     assert self.params.get("LiveParametersV2", return_default=True) is None
 

openpilot/selfdrive/car/card.py

@@ -11,13 +11,13 @@ from opendbc.car.structs import car
 from openpilot.common.params import Params
 from openpilot.common.realtime import config_realtime_process, Priority, Ratekeeper
 from openpilot.common.swaglog import cloudlog, ForwardingHandler
+
 from opendbc.car import DT_CTRL, structs
 from opendbc.car.can_definitions import CanData, CanRecvCallable, CanSendCallable
 from opendbc.car.carlog import carlog
 from opendbc.car.fw_versions import ObdCallback
 from opendbc.car.car_helpers import get_car, interfaces
 from opendbc.car.interfaces import CarInterfaceBase, RadarInterfaceBase
-from opendbc.safety import ALTERNATIVE_EXPERIENCE
 from openpilot.selfdrive.pandad import can_capnp_to_list, can_list_to_can_capnp
 from openpilot.selfdrive.car.cruise import VCruiseHelper
 from openpilot.selfdrive.car.helpers import convert_carControlSP, convert_to_capnp
@@ -123,9 +123,6 @@ class Car:
       self.RI = RI
 
     self.CP.alternativeExperience = 0
-    if self.params.get_bool("ToyotaAutoHold"):
-      self.CP.alternativeExperience |= ALTERNATIVE_EXPERIENCE.ALLOW_AEB
-
     # mads
     set_alternative_experience(self.CP, self.CP_SP, self.params)
     set_car_specific_params(self.CP, self.CP_SP, self.params)

openpilot/selfdrive/car/cruise.py

@@ -19,7 +19,6 @@ IMPERIAL_INCREMENT = round(CV.MPH_TO_KPH, 1)  # round here to avoid rounding err
 ButtonEvent = car.CarState.ButtonEvent
 ButtonType = car.CarState.ButtonEvent.Type
 CRUISE_LONG_PRESS = 50
-TOYOTA_VIRTUAL_CRUISE_LONG_PRESS = 65
 CRUISE_NEAREST_FUNC = {
   ButtonType.accelCruise: math.ceil,
   ButtonType.decelCruise: math.floor,
@@ -44,30 +43,6 @@ class VCruiseHelper(VCruiseHelperSP):
   def v_cruise_initialized(self):
     return self.v_cruise_kph != V_CRUISE_UNSET
 
-  @property
-  def software_pcm_cruise_speed(self) -> bool:
-    return self.CP.brand == "toyota" and self.CP.pcmCruise and self.CP.openpilotLongitudinalControl and not self.CP_SP.pcmCruiseSpeed
-
-  @property
-  def cruise_long_press_frames(self) -> int:
-    return TOYOTA_VIRTUAL_CRUISE_LONG_PRESS if self.software_pcm_cruise_speed else CRUISE_LONG_PRESS
-
-  @property
-  def software_pcm_cruise_initialized(self) -> bool:
-    return 0 < self.v_cruise_kph < V_CRUISE_UNSET and 0 < self.v_cruise_cluster_kph < V_CRUISE_UNSET
-
-  def _apply_software_pcm_cruise_delta(self, delta_kph: float, is_metric: bool) -> None:
-    """Move Toyota's planner/display targets together while respecting both targets' bounds."""
-    cluster_min_kph = self.v_cruise_min if is_metric else self.v_cruise_min * CV.MPH_TO_KPH
-    min_delta = max(V_CRUISE_MIN - self.v_cruise_kph, cluster_min_kph - self.v_cruise_cluster_kph)
-    max_delta = min(V_CRUISE_MAX - self.v_cruise_kph, V_CRUISE_MAX - self.v_cruise_cluster_kph)
-    if delta_kph > 0:
-      applied_delta = min(delta_kph, max(0., max_delta))
-    else:
-      applied_delta = max(delta_kph, min(0., min_delta))
-    self.v_cruise_kph = round(self.v_cruise_kph + applied_delta, 1)
-    self.v_cruise_cluster_kph = round(self.v_cruise_cluster_kph + applied_delta, 1)
-
   def update_v_cruise(self, CS, enabled, is_metric):
     self.v_cruise_kph_last = self.v_cruise_kph
 
@@ -76,21 +51,11 @@ class VCruiseHelper(VCruiseHelperSP):
     _enabled = self.update_enabled_state(CS, enabled)
 
     if CS.cruiseState.available:
-      software_pcm_enabled = not self.CP_SP.pcmCruiseSpeed and _enabled
-      if self.software_pcm_cruise_speed:
-        software_pcm_enabled = software_pcm_enabled and self.software_pcm_cruise_initialized
-
-      if not self.CP.pcmCruise or software_pcm_enabled:
+      if not self.CP.pcmCruise or (not self.CP_SP.pcmCruiseSpeed and _enabled):
         # if stock cruise is completely disabled, then we can use our own set speed logic
         self._update_v_cruise_non_pcm(CS, _enabled, is_metric)
-        v_cruise_kph_before_sla = self.v_cruise_kph
         self.update_speed_limit_assist_v_cruise_non_pcm()
-        if self.software_pcm_cruise_speed:
-          sla_delta_kph = self.v_cruise_kph - v_cruise_kph_before_sla
-          self.v_cruise_kph = v_cruise_kph_before_sla
-          self._apply_software_pcm_cruise_delta(sla_delta_kph, is_metric)
-        else:
-          self.v_cruise_cluster_kph = self.v_cruise_kph
+        self.v_cruise_cluster_kph = self.v_cruise_kph
       else:
         self.v_cruise_kph = CS.cruiseState.speed * CV.MS_TO_KPH
         self.v_cruise_cluster_kph = CS.cruiseState.speedCluster * CV.MS_TO_KPH
@@ -120,13 +85,13 @@ class VCruiseHelper(VCruiseHelperSP):
 
     for b in CS.buttonEvents:
       if b.type.raw in self.button_timers and not b.pressed:
-        if self.button_timers[b.type.raw] > self.cruise_long_press_frames:
+        if self.button_timers[b.type.raw] > CRUISE_LONG_PRESS:
           return  # end long press
         button_type = b.type.raw
         break
     else:
       for k, timer in self.button_timers.items():
-        if timer and timer % self.cruise_long_press_frames == 0:
+        if timer and timer % CRUISE_LONG_PRESS == 0:
           button_type = k
           long_press = True
           break
@@ -150,26 +115,10 @@ class VCruiseHelper(VCruiseHelperSP):
       return
 
     long_press, v_cruise_delta = VCruiseHelperSP.update_v_cruise_delta(self, long_press, v_cruise_delta)
-    # Toyota's canonical PCM set speed and displayed cluster set speed can differ. In
-    # software-owned PCM mode, round the value the driver sees and apply the same delta
-    # to both targets so the planner/cluster calibration offset remains intact.
-    v_cruise_reference = self.v_cruise_cluster_kph if self.software_pcm_cruise_speed else self.v_cruise_kph
-    if long_press and v_cruise_reference % v_cruise_delta != 0:  # partial interval
-      v_cruise_reference_new = CRUISE_NEAREST_FUNC[button_type](v_cruise_reference / v_cruise_delta) * v_cruise_delta
+    if long_press and self.v_cruise_kph % v_cruise_delta != 0:  # partial interval
+      self.v_cruise_kph = CRUISE_NEAREST_FUNC[button_type](self.v_cruise_kph / v_cruise_delta) * v_cruise_delta
     else:
-      v_cruise_reference_new = v_cruise_reference + v_cruise_delta * CRUISE_INTERVAL_SIGN[button_type]
-
-    if self.software_pcm_cruise_speed:
-      delta_kph = v_cruise_reference_new - v_cruise_reference
-
-      # If SET is pressed while overriding, do not lower the target below the current speed.
-      if CS.gasPressed and button_type in (ButtonType.decelCruise, ButtonType.setCruise):
-        delta_kph = max(delta_kph, CS.vEgo * CV.MS_TO_KPH - self.v_cruise_kph)
-
-      self._apply_software_pcm_cruise_delta(delta_kph, is_metric)
-      return
-
-    self.v_cruise_kph += v_cruise_reference_new - v_cruise_reference
+      self.v_cruise_kph += v_cruise_delta * CRUISE_INTERVAL_SIGN[button_type]
 
     # If set is pressed while overriding, clip cruise speed to minimum of vEgo
     if CS.gasPressed and button_type in (ButtonType.decelCruise, ButtonType.setCruise):
@@ -178,12 +127,6 @@ class VCruiseHelper(VCruiseHelperSP):
     self.v_cruise_kph = np.clip(round(self.v_cruise_kph, 1), self.v_cruise_min, V_CRUISE_MAX)
 
   def update_button_timers(self, CS, enabled):
-    if self.software_pcm_cruise_speed and (not enabled or not CS.cruiseState.available or not self.software_pcm_cruise_initialized):
-      for k in self.button_timers:
-        self.button_timers[k] = 0
-        self.button_change_states[k] = {"standstill": False, "enabled": False}
-      return
-
     # increment timer for buttons still pressed
     for k in self.button_timers:
       if self.button_timers[k] > 0:

openpilot/selfdrive/controls/lib/drive_helpers.py

@@ -14,11 +14,8 @@ MAX_LATERAL_JERK = 5.0  # m/s^3
 MAX_LATERAL_ACCEL_NO_ROLL = 3.0  # m/s^2
 
 
-STOPPING_SPEED = 0.25  # m/s
-
-
 def should_stop(v_ego: float, a_target: float) -> bool:
-  return bool(v_ego < STOPPING_SPEED and a_target < 0.1)
+  return bool(v_ego < 0.3 and a_target < 0.1)
 
 def clamp(val, min_val, max_val):
   clamped_val = float(np.clip(val, min_val, max_val))

openpilot/selfdrive/controls/lib/longcontrol.py

@@ -7,8 +7,6 @@ from openpilot.selfdrive.modeld.constants import ModelConstants
 
 CONTROL_N_T_IDX = ModelConstants.T_IDXS[:CONTROL_N]
 
-STOPPING_DECEL_RATE = 0.3  # m/s^2/s while trying to stop
-
 LongCtrlState = car.CarControl.Actuators.LongControlState
 
 
@@ -69,7 +67,8 @@ class LongControl:
       output_accel = self.last_output_accel
       if output_accel > self.CP.stopAccel:
         output_accel = min(output_accel, 0.0)
-        output_accel -= STOPPING_DECEL_RATE * DT_CTRL
+        # TODO: can we just go straight to stopAccel?
+        output_accel -= 1.0 * DT_CTRL  # m/s^2/s while trying to stop
       self.reset()
 
     else:  # LongCtrlState.pid

openpilot/selfdrive/controls/lib/longitudinal_planner.py

@@ -35,12 +35,9 @@ def get_max_accel(v_ego):
 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
 
-def get_cruise_accel(e2e, v_cruise, v_ego, a_cruise_prev, angle_steers, CP, dt, accel_coast, allow_throttle,
-                      max_accel_override=None):
-  if max_accel_override is not None:
-    max_accel = max_accel_override
-  else:
-    max_accel = ACCEL_MAX if e2e else get_max_accel(v_ego)
+def get_cruise_accel(e2e, v_cruise, v_ego, a_cruise_prev, angle_steers, CP, dt, accel_coast, allow_throttle):
+  max_accel = ACCEL_MAX if e2e else get_max_accel(v_ego)
+
   if not e2e:
     a_total_max = np.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)
@@ -87,8 +84,7 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
     v_ego = sm['carState'].vEgo
     v_cruise_kph = min(sm['carState'].vCruise, V_CRUISE_MAX)
     v_cruise = v_cruise_kph * CV.KPH_TO_MS
-    force_decel = sm['controlsState'].forceDecel
-    if force_decel:
+    if sm['controlsState'].forceDecel:
       v_cruise = 0.0
 
     long_control_off = sm['controlsState'].longControlState == LongCtrlState.off
@@ -101,8 +97,7 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
 
     throttle_probs = sm['modelV2'].meta.disengagePredictions.gasPressProbs
     throttle_prob = throttle_probs[1] if len(throttle_probs) > 1 else 1.0
-    self.allow_throttle = self.update_allow_throttle(throttle_prob, low_speed_override=v_ego <= MIN_ALLOW_THROTTLE_SPEED,
-                                                     threshold=ALLOW_THROTTLE_THRESHOLD)
+    self.allow_throttle = throttle_prob > ALLOW_THROTTLE_THRESHOLD or v_ego <= MIN_ALLOW_THROTTLE_SPEED
 
     steer_angle_without_offset = sm['carState'].steeringAngleDeg - sm['vehicleParameters'].angleOffsetDeg
 
@@ -123,7 +118,6 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
     self.mpc.set_weights(prev_accel_constraint, personality=sm['selfdriveState'].personality)
     self.mpc.set_cur_state(self.v_desired_filter.x, self.output_a_target)
     self.mpc.update(sm['radarState'], personality=sm['selfdriveState'].personality)
-    self.update_dec(sm)
 
     self.v_desired_trajectory = np.interp(CONTROL_N_T_IDX, T_IDXS_MPC, self.mpc.v_solution)
     self.a_desired_trajectory = np.interp(CONTROL_N_T_IDX, T_IDXS_MPC, self.mpc.a_solution)
@@ -141,23 +135,14 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
     output_a_target_mpc = get_accel_from_plan(self.v_desired_trajectory, self.a_desired_trajectory, CONTROL_N_T_IDX,
                                               action_t=action_t)
     output_should_stop_mpc = should_stop(v_ego, output_a_target_mpc)
-    output_a_target_mpc, output_should_stop_mpc = self.update_lead_departure(sm, output_a_target_mpc, output_should_stop_mpc, reset_state)
     output_a_target_e2e = sm['modelV2'].action.desiredAcceleration
     output_should_stop_e2e = sm['modelV2'].action.shouldStop
 
     is_e2e = self.is_e2e(sm)
 
-    max_accel_override = self.get_max_accel_override(v_ego, v_cruise, is_e2e)
-    v_cruise = self.get_cruise_target_override(v_ego, v_cruise, is_e2e)
-    a_cruise_prev = self.a_cruise
-    gated_cruise = get_cruise_accel(is_e2e, v_cruise, v_ego, a_cruise_prev, steer_angle_without_offset,
-                                    self.CP, self.dt, accel_coast, self.allow_throttle, max_accel_override)
-    ungated_cruise = get_cruise_accel(is_e2e, v_cruise, v_ego, a_cruise_prev, steer_angle_without_offset,
-                                      self.CP, self.dt, accel_coast, True, max_accel_override)
-    self.a_cruise = self.arbitrate_cruise_candidate(
-      sm, gated_cruise, ungated_cruise, output_a_target_mpc, self.mpc.source,
-      allow_throttle=self.allow_throttle, e2e=is_e2e, force_decel=force_decel,
-    )
+    self.a_cruise = get_cruise_accel(is_e2e, v_cruise, v_ego,
+                                     self.a_cruise, steer_angle_without_offset, self.CP, self.dt,
+                                     accel_coast, self.allow_throttle)
     cruise_should_stop = should_stop(v_ego, self.a_cruise)
 
     candidates = [(output_a_target_mpc, self.mpc.source, output_should_stop_mpc),
@@ -192,7 +177,6 @@ class LongitudinalPlanner(LongitudinalPlannerSP):
     longitudinalPlan.aTarget = float(self.output_a_target)
     longitudinalPlan.shouldStop = bool(self.output_should_stop)
     longitudinalPlan.allowBrake = True
-    # Raw model throttle intent used for path visualization; lead MPC can still request positive acceleration.
     longitudinalPlan.allowThrottle = bool(self.allow_throttle)
 
     pm.send('longitudinalPlan', plan_send)

openpilot/selfdrive/controls/tests/test_longcontrol.py

@@ -1,40 +1,10 @@
-from types import SimpleNamespace
-
 from openpilot.common.test import OpenpilotTestCase
-from openpilot.common.realtime import DT_CTRL
 from openpilot.cereal import custom
-from openpilot.selfdrive.controls.lib.drive_helpers import should_stop
-from openpilot.selfdrive.controls.lib.longcontrol import LongControl, LongCtrlState, long_control_state_trans
-
-
-def make_stopping_control(last_output_accel):
-  CP = SimpleNamespace(stopAccel=-2.0, longitudinalTuning=SimpleNamespace(kiBP=[0.0], kiV=[0.0]))
-  control = LongControl(CP, custom.CarParamsSP.new_message())
-  control.long_control_state = LongCtrlState.stopping
-  control.last_output_accel = last_output_accel
-  CS = SimpleNamespace(aEgo=0.0, brakePressed=False, cruiseState=SimpleNamespace(standstill=False), vEgo=0.0)
-  return control, CS
+from openpilot.selfdrive.controls.lib.longcontrol import LongCtrlState, long_control_state_trans
 
 
 class TestLongControlStateTransition(OpenpilotTestCase):
 
-  def test_stopping_threshold_boundaries(self):
-    assert should_stop(0.249, 0.099)
-    assert not should_stop(0.250, 0.099)
-    assert not should_stop(0.249, 0.1)
-
-  def test_stopping_ramp_rate(self):
-    control, CS = make_stopping_control(-0.2)
-    output = control.update(True, CS, a_target=-0.2, should_stop=True, accel_limits=(-3.5, 2.0))
-
-    self.assertAlmostEqual(output, -0.2 - 0.3 * DT_CTRL)
-
-  def test_stopping_does_not_release_stronger_braking(self):
-    control, CS = make_stopping_control(-2.2)
-    output = control.update(True, CS, a_target=-0.2, should_stop=True, accel_limits=(-3.5, 2.0))
-
-    self.assertEqual(output, -2.2)
-
   def test_stay_stopped(self):
     CP_SP = custom.CarParamsSP.new_message()
     active = True

openpilot/selfdrive/pandad/spi.cc

@@ -29,6 +29,12 @@ enum SpiError {
 
 const unsigned int SPI_ACK_TIMEOUT = 500; // milliseconds
 const std::string SPI_DEVICE = "/dev/spidev0.0";
+// TODO: fix SPI turnaround synchronization at the protocol level.
+static uint64_t spi_last_bus_activity_ns = 0;  // protected by hw_lock
+
+static void wait_for_spi_turnaround(uint64_t start_ns) {
+  while ((nanos_since_boot() - start_ns) < 400000) {}
+}
 
 class LockEx {
 public:
@@ -319,6 +325,8 @@ int PandaSpiHandle::spi_transfer(uint8_t endpoint, uint8_t *tx_data, uint16_t tx
   assert(tx_len < SPI_BUF_SIZE);
   assert(max_rx_len < SPI_BUF_SIZE);
 
+  wait_for_spi_turnaround(spi_last_bus_activity_ns);
+
   xfer_count++;
   header = {
     .sync = SPI_SYNC,
@@ -347,6 +355,7 @@ int PandaSpiHandle::spi_transfer(uint8_t endpoint, uint8_t *tx_data, uint16_t tx
   if (ret < 0) {
     goto fail;
   }
+  wait_for_spi_turnaround(nanos_since_boot());
 
   // Send data
   if (tx_data != NULL) {
@@ -389,6 +398,7 @@ int PandaSpiHandle::spi_transfer(uint8_t endpoint, uint8_t *tx_data, uint16_t tx
     memcpy(rx_data, rx_buf + 3, rx_data_len);
   }
 
+  spi_last_bus_activity_ns = nanos_since_boot();
   return rx_data_len;
 
 fail:
@@ -403,6 +413,7 @@ fail:
     }
   }
 
+  spi_last_bus_activity_ns = nanos_since_boot();
   if (ret >= 0) ret = -1;
   return ret;
 }

openpilot/selfdrive/test/longitudinal_maneuvers/plant.py

@@ -11,15 +11,6 @@ from openpilot.selfdrive.controls.lib.longitudinal_planner import LongitudinalPl
 from openpilot.selfdrive.controls.radard import _LEAD_ACCEL_TAU
 
 
-class PlannerSM(dict):
-  def __init__(self, radar_frame: int, services: dict):
-    super().__init__(services)
-    self.frame = radar_frame
-    self.logMonoTime = {"radarState": radar_frame}
-    self.valid = {"radarState": True}
-    self.alive = {"radarState": True}
-
-
 class Plant:
   messaging_initialized = False
 
@@ -141,7 +132,7 @@ class Plant:
     car_control.carControl.orientationNED = [0., float(pitch), 0.]
 
     # ******** get controlsState messages for plotting ***
-    sm = PlannerSM(self.rk.frame, {'radarState': radar.radarState,
+    sm = {'radarState': radar.radarState,
           'carState': car_state.carState,
           'carControl': car_control.carControl,
           'controlsState': control.controlsState,
@@ -150,7 +141,7 @@ class Plant:
           'modelV2': model.modelV2,
           'carStateSP': car_state_sp.carStateSP,
           'liveMapDataSP': live_map_data_sp.liveMapDataSP,
-          'gpsLocation': gps_data.gpsLocation})
+          'gpsLocation': gps_data.gpsLocation}
     self.planner.update(sm)
     self.acceleration = self.planner.output_a_target
     if self.planner.output_should_stop:

openpilot/selfdrive/ui/layouts/settings/toggles.py

@@ -27,12 +27,6 @@ DESCRIPTIONS = {
     "In relaxed mode sunnypilot will stay further away from lead cars. On supported cars, you can cycle through these personalities with " +
     "your steering wheel distance button."
   ),
-  "AccelPersonalityEnabled": tr_noop(
-    "Lets you choose how sunnypilot starts, catches up, and settles at the cruise speed. Emergency braking and stopping are unchanged."
-  ),
-  "AccelPersonality": tr_noop(
-    "Eco is gentlest, Normal balances a prompt start with smooth catch-up, and Sport is more responsive."
-  ),
   "IsLdwEnabled": tr_noop(
     "Receive alerts to steer back into the lane when your vehicle drifts over a detected lane line " +
     "without a turn signal activated while driving over 31 mph (50 km/h)."
@@ -112,24 +106,6 @@ class TogglesLayout(Widget):
       icon="speed_limit.png"
     )
 
-    self._accel_controller_enabled = toggle_item(
-      lambda: tr("Enable Accel Controller"),
-      lambda: tr(DESCRIPTIONS["AccelPersonalityEnabled"]),
-      self._params.get_bool("AccelPersonalityEnabled"),
-      callback=self._set_accel_controller_enabled,
-      icon="speed_limit.png",
-    )
-
-    self._accel_personality_setting = multiple_button_item(
-      lambda: tr("Acceleration Profile"),
-      lambda: tr(DESCRIPTIONS["AccelPersonality"]),
-      buttons=[lambda: tr("Eco"), lambda: tr("Normal"), lambda: tr("Sport")],
-      button_width=300,
-      callback=self._set_accel_personality,
-      selected_index=self._params.get("AccelPersonality", return_default=True),
-      icon="speed_limit.png"
-    )
-
     self._toggles = {}
     self._locked_toggles = set()
     for param, (title, desc, icon, needs_restart) in self._toggle_defs.items():
@@ -159,11 +135,9 @@ class TogglesLayout(Widget):
 
       self._toggles[param] = toggle
 
-      # insert longitudinal personality and Accel Controller settings after NDOG toggle
+      # insert longitudinal personality after NDOG toggle
       if param == "DisengageOnAccelerator":
         self._toggles["LongitudinalPersonality"] = self._long_personality_setting
-        self._toggles["AccelPersonalityEnabled"] = self._accel_controller_enabled
-        self._toggles["AccelPersonality"] = self._accel_personality_setting
 
     self._update_experimental_mode_icon()
     self._scroller = Scroller(list(self._toggles.values()), line_separator=True, spacing=0)
@@ -184,7 +158,6 @@ class TogglesLayout(Widget):
 
   def _update_toggles(self):
     ui_state.update_params()
-    accel_controller_enabled = self._params.get_bool("AccelPersonalityEnabled")
 
     e2e_description = tr(
       "sunnypilot defaults to driving in chill mode. Experimental mode enables alpha-level features that aren't ready for chill mode. " +
@@ -203,15 +176,11 @@ class TogglesLayout(Widget):
         self._toggles["ExperimentalMode"].action_item.set_enabled(True)
         self._toggles["ExperimentalMode"].set_description(e2e_description)
         self._long_personality_setting.action_item.set_enabled(True)
-        self._accel_controller_enabled.action_item.set_enabled(True)
-        self._accel_personality_setting.action_item.set_enabled(True)
       else:
         # no long for now
         self._toggles["ExperimentalMode"].action_item.set_enabled(False)
         self._toggles["ExperimentalMode"].action_item.set_state(False)
         self._long_personality_setting.action_item.set_enabled(False)
-        self._accel_controller_enabled.action_item.set_enabled(False)
-        self._accel_personality_setting.action_item.set_enabled(False)
         self._params.remove("ExperimentalMode")
 
         unavailable = tr("Experimental mode is currently unavailable on this car since the car's stock ACC is used for longitudinal control.")
@@ -234,8 +203,6 @@ class TogglesLayout(Widget):
     # refresh toggles from params to mirror external changes
     for param in self._toggle_defs:
       self._toggles[param].action_item.set_state(self._params.get_bool(param))
-    self._accel_controller_enabled.action_item.set_state(accel_controller_enabled)
-    self._accel_personality_setting.action_item.set_selected_button(self._params.get("AccelPersonality", return_default=True))
 
     # these toggles need restart, block while engaged
     for toggle_def in self._toggle_defs:
@@ -280,9 +247,3 @@ class TogglesLayout(Widget):
 
   def _set_longitudinal_personality(self, button_index: int):
     self._params.put("LongitudinalPersonality", button_index, block=True)
-
-  def _set_accel_personality(self, button_index: int):
-    self._params.put("AccelPersonality", button_index, block=True)
-
-  def _set_accel_controller_enabled(self, state: bool):
-    self._params.put_bool("AccelPersonalityEnabled", state, block=True)

openpilot/selfdrive/ui/mici/layouts/main.py

@@ -14,7 +14,6 @@ from openpilot.system.ui.lib.application import gui_app
 if gui_app.sunnypilot_ui():
   from openpilot.selfdrive.ui.sunnypilot.mici.layouts.settings import SettingsLayoutSP as SettingsLayout
   from openpilot.selfdrive.ui.sunnypilot.mici.layouts.home import MiciHomeLayoutSP as MiciHomeLayout
-  from openpilot.selfdrive.ui.sunnypilot.mici.layouts.onroad import OnroadViewContainerSP as AugmentedRoadView
 
 ONROAD_DELAY = 2.5  # seconds
 
@@ -73,9 +72,6 @@ class MiciMainLayout(Scroller):
     # For scroll_to
     return self._body_onroad_layout if ui_state.is_body else self._car_onroad_layout
 
-  def _should_auto_scroll_to_onroad(self) -> bool:
-    return True
-
   def _setup_callbacks(self):
     self._home_layout.set_callbacks(
       on_settings=lambda: gui_app.push_widget(self._settings_layout),
@@ -126,15 +122,13 @@ class MiciMainLayout(Scroller):
 
     # FIXME: these two pops can interrupt user interacting in the settings
     if self._onroad_time_delay is not None and rl.get_time() - self._onroad_time_delay >= ONROAD_DELAY:
-      if not gui_app.sunnypilot_ui() or self._should_auto_scroll_to_onroad():
-        gui_app.pop_widgets_to(self, lambda: self._scroll_to(self._onroad_layout))
+      gui_app.pop_widgets_to(self, lambda: self._scroll_to(self._onroad_layout))
       self._onroad_time_delay = None
 
     # When car leaves standstill, pop nav stack and scroll to onroad
     CS = ui_state.sm["carState"]
     if not CS.standstill and self._prev_standstill:
-      if not gui_app.sunnypilot_ui() or self._should_auto_scroll_to_onroad():
-        gui_app.pop_widgets_to(self, lambda: self._scroll_to(self._onroad_layout))
+      gui_app.pop_widgets_to(self, lambda: self._scroll_to(self._onroad_layout))
     self._prev_standstill = CS.standstill
 
   def _on_interactive_timeout(self):

openpilot/selfdrive/ui/mici/layouts/settings/toggles.py

@@ -42,8 +42,6 @@ class TogglesLayoutMici(NavScroller):
     super().__init__()
 
     self._personality_toggle = BigMultiParamToggle("driving personality", "LongitudinalPersonality", ["aggressive", "standard", "relaxed"])
-    self._accel_controller_enabled = BigParamControl("enable accel controller", "AccelPersonalityEnabled")
-    self._accel_personality_toggle = BigMultiParamToggle("acceleration profile", "AccelPersonality", ["eco", "normal", "sport"])
     self._experimental_btn = BigToggle("experimental mode", initial_state=ui_state.params.get_bool("ExperimentalMode"),
                                        toggle_callback=self._on_experimental_mode)
     is_metric_toggle = BigParamControl("use metric units", "IsMetric")
@@ -55,8 +53,6 @@ class TogglesLayoutMici(NavScroller):
 
     self._scroller.add_widgets([
       self._personality_toggle,
-      self._accel_controller_enabled,
-      self._accel_personality_toggle,
       self._experimental_btn,
       is_metric_toggle,
       ldw_toggle,
@@ -69,7 +65,6 @@ class TogglesLayoutMici(NavScroller):
     # Toggle lists
     self._refresh_toggles = (
       ("ExperimentalMode", self._experimental_btn),
-      ("AccelPersonalityEnabled", self._accel_controller_enabled),
       ("IsMetric", is_metric_toggle),
       ("IsLdwEnabled", ldw_toggle),
       ("AlwaysOnDM", always_on_dm_toggle),
@@ -109,23 +104,17 @@ class TogglesLayoutMici(NavScroller):
       if ui_state.has_longitudinal_control:
         self._experimental_btn.set_visible(True)
         self._personality_toggle.set_visible(True)
-        self._accel_controller_enabled.set_visible(True)
-        self._accel_personality_toggle.set_visible(True)
       else:
         # no long for now
         self._experimental_btn.set_visible(False)
         self._experimental_btn.set_checked(False)
         self._personality_toggle.set_visible(False)
-        self._accel_controller_enabled.set_visible(False)
-        self._accel_personality_toggle.set_visible(False)
         ui_state.params.remove("ExperimentalMode")
 
     # Refresh toggles from params to mirror external changes
     for key, item in self._refresh_toggles:
       item.set_checked(ui_state.params.get_bool(key))
 
-    self._accel_personality_toggle.refresh()
-
   def _on_experimental_mode(self, state: bool):
     if state and not ui_state.params.get_bool("ExperimentalModeConfirmed"):
       # Don't show enabled state until confirm

openpilot/selfdrive/ui/mici/onroad/model_renderer.py

@@ -154,8 +154,8 @@ class ModelRenderer(Widget, ModelRendererSP):
       self._draw_lane_lines()
       self._draw_path(sm)
 
-    if render_lead_indicator and radar_state:
-      self._draw_lead_indicator()
+    # if render_lead_indicator and radar_state:
+    #   self._draw_lead_indicator()
 
   def _update_raw_points(self, model):
     """Update raw 3D points from model data"""

openpilot/selfdrive/ui/mici/widgets/button.py

@@ -385,18 +385,13 @@ class BigMultiParamToggle(BigMultiToggle):
     self._load_value()
 
   def _load_value(self):
-    value = self._params.get(self._param, return_default=True)
-    index = value if isinstance(value, int) else 0
-    self.set_value(self._options[max(0, min(index, len(self._options) - 1))])
+    self.set_value(self._options[self._params.get(self._param) or 0])
 
   def _handle_mouse_release(self, mouse_pos: MousePos):
     super()._handle_mouse_release(mouse_pos)
     new_idx = self._options.index(self.value)
     self._params.put(self._param, new_idx)
 
-  def refresh(self):
-    self._load_value()
-
 
 class BigParamControl(BigToggle):
   def __init__(self, text: str, param: str, toggle_callback: Callable | None = None):

openpilot/selfdrive/ui/sunnypilot/layouts/settings/cruise.py

@@ -143,8 +143,7 @@ class CruiseLayout(Widget):
           self.icbm_toggle.show_description(True)
 
       if has_long or has_icbm:
-        software_cruise_speed = has_long and (not ui_state.CP.pcmCruise or not ui_state.CP_SP.pcmCruiseSpeed)
-        self.custom_acc_toggle.action_item.set_enabled((software_cruise_speed or has_icbm) and ui_state.is_offroad())
+        self.custom_acc_toggle.action_item.set_enabled(((has_long and not ui_state.CP.pcmCruise) or has_icbm) and ui_state.is_offroad())
         self.dec_toggle.action_item.set_enabled(has_long)
         self.scc_v_toggle.action_item.set_enabled(True)
         self.scc_m_toggle.action_item.set_enabled(True)
@@ -170,7 +169,7 @@ class CruiseLayout(Widget):
       show_custom_acc_desc = True
     else:
       if has_long or has_icbm:
-        if has_long and ui_state.CP.pcmCruise and ui_state.CP_SP.pcmCruiseSpeed:
+        if has_long and ui_state.CP.pcmCruise:
           new_custom_acc_desc = tr(ACC_PCMCRUISE_DISABLED_DESCRIPTION)
           show_custom_acc_desc = True
         else:

openpilot/selfdrive/ui/sunnypilot/layouts/settings/models.py

@@ -178,27 +178,14 @@ class ModelsLayout(Widget):
     # circled_slash is authored grey; tinting it again only darkens it
     return {"name": name, "text_color": rl.GRAY, "icon": "icons/circled_slash.png", "icon_color": rl.WHITE}
 
-  @staticmethod
-  def _show_reset_params_dialog():
-    def _callback(response):
-      if response == DialogResult.CONFIRM:
-        ui_state.params.remove("CalibrationParams")
-        ui_state.params.remove("LiveTorqueParameters")
-    msg = tr("Model download has started in the background. We suggest resetting calibration. Would you like to do that now?")
-    dialog = ConfirmDialog(msg, tr("Reset Calibration"), callback=_callback)
-    gui_app.push_widget(dialog)
-
   def _on_model_selected(self, result):
     if result != DialogResult.CONFIRM:
       return
     selected_ref = self.model_dialog.selection_ref
     if selected_ref == "Default":
       ui_state.params.remove("ModelManager_ActiveBundle")
-      self._show_reset_params_dialog()
     elif selected_bundle := next((bundle for bundle in self.model_manager.availableBundles if bundle.ref == selected_ref), None):
       ui_state.params.put("ModelManager_DownloadIndex", selected_bundle.index)
-      if self.model_manager.activeBundle and selected_bundle.generation != self.model_manager.activeBundle.generation:
-        self._show_reset_params_dialog()
     self.model_dialog = None
 
   @staticmethod

openpilot/selfdrive/ui/sunnypilot/layouts/settings/vehicle/brands/toyota.py

@@ -23,7 +23,7 @@ DESCRIPTIONS = {
   'stop_and_go_hack': tr_noop(
     'sunnypilot will allow some Toyota/Lexus cars to auto resume during stop and go traffic. ' +
     'This feature is only applicable to certain models that are able to use longitudinal control. This is an alpha feature. Use at your own risk.'
-  ),
+  )
 }
 
 

openpilot/selfdrive/ui/sunnypilot/mici/layouts/main.py

@@ -1,19 +0,0 @@
-"""
-Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
-
-This file is part of sunnypilot and is licensed under the MIT License.
-See the LICENSE.md file in the root directory for more details.
-"""
-
-from openpilot.selfdrive.ui.mici.layouts.main import MiciMainLayout
-from openpilot.selfdrive.ui.sunnypilot.mici.widgets.scroll_panel_sp import GuiScrollPanel2SP
-
-
-class MiciMainLayoutSP(MiciMainLayout):
-  def __init__(self):
-    super().__init__()
-    scroller = self._scroller
-    scroller.scroll_panel = GuiScrollPanel2SP(scroller._horizontal, handle_out_of_bounds=not scroller._snap_items)
-
-  def _should_auto_scroll_to_onroad(self) -> bool:
-    return not self._onroad_layout.is_on_info_panel()

openpilot/selfdrive/ui/sunnypilot/mici/layouts/onroad.py

@@ -1,64 +0,0 @@
-"""
-Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
-
-This file is part of sunnypilot and is licensed under the MIT License.
-See the LICENSE.md file in the root directory for more details.
-"""
-from collections.abc import Callable
-import pyray as rl
-from openpilot.system.ui.lib.application import gui_app
-from openpilot.selfdrive.ui.sunnypilot.mici.widgets.scroller_sp import ScrollerSP
-from openpilot.selfdrive.ui.sunnypilot.mici.onroad.augmented_road_view import AugmentedRoadViewSP
-from openpilot.selfdrive.ui.sunnypilot.mici.layouts.onroad_info_panel import OnroadInfoPanel
-
-CONFIDENCE_BALL_VISIBLE_RATIO = 0.4
-HORIZONTAL_SETTLE_PX = 5
-HORIZONTAL_RESET_RATIO = 0.5
-
-
-class OnroadViewContainerSP(ScrollerSP):
-  def __init__(self, bookmark_callback=None):
-    super().__init__(horizontal=False, snap_items=True, spacing=0, pad=0, scroll_indicator=False, edge_shadows=False)
-    self.road_view = AugmentedRoadViewSP(bookmark_callback=bookmark_callback)
-    self.onroad_info_panel = OnroadInfoPanel(bookmark_callback=bookmark_callback)
-
-    self._scroller.add_widgets([
-      self.road_view,
-      self.onroad_info_panel,
-    ])
-    self._scroller.set_reset_scroll_at_show(False)
-    self._scroller.set_scrolling_enabled(lambda: abs(self.rect.x) < HORIZONTAL_SETTLE_PX)
-
-    for child in (self.road_view, self.onroad_info_panel):
-      inner_touch_valid = child._touch_valid_callback
-      child.set_touch_valid_callback(
-        lambda inner=inner_touch_valid: self._touch_valid() and (inner() if inner else True)
-      )
-
-  def set_rect(self, rect: rl.Rectangle):
-    super().set_rect(rect)
-    self.road_view.set_rect(rect)
-    self.onroad_info_panel.set_rect(rect)
-    return self
-
-  def is_swiping_left(self) -> bool:
-    return self.road_view.is_swiping_left() or self.onroad_info_panel.is_swiping_left()
-
-  def set_click_callback(self, click_callback: Callable[[], None] | None) -> None:
-    self.road_view.set_click_callback(click_callback)
-    self.onroad_info_panel.set_click_callback(click_callback)
-
-  def is_on_info_panel(self) -> bool:
-    """True when scrolled past halfway toward onroad_info_panel (used by main layout
-    to skip auto-pop-back-to-camera while user is reading the info panel)."""
-    return abs(self._scroller.scroll_panel.get_offset()) > self._rect.height / 2
-
-  def _render(self, rect: rl.Rectangle):
-    if abs(self.rect.x) > gui_app.width * HORIZONTAL_RESET_RATIO:
-      self._scroller.scroll_panel.set_offset(0)
-
-    vertical_offset = self._scroller.scroll_panel.get_offset()
-    show_ball = abs(vertical_offset) < rect.height * CONFIDENCE_BALL_VISIBLE_RATIO
-    self.road_view.set_show_confidence_ball(show_ball)
-
-    super()._render(rect)

openpilot/selfdrive/ui/sunnypilot/mici/layouts/onroad_info_panel.py

@@ -1,403 +0,0 @@
-"""
-Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
-
-This file is part of sunnypilot and is licensed under the MIT License.
-See the LICENSE.md file in the root directory for more details.
-"""
-
-import pyray as rl
-from dataclasses import dataclass, field
-from openpilot.common.constants import CV
-from openpilot.common.filter_simple import FirstOrderFilter
-from openpilot.selfdrive.ui.ui_state import ui_state
-from openpilot.system.ui.lib.application import gui_app, FontWeight, MousePos
-from openpilot.system.ui.lib.multilang import tr
-from openpilot.system.ui.lib.text_measure import measure_text_cached
-from openpilot.system.ui.widgets import Widget
-from openpilot.selfdrive.ui.mici.onroad.alert_renderer import AlertRenderer
-from openpilot.selfdrive.ui.mici.onroad.augmented_road_view import BookmarkIcon
-
-METER_TO_KM = 0.001
-METER_TO_MILE = 0.000621371
-
-CONTENT_MARGIN = 16
-SPEED_LIMIT_SIGN_WIDTH = 146
-VIENNA_SIGN_SIZE = 146
-MUTCD_SIGN_HEIGHT = 178
-OFFSET_BADGE_SIZE = 50
-OFFSET_BADGE_PANEL_PADDING = 4
-MUTCD_OFFSET_SIGN_Y_SHIFT = 6
-VIENNA_BADGE_X_RATIO = 0.80
-VIENNA_BADGE_UPCOMING_X_RATIO = 0.70
-VIENNA_BADGE_Y_RATIO = -0.82
-UPCOMING_SIGN_SIZE_RATIO = 0.76
-UPCOMING_SIGN_OVERLAP_RATIO = 0.05
-UNIT_FONT_SIZE = 40
-SPEED_FONT_SIZE = 114
-ROAD_FONT_SIZE = 32
-SCC_TAG_WIDTH = 78
-SCC_TAG_HEIGHT = 30
-SCC_TAG_GAP = 5
-COLUMN_GAP = 12
-
-
-@dataclass(frozen=True)
-class OnroadInfoPanelColors:
-  white: rl.Color = rl.WHITE
-  black: rl.Color = rl.BLACK
-  red: rl.Color = field(default_factory=lambda: rl.Color(255, 0, 0, 255))
-  green: rl.Color = field(default_factory=lambda: rl.Color(0, 255, 0, 255))
-  grey: rl.Color = field(default_factory=lambda: rl.Color(190, 195, 190, 255))
-  light_grey: rl.Color = field(default_factory=lambda: rl.Color(200, 200, 200, 255))
-  dark_grey: rl.Color = field(default_factory=lambda: rl.Color(100, 100, 100, 255))
-  bg_dark: rl.Color = field(default_factory=lambda: rl.Color(0, 0, 0, 255))
-  card_bg: rl.Color = field(default_factory=lambda: rl.Color(50, 50, 50, 200))
-  badge_bg: rl.Color = field(default_factory=lambda: rl.Color(60, 60, 60, 255))
-
-
-COLORS = OnroadInfoPanelColors()
-
-
-class OnroadInfoPanel(Widget):
-  def __init__(self, bookmark_callback=None):
-    super().__init__()
-    self.speed_limit: float = 0.0
-    self.speed_limit_valid: bool = False
-    self.speed_limit_offset: float = 0.0
-    self.next_speed_limit: float = 0.0
-    self.next_speed_limit_distance: float = 0.0
-    self.road_name: str = ""
-    self.current_speed: float = 0.0
-    self.set_speed: float = 0.0
-    self.cruise_enabled: bool = False
-
-    self._sign_slide: float = 0.0
-
-    self._font_bold: rl.Font = gui_app.font(FontWeight.BOLD)
-    self._font_semi_bold: rl.Font = gui_app.font(FontWeight.SEMI_BOLD)
-    self._font_medium: rl.Font = gui_app.font(FontWeight.MEDIUM)
-
-    self._marquee_offset: float = 0.0
-    self._marquee_direction: int = 1
-    self._marquee_pause_timer: float = 0.0
-    self._marquee_speed: float = 40.0
-    self._marquee_pause_duration: float = 1.5
-
-    self._alert_renderer = AlertRenderer()
-    self._alert_alpha_filter = FirstOrderFilter(0, 0.05, 1 / gui_app.target_fps)
-
-    self._bookmark_icon = BookmarkIcon(bookmark_callback)
-
-  def is_swiping_left(self) -> bool:
-    return self._bookmark_icon.is_swiping_left()
-
-  def _handle_mouse_release(self, mouse_pos: MousePos) -> None:
-    # Mirror stock AugmentedRoadView: suppress click while bookmark gesture active
-    if not self._bookmark_icon.interacting():
-      super()._handle_mouse_release(mouse_pos)
-
-  def _update_state(self) -> None:
-    sm = ui_state.sm
-    speed_conv = CV.MS_TO_KPH if ui_state.is_metric else CV.MS_TO_MPH
-
-    if sm.valid["longitudinalPlanSP"]:
-      lp_sp = sm["longitudinalPlanSP"]
-      resolver = lp_sp.speedLimit.resolver
-      self.speed_limit = resolver.speedLimit * speed_conv
-      self.speed_limit_valid = resolver.speedLimitValid
-      self.speed_limit_offset = resolver.speedLimitOffset * speed_conv
-
-    if sm.valid["liveMapDataSP"]:
-      lmd = sm["liveMapDataSP"]
-      self.next_speed_limit = lmd.speedLimitAhead * speed_conv
-      self.next_speed_limit_distance = lmd.speedLimitAheadDistance
-      self.road_name = lmd.roadName
-
-    if sm.updated["carState"]:
-      self.current_speed = sm["carState"].vEgo * speed_conv
-
-    if sm.valid["carState"] and sm.valid["controlsState"]:
-      self.cruise_enabled = sm["carState"].cruiseState.enabled
-      v_cruise_cluster = sm["carState"].vCruiseCluster
-      set_speed_kph = sm["controlsState"].vCruiseDEPRECATED if v_cruise_cluster == 0.0 else v_cruise_cluster
-      self.set_speed = set_speed_kph * (METER_TO_MILE / METER_TO_KM) if not ui_state.is_metric else set_speed_kph
-
-  def _render(self, rect: rl.Rectangle) -> None:
-    self._update_state()
-
-    rl.draw_rectangle(int(rect.x), int(rect.y), int(rect.width), int(rect.height), COLORS.bg_dark)
-
-    left_x = rect.x + CONTENT_MARGIN
-
-    if self.cruise_enabled:
-      unit = tr("MAX")
-      display_speed = self.set_speed
-    else:
-      unit = tr("km/h") if ui_state.is_metric else tr("MPH")
-      display_speed = self.current_speed
-
-    display_speed_text = str(round(display_speed))
-    if self.speed_limit_valid and display_speed > self.speed_limit:
-      speed_color = COLORS.red
-    else:
-      speed_color = COLORS.white
-
-    sign_width = min(SPEED_LIMIT_SIGN_WIDTH, rect.width * 0.30)
-    sign_height = VIENNA_SIGN_SIZE if ui_state.is_metric else MUTCD_SIGN_HEIGHT
-
-    has_upcoming_limit = self.next_speed_limit > 0 and self.next_speed_limit != self.speed_limit
-    target_sign_slide = 1.0 if has_upcoming_limit else 0.0
-    slide_speed = 3.0 * rl.get_frame_time()
-    if self._sign_slide < target_sign_slide:
-      self._sign_slide = min(self._sign_slide + slide_speed, target_sign_slide)
-    elif self._sign_slide > target_sign_slide:
-      self._sign_slide = max(self._sign_slide - slide_speed, target_sign_slide)
-
-    upcoming_width = int(sign_width * UPCOMING_SIGN_SIZE_RATIO)
-    upcoming_height = int(sign_height * UPCOMING_SIGN_SIZE_RATIO)
-    upcoming_reserved_width = int(upcoming_width * 0.85) + 5
-    sign_x_without_upcoming = rect.x + rect.width - sign_width - CONTENT_MARGIN
-    sign_x_with_upcoming = rect.x + rect.width - sign_width - CONTENT_MARGIN - upcoming_reserved_width
-    sign_x = sign_x_without_upcoming + (sign_x_with_upcoming - sign_x_without_upcoming) * self._sign_slide
-    sign_y = rect.y + (rect.height - sign_height) / 2
-    if not ui_state.is_metric and self.speed_limit_offset != 0 and self.speed_limit_valid:
-      sign_y += MUTCD_OFFSET_SIGN_Y_SHIFT
-
-    readout_right = sign_x - COLUMN_GAP
-    readout_width = max(1, readout_right - left_x)
-    road_y = rect.y + rect.height - 44
-
-    unit_font_size = self._fit_font_size(self._font_semi_bold, unit, readout_width, 46, UNIT_FONT_SIZE, 28)
-    speed_font_size = self._fit_font_size(self._font_bold, display_speed_text, readout_width, road_y - (rect.y + 54) - 8,
-                                          SPEED_FONT_SIZE, 76)
-    speed_size = measure_text_cached(self._font_bold, display_speed_text, speed_font_size)
-    speed_y = min(rect.y + 54, road_y - speed_size.y - 8)
-    unit_y = max(rect.y + 14, speed_y - unit_font_size - 6)
-
-    rl.draw_text_ex(self._font_semi_bold, unit, rl.Vector2(left_x, unit_y), unit_font_size, 0, COLORS.grey)
-    rl.draw_text_ex(self._font_bold, display_speed_text, rl.Vector2(left_x, speed_y), speed_font_size, 0, speed_color)
-    self._draw_road_name(left_x, road_y, readout_width)
-
-    if has_upcoming_limit and self._sign_slide > 0.01:
-      upcoming_speed_text = str(round(self.next_speed_limit))
-      distance_text = self._format_distance(self.next_speed_limit_distance)
-      upcoming_x = sign_x + sign_width - int(upcoming_width * UPCOMING_SIGN_OVERLAP_RATIO)
-      upcoming_y = sign_y + (sign_height - upcoming_height) / 2
-
-      upcoming_speed_color = COLORS.black
-      if ui_state.is_metric:
-        self._draw_vienna_sign(upcoming_x, upcoming_y, upcoming_width, upcoming_height, upcoming_speed_text, upcoming_speed_color, is_upcoming=True)
-      else:
-        self._draw_mutcd_sign(upcoming_x, upcoming_y, upcoming_width, upcoming_height, upcoming_speed_text, upcoming_speed_color, is_upcoming=True)
-
-      distance_font_size = self._fit_font_size(self._font_medium, distance_text, upcoming_width, 30, 24, 16)
-      distance_size = measure_text_cached(self._font_medium, distance_text, distance_font_size)
-      rl.draw_text_ex(self._font_medium, distance_text, rl.Vector2(upcoming_x + upcoming_width / 2 - distance_size.x / 2, upcoming_y + upcoming_height),
-                      distance_font_size, 0, COLORS.grey)
-
-    self._draw_speed_limit_sign(sign_x, sign_y, sign_width, sign_height)
-
-    if self.speed_limit_offset != 0 and self.speed_limit_valid:
-      offset_text = str(abs(round(self.speed_limit_offset)))
-      badge_size = OFFSET_BADGE_SIZE
-      badge_rect = self._offset_badge_rect(rect, sign_x, sign_y, sign_width, sign_height, badge_size, has_upcoming_limit)
-
-      if ui_state.is_metric:
-        badge_radius = badge_size / 2
-        badge_center_x = badge_rect.x + badge_radius
-        badge_center_y = badge_rect.y + badge_radius
-        rl.draw_circle(int(badge_center_x), int(badge_center_y), badge_radius + 2, COLORS.dark_grey)
-        rl.draw_circle(int(badge_center_x), int(badge_center_y), badge_radius, COLORS.badge_bg)
-        self._draw_text_centered_fit(self._font_bold, offset_text, 32, rl.Vector2(badge_center_x, badge_center_y), COLORS.white,
-                                     badge_size - 10, badge_size - 8, min_size=24)
-      else:
-        rl.draw_rectangle_rounded(badge_rect, 0.25, 10, COLORS.badge_bg)
-        rl.draw_rectangle_rounded_lines_ex(badge_rect, 0.25, 10, 2, COLORS.dark_grey)
-        self._draw_text_centered_fit(self._font_bold, offset_text, 32, rl.Vector2(badge_rect.x + badge_size / 2, badge_rect.y + badge_size / 2),
-                                     COLORS.white, badge_size - 10, badge_size - 8, min_size=24)
-
-    scc_tag_x = min(left_x + speed_size.x + COLUMN_GAP, readout_right - SCC_TAG_WIDTH)
-    scc_tag_y = speed_y + (speed_size.y - (SCC_TAG_HEIGHT * 2 + SCC_TAG_GAP)) / 2
-    if scc_tag_x >= left_x + speed_size.x + 8:
-      self._draw_scc_icons(scc_tag_x, scc_tag_y, readout_right)
-
-    self._bookmark_icon.render(rect)
-
-    if ui_state.started:
-      alert_obj, no_alert = self._alert_renderer.will_render()
-      self._alert_alpha_filter.update(0 if no_alert else 1)
-      alpha = self._alert_alpha_filter.x
-      if alpha > 0.01:
-        rl.draw_rectangle(int(rect.x), int(rect.y), int(rect.width), int(rect.height), rl.Color(0, 0, 0, int(150 * alpha)))
-      self._alert_renderer.render(rect)
-
-  def _draw_scc_icons(self, x: float, y: float, right_limit: float) -> None:
-    sm = ui_state.sm
-    if not sm.valid["longitudinalPlanSP"]:
-      return
-    scc = sm["longitudinalPlanSP"].smartCruiseControl
-
-    drawn = 0
-
-    for label, active in [("SCC-V", scc.vision.active), ("SCC-M", scc.map.active)]:
-      if not active:
-        continue
-      tag_x = x
-      if tag_x + SCC_TAG_WIDTH > right_limit:
-        return
-      tag_y = y + drawn * (SCC_TAG_HEIGHT + SCC_TAG_GAP)
-      rl.draw_rectangle_rounded(rl.Rectangle(tag_x, tag_y, SCC_TAG_WIDTH, SCC_TAG_HEIGHT), 0.3, 10, COLORS.green)
-      self._draw_text_centered_fit(self._font_bold, label, 18, rl.Vector2(tag_x + SCC_TAG_WIDTH / 2, tag_y + SCC_TAG_HEIGHT / 2), COLORS.black,
-                                   SCC_TAG_WIDTH - 10, SCC_TAG_HEIGHT - 4, min_size=14)
-      drawn += 1
-
-  def _draw_speed_limit_sign(self, x: float, y: float, sign_width: float, sign_height: float) -> None:
-    speed_str = str(round(self.speed_limit)) if self.speed_limit_valid and self.speed_limit > 0 else "--"
-    speed_color = COLORS.black if not self.speed_limit_valid or self.current_speed <= self.speed_limit else COLORS.red
-
-    if ui_state.is_metric:
-      self._draw_vienna_sign(x, y, sign_width, sign_height, speed_str, speed_color, is_upcoming=False)
-    else:
-      self._draw_mutcd_sign(x, y, sign_width, sign_height, speed_str, speed_color, is_upcoming=False)
-
-  def _draw_road_name(self, x: float, y: float, width: float) -> None:
-    if width <= 0:
-      return
-
-    road_display = self.road_name if self.road_name else "--"
-    font_size = self._fit_font_size(self._font_semi_bold, road_display, width, 38, ROAD_FONT_SIZE, 28)
-    road_size = measure_text_cached(self._font_semi_bold, road_display, font_size)
-    text_width = road_size.x
-
-    if text_width <= width:
-      self._marquee_offset = 0.0
-      self._marquee_direction = 1
-      self._marquee_pause_timer = 0.0
-      rl.draw_text_ex(self._font_semi_bold, road_display, rl.Vector2(x, y), font_size, 0, COLORS.white)
-    else:
-      overflow = text_width - width
-      dt = rl.get_frame_time()
-
-      if self._marquee_pause_timer > 0:
-        self._marquee_pause_timer -= dt
-      else:
-        self._marquee_offset += self._marquee_direction * self._marquee_speed * dt
-
-        if self._marquee_offset >= overflow:
-          self._marquee_offset = overflow
-          self._marquee_direction = -1
-          self._marquee_pause_timer = self._marquee_pause_duration
-        elif self._marquee_offset <= 0:
-          self._marquee_offset = 0
-          self._marquee_direction = 1
-          self._marquee_pause_timer = self._marquee_pause_duration
-
-      rl.begin_scissor_mode(int(x), int(y), int(width), int(road_size.y + 4))
-      text_pos = rl.Vector2(x - self._marquee_offset, y)
-      rl.draw_text_ex(self._font_semi_bold, road_display, text_pos, font_size, 0, COLORS.white)
-      rl.end_scissor_mode()
-
-  def _draw_vienna_sign(self, x: float, y: float, width: float, height: float, speed_str: str, speed_color: rl.Color, is_upcoming: bool = False) -> None:
-    center = rl.Vector2(x + width / 2, y + height / 2)
-    outer_radius = min(width, height) / 2
-
-    rl.draw_circle_v(center, outer_radius, COLORS.white)
-    ring_width = outer_radius * 0.18
-    rl.draw_ring(center, outer_radius - ring_width, outer_radius, 0, 360, 36, COLORS.red)
-
-    font_size = outer_radius * (0.7 if len(speed_str) >= 3 else 0.9)
-    self._draw_text_centered_fit(self._font_bold, speed_str, int(font_size), center, speed_color, width * 0.72, height * 0.50, min_size=24)
-
-  def _draw_mutcd_sign(self, x: float, y: float, width: float, height: float, speed_str: str, speed_color: rl.Color, is_upcoming: bool = False) -> None:
-    sign_rect = rl.Rectangle(x, y, width, height)
-    rl.draw_rectangle_rounded(sign_rect, 0.35, 10, COLORS.white)
-
-    inset = max(4, width * 0.05)
-    inner_rect = rl.Rectangle(x + inset, y + inset, width - inset * 2, height - inset * 2)
-    outer_radius = 0.35 * width / 2.0
-    inner_radius = outer_radius - inset
-    inner_roundness = inner_radius / (inner_rect.width / 2.0)
-    rl.draw_rectangle_rounded_lines_ex(inner_rect, inner_roundness, 10, 3, COLORS.black)
-
-    mid_x = x + width / 2
-    label_size = max(18, int(width * 0.26))
-    if is_upcoming:
-      self._draw_text_centered_fit(self._font_bold, tr("AHEAD"), int(width * 0.34), rl.Vector2(mid_x, y + height * 0.28), COLORS.black,
-                                   width * 0.94, height * 0.32, min_size=20)
-    else:
-      self._draw_text_centered_fit(self._font_bold, tr("SPEED"), label_size, rl.Vector2(mid_x, y + height * 0.20), COLORS.black,
-                                   width * 0.84, height * 0.24, min_size=16)
-      self._draw_text_centered_fit(self._font_bold, tr("LIMIT"), label_size, rl.Vector2(mid_x, y + height * 0.40), COLORS.black,
-                                   width * 0.84, height * 0.24, min_size=16)
-
-    speed_font_size = int(width * 0.60) if len(speed_str) >= 3 else int(width * 0.72)
-    self._draw_text_centered_fit(self._font_bold, speed_str, speed_font_size, rl.Vector2(mid_x, y + height * 0.72), speed_color,
-                                 width * 0.90, height * 0.52, min_size=32)
-
-  def _draw_text_centered(self, font, text, size, pos_center, color):
-    sz = measure_text_cached(font, text, size)
-    rl.draw_text_ex(font, text, rl.Vector2(pos_center.x - sz.x / 2, pos_center.y - sz.y / 2), size, 0, color)
-
-  def _draw_text_centered_fit(self, font, text, size, pos_center, color, max_width: float, max_height: float, min_size: int = 10):
-    size = self._fit_font_size(font, text, max_width, max_height, size, min_size)
-    self._draw_text_centered(font, text, size, pos_center, color)
-
-  def _fit_font_size(self, font, text: str, max_width: float, max_height: float, max_size: int | float, min_size: int) -> int:
-    size = int(max_size)
-    while size > min_size:
-      text_size = measure_text_cached(font, text, size)
-      if text_size.x <= max_width and text_size.y <= max_height:
-        return size
-      size -= 2
-    return min_size
-
-  def _offset_badge_rect(self, panel_rect: rl.Rectangle, sign_x: float, sign_y: float, sign_width: float, sign_height: float,
-                         badge_size: float, has_upcoming_limit: bool) -> rl.Rectangle:
-    if ui_state.is_metric:
-      radius = min(sign_width, sign_height) / 2
-      center_x = sign_x + sign_width / 2
-      center_y = sign_y + sign_height / 2
-      badge_x_ratio = VIENNA_BADGE_UPCOMING_X_RATIO if has_upcoming_limit else VIENNA_BADGE_X_RATIO
-      badge_center_x = center_x + radius * badge_x_ratio
-      badge_center_y = center_y + radius * VIENNA_BADGE_Y_RATIO
-      badge_x = badge_center_x - badge_size / 2
-      badge_y = badge_center_y - badge_size / 2
-    else:
-      badge_x = sign_x + sign_width - badge_size * 0.45
-      badge_y = sign_y - badge_size * 0.75
-
-    return rl.Rectangle(
-      self._clamp(
-        badge_x,
-        panel_rect.x + OFFSET_BADGE_PANEL_PADDING,
-        panel_rect.x + panel_rect.width - badge_size - OFFSET_BADGE_PANEL_PADDING,
-      ),
-      self._clamp(
-        badge_y,
-        panel_rect.y + OFFSET_BADGE_PANEL_PADDING,
-        panel_rect.y + panel_rect.height - badge_size - OFFSET_BADGE_PANEL_PADDING,
-      ),
-      badge_size,
-      badge_size,
-    )
-
-  @staticmethod
-  def _clamp(value: float, min_value: float, max_value: float) -> float:
-    return max(min_value, min(max_value, value))
-
-  def _format_distance(self, distance: float) -> str:
-    if ui_state.is_metric:
-      if distance < 50:
-        return tr("Near")
-      if distance >= 1000:
-        return f"{distance * METER_TO_KM:.1f}" + tr("km")
-      if distance < 200:
-        rounded = max(10, int(distance / 10) * 10)
-      else:
-        rounded = int(distance / 100) * 100
-      return str(rounded) + tr("m")
-    else:
-      distance_mi = distance * METER_TO_MILE
-      if distance_mi < 0.1:
-        return tr("Near")
-      return f"{distance_mi:.1f}" + tr("mi")

openpilot/selfdrive/ui/sunnypilot/mici/onroad/augmented_road_view.py

@@ -1,29 +0,0 @@
-"""
-Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
-
-This file is part of sunnypilot and is licensed under the MIT License.
-See the LICENSE.md file in the root directory for more details.
-"""
-
-from openpilot.selfdrive.ui.mici.onroad.augmented_road_view import AugmentedRoadView
-
-
-class _SuppressedConfidenceBall:
-  def render(self, *_):
-    pass
-
-
-class AugmentedRoadViewSP(AugmentedRoadView):
-  def __init__(self, **kwargs):
-    super().__init__(**kwargs)
-    self._show_confidence_ball: bool = True
-    self._real_confidence_ball = self._confidence_ball
-    self._confidence_ball = _SuppressedConfidenceBall()
-
-  def set_show_confidence_ball(self, show: bool) -> None:
-    self._show_confidence_ball = show
-
-  def _render(self, _) -> None:
-    super()._render(_)
-    if self._show_confidence_ball:
-      self._real_confidence_ball.render(self.rect)

openpilot/selfdrive/ui/sunnypilot/mici/tests/test_scroller_sp.py

@@ -1,83 +0,0 @@
-import pyray as rl
-
-from openpilot.common.test import OpenpilotTestCase
-from openpilot.system.ui.lib.application import MouseEvent, MousePos, gui_app
-from openpilot.system.ui.lib.scroll_panel2 import ScrollState
-from openpilot.system.ui.widgets import Widget
-from openpilot.system.ui.widgets import scroller as scroller_mod
-from openpilot.selfdrive.ui.sunnypilot.mici.widgets.scroll_panel_sp import GuiScrollPanel2SP
-
-
-class DummyScrollIndicator:
-  def update(self, *_) -> None:
-    pass
-
-  def render(self) -> None:
-    pass
-
-
-class DummyWidget(Widget):
-  def __init__(self, rect: rl.Rectangle):
-    super().__init__()
-    self.set_rect(rect)
-
-  def _render(self, _) -> None:
-    pass
-
-
-def _mouse_event(x: float, y: float, *, pressed: bool = False, released: bool = False,
-                 down: bool = True, t: float = 0.0) -> MouseEvent:
-  return MouseEvent(MousePos(x, y), 0, pressed, released, down, t)
-
-
-class TestScrollerSP(OpenpilotTestCase):
-  def test_vertical_snap_items_are_supported(self, monkeypatch):
-    monkeypatch.setattr(scroller_mod, "ScrollIndicator", DummyScrollIndicator)
-
-    scroller = scroller_mod._Scroller([], horizontal=False, snap_items=True, scroll_indicator=False)
-    scroller.set_rect(rl.Rectangle(0, 0, 100, 100))
-    scroller.scroll_panel.set_offset(-60)
-
-    captured_snap_target = None
-
-    def update(_, __, snap_target=None):
-      nonlocal captured_snap_target
-      captured_snap_target = snap_target
-      return scroller.scroll_panel.get_offset()
-
-    monkeypatch.setattr(scroller.scroll_panel, "update", update)
-
-    visible_items: list[Widget] = [
-      DummyWidget(rl.Rectangle(0, -60, 100, 100)),
-      DummyWidget(rl.Rectangle(0, 40, 100, 100)),
-    ]
-    scroller._get_scroll(visible_items, 200)
-
-    assert captured_snap_target == -100
-
-  def test_scroll_panel_sp_rejects_orthogonal_drags(self, monkeypatch):
-    panel = GuiScrollPanel2SP(horizontal=True)
-    bounds = rl.Rectangle(0, 0, 100, 100)
-
-    monkeypatch.setattr(gui_app, "_mouse_events", [_mouse_event(10, 10, pressed=True, t=1.0)])
-    panel.update(bounds, 200)
-    assert panel.state == ScrollState.PRESSED
-
-    monkeypatch.setattr(gui_app, "_mouse_events", [_mouse_event(23, 60, t=1.1)])
-    panel.update(bounds, 200)
-
-    assert panel.state == ScrollState.STEADY
-    assert panel.get_offset() == 0
-
-  def test_scroll_panel_sp_can_disable_out_of_bounds_handling(self, monkeypatch):
-    panel = GuiScrollPanel2SP(horizontal=False, handle_out_of_bounds=False)
-    bounds = rl.Rectangle(0, 0, 100, 100)
-    monkeypatch.setattr(gui_app, "_mouse_events", [])
-
-    panel.set_offset(20)
-    panel.update(bounds, 200)
-    assert panel.get_offset() == 0
-
-    panel.set_offset(-150)
-    panel.update(bounds, 200)
-    assert panel.get_offset() == -100

openpilot/selfdrive/ui/sunnypilot/mici/widgets/scroll_panel_sp.py

@@ -1,33 +0,0 @@
-"""
-Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
-
-This file is part of sunnypilot and is licensed under the MIT License.
-See the LICENSE.md file in the root directory for more details.
-"""
-
-import pyray as rl
-from openpilot.system.ui.lib.application import MouseEvent
-from openpilot.system.ui.lib.scroll_panel2 import GuiScrollPanel2, ScrollState
-
-
-class GuiScrollPanel2SP(GuiScrollPanel2):
-  """Scroll panel behavior for nested Mici pagers."""
-
-  def __init__(self, horizontal: bool = True, handle_out_of_bounds: bool = True) -> None:
-    super().__init__(horizontal, handle_out_of_bounds=handle_out_of_bounds)
-
-  def _handle_mouse_event(self, mouse_event: MouseEvent, bounds: rl.Rectangle, bounds_size: float,
-                          content_size: float) -> None:
-    state_before_update = self._state
-    super()._handle_mouse_event(mouse_event, bounds, bounds_size, content_size)
-
-    if self._state == ScrollState.MANUAL_SCROLL and state_before_update == ScrollState.PRESSED and \
-       self._initial_click_event is not None:
-      drag_x = abs(mouse_event.pos.x - self._initial_click_event.pos.x)
-      drag_y = abs(mouse_event.pos.y - self._initial_click_event.pos.y)
-      primary_drag = drag_x if self._horizontal else drag_y
-      cross_drag = drag_y if self._horizontal else drag_x
-      if cross_drag > primary_drag:
-        self._state = ScrollState.STEADY
-        self._velocity = 0.0
-        self._velocity_buffer.clear()

openpilot/selfdrive/ui/sunnypilot/mici/widgets/scroller_sp.py

@@ -1,16 +0,0 @@
-"""
-Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
-
-This file is part of sunnypilot and is licensed under the MIT License.
-See the LICENSE.md file in the root directory for more details.
-"""
-
-from openpilot.system.ui.widgets.scroller import Scroller
-from openpilot.selfdrive.ui.sunnypilot.mici.widgets.scroll_panel_sp import GuiScrollPanel2SP
-
-
-class ScrollerSP(Scroller):
-  def __init__(self, **kwargs):
-    super().__init__(**kwargs)
-    inner = self._scroller
-    inner.scroll_panel = GuiScrollPanel2SP(inner._horizontal, handle_out_of_bounds=not inner._snap_items)

openpilot/selfdrive/ui/sunnypilot/onroad/model_renderer.py

@@ -8,6 +8,7 @@ from openpilot.common.filter_simple import FirstOrderFilter
 from openpilot.selfdrive.ui.ui_state import ui_state, UIStatus
 from openpilot.selfdrive.ui.sunnypilot.onroad.chevron_metrics import ChevronMetrics
 from openpilot.selfdrive.ui.sunnypilot.onroad.rainbow_path import RainbowPath
+from openpilot.selfdrive.ui.sunnypilot.ui_state import MADSState
 from openpilot.system.ui.lib.application import gui_app
 
 
@@ -19,6 +20,11 @@ class ModelRendererSP:
 
   @property
   def _lateral_active(self) -> bool:
+    sm = ui_state.sm
+    if sm.valid["selfdriveStateSP"]:
+      mads = sm["selfdriveStateSP"].mads
+      if mads.available:
+        return mads.enabled and mads.state != MADSState.paused
     return ui_state.status in (UIStatus.ENGAGED, UIStatus.LAT_ONLY)
 
   def _get_path_half_width(self) -> float:

openpilot/selfdrive/ui/ui.py

@@ -10,9 +10,6 @@ from openpilot.selfdrive.ui.layouts.main import MainLayout
 from openpilot.selfdrive.ui.mici.layouts.main import MiciMainLayout
 from openpilot.selfdrive.ui.ui_state import ui_state
 
-if gui_app.sunnypilot_ui():
-  from openpilot.selfdrive.ui.sunnypilot.mici.layouts.main import MiciMainLayoutSP as MiciMainLayout
-
 BIG_UI = gui_app.big_ui()
 
 

openpilot/sunnypilot/modeld_v2/compile_modeld.py

@@ -7,7 +7,6 @@ See the LICENSE.md file in the root directory for more details.
 """
 
 import argparse
-import math
 import os
 import tempfile
 import time
@@ -67,15 +66,14 @@ def get_policy_npy_shapes(input_shapes: dict, is_supercombo: bool = False) -> tu
   if desire_key:
     shapes['desire'] = (input_shapes[desire_key][2],)
 
+  if is_supercombo and 'features_buffer' in input_shapes:
+    fb = input_shapes['features_buffer']
+    shapes['prev_feat'] = (fb[0], fb[2])
+
   for key, shape in input_shapes.items():
     if key not in (desire_key, 'features_buffer') and 'img' not in key:
       shapes[key] = tuple(shape)
 
-  if is_supercombo and 'features_buffer' in input_shapes:
-    fb = input_shapes['features_buffer']
-    feat_dim = math.prod(fb[2:])
-    shapes['prev_feat'] = (fb[0], feat_dim)
-
   sizes = [int(np.prod(size)) for size in shapes.values()]
   return shapes, sizes
 
@@ -119,9 +117,8 @@ def generate_queues_and_npy(input_shapes: dict, frame_skip: int, device: str = D
   }
 
   if features_buffer:
-    feat_dim = math.prod(features_buffer[2:])
     feat_q_len = frame_skip * features_buffer[1] if is_supercombo else frame_skip * (features_buffer[1] - 1) + 1
-    queues['feat_q'] = Tensor(np.zeros((feat_q_len, features_buffer[0], feat_dim),
+    queues['feat_q'] = Tensor(np.zeros((feat_q_len, features_buffer[0], features_buffer[2]),
                        dtype=np.float32), device=device).contiguous().realize()
 
   queues.update({key: Tensor(value, device='NPY').realize() for key, value in npy_arrays.items() if key in ('tfm', 'big_tfm')})
@@ -186,14 +183,14 @@ def make_run_policy(vision_runner, policy_runners: list, features_slice: slice,
     warped_dev = warped.to(Device.DEFAULT)
     Tensor.realize(packed_npy_inputs_dev, warped_dev)
 
-    img = shift_and_sample(img_q, warped_dev[0:1], sample_skip_fn)
-    big_img = shift_and_sample(big_img_q, warped_dev[1:2], sample_skip_fn)
+    img = shift_and_sample(img_q, warped_dev[0:1], sample_skip_fn).realize()
+    big_img = shift_and_sample(big_img_q, warped_dev[1:2], sample_skip_fn).realize()
 
     unpacked_tensors = [tensor.reshape(shape) for tensor, shape in zip(packed_npy_inputs_dev.split(npy_sizes), npy_shapes.values(), strict=True)]
     unpacked_dict = dict(zip(npy_shapes.keys(), unpacked_tensors, strict=True))
 
     desire_dev = unpacked_dict['desire']
-    desire_buf = shift_and_sample(desire_q, desire_dev.reshape(1, 1, -1), sample_desire_fn)
+    desire_buf = shift_and_sample(desire_q, desire_dev.reshape(1, 1, -1), sample_desire_fn).realize()
 
     inputs = {desire_key: desire_buf}
     for key, tensor_val in unpacked_dict.items():
@@ -202,22 +199,19 @@ def make_run_policy(vision_runner, policy_runners: list, features_slice: slice,
 
     if 'prev_feat' in unpacked_dict:
       prev_feat_dev = unpacked_dict['prev_feat']
-      feat_buf = shift_and_sample(feat_q, prev_feat_dev.reshape(1, 1, -1), sample_skip_fn)
-      inputs['features_buffer'] = feat_buf if len(fb := input_shapes['features_buffer']) <= 3 else feat_buf.reshape(fb)
+      inputs['features_buffer'] = shift_and_sample(feat_q, prev_feat_dev.reshape(1, 1, -1), sample_skip_fn).realize()
 
     if vision_runner:
       vision_out_cast = next(iter(vision_runner({road_key: img, wide_key: big_img}).values())).cast('float32').realize()
       if 'features_buffer' not in inputs:
         new_feat = vision_out_cast[:, features_slice].reshape(1, -1).unsqueeze(0)
-        feat_buf = shift_and_sample(feat_q, new_feat, sample_skip_fn).realize()
-        inputs['features_buffer'] = feat_buf if len(fb := input_shapes['features_buffer']) <= 3 else feat_buf.reshape(fb)
+        inputs['features_buffer'] = shift_and_sample(feat_q, new_feat, sample_skip_fn).realize()
       policy_outs = [next(iter(pol_runner(inputs).values())).cast('float32').realize() for pol_runner in policy_runners]
       return (vision_out_cast, *policy_outs) if len(policy_outs) > 1 else (vision_out_cast, policy_outs[0])
 
     inputs.update({road_key: img, wide_key: big_img})
     if 'features_buffer' not in inputs:
-      feat_buf = sample_skip_fn(feat_q)
-      inputs['features_buffer'] = feat_buf if len(fb := input_shapes['features_buffer']) <= 3 else feat_buf.reshape(fb)
+      inputs['features_buffer'] = sample_skip_fn(feat_q)
 
     policy_out = next(iter(policy_runners[0](inputs).values())).cast('float32').realize()
     if 'features_buffer' not in inputs and features_slice is not None:

openpilot/sunnypilot/modeld_v2/tests/test_compile_modeld.py

@@ -195,85 +195,3 @@ class TestReadFileChunkedToDisk(OpenpilotTestCase):
 
       assert out.parent == Path(d)
       assert out.read_bytes() == payload
-
-
-class Test4DFeaturesBuffer(OpenpilotTestCase):
-  def test_get_policy_npy_shapes_4d(self):
-    from openpilot.sunnypilot.modeld_v2.compile_modeld import get_policy_npy_shapes
-    input_shapes = {
-      'desire_pulse': (1, 25, 8),
-      'features_buffer': (1, 24, 32, 512),  # compare 4d to 3d for regression
-      'traffic_convention': (1, 2),
-      'action_t': (1, 2)
-    }
-    shapes, sizes = get_policy_npy_shapes(input_shapes, is_supercombo=True)
-    assert shapes['prev_feat'] == (1, 16384)
-    assert sizes == [8, 2, 2, 16384]
-
-  def test_get_policy_npy_shapes_3d(self):
-    from openpilot.sunnypilot.modeld_v2.compile_modeld import get_policy_npy_shapes
-    input_shapes = {
-      'desire_pulse': (1, 25, 8),
-      'features_buffer': (1, 24, 512),
-      'traffic_convention': (1, 2),
-      'action_t': (1, 2)
-    }
-    shapes, sizes = get_policy_npy_shapes(input_shapes, is_supercombo=True)
-    assert shapes['prev_feat'] == (1, 512)
-    assert sizes == [8, 2, 2, 512]
-
-
-class TestStockCompileModeldEquivalence(OpenpilotTestCase):
-  def test_get_policy_npy_shapes_matches_stock(self):
-    from openpilot.selfdrive.modeld.compile_modeld import get_policy_npy_shapes as stock_get_policy_npy_shapes
-    from openpilot.sunnypilot.modeld_v2.compile_modeld import get_policy_npy_shapes as sunny_get_policy_npy_shapes
-
-    stock_input_shapes = {
-      'desire_pulse': (1, 25, 8),
-      'features_buffer': (1, 24, 512), # see below comment
-      'traffic_convention': (1, 2),
-      'action_t': (1, 2),
-    }
-
-    stock_shapes, stock_sizes = stock_get_policy_npy_shapes(stock_input_shapes)
-    sunny_shapes, sunny_sizes = sunny_get_policy_npy_shapes(stock_input_shapes, is_supercombo=True)
-
-    assert sunny_shapes == stock_shapes
-    assert sunny_sizes == stock_sizes
-    assert sunny_shapes['prev_feat'] == (1, 512)
-
-  def test_make_input_queues_full_stock_equivalence(self):
-    from openpilot.selfdrive.modeld.compile_modeld import make_input_queues as stock_make_input_queues
-    from openpilot.sunnypilot.modeld_v2.compile_modeld import make_supercombo_input_queues as sunny_make_supercombo_input_queues
-    input_shapes = {
-      'img': (1, 12, 128, 256),
-      'desire_pulse': (1, 25, 8),
-      'features_buffer': (1, 24, 512),  # when https://github.com/commaai/openpilot/pull/38681 merges, update to 1,24,32,512
-      'traffic_convention': (1, 2),
-      'action_t': (1, 2),
-    }
-    frame_skip = 4
-
-    stock_queues, stock_npy = stock_make_input_queues(input_shapes, frame_skip, device='NPY')
-    sunny_queues, sunny_npy = sunny_make_supercombo_input_queues(input_shapes, frame_skip, device='NPY')
-    assert set(sunny_queues.keys()) == set(stock_queues.keys())
-    for key in stock_queues:
-      assert sunny_queues[key].shape == stock_queues[key].shape, \
-        f"Queue shape mismatch for {key}: sunny {sunny_queues[key].shape} != stock {stock_queues[key].shape}"
-    assert set(sunny_npy.keys()) == set(stock_npy.keys())
-    for key in stock_npy:
-      assert sunny_npy[key].shape == stock_npy[key].shape, \
-        f"Numpy array shape mismatch for {key}: sunny {sunny_npy[key].shape} != stock {stock_npy[key].shape}"
-
-  def test_make_warp_queues_stock_equivalence(self):
-    from openpilot.selfdrive.modeld.compile_modeld import make_warp_input_queues as stock_make_warp_queues
-    from openpilot.sunnypilot.modeld_v2.compile_modeld import make_warp_queues as sunny_make_warp_queues
-    stock_vision_shapes = {'img': (1, 12, 128, 256)}  # for now?
-    stock_queues, stock_npy = stock_make_warp_queues(stock_vision_shapes, frame_skip=4, device='NPY')
-    sunny_queues, sunny_npy = sunny_make_warp_queues(device='NPY')
-
-    assert set(sunny_npy.keys()) == set(stock_npy.keys()) == {'tfm', 'big_tfm'}
-    for key in sunny_npy:
-      assert sunny_npy[key].shape == stock_npy[key].shape == (3, 3)
-
-

openpilot/sunnypilot/models/fetcher.py

@@ -141,7 +141,7 @@ class ModelCache:
 class ModelFetcher:
   """Handles fetching and caching of model data from remote source"""
   MODEL_URL = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_v20.json"
-  MODEL_URL_USBGPU = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_usbgpu_v22.json"
+  MODEL_URL_USBGPU = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_usbgpu_v21.json"
 
   def __init__(self, params: Params):
     self.params = params

openpilot/sunnypilot/models/manager.py

@@ -143,13 +143,17 @@ class ModelManagerSP:
       is_cached = False
       if len(artifact.chunks) > 0:
         from openpilot.common.file_chunker import get_chunk_name
+        num_chunks = len(artifact.chunks)
         chunks_valid = True
         for i, chunk in enumerate(artifact.chunks):
-          chunk_path = get_chunk_name(full_path, i, len(artifact.chunks))
+          chunk_path = get_chunk_name(full_path, i, num_chunks)
           if not await verify_file(chunk_path, chunk.sha256):
             chunks_valid = False
             break
-        if chunks_valid and len(artifact.chunks) > 0:
+          artifact.downloadProgress.progress = ((i + 1) / num_chunks) * 100
+          self._sync_artifact_progress(artifact)
+          self._report_status()
+        if chunks_valid and num_chunks > 0:
           is_cached = True
       else:
         if await verify_file(full_path, expected_hash):
@@ -216,6 +220,9 @@ class ModelManagerSP:
     """Downloads all models in a bundle"""
     self.selected_bundle = model_bundle
     self.selected_bundle.status = custom.ModelManagerSP.DownloadStatus.downloading
+    for model in self.selected_bundle.models:
+      model.artifact.downloadProgress.status = custom.ModelManagerSP.DownloadStatus.downloading
+    self._report_status()
     os.makedirs(destination_path, exist_ok=True)
 
     try:
@@ -260,7 +267,9 @@ class ModelManagerSP:
         self.active_bundle = get_active_bundle(self.params)
 
         if (index_to_download := self.params.get("ModelManager_DownloadIndex")) is not None:
-          if model_to_download := next((model for model in self.available_models if model.index == index_to_download), None):
+          if self.active_bundle and self.active_bundle.index == index_to_download:
+            self.params.remove("ModelManager_DownloadIndex")
+          elif model_to_download := next((model for model in self.available_models if model.index == index_to_download), None):
             try:
               self.download(model_to_download, Paths.model_root())
             except Exception as e:

openpilot/sunnypilot/selfdrive/car/intelligent_cruise_button_management/controller.py

@@ -115,7 +115,7 @@ class IntelligentCruiseButtonManagement:
     self.is_ready = ready and not button_pressed
 
   def run(self, CS: car.CarState, CC: car.CarControl, LP_SP: custom.LongitudinalPlanSP, is_metric: bool) -> None:
-    if self.CP_SP.pcmCruiseSpeed or not self.CP_SP.intelligentCruiseButtonManagementAvailable:
+    if self.CP_SP.pcmCruiseSpeed:
       return
 
     self.is_metric = is_metric

openpilot/sunnypilot/selfdrive/car/interfaces.py

@@ -136,9 +136,6 @@ def initialize_params(params) -> list[dict[str, Any]]:
   keys.extend([
     "ToyotaEnforceStockLongitudinal",
     "ToyotaStopAndGoHack",
-    "ToyotaTSS2Long",
-    "ToyotaEnhancedBsm",
-    "ToyotaAutoHold",
   ])
 
   return [{k: params.get(k, return_default=True)} for k in keys]

openpilot/sunnypilot/selfdrive/car/tests/test_custom_cruise.py

@@ -1,26 +1,14 @@
-from opendbc.can.parser import CANParser
-from opendbc.car import create_button_events
 from opendbc.car.structs import car
-from opendbc.car.toyota.carstate import get_virtual_cruise_button, VIRTUAL_CRUISE_BUTTONS
-from openpilot.cereal import custom
 from openpilot.common.constants import CV
 from openpilot.common.parameterized import parameterized, parameterized_class
 from openpilot.common.params import Params
-from openpilot.common.test import OpenpilotTestCase
-from openpilot.selfdrive.car.cruise import TOYOTA_VIRTUAL_CRUISE_LONG_PRESS, VCruiseHelper, V_CRUISE_INITIAL, V_CRUISE_UNSET
+from openpilot.selfdrive.car.cruise import V_CRUISE_INITIAL
 from openpilot.selfdrive.car.tests.test_cruise_speed import TestVCruiseHelper
-from openpilot.sunnypilot.selfdrive.car.interfaces import initialize_params
 
 ButtonEvent = car.CarState.ButtonEvent
 ButtonType = car.CarState.ButtonEvent.Type
 
 
-class TestToyotaParamsHandoff(OpenpilotTestCase):
-  def test_tss2_long_tuning_param_is_forwarded_to_opendbc(self):
-    keys = {next(iter(entry)) for entry in initialize_params(Params())}
-    assert "ToyotaTSS2Long" in keys
-
-
 # TODO: test pcmCruise and pcmCruiseSpeed
 @parameterized_class(('pcm_cruise', 'pcm_cruise_speed'), [(False, True)])
 class TestCustomAccIncrements(TestVCruiseHelper):
@@ -126,8 +114,8 @@ class TestCustomAccIncrements(TestVCruiseHelper):
   def test_rounding_behavior(self):
     """Test rounding behavior for 5 and 10 increments"""
     test_cases = [
-      (47, 5, 50),  # 47 -> 50 (round up to next 5)
-      (45, 5, 50),  # 45 -> 50 (already at 5, increment by 5)
+      (47, 5, 50),   # 47 -> 50 (round up to next 5)
+      (45, 5, 50),   # 45 -> 50 (already at 5, increment by 5)
       (43, 10, 50),  # 43 -> 50 (round up to next 10)
       (40, 10, 50),  # 40 -> 50 (already at 10, increment by 10)
     ]
@@ -158,302 +146,3 @@ class TestCustomAccIncrements(TestVCruiseHelper):
     initial_speed = self.v_cruise_helper.v_cruise_kph
     self.press_button_long(ButtonType.accelCruise)
     assert self.v_cruise_helper.v_cruise_kph == initial_speed + 10  # Should fallback to 10
-
-
-class TestToyotaVirtualCruiseSpeed(OpenpilotTestCase):
-  def setup_method(self):
-    self.params = Params()
-    self.params.put_bool("CustomAccIncrementsEnabled", True, block=True)
-    self.params.put("CustomAccShortPressIncrement", 5, block=True)
-    self.params.put("CustomAccLongPressIncrement", 5, block=True)
-
-    CP = car.CarParams(brand="toyota", pcmCruise=True, openpilotLongitudinalControl=True)
-    CP_SP = custom.CarParamsSP(pcmCruiseSpeed=False)
-    self.v_cruise_helper = VCruiseHelper(CP, CP_SP)
-    self.v_cruise_helper.read_custom_set_speed_params()
-    self.route_parser = CANParser("toyota_nodsu_pt_generated", [("CLUTCH", 16)], 0)
-    self.route_button = 0
-
-  @staticmethod
-  def car_state(canonical_kph, cluster_kph, *, available=True, standstill=False, gas_pressed=False, v_ego_kph=0.0, button_events=None):
-    CS = car.CarState(
-      gasPressed=gas_pressed,
-      vEgo=v_ego_kph * CV.KPH_TO_MS,
-      cruiseState={
-        "available": available,
-        "speed": canonical_kph * CV.KPH_TO_MS,
-        "speedCluster": cluster_kph * CV.KPH_TO_MS,
-        "standstill": standstill,
-      },
-    )
-    CS.buttonEvents = button_events or []
-    return CS
-
-  def seed_enabled(self, canonical_kph, cluster_kph, *, is_metric=True):
-    CS = self.car_state(canonical_kph, cluster_kph)
-    self.v_cruise_helper.update_v_cruise(CS, enabled=False, is_metric=is_metric)
-    self.v_cruise_helper.update_v_cruise(CS, enabled=True, is_metric=is_metric)
-    self.v_cruise_helper.update_v_cruise(CS, enabled=True, is_metric=is_metric)
-    assert self.v_cruise_helper.v_cruise_kph == canonical_kph
-    assert self.v_cruise_helper.v_cruise_cluster_kph == cluster_kph
-
-  def press(self, button_type, canonical_kph, cluster_kph, hold_frames=0, *, standstill=False, gas_pressed=False, v_ego_kph=0.0, is_metric=True):
-    pressed = [ButtonEvent(type=button_type, pressed=True)]
-    self.v_cruise_helper.update_v_cruise(
-      self.car_state(canonical_kph, cluster_kph, standstill=standstill, gas_pressed=gas_pressed, v_ego_kph=v_ego_kph, button_events=pressed),
-      enabled=True,
-      is_metric=is_metric,
-    )
-    for _ in range(hold_frames):
-      self.v_cruise_helper.update_v_cruise(
-        self.car_state(canonical_kph, cluster_kph, standstill=standstill, gas_pressed=gas_pressed, v_ego_kph=v_ego_kph),
-        enabled=True,
-        is_metric=is_metric,
-      )
-    released = [ButtonEvent(type=button_type, pressed=False)]
-    self.v_cruise_helper.update_v_cruise(
-      self.car_state(canonical_kph, cluster_kph, standstill=standstill, gas_pressed=gas_pressed, v_ego_kph=v_ego_kph, button_events=released),
-      enabled=True,
-      is_metric=is_metric,
-    )
-
-  def set_increments(self, short_increment, long_increment):
-    self.params.put("CustomAccShortPressIncrement", short_increment, block=True)
-    self.params.put("CustomAccLongPressIncrement", long_increment, block=True)
-    self.v_cruise_helper.read_custom_set_speed_params()
-
-  def assert_kph_almost_equal(self, actual, expected):
-    self.assertAlmostEqual(actual, expected, delta=abs(expected) * 1e-6)
-
-  def route_button_events(self, payload):
-    self.route_parser.update((1, [(0x361, bytes.fromhex(payload), 0)]))
-    current = get_virtual_cruise_button(
-      self.route_parser.vl["CLUTCH"]["CRUISE_RES"],
-      self.route_parser.vl["CLUTCH"]["CRUISE_SET"],
-    )
-    events = create_button_events(current, self.route_button, VIRTUAL_CRUISE_BUTTONS)
-    self.route_button = current
-    return events
-
-  def test_short_press_rounds_display_target_and_preserves_offset(self):
-    self.seed_enabled(27, 31)
-    self.press(ButtonType.accelCruise, 28, 32)
-
-    assert self.v_cruise_helper.v_cruise_kph == 31
-    assert self.v_cruise_helper.v_cruise_cluster_kph == 35
-
-  def test_decel_at_display_minimum_does_not_increase_target(self):
-    self.seed_enabled(26, 30)
-    self.press(ButtonType.decelCruise, 25, 29)
-
-    assert self.v_cruise_helper.v_cruise_kph == 26
-    assert self.v_cruise_helper.v_cruise_cluster_kph == 30
-
-  @parameterized.expand((52, TOYOTA_VIRTUAL_CRUISE_LONG_PRESS - 1))
-  def test_route_length_short_press_is_not_a_long_press(self, hold_frames):
-    self.set_increments(short_increment=2, long_increment=5)
-    self.seed_enabled(27, 31)
-    self.press(ButtonType.accelCruise, 28, 32, hold_frames=hold_frames)
-
-    assert self.v_cruise_helper.v_cruise_kph == 29
-    assert self.v_cruise_helper.v_cruise_cluster_kph == 33
-
-  def test_toyota_long_press_uses_route_validated_cadence_and_suppresses_release(self):
-    self.set_increments(short_increment=2, long_increment=5)
-    self.seed_enabled(27, 31)
-
-    pressed = [ButtonEvent(type=ButtonType.accelCruise, pressed=True)]
-    self.v_cruise_helper.update_v_cruise(self.car_state(31, 35, button_events=pressed), enabled=True, is_metric=True)
-    for _ in range(TOYOTA_VIRTUAL_CRUISE_LONG_PRESS):
-      self.v_cruise_helper.update_v_cruise(self.car_state(31, 35), enabled=True, is_metric=True)
-
-    assert self.v_cruise_helper.v_cruise_kph == 31
-    assert self.v_cruise_helper.v_cruise_cluster_kph == 35
-
-    released = [ButtonEvent(type=ButtonType.accelCruise, pressed=False)]
-    self.v_cruise_helper.update_v_cruise(self.car_state(31, 35, button_events=released), enabled=True, is_metric=True)
-    assert self.v_cruise_helper.v_cruise_kph == 31
-    assert self.v_cruise_helper.v_cruise_cluster_kph == 35
-
-  def test_route_4_32_second_hold_repeats_six_times(self):
-    self.seed_enabled(26, 30)
-    self.press(ButtonType.accelCruise, 30, 34, hold_frames=432)
-
-    assert self.v_cruise_helper.v_cruise_kph == 56
-    assert self.v_cruise_helper.v_cruise_cluster_kph == 60
-
-  def test_maximum_boundary_caps_pair_and_preserves_offset(self):
-    self.seed_enabled(141, 145)
-    self.press(ButtonType.accelCruise, 142, 146)
-
-    assert self.v_cruise_helper.v_cruise_kph == 141
-    assert self.v_cruise_helper.v_cruise_cluster_kph == 145
-
-    self.press(ButtonType.accelCruise, 143, 147)
-    assert self.v_cruise_helper.v_cruise_kph == 141
-    assert self.v_cruise_helper.v_cruise_cluster_kph == 145
-
-  @parameterized.expand(
-    (
-      (25, 29, ButtonType.decelCruise),
-      (141, 147, ButtonType.accelCruise),
-    )
-  )
-  def test_out_of_range_raw_pair_is_not_moved_in_opposite_direction(self, canonical_kph, cluster_kph, button_type):
-    self.seed_enabled(canonical_kph, cluster_kph)
-    self.press(button_type, canonical_kph, cluster_kph)
-
-    assert self.v_cruise_helper.v_cruise_kph == canonical_kph
-    assert self.v_cruise_helper.v_cruise_cluster_kph == cluster_kph
-
-  def test_imperial_increment_preserves_canonical_cluster_pair(self):
-    self.seed_enabled(45, 50, is_metric=False)
-    self.press(ButtonType.accelCruise, 46, 51, is_metric=False)
-
-    assert self.v_cruise_helper.v_cruise_kph == 51
-    assert self.v_cruise_helper.v_cruise_cluster_kph == 56
-
-  def test_engagement_button_held_does_not_change_target(self):
-    initial = self.car_state(27, 31)
-    self.v_cruise_helper.update_v_cruise(initial, enabled=False, is_metric=True)
-
-    pressed = [ButtonEvent(type=ButtonType.decelCruise, pressed=True)]
-    self.v_cruise_helper.update_v_cruise(self.car_state(27, 31, button_events=pressed), enabled=False, is_metric=True)
-    for _ in range(TOYOTA_VIRTUAL_CRUISE_LONG_PRESS + 10):
-      self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=True, is_metric=True)
-
-    released = [ButtonEvent(type=ButtonType.decelCruise, pressed=False)]
-    self.v_cruise_helper.update_v_cruise(self.car_state(28, 32, button_events=released), enabled=True, is_metric=True)
-    self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=True, is_metric=True)
-
-    assert self.v_cruise_helper.v_cruise_kph == 28
-    assert self.v_cruise_helper.v_cruise_cluster_kph == 32
-
-  def test_delayed_pcm_target_seeds_before_software_ownership(self):
-    invalid = self.car_state(0, 0)
-    self.v_cruise_helper.update_v_cruise(invalid, enabled=False, is_metric=True)
-
-    release = [ButtonEvent(type=ButtonType.decelCruise, pressed=False)]
-    for _ in range(4):
-      self.v_cruise_helper.update_v_cruise(self.car_state(0, 0, button_events=release), enabled=True, is_metric=True)
-      assert self.v_cruise_helper.v_cruise_kph == V_CRUISE_UNSET
-      assert self.v_cruise_helper.v_cruise_cluster_kph == V_CRUISE_UNSET
-
-    self.v_cruise_helper.update_v_cruise(self.car_state(27, 31), enabled=True, is_metric=True)
-    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_kph, 27)
-    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_cluster_kph, 31)
-
-    self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=True, is_metric=True)
-    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_kph, 27)
-    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_cluster_kph, 31)
-
-  def test_route_payload_short_press_drives_virtual_target(self):
-    self.seed_enabled(27, 31)
-
-    pressed = self.route_button_events("a61a0000561a1a81")
-    self.v_cruise_helper.update_v_cruise(self.car_state(27, 31, button_events=pressed), enabled=True, is_metric=True)
-    for _ in range(52):
-      self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=True, is_metric=True)
-
-    released = self.route_button_events("861a0000561b1a81")
-    self.v_cruise_helper.update_v_cruise(self.car_state(28, 32, button_events=released), enabled=True, is_metric=True)
-    assert self.v_cruise_helper.v_cruise_kph == 31
-    assert self.v_cruise_helper.v_cruise_cluster_kph == 35
-
-  def test_prius_route_payload_short_set_drives_virtual_target(self):
-    self.seed_enabled(31, 35)
-
-    pressed = self.route_button_events("965f000056666585")
-    self.v_cruise_helper.update_v_cruise(self.car_state(31, 35, button_events=pressed), enabled=True, is_metric=True)
-    for _ in range(45):
-      self.v_cruise_helper.update_v_cruise(self.car_state(30, 34), enabled=True, is_metric=True)
-
-    released = self.route_button_events("865f000056666585")
-    self.v_cruise_helper.update_v_cruise(self.car_state(30, 34, button_events=released), enabled=True, is_metric=True)
-    assert self.v_cruise_helper.v_cruise_kph == 26
-    assert self.v_cruise_helper.v_cruise_cluster_kph == 30
-
-  def test_prius_route_payload_standstill_res_does_not_change_target(self):
-    self.seed_enabled(27, 31)
-
-    pressed = self.route_button_events("a61b0000561c1c80")
-    self.v_cruise_helper.update_v_cruise(
-      self.car_state(27, 31, standstill=True, button_events=pressed),
-      enabled=True,
-      is_metric=True,
-    )
-    for _ in range(TOYOTA_VIRTUAL_CRUISE_LONG_PRESS):
-      self.v_cruise_helper.update_v_cruise(self.car_state(27, 31, standstill=True), enabled=True, is_metric=True)
-
-    released = self.route_button_events("865f000056666585")
-    self.v_cruise_helper.update_v_cruise(
-      self.car_state(27, 31, standstill=True, button_events=released),
-      enabled=True,
-      is_metric=True,
-    )
-    assert self.v_cruise_helper.v_cruise_kph == 27
-    assert self.v_cruise_helper.v_cruise_cluster_kph == 31
-
-  def test_route_payload_disengage_mid_hold_clears_pending_action(self):
-    self.seed_enabled(27, 31)
-
-    pressed = self.route_button_events("a61a0000561a1a81")
-    self.v_cruise_helper.update_v_cruise(self.car_state(27, 31, button_events=pressed), enabled=True, is_metric=True)
-    for _ in range(30):
-      self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=True, is_metric=True)
-
-    self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=False, is_metric=True)
-    released = self.route_button_events("861a0000561b1a81")
-    self.v_cruise_helper.update_v_cruise(self.car_state(28, 32, available=False, button_events=released), enabled=False, is_metric=True)
-
-    self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=False, is_metric=True)
-    self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=True, is_metric=True)
-    self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=True, is_metric=True)
-    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_kph, 28)
-    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_cluster_kph, 32)
-
-  def test_standstill_resume_does_not_change_target(self):
-    self.seed_enabled(27, 31)
-    self.press(ButtonType.accelCruise, 27, 31, standstill=True)
-
-    assert self.v_cruise_helper.v_cruise_kph == 27
-    assert self.v_cruise_helper.v_cruise_cluster_kph == 31
-
-  def test_disengagement_discards_virtual_target_and_reseeds_raw_pair(self):
-    self.seed_enabled(27, 31)
-    self.press(ButtonType.accelCruise, 28, 32)
-    assert self.v_cruise_helper.v_cruise_kph == 31
-
-    raw = self.car_state(28, 32)
-    self.v_cruise_helper.update_v_cruise(raw, enabled=False, is_metric=True)
-    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_kph, 28)
-    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_cluster_kph, 32)
-
-    self.v_cruise_helper.update_v_cruise(raw, enabled=True, is_metric=True)
-    self.v_cruise_helper.update_v_cruise(raw, enabled=True, is_metric=True)
-    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_kph, 28)
-    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_cluster_kph, 32)
-
-  def test_unavailable_and_mads_handback_discard_virtual_target(self):
-    self.seed_enabled(27, 31)
-    self.press(ButtonType.accelCruise, 28, 32)
-    assert self.v_cruise_helper.v_cruise_kph == 31
-
-    self.v_cruise_helper.update_v_cruise(self.car_state(28, 32), enabled=False, is_metric=True)
-    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_kph, 28)
-    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_cluster_kph, 32)
-
-    self.v_cruise_helper.update_v_cruise(self.car_state(0, 0, available=False), enabled=False, is_metric=True)
-    assert self.v_cruise_helper.v_cruise_kph == V_CRUISE_UNSET
-    assert self.v_cruise_helper.v_cruise_cluster_kph == V_CRUISE_UNSET
-
-    self.v_cruise_helper.update_v_cruise(self.car_state(29, 33), enabled=False, is_metric=True)
-    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_kph, 29)
-    self.assert_kph_almost_equal(self.v_cruise_helper.v_cruise_cluster_kph, 33)
-
-  def test_set_during_gas_override_clips_target_to_ego_speed(self):
-    self.seed_enabled(27, 31)
-    self.press(ButtonType.decelCruise, 26, 30, gas_pressed=True, v_ego_kph=50)
-
-    assert self.v_cruise_helper.v_cruise_kph == 50
-    assert self.v_cruise_helper.v_cruise_cluster_kph == 54

openpilot/sunnypilot/selfdrive/controls/lib/accel_controller/accel_controller.py

@@ -1,109 +0,0 @@
-"""
-Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
-
-This file is part of sunnypilot and is licensed under the MIT License.
-See the LICENSE.md file in the root directory for more details.
-"""
-
-import numpy as np
-
-from openpilot.cereal import custom
-from openpilot.common.params import Params
-from openpilot.common.realtime import DT_MDL
-from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import MAX_T, STOP_DISTANCE
-from openpilot.sunnypilot import get_sanitize_int_param
-
-AccelProfile = custom.LongitudinalPlanSP.AccelController.Profile
-
-MAX_ACCEL_BREAKPOINTS = [0., 3., 5., 8., 10., 25., 40.]
-MAX_ACCEL_PROFILES = {
-  AccelProfile.eco:    [1.20, 0.95, 0.70, 0.48, 0.40, 0.28, 0.18],
-  AccelProfile.normal: [1.60, 1.35, 1.05, 0.65, 0.52, 0.40, 0.28],
-  AccelProfile.sport:  [2.00, 1.90, 1.55, 1.00, 0.80, 0.60, 0.40],
-}
-TARGET_SPEED_DEADBAND = 0.2  # m/s
-TARGET_SPEED_APPROACH_WINDOW = 2.0  # m/s
-TARGET_SPEED_APPROACH_GAIN = 0.5
-TARGET_SPEED_APPROACH_MIN_SPEED = 3.0  # m/s
-TARGET_SPEED_APPROACH_FULL_SPEED = 5.0  # m/s
-CATCHUP_ERROR_BREAKPOINTS = [TARGET_SPEED_DEADBAND, 0.5, 1.0, 2.0, 3.0, 4.0]
-CATCHUP_ACCEL_SCALE = [0.0, 0.3, 0.5, 0.7, 0.85, 1.0]
-LEAD_COMFORT_ACCEL = -0.4  # m/s^2
-LEAD_COMFORT_JERK = 0.6  # m/s^3
-
-
-class AccelController:
-  def __init__(self):
-    self.params = Params()
-    self.frame = 0
-    self._profile = get_sanitize_int_param("AccelPersonality", AccelProfile.eco, AccelProfile.sport, self.params)
-    self._enabled = self.params.get_bool("AccelPersonalityEnabled")
-
-  def update(self) -> None:
-    self.frame += 1
-    if self.frame % int(1.0 / DT_MDL) == 0:
-      self._profile = get_sanitize_int_param("AccelPersonality", AccelProfile.eco, AccelProfile.sport, self.params)
-      self._enabled = self.params.get_bool("AccelPersonalityEnabled")
-
-  @property
-  def profile(self) -> int:
-    return self._profile
-
-  def is_enabled(self) -> bool:
-    return self._enabled
-
-  def get_max_accel(self, v_ego: float, v_target: float | None = None) -> float:
-    v_ego = max(0.0, v_ego)
-    max_accel = float(np.interp(v_ego, MAX_ACCEL_BREAKPOINTS, MAX_ACCEL_PROFILES[self._profile]))
-    if v_target is None or v_ego <= TARGET_SPEED_APPROACH_MIN_SPEED or v_target <= v_ego:
-      return max_accel
-
-    speed_error = v_target - v_ego
-    speed_blend = float(np.interp(v_ego, [TARGET_SPEED_APPROACH_MIN_SPEED, TARGET_SPEED_APPROACH_FULL_SPEED], [0.0, 1.0]))
-    catchup_scale = float(np.interp(speed_error, CATCHUP_ERROR_BREAKPOINTS, CATCHUP_ACCEL_SCALE))
-    raw_accel = min(speed_error, max_accel)
-    catchup_accel = min(speed_error, max_accel * catchup_scale)
-    return float(raw_accel + speed_blend * (catchup_accel - raw_accel))
-
-  def get_cruise_target(self, v_ego: float, v_target: float) -> float:
-    if v_ego <= TARGET_SPEED_APPROACH_MIN_SPEED:
-      return v_target
-
-    speed_error = v_target - v_ego
-    if speed_error >= 0.0:
-      return v_target
-
-    speed_blend = float(np.interp(v_ego, [TARGET_SPEED_APPROACH_MIN_SPEED, TARGET_SPEED_APPROACH_FULL_SPEED], [0.0, 1.0]))
-    target_blend = float(np.interp(abs(speed_error), [TARGET_SPEED_DEADBAND, TARGET_SPEED_APPROACH_WINDOW], [1.0, 0.0]))
-    deadband = TARGET_SPEED_DEADBAND * speed_blend * target_blend
-    adjusted_error = np.sign(speed_error) * max(0.0, abs(speed_error) - deadband)
-    gain = 1.0 - (1.0 - TARGET_SPEED_APPROACH_GAIN) * speed_blend * target_blend
-    return float(v_ego + gain * adjusted_error)
-
-  def get_lead_departure_accel(self, v_ego: float, v_lead: float, a_lead: float, mpc_accel: float) -> float:
-    values = (v_ego, v_lead, a_lead, mpc_accel)
-    if not self._enabled or not all(np.isfinite(value) for value in values) or a_lead < 0.0 or mpc_accel < 0.0 or v_lead <= v_ego:
-      return mpc_accel
-
-    return max(mpc_accel, min(v_lead - v_ego, self.get_max_accel(v_ego, v_lead)))
-
-  def get_lead_accel(self, v_ego: float, d_rel: float, v_rel: float, a_lead: float,
-                     cruise_accel: float, previous_accel: float, t_follow: float) -> float:
-    values = (v_ego, d_rel, v_rel, a_lead, cruise_accel, previous_accel, t_follow)
-    if not self._enabled or not all(np.isfinite(value) for value in values) or v_ego < TARGET_SPEED_APPROACH_FULL_SPEED or d_rel <= 0.0:
-      return cruise_accel
-
-    v_lead = max(v_ego + v_rel, 0.0)
-    clearance = d_rel - (STOP_DISTANCE + t_follow * v_lead)
-    lead_lookahead = 2.0 * t_follow
-    projected_closing = max(-(v_rel + a_lead * lead_lookahead), 0.0)
-    if projected_closing <= 0.0 or clearance / projected_closing >= MAX_T:
-      return cruise_accel
-
-    required_accel = a_lead - projected_closing ** 2 / (2.0 * max(clearance, STOP_DISTANCE))
-    target_accel = float(np.clip(required_accel, LEAD_COMFORT_ACCEL, 0.0))
-
-    max_step = LEAD_COMFORT_JERK * DT_MDL
-    previous_comfort_accel = max(previous_accel, LEAD_COMFORT_ACCEL)
-    lead_accel = float(np.clip(target_accel, previous_comfort_accel - max_step, previous_comfort_accel + max_step))
-    return min(cruise_accel, lead_accel)

openpilot/sunnypilot/selfdrive/controls/lib/accel_controller/tests/test_accel_controller.py

@@ -1,408 +0,0 @@
-"""
-Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
-
-This file is part of sunnypilot and is licensed under the MIT License.
-See the LICENSE.md file in the root directory for more details.
-"""
-
-import numpy as np
-
-from opendbc.car.interfaces import ACCEL_MAX
-from openpilot.common.params import Params
-from openpilot.common.realtime import DT_MDL
-from openpilot.common.test import OpenpilotTestCase
-from openpilot.selfdrive.controls.lib.longitudinal_planner import (
-  A_CRUISE_MAX_BP, A_CRUISE_MIN, J_CRUISE_VALS, get_cruise_accel, get_max_accel,
-)
-from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import MAX_T, STOP_DISTANCE
-from openpilot.sunnypilot.selfdrive.controls.lib.accel_controller.accel_controller import (
-  AccelController, AccelProfile, CATCHUP_ACCEL_SCALE, CATCHUP_ERROR_BREAKPOINTS, MAX_ACCEL_BREAKPOINTS, MAX_ACCEL_PROFILES,
-  LEAD_COMFORT_ACCEL, LEAD_COMFORT_JERK,
-  TARGET_SPEED_APPROACH_FULL_SPEED, TARGET_SPEED_APPROACH_GAIN, TARGET_SPEED_APPROACH_MIN_SPEED, TARGET_SPEED_APPROACH_WINDOW,
-  TARGET_SPEED_DEADBAND,
-)
-
-
-class TestAccelController(OpenpilotTestCase):
-  def setUp(self):
-    self.params = Params()
-    self.params.put_bool("AccelPersonalityEnabled", True, block=True)
-    self.params.put("AccelPersonality", AccelProfile.normal, block=True)
-
-  def set_profile(self, profile: int) -> AccelController:
-    self.params.put("AccelPersonality", profile, block=True)
-    return AccelController()
-
-  def test_table_breakpoints(self):
-    for profile, values in MAX_ACCEL_PROFILES.items():
-      controller = self.set_profile(profile)
-      for speed, expected in zip(MAX_ACCEL_BREAKPOINTS, values, strict=True):
-        assert controller.get_max_accel(speed) == expected
-
-  def test_profile_ordering_and_bounds(self):
-    controllers = {
-      AccelProfile.eco: self.set_profile(AccelProfile.eco),
-      AccelProfile.normal: self.set_profile(AccelProfile.normal),
-      AccelProfile.sport: self.set_profile(AccelProfile.sport),
-    }
-    previous = {profile: float("inf") for profile in controllers}
-
-    for speed in np.linspace(0.0, 55.0, 551):
-      values = {profile: controller.get_max_accel(speed) for profile, controller in controllers.items()}
-      assert 0.0 <= values[AccelProfile.eco] <= values[AccelProfile.normal] <= values[AccelProfile.sport] <= 2.0
-      for profile, value in values.items():
-        assert value <= previous[profile]
-        previous[profile] = value
-
-  def test_profiles_stay_within_openpilot_accel_max(self):
-    for profile in (AccelProfile.eco, AccelProfile.normal, AccelProfile.sport):
-      controller = self.set_profile(profile)
-      for speed in np.linspace(0.0, 55.0, 551):
-        assert controller.get_max_accel(speed) <= ACCEL_MAX
-
-  def test_profiles_do_not_exceed_stock_at_road_speed(self):
-    for profile in (AccelProfile.eco, AccelProfile.normal, AccelProfile.sport):
-      controller = self.set_profile(profile)
-      for speed in np.linspace(8.0, 40.0, 321):
-        assert controller.get_max_accel(speed) <= get_max_accel(speed) + 1e-12
-
-  def test_profiles_have_material_separation(self):
-    controllers = [self.set_profile(profile) for profile in (AccelProfile.eco, AccelProfile.normal, AccelProfile.sport)]
-    for speed in MAX_ACCEL_BREAKPOINTS:
-      eco, normal, sport = (controller.get_max_accel(speed) for controller in controllers)
-      assert normal - eco >= 0.1
-      assert sport - normal >= 0.1
-    for speed in MAX_ACCEL_BREAKPOINTS[1:-1]:
-      assert controllers[2].get_max_accel(speed) - controllers[0].get_max_accel(speed) >= 0.3 - 1e-12
-
-  def test_eco_keeps_useful_road_speed_acceleration(self):
-    controller = self.set_profile(AccelProfile.eco)
-    for speed in np.linspace(8.0, 40.0, 321):
-      assert controller.get_max_accel(speed) >= 0.25 * get_max_accel(speed) - 1e-12
-
-  def test_comfort_profile_caps_taper_after_launch(self):
-    for profile in (AccelProfile.eco, AccelProfile.normal):
-      values = MAX_ACCEL_PROFILES[profile]
-      assert values[3] <= 0.55 * values[0]
-
-  def test_sport_uses_openpilot_accel_max_at_launch(self):
-    controller = self.set_profile(AccelProfile.sport)
-    assert controller.get_max_accel(0.0) == ACCEL_MAX
-    assert all(controller.get_max_accel(speed) <= ACCEL_MAX for speed in np.linspace(0.0, 55.0, 551))
-
-  def test_positive_catchup_limit_is_continuous_and_monotonic(self):
-    controller = self.set_profile(AccelProfile.normal)
-    v_ego = 20.0
-    max_accel = controller.get_max_accel(v_ego)
-    errors = np.linspace(1e-4, 8.0, 321)
-    accel_limits = np.asarray([controller.get_max_accel(v_ego, v_ego + error) for error in errors])
-
-    assert np.all(np.isfinite(accel_limits))
-    assert np.all(np.diff(accel_limits) >= -1e-12)
-    assert np.all(accel_limits <= errors + 1e-12)
-    assert np.all(accel_limits <= max_accel + 1e-12)
-    assert controller.get_max_accel(v_ego, v_ego + TARGET_SPEED_DEADBAND) == 0.0
-    assert np.isclose(controller.get_max_accel(v_ego, v_ego + CATCHUP_ERROR_BREAKPOINTS[-1]), max_accel)
-
-    for error, scale in zip(CATCHUP_ERROR_BREAKPOINTS, CATCHUP_ACCEL_SCALE, strict=True):
-      expected_accel = min(error, max_accel * scale)
-      assert np.isclose(controller.get_max_accel(v_ego, v_ego + error), expected_accel)
-      below = controller.get_max_accel(v_ego, v_ego + error - 1e-6)
-      above = controller.get_max_accel(v_ego, v_ego + error + 1e-6)
-      assert above >= below
-      assert above - below < 1e-4
-
-  def test_cruise_decel_settling_is_continuous(self):
-    controller = self.set_profile(AccelProfile.normal)
-    v_ego = 20.0
-    near_error = 0.5
-    target_blend = (TARGET_SPEED_APPROACH_WINDOW - near_error) / (TARGET_SPEED_APPROACH_WINDOW - TARGET_SPEED_DEADBAND)
-    adjusted_error = near_error - TARGET_SPEED_DEADBAND * target_blend
-    gain = 1.0 - (1.0 - TARGET_SPEED_APPROACH_GAIN) * target_blend
-    expected_error = adjusted_error * gain
-
-    assert np.isclose(controller.get_cruise_target(v_ego, v_ego - near_error), v_ego - expected_error)
-    assert controller.get_cruise_target(v_ego, v_ego - TARGET_SPEED_DEADBAND) == v_ego
-    assert controller.get_cruise_target(v_ego, v_ego - TARGET_SPEED_APPROACH_WINDOW) == v_ego - TARGET_SPEED_APPROACH_WINDOW
-
-    errors = np.linspace(-5.0, 0.0, 201)
-    shaped_errors = np.asarray([controller.get_cruise_target(v_ego, v_ego + error) - v_ego for error in errors])
-    assert np.all(np.isfinite(shaped_errors))
-    assert np.all(np.diff(shaped_errors) >= 0.0)
-    assert np.all(np.abs(shaped_errors) <= np.abs(errors) + 1e-12)
-
-  def test_lead_departure_accel_is_bounded_by_lead_speed_and_profile(self):
-    controller = self.set_profile(AccelProfile.eco)
-    assert controller.get_lead_departure_accel(0.0, 0.7, 0.1, 0.1) == 0.7
-    assert controller.get_lead_departure_accel(0.0, 2.0, 0.1, 0.1) == MAX_ACCEL_PROFILES[AccelProfile.eco][0]
-
-  def test_lead_departure_accel_preserves_non_acceleration_cases(self):
-    controller = self.set_profile(AccelProfile.normal)
-    assert controller.get_lead_departure_accel(0.0, 1.0, 0.1, -0.1) == -0.1
-    assert controller.get_lead_departure_accel(0.0, 1.0, -0.1, 0.1) == 0.1
-    assert controller.get_lead_departure_accel(1.0, 1.0, 0.1, 0.1) == 0.1
-    assert controller.get_lead_departure_accel(0.0, float("nan"), 0.1, 0.1) == 0.1
-
-    self.params.put_bool("AccelPersonalityEnabled", False, block=True)
-    assert AccelController().get_lead_departure_accel(0.0, 1.0, 0.1, 0.1) == 0.1
-
-  def test_catchup_limit_does_not_touch_launch(self):
-    controller = self.set_profile(AccelProfile.sport)
-
-    def command(speed: float, target: float, dynamic: bool = True) -> float:
-      max_accel = controller.get_max_accel(speed, target) if dynamic else controller.get_max_accel(speed)
-      return get_cruise_accel(False, target, speed, 0.0, 0.0, _fake_cp(), 10.0, 0.0, True, max_accel)
-
-    for speed in np.linspace(0.0, TARGET_SPEED_APPROACH_MIN_SPEED, 101):
-      for target in (0.0, 8.0, 30.0):
-        assert command(speed, target) == command(speed, target, dynamic=False)
-
-    below = command(TARGET_SPEED_APPROACH_MIN_SPEED - 1e-3, TARGET_SPEED_APPROACH_MIN_SPEED + 0.5 - 1e-3)
-    at = command(TARGET_SPEED_APPROACH_MIN_SPEED, TARGET_SPEED_APPROACH_MIN_SPEED + 0.5)
-    above = command(TARGET_SPEED_APPROACH_MIN_SPEED + 1e-3, TARGET_SPEED_APPROACH_MIN_SPEED + 0.5 + 1e-3)
-    assert np.isclose(below, 0.5)
-    assert np.isclose(at, 0.5)
-    assert abs(above - at) < 1e-3
-
-    below_full = command(TARGET_SPEED_APPROACH_FULL_SPEED - 1e-3, TARGET_SPEED_APPROACH_FULL_SPEED + 0.5 - 1e-3)
-    at_full = command(TARGET_SPEED_APPROACH_FULL_SPEED, TARGET_SPEED_APPROACH_FULL_SPEED + 0.5)
-    above_full = command(TARGET_SPEED_APPROACH_FULL_SPEED + 1e-3, TARGET_SPEED_APPROACH_FULL_SPEED + 0.5 + 1e-3)
-    assert abs(below_full - at_full) < 1e-3
-    assert abs(above_full - at_full) < 1e-3
-
-  def test_cruise_target_deadband_removes_small_sign_flips(self):
-    controller = self.set_profile(AccelProfile.normal)
-    v_ego = 20.0
-    errors = np.asarray([0.10, -0.10, 0.15, -0.15, 0.30, -0.30])
-    commands = []
-    for error in errors:
-      raw_target = v_ego + error
-      target = controller.get_cruise_target(v_ego, raw_target)
-      max_accel = controller.get_max_accel(v_ego, raw_target)
-      commands.append(get_cruise_accel(False, target, v_ego, 0.0, 0.0, _fake_cp(), 10.0, 0.0, True, max_accel))
-    shaped = np.asarray(commands)
-
-    assert np.count_nonzero(shaped[:4]) == 0
-    assert shaped[4] > 0.0
-    assert shaped[5] < 0.0
-    assert np.all(np.abs(shaped) <= np.abs(errors) + 1e-12)
-
-  def test_negative_speed_uses_standstill_value(self):
-    controller = self.set_profile(AccelProfile.sport)
-    assert controller.get_max_accel(-1.0) == MAX_ACCEL_PROFILES[AccelProfile.sport][0]
-
-  def test_profile_change_has_no_controller_filter(self):
-    controller = self.set_profile(AccelProfile.normal)
-    self.params.put("AccelPersonality", AccelProfile.sport, block=True)
-    controller.frame = int(1.0 / DT_MDL) - 1
-    controller.update()
-    assert controller.get_max_accel(8.0) == MAX_ACCEL_PROFILES[AccelProfile.sport][3]
-
-  def test_params_refresh_once_per_second(self):
-    controller = self.set_profile(AccelProfile.normal)
-    self.params.put("AccelPersonality", AccelProfile.sport, block=True)
-    controller.update()
-    assert controller.profile == AccelProfile.normal
-    controller.frame = int(1.0 / DT_MDL) - 1
-    controller.update()
-    assert controller.profile == AccelProfile.sport
-
-  def test_enabled_param_refresh(self):
-    controller = self.set_profile(AccelProfile.normal)
-    self.params.put_bool("AccelPersonalityEnabled", False, block=True)
-    controller.frame = int(1.0 / DT_MDL) - 1
-    controller.update()
-    assert not controller.is_enabled()
-
-  def test_closing_lead_prevents_acceleration_rebound(self):
-    controller = self.set_profile(AccelProfile.normal)
-    previous_accel = -0.647
-    samples = (
-      (17.33, 120.82, -16.35, -1.70, 0.50),
-      (17.30, 88.70, -14.95, -0.76, -0.332),
-      (17.18, 103.98, -17.15, -0.24, -0.992),
-    )
-    outputs = []
-    for v_ego, d_rel, v_rel, a_lead, mpc_accel in samples:
-      lead_accel = controller.get_lead_accel(v_ego, d_rel, v_rel, a_lead, 0.31, previous_accel, 1.45)
-      previous_accel = min(lead_accel, mpc_accel)
-      outputs.append(previous_accel)
-
-    assert np.allclose(outputs, [LEAD_COMFORT_ACCEL, LEAD_COMFORT_ACCEL, -0.992])
-    assert all(accel <= 0.0 for accel in outputs)
-
-  def test_lead_comfort_does_not_replay_hard_braking(self):
-    controller = self.set_profile(AccelProfile.normal)
-    output = controller.get_lead_accel(20.0, 60.0, -8.0, -1.0, 0.5, -1.77, 1.45)
-    assert output == LEAD_COMFORT_ACCEL
-
-  def test_lead_approach_uses_existing_mpc_horizon(self):
-    controller = self.set_profile(AccelProfile.normal)
-    for t_follow in (1.25, 1.45, 1.75):
-      v_ego, v_rel, closing = 20.0, -2.0, 2.0
-      boundary = STOP_DISTANCE + t_follow * (v_ego + v_rel) + closing * MAX_T
-      assert controller.get_lead_accel(v_ego, boundary + 1e-3, v_rel, 0.0, 0.5, 0.2, t_follow) == 0.5
-      assert controller.get_lead_accel(v_ego, boundary - 1e-3, v_rel, 0.0, 0.5, 0.2, t_follow) < 0.2
-
-  def test_braking_lead_gently_removes_positive_acceleration(self):
-    controller = self.set_profile(AccelProfile.normal)
-    previous_accel = 0.544
-    outputs = []
-    for _ in range(40):
-      output = controller.get_lead_accel(30.56, 47.62, 5.5, -1.93, 0.544, previous_accel, 1.45)
-      outputs.append(output)
-      previous_accel = output
-
-    max_step = LEAD_COMFORT_JERK * DT_MDL
-    assert np.isclose(outputs[0], 0.544 - max_step)
-    assert np.all(np.diff(outputs) >= -max_step - 1e-12)
-    assert np.isclose(outputs[-1], LEAD_COMFORT_ACCEL)
-
-  def test_transient_lead_deceleration_is_one_small_step(self):
-    controller = self.set_profile(AccelProfile.normal)
-    first = controller.get_lead_accel(31.1, 51.3, 2.8, -2.5, 0.54, 0.4, 1.45)
-    second = controller.get_lead_accel(31.1, 52.0, 3.0, 0.0, 0.54, first, 1.45)
-
-    assert np.isclose(first, 0.4 - LEAD_COMFORT_JERK * DT_MDL)
-    assert second == 0.54
-
-  def test_non_closing_and_distant_leads_do_not_change_cruise(self):
-    controller = self.set_profile(AccelProfile.normal)
-    assert controller.get_lead_accel(30.0, 52.0, 0.0, 0.0, 0.1, 0.1, 1.45) == 0.1
-    assert controller.get_lead_accel(20.0, 200.0, -1.0, 0.0, 0.1, 0.1, 1.45) == 0.1
-
-  def test_accelerating_lead_returns_cruise(self):
-    controller = self.set_profile(AccelProfile.normal)
-    output = controller.get_lead_accel(20.0, 45.0, -1.0, 1.0, 0.3, -0.2, 1.45)
-    assert output == 0.3
-
-  def test_active_approach_cannot_rebound_from_brake_to_gas(self):
-    controller = self.set_profile(AccelProfile.normal)
-    output = controller.get_lead_accel(20.0, 30.0, -5.0, 1.0, 0.3, -0.2, 1.45)
-    assert -0.2 < output <= 0.0
-
-  def test_stock_lead_braking_always_wins(self):
-    controller = self.set_profile(AccelProfile.normal)
-    assert controller.get_lead_accel(20.0, 60.0, -8.0, -1.0, -2.0, 0.2, 1.45) == -2.0
-
-  def test_invalid_disabled_and_launch_cases_match_cruise(self):
-    controller = self.set_profile(AccelProfile.normal)
-    assert controller.get_lead_accel(20.0, float("nan"), -8.0, -1.0, -0.5, 0.2, 1.45) == -0.5
-    assert controller.get_lead_accel(TARGET_SPEED_APPROACH_FULL_SPEED - 0.01, 20.0, -5.0, -1.0, 0.5, 0.0, 1.45) == 0.5
-
-    self.params.put_bool("AccelPersonalityEnabled", False, block=True)
-    controller = AccelController()
-    assert controller.get_lead_accel(20.0, 60.0, -8.0, -1.0, -0.5, 0.2, 1.45) == -0.5
-
-
-class TestPlannerIntegration(OpenpilotTestCase):
-  def setUp(self):
-    self.params = Params()
-    self.params.put_bool("AccelPersonalityEnabled", False, block=True)
-
-  def test_none_override_matches_stock(self):
-    for e2e in (False, True):
-      for allow_throttle in (False, True):
-        args = (e2e, 30.0, 12.0, 0.2, 4.0, _fake_cp(), DT_MDL, -0.3, allow_throttle)
-        assert get_cruise_accel(*args) == get_cruise_accel(*args, max_accel_override=None)
-
-  def test_profiles_do_not_change_far_braking(self):
-    args = (False, 0.0, 20.0, 0.0, 0.0, _fake_cp(), 10.0, -0.3, True)
-    stock = get_cruise_accel(*args)
-    assert stock == A_CRUISE_MIN
-    for profile_values in MAX_ACCEL_PROFILES.values():
-      assert get_cruise_accel(*args, max_accel_override=profile_values[0]) == stock
-
-  def test_stock_jerk_limit_still_owns_smoothing(self):
-    speed = 8.0
-    sport_limit = np.interp(speed, MAX_ACCEL_BREAKPOINTS, MAX_ACCEL_PROFILES[AccelProfile.sport])
-    target = get_cruise_accel(False, 30.0, speed, 0.0, 0.0, _fake_cp(), DT_MDL, 0.0, True, sport_limit)
-    jerk_limit = np.interp(speed, A_CRUISE_MAX_BP, J_CRUISE_VALS) * DT_MDL
-    assert np.isclose(target, jerk_limit)
-
-  def test_cruise_accel_tapers_before_target(self):
-    self.params.put_bool("AccelPersonalityEnabled", True, block=True)
-    self.params.put("AccelPersonality", AccelProfile.normal, block=True)
-    controller = AccelController()
-    speed = 20.0
-    speed_errors = (4.0, 3.0, 2.0, 1.0, 0.5, TARGET_SPEED_DEADBAND)
-    targets = [controller.get_cruise_target(speed, speed + error) for error in speed_errors]
-    max_accels = [controller.get_max_accel(speed, speed + error) for error in speed_errors]
-    accels = [get_cruise_accel(False, target, speed, 0.0, 0.0, _fake_cp(), 10.0, 0.0, True, max_accel)
-              for target, max_accel in zip(targets, max_accels, strict=True)]
-
-    assert np.isclose(accels[0], controller.get_max_accel(speed))
-    assert accels[1] < controller.get_max_accel(speed)
-    assert all(current > following for current, following in zip(accels, accels[1:], strict=False))
-    assert accels[-1] == 0.0
-
-  def test_disabled_leaves_stock_limit_active(self):
-    planner = _bare_planner()
-    for e2e in (False, True):
-      assert planner.get_max_accel_override(5.0, 30.0, e2e=e2e) is None
-      assert planner.get_cruise_target_override(20.0, 20.5, e2e=e2e) == 20.5
-      assert planner.accel_controller_active is False
-
-  def test_e2e_uses_enabled_profile(self):
-    self.params.put_bool("AccelPersonalityEnabled", True, block=True)
-    planner = _bare_planner()
-    assert planner.get_max_accel_override(5.0, 30.0, e2e=True) == MAX_ACCEL_PROFILES[AccelProfile.normal][2]
-    assert planner.accel_controller_active is True
-
-  def test_enabled_acc_uses_python_native_telemetry_types(self):
-    self.params.put_bool("AccelPersonalityEnabled", True, block=True)
-    self.params.put("AccelPersonality", AccelProfile.sport, block=True)
-    planner = _bare_planner()
-    assert planner.get_max_accel_override(5.0, 30.0, e2e=False) == MAX_ACCEL_PROFILES[AccelProfile.sport][2]
-    assert type(planner.accel_controller_active) is bool
-    assert type(planner.accel_controller.is_enabled()) is bool
-    assert type(planner.accel_controller.profile) is int
-
-  def test_normal_profile_uses_tuned_limit(self):
-    self.params.put_bool("AccelPersonalityEnabled", True, block=True)
-    self.params.put("AccelPersonality", AccelProfile.normal, block=True)
-    planner = _bare_planner()
-    assert planner.get_max_accel_override(5.0, 30.0, e2e=False) == MAX_ACCEL_PROFILES[AccelProfile.normal][2]
-    assert planner.accel_controller_active is True
-
-  def test_planner_applies_cruise_settling_only_when_safe(self):
-    from openpilot.sunnypilot.selfdrive.controls.lib.longitudinal_planner import LongitudinalPlanSource
-
-    self.params.put_bool("AccelPersonalityEnabled", True, block=True)
-    planner = _bare_planner()
-    expected_limit = planner.accel_controller.get_max_accel(20.0, 20.5)
-    expected_decel_target = planner.accel_controller.get_cruise_target(20.5, 20.0)
-    assert planner.get_cruise_target_override(20.0, 20.5, e2e=False) == 20.5
-    assert np.isclose(planner.get_cruise_target_override(20.5, 20.0, e2e=False), expected_decel_target)
-    assert np.isclose(planner.get_max_accel_override(20.0, 20.5, e2e=False), expected_limit)
-
-    planner.allow_throttle = False
-    assert planner.get_cruise_target_override(20.0, 20.5, e2e=False) == 20.5
-    assert planner.get_max_accel_override(20.0, 20.5, e2e=False) is None
-    assert planner.accel_controller_active is False
-    assert planner.get_cruise_target_override(20.0, 20.5, e2e=True) == 20.5
-    assert np.isclose(planner.get_max_accel_override(20.0, 20.5, e2e=True), expected_limit)
-    assert planner.accel_controller_active is True
-
-    planner.source = LongitudinalPlanSource.sccVision
-    assert planner.get_cruise_target_override(20.0, 20.5, e2e=True) == 20.5
-    assert planner.get_max_accel_override(20.0, 20.5, e2e=True) == planner.accel_controller.get_max_accel(20.0)
-
-
-def _fake_cp():
-  class CP:
-    steerRatio = 15.0
-    wheelbase = 2.7
-
-  return CP()
-
-
-def _bare_planner():
-  from openpilot.sunnypilot.selfdrive.controls.lib.longitudinal_planner import LongitudinalPlannerSP, LongitudinalPlanSource
-
-  planner = LongitudinalPlannerSP.__new__(LongitudinalPlannerSP)
-  planner.accel_controller = AccelController()
-  planner.accel_controller_active = False
-  planner.allow_throttle = True
-  planner.source = LongitudinalPlanSource.cruise
-  return planner

openpilot/sunnypilot/selfdrive/controls/lib/accel_controller/tests/test_accel_controller_closed_loop.py

@@ -1,398 +0,0 @@
-"""
-Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
-
-This file is part of sunnypilot and is licensed under the MIT License.
-See the LICENSE.md file in the root directory for more details.
-"""
-
-from collections.abc import Callable
-from unittest import mock
-
-import numpy as np
-
-from openpilot.common.constants import CV
-from openpilot.common.params import Params
-from openpilot.common.realtime import DT_MDL
-from openpilot.common.test import OpenpilotTestCase
-from openpilot.selfdrive.controls.lib.drive_helpers import should_stop
-from openpilot.selfdrive.controls.lib.longitudinal_planner import A_CRUISE_MAX_BP, J_CRUISE_VALS, get_cruise_accel
-from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import LongitudinalPlanSource, T_IDXS as T_IDXS_MPC
-from openpilot.sunnypilot.selfdrive.controls.lib.accel_controller.accel_controller import (
-  AccelController, AccelProfile, MAX_ACCEL_BREAKPOINTS, MAX_ACCEL_PROFILES, TARGET_SPEED_DEADBAND,
-)
-from openpilot.sunnypilot.selfdrive.test.longitudinal_maneuvers.plant import PRIUS_TSS2_ROUTE_MODEL, PlantSP
-
-
-class CarParams:
-  steerRatio = 15.0
-  wheelbase = 2.7
-
-
-def _set_mpc_acceleration(plant: PlantSP, acceleration: float = 2.0) -> None:
-  def update(_radar_state, **_kwargs):
-    mpc = plant.planner.mpc
-    mpc.source = LongitudinalPlanSource.lead0
-    mpc.v_solution[:] = mpc.x0[1] + acceleration * T_IDXS_MPC
-    mpc.a_solution.fill(acceleration)
-    mpc.j_solution.fill(0.0)
-
-  plant.planner.mpc.update = update
-
-
-def run_profile(profile: int, *, enabled: bool = True, speed: float = 0.0, v_cruise: float = 30.0,
-                v_cruise_fn: Callable[[int], float] | None = None, e2e: bool = False, steps: int = 120):
-  params = Params()
-  params.put_bool("AccelPersonalityEnabled", enabled, block=True)
-  params.put("AccelPersonality", profile, block=True)
-  controller = AccelController()
-
-  accel = 0.0
-  rows = []
-  for frame in range(steps):
-    target_speed = v_cruise if v_cruise_fn is None else v_cruise_fn(frame)
-    use_profile = controller.is_enabled()
-    cruise_target = controller.get_cruise_target(speed, target_speed) if use_profile else target_speed
-    max_accel_override = controller.get_max_accel(speed, target_speed) if use_profile else None
-    accel = get_cruise_accel(e2e, cruise_target, speed, accel, 0.0, CarParams(), DT_MDL, 2.0, True, max_accel_override)
-    speed = max(0.0, speed + accel * DT_MDL)
-    rows.append((speed, accel, should_stop(speed, accel)))
-  return rows
-
-
-def run_vehicle_profile(profile: int, duration: float = 80.0):
-  params = Params()
-  params.put_bool("AccelPersonalityEnabled", True, block=True)
-  params.put("AccelPersonality", profile, block=True)
-
-  plant = PlantSP(speed=0.0, actuator_model=PRIUS_TSS2_ROUTE_MODEL, run_long_control=True)
-  _set_mpc_acceleration(plant)
-  rows = []
-  while plant.current_time < duration:
-    result = plant.step(v_cruise=25.0)
-    rows.append((plant.current_time, result["speed"], result["a_target"], result["actuator_command"], result["acceleration"]))
-  return np.asarray(rows)
-
-
-def run_lead_comfort(*, comfort_enabled: bool, speed: float, distance_lead: float,
-                     lead_speed_fn: Callable[[float], float], duration: float = 12.0):
-  params = Params()
-  params.put_bool("DynamicExperimentalControl", False, block=True)
-  params.put_bool("AccelPersonalityEnabled", True, block=True)
-  params.put("AccelPersonality", AccelProfile.eco, block=True)
-
-  plant = PlantSP(lead_relevancy=True, speed=speed, distance_lead=distance_lead, only_radar=True)
-  plant.v_lead_prev = lead_speed_fn(0.0)
-  planner = plant.planner
-  raw_mpc, raw_cruise, adjusted_cruise, rows = [], [], [], []
-  mpc_failures = 0
-  original_arbitrate = planner.arbitrate_cruise_candidate
-  original_lead_accel = planner.accel_controller.get_lead_accel
-  original_mpc_reset = planner.mpc.reset
-
-  def record_mpc_reset(*args, **kwargs):
-    nonlocal mpc_failures
-    mpc_failures += int(planner.mpc.solution_status != 0)
-    return original_mpc_reset(*args, **kwargs)
-
-  def record_arbitration(sm, gated, ungated, mpc_accel, mpc_source, **kwargs):
-    raw_mpc.append(mpc_accel)
-    return original_arbitrate(sm, gated, ungated, mpc_accel, mpc_source, **kwargs)
-
-  def record_lead_accel(v_ego, d_rel, v_rel, a_lead, a_target, previous_accel, t_follow):
-    raw_cruise.append(a_target)
-    adjusted = original_lead_accel(v_ego, d_rel, v_rel, a_lead, a_target, previous_accel, t_follow) if comfort_enabled else a_target
-    adjusted_cruise.append(adjusted)
-    return adjusted
-
-  with (
-    mock.patch.object(planner.mpc, "reset", side_effect=record_mpc_reset),
-    mock.patch.object(planner, "arbitrate_cruise_candidate", side_effect=record_arbitration),
-    mock.patch.object(planner.accel_controller, "get_lead_accel", side_effect=record_lead_accel),
-  ):
-    while plant.current_time < duration:
-      output = plant.step(v_lead=lead_speed_fn(plant.current_time), v_cruise=30.0)
-      rows.append((
-        output["distance_lead"] - output["distance"], output["actuator_command"], output["a_target"], output["fcw"], planner.mpc.solution_status,
-      ))
-
-  data = np.asarray(rows, dtype=float)
-  commands = data[:, 1]
-  braking_frames = np.flatnonzero(commands < -0.05)
-  return {
-    "min_gap": float(np.min(data[:, 0])),
-    "min_command": float(np.min(commands)),
-    "min_jerk": float(np.min(np.diff(commands) / DT_MDL)),
-    "first_brake_frame": int(braking_frames[0]) if len(braking_frames) else len(commands),
-    "a_targets": data[:, 2],
-    "fcw": bool(np.any(data[:, 3])),
-    "mpc_failures": mpc_failures + int(data[-1, 4] != 0),
-    "raw_mpc": np.asarray(raw_mpc),
-    "raw_cruise": np.asarray(raw_cruise),
-    "adjusted_cruise": np.asarray(adjusted_cruise),
-  }
-
-
-class TestAccelControllerClosedLoop(OpenpilotTestCase):
-  def test_profiles_are_immediate_smooth_and_clearly_distinct(self):
-    traces = {profile: run_vehicle_profile(profile) for profile in (AccelProfile.eco, AccelProfile.normal, AccelProfile.sport)}
-
-    def crossing(trace, speed):
-      return float(trace[np.flatnonzero(trace[:, 1] >= speed)[0], 0])
-
-    time_to_20 = {profile: crossing(trace, 20.0 * CV.MPH_TO_MS) for profile, trace in traces.items()}
-    time_to_50 = {profile: crossing(trace, 50.0 * CV.MPH_TO_MS) for profile, trace in traces.items()}
-    first_motion = {profile: int(np.flatnonzero(trace[:, 1] > 0.01)[0]) for profile, trace in traces.items()}
-
-    self.assertEqual(len(set(first_motion.values())), 1)
-    self.assertTrue(all(trace[0, 2] > 0.0 and trace[1, 3] > 0.0 for trace in traces.values()))
-    self.assertGreaterEqual(time_to_20[AccelProfile.eco] - time_to_20[AccelProfile.normal], 2.0)
-    self.assertGreaterEqual(time_to_20[AccelProfile.normal] - time_to_20[AccelProfile.sport], 2.0)
-    self.assertGreaterEqual(time_to_50[AccelProfile.eco] - time_to_50[AccelProfile.normal], 10.0)
-    self.assertGreaterEqual(time_to_50[AccelProfile.normal] - time_to_50[AccelProfile.sport], 10.0)
-
-    for trace in traces.values():
-      command_jerk = np.abs(np.diff(trace[:, 3])) / DT_MDL
-      self.assertLessEqual(float(np.max(command_jerk)), PRIUS_TSS2_ROUTE_MODEL.command_rate_limit + 1e-9)
-
-      settled = np.flatnonzero(trace[:, 1] >= 25.0 - TARGET_SPEED_DEADBAND - 0.1)
-      self.assertGreater(len(settled), 0)
-      settled_trace = trace[settled[0]:]
-      self.assertGreaterEqual(float(np.min(settled_trace[:, 3])), -0.05)
-      self.assertGreaterEqual(float(np.min(np.diff(settled_trace[:, 1]))), -1e-8)
-      self.assertLessEqual(float(np.max(trace[:, 1])), 25.0 + 1e-9)
-      self.assertLessEqual(25.0 - float(trace[-1, 1]), TARGET_SPEED_DEADBAND + 0.02)
-
-  def test_lead_comfort_brakes_earlier_without_stronger_peak_for_slowing_lead(self):
-    def slowing_lead(t: float) -> float:
-      return float(np.clip(20.0 - 2.5 * max(t - 2.0, 0.0), 15.0, 20.0))
-
-    baseline = run_lead_comfort(comfort_enabled=False, speed=20.0, distance_lead=70.0, lead_speed_fn=slowing_lead)
-    comfort = run_lead_comfort(comfort_enabled=True, speed=20.0, distance_lead=70.0, lead_speed_fn=slowing_lead)
-
-    self.assertFalse(comfort["fcw"])
-    self.assertLessEqual(comfort["mpc_failures"], baseline["mpc_failures"])
-    self.assertGreater(comfort["min_gap"], 0.0)
-    self.assertGreaterEqual(comfort["min_gap"], baseline["min_gap"] - 0.1)
-    self.assertGreaterEqual(comfort["min_command"], baseline["min_command"] - 0.01)
-    self.assertGreaterEqual(comfort["min_jerk"], baseline["min_jerk"] - 0.05)
-    self.assertLessEqual(comfort["first_brake_frame"], baseline["first_brake_frame"])
-    self.assertTrue(np.all(comfort["a_targets"] <= comfort["raw_mpc"] + 1e-9))
-    self.assertTrue(np.all(comfort["adjusted_cruise"] <= comfort["raw_cruise"] + 1e-9))
-    self.assertTrue(np.any(comfort["adjusted_cruise"] < comfort["raw_cruise"] - 1e-3))
-
-  def test_lead_comfort_preserves_stopped_lead_safety(self):
-    def stopped_lead(_t: float) -> float:
-      return 0.0
-
-    baseline = run_lead_comfort(comfort_enabled=False, speed=20.0, distance_lead=90.0, lead_speed_fn=stopped_lead)
-    comfort = run_lead_comfort(comfort_enabled=True, speed=20.0, distance_lead=90.0, lead_speed_fn=stopped_lead)
-
-    self.assertFalse(comfort["fcw"])
-    self.assertLessEqual(comfort["mpc_failures"], baseline["mpc_failures"])
-    self.assertGreater(comfort["min_gap"], 0.0)
-    self.assertGreaterEqual(comfort["min_gap"], baseline["min_gap"] - 0.1)
-    self.assertGreaterEqual(comfort["min_command"], baseline["min_command"] - 0.01)
-    self.assertTrue(np.all(comfort["a_targets"] <= comfort["raw_mpc"] + 1e-9))
-    self.assertTrue(np.all(comfort["adjusted_cruise"] <= comfort["raw_cruise"] + 1e-9))
-
-  def test_blended_positive_model_request_uses_profile_cruise_cap(self):
-    params = Params()
-    params.put_bool("DynamicExperimentalControl", False, block=True)
-    params.put_bool("AccelPersonalityEnabled", True, block=True)
-    params.put("AccelPersonality", AccelProfile.eco, block=True)
-
-    def request_acceleration(_current_time: float, _speed: float, _acceleration: float) -> tuple[float, bool]:
-      return 2.0, False
-
-    plant = PlantSP(speed=15.0, e2e=True, model_action_fn=request_acceleration)
-    _set_mpc_acceleration(plant)
-    results = [plant.step(v_cruise=35.0) for _ in range(20)]
-    settled = results[-1]
-    eco_limit = float(np.interp(settled["published_v_ego"], MAX_ACCEL_BREAKPOINTS, MAX_ACCEL_PROFILES[AccelProfile.eco]))
-
-    self.assertTrue(settled["controller_active"])
-    self.assertEqual(settled["mpc_source"], LongitudinalPlanSource.cruise)
-    self.assertAlmostEqual(settled["a_target"], eco_limit, delta=0.01)
-    self.assertLess(settled["a_target"], settled["model_action"]["desiredAcceleration"])
-
-  def test_blended_profile_does_not_change_model_braking(self):
-    params = Params()
-    params.put_bool("DynamicExperimentalControl", False, block=True)
-    params.put("AccelPersonality", AccelProfile.eco, block=True)
-
-    def request_braking(_current_time: float, _speed: float, _acceleration: float) -> tuple[float, bool]:
-      return -0.8, False
-
-    traces = {}
-    for enabled in (False, True):
-      params.put_bool("AccelPersonalityEnabled", enabled, block=True)
-      plant = PlantSP(speed=20.0, e2e=True, model_action_fn=request_braking)
-      _set_mpc_acceleration(plant)
-      traces[enabled] = [plant.step(v_cruise=30.0) for _ in range(10)]
-
-    self.assertTrue(all(row["mpc_source"] == LongitudinalPlanSource.e2e for row in traces[True]))
-    self.assertTrue(all(row["controller_active"] for row in traces[True]))
-    self.assertTrue(all(not row["controller_active"] for row in traces[False]))
-    for key in ("a_target", "should_stop", "mpc_source"):
-      self.assertEqual([row[key] for row in traces[True]], [row[key] for row in traces[False]])
-
-  def test_profile_does_not_change_model_stop_request(self):
-    params = Params()
-    params.put_bool("DynamicExperimentalControl", False, block=True)
-    params.put("AccelPersonality", AccelProfile.eco, block=True)
-
-    def request_stop(_current_time: float, _speed: float, _acceleration: float) -> tuple[float, bool]:
-      return -0.8, True
-
-    traces = {}
-    for enabled in (False, True):
-      params.put_bool("AccelPersonalityEnabled", enabled, block=True)
-      plant = PlantSP(speed=1.0, e2e=True, model_action_fn=request_stop)
-      _set_mpc_acceleration(plant)
-      traces[enabled] = [plant.step(v_cruise=30.0) for _ in range(10)]
-
-    for key in ("a_target", "should_stop", "mpc_source"):
-      self.assertEqual([row[key] for row in traces[True]], [row[key] for row in traces[False]])
-
-  def test_profile_does_not_change_lead_braking(self):
-    params = Params()
-    params.put_bool("DynamicExperimentalControl", False, block=True)
-    params.put("AccelPersonality", AccelProfile.eco, block=True)
-
-    traces = {}
-    for enabled in (False, True):
-      params.put_bool("AccelPersonalityEnabled", enabled, block=True)
-      plant = PlantSP(speed=20.0)
-      _set_mpc_acceleration(plant, -0.8)
-      traces[enabled] = [plant.step(v_cruise=30.0) for _ in range(10)]
-
-    self.assertTrue(all(row["mpc_source"] == LongitudinalPlanSource.lead0 for row in traces[True]))
-    for key in ("a_target", "should_stop", "mpc_source"):
-      self.assertEqual([row[key] for row in traces[True]], [row[key] for row in traces[False]])
-
-  def test_blended_cruise_settling_reduces_small_corrections_both_directions(self):
-    params = Params()
-    params.put_bool("DynamicExperimentalControl", False, block=True)
-    params.put("AccelPersonality", AccelProfile.normal, block=True)
-
-    def request_acceleration(_current_time: float, _speed: float, _acceleration: float) -> tuple[float, bool]:
-      return 2.0, False
-
-    peak_corrections = {}
-    for enabled in (False, True):
-      params.put_bool("AccelPersonalityEnabled", enabled, block=True)
-      for direction, speed, cruise in (("accelerate", 20.0, 20.5), ("decelerate", 20.5, 20.0)):
-        plant = PlantSP(speed=speed, e2e=True, model_action_fn=request_acceleration)
-        _set_mpc_acceleration(plant)
-        trace = [plant.step(v_cruise=cruise) for _ in range(20)]
-        peak_corrections[enabled, direction] = max(abs(row["a_target"]) for row in trace)
-
-    for direction in ("accelerate", "decelerate"):
-      self.assertLess(peak_corrections[True, direction], peak_corrections[False, direction])
-
-  def test_normal_is_less_aggressive_than_disabled_stock_path(self):
-    stock = run_profile(AccelProfile.normal, enabled=False, speed=4.0, steps=120)
-    normal = run_profile(AccelProfile.normal, speed=4.0, steps=120)
-    self.assertTrue(all(tuned[1] <= original[1] + 1e-12 for tuned, original in zip(normal, stock, strict=True)))
-    self.assertLess(normal[-1][0], stock[-1][0])
-
-  def test_profiles_do_not_change_far_braking(self):
-    for e2e in (False, True):
-      stock = run_profile(AccelProfile.normal, enabled=False, speed=20.0, v_cruise=0.0, e2e=e2e, steps=100)
-      for profile in (AccelProfile.eco, AccelProfile.normal, AccelProfile.sport):
-        self.assertEqual(run_profile(profile, speed=20.0, v_cruise=0.0, e2e=e2e, steps=100), stock)
-
-  def test_blended_launch_respects_profiles(self):
-    traces = {
-      profile: run_profile(profile, v_cruise=8.0, e2e=True, steps=180)
-      for profile in (AccelProfile.eco, AccelProfile.normal, AccelProfile.sport)
-    }
-    time_to_five = {
-      profile: next(frame for frame, row in enumerate(rows) if row[0] >= 5.0) * DT_MDL
-      for profile, rows in traces.items()
-    }
-
-    self.assertLess(time_to_five[AccelProfile.sport], time_to_five[AccelProfile.normal])
-    self.assertLess(time_to_five[AccelProfile.normal], time_to_five[AccelProfile.eco])
-
-  def test_launch_ordering_without_departure_delay(self):
-    stock = run_profile(AccelProfile.normal, enabled=False, v_cruise=8.0, steps=160)
-    traces = {
-      profile: run_profile(profile, v_cruise=8.0, steps=160)
-      for profile in (AccelProfile.eco, AccelProfile.normal, AccelProfile.sport)
-    }
-    first_motion = {
-      profile: next(frame for frame, row in enumerate(rows) if row[0] > 0.01)
-      for profile, rows in traces.items()
-    }
-    time_to_five = {
-      profile: next(frame for frame, row in enumerate(rows) if row[0] >= 5.0) * DT_MDL
-      for profile, rows in traces.items()
-    }
-    stock_first_motion = next(frame for frame, row in enumerate(stock) if row[0] > 0.01)
-    stock_time_to_two = next(frame for frame, row in enumerate(stock) if row[0] >= 2.0) * DT_MDL
-    stock_time_to_three = next(frame for frame, row in enumerate(stock) if row[0] >= 3.0) * DT_MDL
-
-    self.assertEqual(len(set(first_motion.values())), 1)
-    self.assertTrue(all(frame == stock_first_motion for frame in first_motion.values()))
-    self.assertLess(stock_time_to_two, next(frame for frame, row in enumerate(traces[AccelProfile.eco]) if row[0] >= 2.0) * DT_MDL)
-    self.assertLess(stock_time_to_three, next(frame for frame, row in enumerate(traces[AccelProfile.eco]) if row[0] >= 3.0) * DT_MDL)
-    self.assertGreaterEqual(time_to_five[AccelProfile.eco] - time_to_five[AccelProfile.normal], 0.5)
-    self.assertGreaterEqual(time_to_five[AccelProfile.normal] - time_to_five[AccelProfile.sport], 0.5)
-
-  def test_road_speed_catchup_stays_useful(self):
-    traces = {
-      profile: run_profile(profile, speed=20.0, v_cruise=30.0, steps=100)
-      for profile in (AccelProfile.eco, AccelProfile.normal, AccelProfile.sport)
-    }
-    gains = {profile: rows[-1][0] - 20.0 for profile, rows in traces.items()}
-    self.assertGreaterEqual(gains[AccelProfile.normal], 1.25 * gains[AccelProfile.eco])
-    self.assertGreaterEqual(gains[AccelProfile.sport], 1.25 * gains[AccelProfile.normal])
-
-  def test_catchup_settles_inside_deadband_without_oscillation(self):
-    target_speed = 24.0
-    rows = run_profile(AccelProfile.normal, speed=20.0, v_cruise=target_speed, steps=800)
-    final_deficit = target_speed - rows[-1][0]
-
-    self.assertGreaterEqual(final_deficit, -1e-9)
-    self.assertLessEqual(final_deficit, TARGET_SPEED_DEADBAND + 0.01)
-    self.assertTrue(all(row[1] >= -1e-12 for row in rows))
-    self.assertTrue(all(current[0] <= following[0] for current, following in zip(rows, rows[1:], strict=False)))
-
-  def test_smaller_target_gap_uses_stock_downward_jerk(self):
-    def target_speed(frame: int) -> float:
-      return 24.0 if frame < 40 else 21.5
-
-    rows = run_profile(AccelProfile.normal, speed=20.0, v_cruise_fn=target_speed, steps=80)
-    command_drop = rows[39][1] - rows[40][1]
-
-    self.assertLessEqual(command_drop, max(J_CRUISE_VALS) * DT_MDL + 1e-12)
-    self.assertTrue(all(row[1] >= -1e-12 for row in rows[40:]))
-
-  def test_full_catchup_trace_respects_stock_jerk(self):
-    for profile in (AccelProfile.eco, AccelProfile.normal, AccelProfile.sport):
-      rows = run_profile(profile, v_cruise=30.0, steps=300)
-      previous_speed = 0.0
-      previous_accel = 0.0
-      for speed, accel, _should_stop in rows:
-        jerk_step = float(np.interp(previous_speed, A_CRUISE_MAX_BP, J_CRUISE_VALS)) * DT_MDL
-        self.assertLessEqual(abs(accel - previous_accel), jerk_step + 1e-12)
-        previous_speed = speed
-        previous_accel = accel
-
-  def test_stop_release_frame_is_profile_independent(self):
-    def target_speed(frame: int) -> float:
-      return 0.0 if frame < 20 else 8.0
-
-    traces = {
-      profile: run_profile(profile, v_cruise_fn=target_speed, steps=80)
-      for profile in (AccelProfile.eco, AccelProfile.normal, AccelProfile.sport)
-    }
-    release_frames = {
-      profile: next(frame for frame, row in enumerate(rows) if frame >= 20 and not row[2])
-      for profile, rows in traces.items()
-    }
-    stock = run_profile(AccelProfile.normal, enabled=False, v_cruise_fn=target_speed, steps=80)
-    stock_release_frame = next(frame for frame, row in enumerate(stock) if frame >= 20 and not row[2])
-    self.assertEqual(len(set(release_frames.values())), 1)
-    self.assertTrue(all(frame == stock_release_frame for frame in release_frames.values()))

openpilot/sunnypilot/selfdrive/controls/lib/dec/constants.py

@@ -0,0 +1,17 @@
+class WMACConstants:
+  # Lead detection parameters
+  LEAD_WINDOW_SIZE = 6  # Stable detection window
+  LEAD_PROB = 0.45  # Balanced threshold for lead detection
+
+  # Slow down detection parameters
+  SLOW_DOWN_WINDOW_SIZE = 5  # Responsive but stable
+  SLOW_DOWN_PROB = 0.3  # Balanced threshold for slow down scenarios
+
+  # Optimized slow down distance curve - smooth and progressive
+  SLOW_DOWN_BP = [0., 10., 20., 30., 40., 50., 55., 60.]
+  SLOW_DOWN_DIST = [32., 46., 64., 86., 108., 130., 145., 165.]
+
+  # Slowness detection parameters
+  SLOWNESS_WINDOW_SIZE = 10  # Stable slowness detection
+  SLOWNESS_PROB = 0.55  # Clear threshold for slowness
+  SLOWNESS_CRUISE_OFFSET = 1.025  # Conservative cruise speed offset

openpilot/sunnypilot/selfdrive/controls/lib/dec/dec.py

@@ -4,118 +4,192 @@ Copyright (c) 2021-, rav4kumar, sunnypilot, and a number of other contributors.
 This file is part of sunnypilot and is licensed under the MIT License.
 See the LICENSE.md file in the root directory for more details.
 """
-from dataclasses import dataclass
-from typing import Literal
-
-import numpy as np
+# Version = 2025-6-30
 
 from openpilot.cereal import messaging
 from opendbc.car import structs
+from numpy import interp
 from openpilot.common.params import Params
-from openpilot.selfdrive.modeld.constants import ModelConstants
+from openpilot.common.realtime import DT_MDL
+from openpilot.sunnypilot.selfdrive.controls.lib.dec.constants import WMACConstants
+from typing import Literal
 
+# d-e2e, from modeldata.h
+TRAJECTORY_SIZE = 33
+SET_MODE_TIMEOUT = 15
+
+# Define the valid mode types
 ModeType = Literal['acc', 'blended']
 
-_DECEL_LOOKAHEAD_MIN_T = 1.0
-_DECEL_LOOKAHEAD_MAX_T = 6.0
-_T_IDXS = np.array(ModelConstants.T_IDXS)
-_DECEL_IDX = np.where((_T_IDXS >= _DECEL_LOOKAHEAD_MIN_T) & (_T_IDXS <= _DECEL_LOOKAHEAD_MAX_T))[0]
-_DECEL_INV_T = 1.0 / _T_IDXS[_DECEL_IDX]
 
-DECEL_INTENT_A_HINT = 0.35
-DECEL_INTENT_A_FULL = 1.30
-DECEL_INTENT_TRIGGER = 0.5
-DECEL_INTENT_CURVE_OVERRIDE = 0.9
+class SmoothKalmanFilter:
+  """Enhanced Kalman filter with smoothing for stable decision making."""
 
-CURVE_Y_MAX = 5.0
+  def __init__(self, initial_value=0, measurement_noise=0.1, process_noise=0.01,
+               alpha=1.0, smoothing_factor=0.85):
+    self.x = initial_value
+    self.P = 1.0
+    self.R = measurement_noise
+    self.Q = process_noise
+    self.alpha = alpha
+    self.smoothing_factor = smoothing_factor
+    self.initialized = False
+    self.history = []
+    self.max_history = 10
+    self.confidence = 0.0
 
-LEAD_FUTURE_PROB_VANISH = 0.35
+  def add_data(self, measurement):
+    if len(self.history) >= self.max_history:
+      self.history.pop(0)
+    self.history.append(measurement)
 
-MODEL_DROP_TRUST_FULL = 5.0
-MODEL_DROP_TRUST_NONE = 30.0
-MODEL_TRUST_MIN = 0.5
+    if not self.initialized:
+      self.x = measurement
+      self.initialized = True
+      self.confidence = 0.1
+      return
 
-CREEP_SPEED_ENTER = 2.0
-CREEP_SPEED_EXIT = 3.0
+    self.P = self.alpha * self.P + self.Q
 
-ENTER_FRAMES = 3
-EXIT_FRAMES = 16
-MIN_BLENDED_FRAMES = 20
+    K = self.P / (self.P + self.R)
+    effective_K = K * (1.0 - self.smoothing_factor) + self.smoothing_factor * 0.1
 
-PARAM_READ_FRAMES = 5
+    innovation = measurement - self.x
+    self.x = self.x + effective_K * innovation
+    self.P = (1 - effective_K) * self.P
 
-
-@dataclass
-class DecSignals:
-  decel_intent: float = 0.0
-  curve_detected: bool = False
-  model_trust: float = 1.0
-  creeping: bool = False
-
-
-def should_blend(s: DecSignals) -> bool:
-  degraded = s.model_trust < MODEL_TRUST_MIN
-  curve_gate = s.decel_intent >= DECEL_INTENT_CURVE_OVERRIDE or not s.curve_detected
-  slowdown_detected = not degraded and s.decel_intent >= DECEL_INTENT_TRIGGER and curve_gate
-  return slowdown_detected or s.creeping
-
-
-class ModeHysteresis:
-  def __init__(self):
-    self.mode: ModeType = 'acc'
-    self.above = 0
-    self.below = 0
-    self.blended_frames = 0
-
-  def update(self, want_blended: bool, override: bool, veto: bool) -> ModeType:
-    self.above = self.above + 1 if want_blended else 0
-    self.below = 0 if want_blended else self.below + 1
-
-    if override:
-      self.mode, self.blended_frames = 'blended', 0
-    elif veto:
-      self.mode = 'acc'
-    elif self.mode == 'acc':
-      if self.above >= ENTER_FRAMES:
-        self.mode, self.blended_frames = 'blended', 0
+    if abs(innovation) < 0.1:
+      self.confidence = min(1.0, self.confidence + 0.05)
     else:
-      self.blended_frames += 1
-      if self.blended_frames >= MIN_BLENDED_FRAMES and self.below >= EXIT_FRAMES:
-        self.mode = 'acc'
-    return self.mode
+      self.confidence = max(0.1, self.confidence - 0.02)
 
-  def reset(self) -> None:
-    self.mode = 'acc'
-    self.above = 0
-    self.below = 0
-    self.blended_frames = 0
+  def get_value(self):
+    return self.x if self.initialized else None
+
+  def get_confidence(self):
+    return self.confidence
+
+  def reset_data(self):
+    self.initialized = False
+    self.history = []
+    self.confidence = 0.0
+
+
+class ModeTransitionManager:
+  """Manages smooth transitions between driving modes with hysteresis."""
+
+  def __init__(self):
+    self.current_mode: ModeType = 'acc'
+    self.mode_confidence = {'acc': 1.0, 'blended': 0.0}
+    self.transition_timeout = 0
+    self.min_mode_duration = 10
+    self.mode_duration = 0
+    self.emergency_override = False
+
+  def request_mode(self, mode: ModeType, confidence: float = 1.0, emergency: bool = False):
+    # Emergency override for critical situations (stops, collisions)
+    if emergency:
+      self.emergency_override = True
+      self.current_mode = mode
+      self.transition_timeout = SET_MODE_TIMEOUT
+      self.mode_duration = 0
+      return
+
+    self.mode_confidence[mode] = min(1.0, self.mode_confidence[mode] + 0.1 * confidence)
+    for m in self.mode_confidence:
+      if m != mode:
+        self.mode_confidence[m] = max(0.0, self.mode_confidence[m] - 0.05)
+
+    # Require minimum duration in current mode (unless emergency)
+    if self.mode_duration < self.min_mode_duration and not self.emergency_override:
+      return
+
+    # Hysteresis: higher threshold for mode changes
+    confidence_threshold = 0.6 if mode != self.current_mode else 0.3  # Lower threshold for faster response
+
+    if self.mode_confidence[mode] > confidence_threshold:
+      if mode != self.current_mode and self.transition_timeout == 0:
+        self.transition_timeout = SET_MODE_TIMEOUT
+        self.current_mode = mode
+        self.mode_duration = 0
+
+  def update(self):
+    if self.transition_timeout > 0:
+      self.transition_timeout -= 1
+    self.mode_duration += 1
+
+    # Reset emergency override after some time
+    if self.emergency_override and self.mode_duration > 20:
+      self.emergency_override = False
+
+    # Gradual confidence decay
+    for mode in self.mode_confidence:
+      self.mode_confidence[mode] *= 0.98
+
+  def get_mode(self) -> ModeType:
+    return self.current_mode
 
 
 class DynamicExperimentalController:
   def __init__(self, CP: structs.CarParams, mpc, params=None):
+    self._CP = CP
     self._mpc = mpc
     self._params = params or Params()
     self._enabled: bool = self._params.get_bool("DynamicExperimentalControl")
     self._active: bool = False
     self._frame: int = 0
+    self._urgency = 0.0
 
-    self._hysteresis = ModeHysteresis()
-    self._creeping = False
+    self._mode_manager = ModeTransitionManager()
 
-    self.signals = DecSignals()
-    self.want_blended = False
-    self.lead_veto = False
+    # Smooth filters for stable decision making with faster response for critical scenarios
+    self._lead_filter = SmoothKalmanFilter(
+      measurement_noise=0.15,
+      process_noise=0.05,
+      alpha=1.02,
+      smoothing_factor=0.8
+    )
 
-  def _update_creeping(self, v_ego: float) -> bool:
-    self._creeping = v_ego < CREEP_SPEED_EXIT if self._creeping else v_ego <= CREEP_SPEED_ENTER
-    return self._creeping
+    self._slow_down_filter = SmoothKalmanFilter(
+      measurement_noise=0.1,
+      process_noise=0.1,
+      alpha=1.05,
+      smoothing_factor=0.7
+    )
+
+    self._slowness_filter = SmoothKalmanFilter(
+      measurement_noise=0.1,
+      process_noise=0.06,
+      alpha=1.015,
+      smoothing_factor=0.92
+    )
+
+    self._mpc_fcw_filter = SmoothKalmanFilter(
+      measurement_noise=0.2,
+      process_noise=0.1,
+      alpha=1.1,
+      smoothing_factor=0.5
+    )
+    self._has_lead_filtered = False
+    self._has_slow_down = False
+    self._has_slowness = False
+    self._has_mpc_fcw = False
+    self._v_ego_kph = 0.0
+    self._v_cruise_kph = 0.0
+    self._has_standstill = False
+    self._mpc_fcw_crash_cnt = 0
+    self._standstill_count = 0
+    # debug
+    self._endpoint_x = float('inf')
+    self._expected_distance = 0.0
+    self._trajectory_valid = False
 
   def _read_params(self) -> None:
-    if self._frame % PARAM_READ_FRAMES == 0:
+    if self._frame % int(1. / DT_MDL) == 0:
       self._enabled = self._params.get_bool("DynamicExperimentalControl")
 
   def mode(self) -> str:
-    return self._hysteresis.mode
+    return self._mode_manager.get_mode()
 
   def enabled(self) -> bool:
     return self._enabled
@@ -123,61 +197,192 @@ class DynamicExperimentalController:
   def active(self) -> bool:
     return self._active
 
-  @staticmethod
-  def _decel_intent(md) -> float:
-    v = np.asarray(md.velocity.x)
-    if len(v) != len(_T_IDXS):
-      return 0.0
-    a_req = float(np.min((v[_DECEL_IDX] - v[0]) * _DECEL_INV_T))
-    return float(np.interp(-a_req, [DECEL_INTENT_A_HINT, DECEL_INTENT_A_FULL], [0.0, 1.0]))
+  def set_mpc_fcw_crash_cnt(self) -> None:
+    """Set MPC FCW crash count"""
+    self._mpc_fcw_crash_cnt = self._mpc.crash_cnt
 
-  @staticmethod
-  def _curve_detected(md) -> bool:
-    y = md.position.y
-    if len(y) < 1:
-      return False
-    return abs(y[-1]) >= CURVE_Y_MAX
+  def _update_calculations(self, sm: messaging.SubMaster) -> None:
+    car_state = sm['carState']
+    lead_one = sm['radarState'].leadOne
+    md = sm['modelV2']
 
-  @staticmethod
-  def _model_trust(md) -> float:
-    if len(md.velocity.x) != len(_T_IDXS):
-      return 0.0
-    return float(np.interp(md.frameDropPerc, [MODEL_DROP_TRUST_FULL, MODEL_DROP_TRUST_NONE], [1.0, 0.0]))
+    self._v_ego_kph = car_state.vEgo * 3.6
+    self._v_cruise_kph = car_state.vCruise
+    self._has_standstill = car_state.standstill
 
-  @staticmethod
-  def _lead_veto(radar_state, md) -> bool:
-    lead_one, lead_two = radar_state.leadOne, radar_state.leadTwo
-    lead_now = lead_one.present or lead_two.present
-    probs = md.leadsV3
-    future = min(probs[1].prob, probs[2].prob) if len(probs) >= 3 else 1.0
-    return bool(lead_now and future > LEAD_FUTURE_PROB_VANISH)
+    # standstill detection
+    if self._has_standstill:
+      self._standstill_count = min(20, self._standstill_count + 1)
+    else:
+      self._standstill_count = max(0, self._standstill_count - 1)
+
+    # Lead detection
+    self._lead_filter.add_data(float(lead_one.present))
+    lead_value = self._lead_filter.get_value() or 0.0
+    self._has_lead_filtered = lead_value > WMACConstants.LEAD_PROB
+
+    # MPC FCW detection
+    fcw_filtered_value = self._mpc_fcw_filter.get_value() or 0.0
+    self._mpc_fcw_filter.add_data(float(self._mpc_fcw_crash_cnt > 0))
+    self._has_mpc_fcw = fcw_filtered_value > 0.5
+
+    # Slow down detection
+    self._calculate_slow_down(md)
+
+    # Slowness detection
+    if not (self._standstill_count > 5) and not self._has_slow_down:
+      current_slowness = float(self._v_ego_kph <= (self._v_cruise_kph * WMACConstants.SLOWNESS_CRUISE_OFFSET))
+      self._slowness_filter.add_data(current_slowness)
+      slowness_value = self._slowness_filter.get_value() or 0.0
+
+      # Hysteresis for slowness
+      threshold = WMACConstants.SLOWNESS_PROB * (0.8 if self._has_slowness else 1.1)
+      self._has_slowness = slowness_value > threshold
+
+  def _calculate_slow_down(self, md):
+    """Calculate urgency based on trajectory endpoint vs expected distance."""
+
+    # Reset to safe defaults
+    urgency = 0.0
+    self._endpoint_x = float('inf')
+    self._trajectory_valid = False
+
+    #Require exact trajectory size
+    position_valid = len(md.position.x) == TRAJECTORY_SIZE
+    orientation_valid = len(md.orientation.x) == TRAJECTORY_SIZE
+
+    if not (position_valid and orientation_valid):
+      # Invalid trajectory - this itself might indicate a stop scenario
+      # Apply moderate urgency for incomplete trajectories at speed
+      if self._v_ego_kph > 20.0:
+        urgency = 0.3
+
+      self._slow_down_filter.add_data(urgency)
+      urgency_filtered = self._slow_down_filter.get_value() or 0.0
+      self._has_slow_down = urgency_filtered > WMACConstants.SLOW_DOWN_PROB
+      self._urgency = urgency_filtered
+      return
+
+    # We have a valid full trajectory
+    self._trajectory_valid = True
+
+    # Use the exact endpoint (33rd point, index 32)
+    endpoint_x = md.position.x[TRAJECTORY_SIZE - 1]
+    self._endpoint_x = endpoint_x
+
+    # Get expected distance based on current speed using tuned constants
+    expected_distance = interp(self._v_ego_kph,
+                               WMACConstants.SLOW_DOWN_BP,
+                               WMACConstants.SLOW_DOWN_DIST)
+    self._expected_distance = expected_distance
+
+    # Calculate urgency based on trajectory shortage
+    if endpoint_x < expected_distance:
+      shortage = expected_distance - endpoint_x
+      shortage_ratio = shortage / expected_distance
+
+      # Base urgency on shortage ratio
+      urgency = min(1.0, shortage_ratio * 2.0)
+
+      # Increase urgency for very short trajectories (imminent stops)
+      critical_distance = expected_distance * 0.3
+      if endpoint_x < critical_distance:
+        urgency = min(1.0, urgency * 2.0)
+
+      # Speed-based urgency adjustment
+      if self._v_ego_kph > 25.0:
+        speed_factor = 1.0 + (self._v_ego_kph - 25.0) / 80.0
+        urgency = min(1.0, urgency * speed_factor)
+
+    # Apply filtering but with less smoothing for stops
+    self._slow_down_filter.add_data(urgency)
+    urgency_filtered = self._slow_down_filter.get_value() or 0.0
+
+    # Update state with lower threshold for better stop detection
+    self._has_slow_down = urgency_filtered > (WMACConstants.SLOW_DOWN_PROB * 0.8)
+    self._urgency = urgency_filtered
+
+  def _radarless_mode(self) -> None:
+    """Radarless mode decision logic with emergency handling."""
+
+    # EMERGENCY: MPC FCW - immediate blended mode
+    if self._has_mpc_fcw:
+      self._mode_manager.request_mode('blended', confidence=1.0, emergency=True)
+      return
+
+    # Standstill: use blended
+    if self._standstill_count > 3:
+      self._mode_manager.request_mode('blended', confidence=0.9)
+      return
+
+    # Slow down scenarios: emergency for high urgency, normal for lower urgency
+    if self._has_slow_down:
+      if self._urgency > 0.7:
+        # Emergency: immediate blended mode for high urgency stops
+        self._mode_manager.request_mode('blended', confidence=1.0, emergency=True)
+      else:
+        # Normal: blended with urgency-based confidence
+        confidence = min(1.0, self._urgency * 1.5)
+        self._mode_manager.request_mode('blended', confidence=confidence)
+      return
+
+    # Driving slow: use ACC (but not if actively slowing down)
+    if self._has_slowness and not self._has_slow_down:
+      self._mode_manager.request_mode('acc', confidence=0.8)
+      return
+
+    # Default: ACC
+    self._mode_manager.request_mode('acc', confidence=0.7)
+
+  def _radar_mode(self) -> None:
+    """Radar mode with emergency handling."""
+
+    # EMERGENCY: MPC FCW - immediate blended mode
+    if self._has_mpc_fcw:
+      self._mode_manager.request_mode('blended', confidence=1.0, emergency=True)
+      return
+
+    # If lead detected and not in standstill: always use ACC
+    if self._has_lead_filtered and not (self._standstill_count > 3):
+      self._mode_manager.request_mode('acc', confidence=1.0)
+      return
+
+    # Slow down scenarios: emergency for high urgency, normal for lower urgency
+    if self._has_slow_down:
+      if self._urgency > 0.7:
+        # Emergency: immediate blended mode for high urgency stops
+        self._mode_manager.request_mode('blended', confidence=1.0, emergency=True)
+      else:
+        # Normal: blended with urgency-based confidence
+        confidence = min(1.0, self._urgency * 1.3)
+        self._mode_manager.request_mode('blended', confidence=confidence)
+      return
+
+    # Standstill: use blended
+    if self._standstill_count > 3:
+      self._mode_manager.request_mode('blended', confidence=0.9)
+      return
+
+    # Driving slow: use ACC (but not if actively slowing down)
+    if self._has_slowness and not self._has_slow_down:
+      self._mode_manager.request_mode('acc', confidence=0.8)
+      return
+
+    # Default: ACC
+    self._mode_manager.request_mode('acc', confidence=0.7)
 
   def update(self, sm: messaging.SubMaster) -> None:
     self._read_params()
 
-    car_state = sm['carState']
-    md = sm['modelV2']
-    radar_state = sm['radarState']
+    self.set_mpc_fcw_crash_cnt()
 
-    is_creeping = self._update_creeping(car_state.vEgo)
-    self.lead_veto = self._lead_veto(radar_state, md)
+    self._update_calculations(sm)
 
-    self.signals = DecSignals(
-      decel_intent=self._decel_intent(md),
-      curve_detected=self._curve_detected(md),
-      model_trust=self._model_trust(md),
-      creeping=is_creeping,
-    )
-    self.want_blended = should_blend(self.signals)
-
-    crash_override = self._mpc.crash_cnt >= 1
-    hard_brake_override = bool(md.meta.hardBrakePredicted)
-    override = (crash_override or hard_brake_override) and not self.lead_veto
-
-    if self._enabled:
-      self._hysteresis.update(self.want_blended, override, self.lead_veto)
+    if self._CP.radarUnavailable:
+      self._radarless_mode()
     else:
-      self._hysteresis.reset()
+      self._radar_mode()
 
+    self._mode_manager.update()
     self._active = sm['selfdriveState'].experimentalMode and self._enabled
     self._frame += 1

openpilot/sunnypilot/selfdrive/controls/lib/dec/tests/test_dynamic_controller.py

@@ -1,295 +1,91 @@
-import numpy as np
-
-from openpilot.cereal import messaging
-from opendbc.car import structs
 from openpilot.common.test import OpenpilotTestCase
-from openpilot.selfdrive.modeld.constants import ModelConstants
-from openpilot.sunnypilot.selfdrive.controls.lib.dec.dec import (
-  DecSignals,
-  DynamicExperimentalController,
-  ModeHysteresis,
-  should_blend,
-  ENTER_FRAMES,
-  MIN_BLENDED_FRAMES,
-)
+from openpilot.sunnypilot.selfdrive.controls.lib.dec.dec import DynamicExperimentalController
 
-T_IDXS = np.array(ModelConstants.T_IDXS)
+class MockLeadOne:
+  def __init__(self, present=0.0):
+    self.present = present
 
+class MockRadarState:
+  def __init__(self, present=0.0):
+    self.leadOne = MockLeadOne(present=present)
+
+class MockCarState:
+  def __init__(self, vEgo=0.0, vCruise=0.0, standstill=False):
+    self.vEgo = vEgo
+    self.vCruise = vCruise
+    self.standstill = standstill
+
+class MockModelData:
+  def __init__(self, valid=True):
+    size = 33 if valid else 10  # incomplete if invalid
+    self.position = type("Pos", (), {"x": [0.0] * size})()
+    self.orientation = type("Ori", (), {"x": [0.0] * size})()
+
+class MockSelfDriveState:
+  def __init__(self, experimentalMode=False):
+    self.experimentalMode = experimentalMode
 
 class MockParams:
-  def __init__(self, enabled=True):
-    self._enabled = enabled
-
   def get_bool(self, name):
-    return self._enabled
+    return True
 
-
-class MockMpc:
-  def __init__(self, crash_cnt=0):
-    self.crash_cnt = crash_cnt
-
-
-def flat_velocity(v):
-  return [float(v)] * len(T_IDXS)
-
-
-def decel_velocity(v0, a):
-  return [float(max(0.0, v0 + a * t)) for t in T_IDXS]
-
-
-def make_car_state(v_ego=10.0, v_cruise=20.0):
-  msg = messaging.new_message('carState')
-  msg.carState.vEgo = v_ego
-  msg.carState.vCruise = v_cruise
-  return msg.carState.as_reader()
-
-
-def make_selfdrive_state(experimental_mode=True):
-  msg = messaging.new_message('selfdriveState')
-  msg.selfdriveState.experimentalMode = experimental_mode
-  return msg.selfdriveState.as_reader()
-
-
-def make_radar_state(lead_present=False, lead_radar=False, lead_two_present=False):
-  msg = messaging.new_message('radarState')
-  msg.radarState.leadOne.present = lead_present
-  msg.radarState.leadOne.radar = lead_radar
-  msg.radarState.leadTwo.present = lead_two_present
-  return msg.radarState.as_reader()
-
-
-def make_model_v2(velocity=None, position_y=None, hard_brake=False, lead_probs=None, frame_drop_perc=0.0):
-  msg = messaging.new_message('modelV2')
-  msg.modelV2.velocity.x = velocity if velocity is not None else flat_velocity(0.0)
-  msg.modelV2.position.y = position_y if position_y is not None else [0.0] * len(T_IDXS)
-  msg.modelV2.frameDropPerc = frame_drop_perc
-  msg.modelV2.meta.hardBrakePredicted = hard_brake
-  if lead_probs is not None:
-    msg.modelV2.init('leadsV3', 3)
-    for i, (prob, prob_time) in enumerate(zip(lead_probs, (0.0, 2.0, 4.0), strict=True)):
-      msg.modelV2.leadsV3[i].prob = prob
-      msg.modelV2.leadsV3[i].probTime = prob_time
-  return msg.modelV2.as_reader()
-
-
-def make_sm(v_ego=10.0, v_cruise=20.0, velocity=None, position_y=None, hard_brake=False,
-            lead_present=False, lead_radar=False, lead_two_present=False, lead_probs=None,
-            frame_drop_perc=0.0, experimental_mode=True):
-  return {
-    'carState': make_car_state(v_ego, v_cruise),
-    'radarState': make_radar_state(lead_present, lead_radar, lead_two_present),
-    'modelV2': make_model_v2(velocity, position_y, hard_brake, lead_probs, frame_drop_perc),
-    'selfdriveState': make_selfdrive_state(experimental_mode),
+def default_sm():
+  sm = {
+    'carState': MockCarState(vEgo=10.0, vCruise=20.0),
+    'radarState': MockRadarState(present=1.0),
+    'modelV2': MockModelData(valid=True),
+    'selfdriveState': MockSelfDriveState(experimentalMode=True),
   }
+  return sm
 
+def mock_cp():
+  class CP:
+    radarUnavailable = False
+  return CP()
 
-def make_controller(cp=None, mpc=None, enabled=True):
-  return DynamicExperimentalController(cp or structs.CarParams(), mpc or MockMpc(), params=MockParams(enabled))
+def mock_mpc():
+  class MPC:
+    crash_cnt = 0
+  return MPC()
 
+# Fake Kalman Filter that always returns a given value
+class FakeKalman:
+  def __init__(self, value=1.0):
+    self.value = value
+  def add_data(self, v): pass
+  def get_value(self): return self.value
+  def get_confidence(self): return 1.0
+  def reset_data(self): pass
 
 class TestDynamicExperimentalController(OpenpilotTestCase):
-  def test_initial_mode_is_acc(self):
-    controller = make_controller()
+  def test_initial_mode_is_acc(self, mock_cp, mock_mpc):
+    controller = DynamicExperimentalController(mock_cp, mock_mpc, params=MockParams())
     assert controller.mode() == "acc"
 
-  def test_flat_plan_never_blends_at_any_speed(self):
-    for v_ego in (2.5, 5.6, 8.3, 13.9, 22.2, 30.6):
-      controller = make_controller()
-      sm = make_sm(v_ego=v_ego, velocity=flat_velocity(v_ego))
-      for _ in range(100):
-        controller.update(sm)
-      assert controller.mode() == "acc", f"false blend on a flat plan at v_ego={v_ego}"
-
-  def test_highway_slowdown_without_lead_blends(self):
-    v0 = 110 / 3.6
-    a = (70 / 3.6 - v0) / 6.0
-    controller = make_controller()
-    sm = make_sm(v_ego=v0, velocity=decel_velocity(v0, a))
+  def test_standstill_triggers_blended(self, mock_cp, mock_mpc, default_sm):
+    controller = DynamicExperimentalController(mock_cp, mock_mpc, params=MockParams())
+    default_sm['carState'].standstill = True
     for _ in range(10):
-      controller.update(sm)
+      controller.update(default_sm)
     assert controller.mode() == "blended"
 
-  def test_curve_exclusion_prevents_false_blend(self):
-    controller = make_controller()
-    sm = make_sm(v_ego=20.0, velocity=decel_velocity(20.0, -1.0), position_y=[6.0] * len(T_IDXS))
-    for _ in range(30):
-      controller.update(sm)
-    assert controller.mode() == "acc"
-
-  def test_curve_does_not_override_saturated_decel_intent(self):
-    controller = make_controller()
-    sm = make_sm(v_ego=20.0, velocity=decel_velocity(20.0, -2.0), position_y=[6.0] * len(T_IDXS))
-    for _ in range(10):
-      controller.update(sm)
+  def test_emergency_blended_on_fcw(self, mock_cp, mock_mpc, default_sm):
+    controller = DynamicExperimentalController(mock_cp, mock_mpc, params=MockParams())
+    mock_mpc.crash_cnt = 1  # simulate FCW
+    for _ in range(2):
+      controller.update(default_sm)
     assert controller.mode() == "blended"
 
-  def test_any_lead_forces_acc_even_with_strong_model_signal(self):
-    for lead_radar in (True, False):
-      controller = make_controller()
-      sm = make_sm(v_ego=20.0, velocity=decel_velocity(20.0, -2.0),
-                   lead_present=True, lead_radar=lead_radar, lead_probs=[1.0, 1.0, 1.0])
-      for _ in range(60):
-        controller.update(sm)
-        assert controller.mode() == "acc"
+  def test_radarless_slowdown_triggers_blended(self, mock_cp, mock_mpc, default_sm):
+    mock_cp.radarUnavailable = True
+    controller = DynamicExperimentalController(mock_cp, mock_mpc, params=MockParams())
 
-  def test_veto_releases_without_rebuild_lag(self):
-    controller = make_controller()
-    lead_sm = make_sm(v_ego=20.0, velocity=decel_velocity(20.0, -2.0),
-                       lead_present=True, lead_probs=[1.0, 1.0, 1.0])
-    for _ in range(30):
-      controller.update(lead_sm)
-    assert controller.mode() == "acc"
-    assert controller.lead_veto
+    # Force conditions to simulate slowdown
+    controller._slow_down_filter = FakeKalman(value=1.0)  # ty: ignore[invalid-assignment]
+    controller._v_ego_kph = 35.0
+    default_sm['modelV2'] = MockModelData(valid=False)  # Incomplete trajectory
+
+    for _ in range(3):
+      controller.update(default_sm)
 
-    no_lead_sm = make_sm(v_ego=20.0, velocity=decel_velocity(20.0, -2.0), lead_present=False)
-    for _ in range(ENTER_FRAMES + 2):
-      controller.update(no_lead_sm)
-      if controller.mode() == "blended":
-        break
     assert controller.mode() == "blended"
-
-  def test_lead_gone_with_no_underlying_slowdown_stays_acc(self):
-    controller = make_controller()
-    lead_sm = make_sm(v_ego=20.0, velocity=flat_velocity(20.0), lead_present=True, lead_probs=[1.0, 1.0, 1.0])
-    for _ in range(30):
-      controller.update(lead_sm)
-    assert controller.mode() == "acc"
-
-    no_lead_sm = make_sm(v_ego=20.0, velocity=flat_velocity(20.0), lead_present=False)
-    for _ in range(20):
-      controller.update(no_lead_sm)
-    assert controller.mode() == "acc"
-
-  def test_creep_does_not_release_lead_veto(self):
-    controller = make_controller()
-    sm = make_sm(v_ego=1.0, velocity=flat_velocity(1.0), lead_present=True, lead_probs=[1.0, 1.0, 1.0])
-    for _ in range(10):
-      controller.update(sm)
-    assert controller.mode() == "acc"
-    assert controller.lead_veto
-
-  def test_creep_hysteresis_band_without_lead(self):
-    controller = make_controller()
-    controller.update(make_sm(v_ego=1.5, velocity=flat_velocity(1.5)))
-    assert controller.signals.creeping
-
-    controller.update(make_sm(v_ego=2.5, velocity=flat_velocity(2.5)))
-    assert controller.signals.creeping, "a small excursion above CREEP_SPEED_ENTER should not exit creeping"
-
-    controller.update(make_sm(v_ego=5.0, velocity=flat_velocity(5.0)))
-    assert not controller.signals.creeping, "should exit creeping once genuinely above CREEP_SPEED_EXIT"
-
-  def test_crash_cnt_override_inert_while_lead_present(self):
-    mpc = MockMpc(crash_cnt=0)
-    controller = make_controller(mpc=mpc)
-    sm = make_sm(v_ego=20.0, velocity=flat_velocity(20.0), lead_present=True, lead_probs=[1.0, 1.0, 1.0])
-    for _ in range(30):
-      controller.update(sm)
-    assert controller.mode() == "acc"
-
-    mpc.crash_cnt = 1
-    controller.update(sm)
-    assert controller.mode() == "acc"
-
-  def test_crash_cnt_blends_within_one_frame_without_lead(self):
-    mpc = MockMpc(crash_cnt=1)
-    controller = make_controller(mpc=mpc)
-    sm = make_sm(v_ego=20.0, velocity=flat_velocity(20.0), lead_present=False)
-    controller.update(sm)
-    assert controller.mode() == "blended"
-
-  def test_hard_brake_predicted_blends_within_one_frame_without_lead(self):
-    controller = make_controller()
-    sm = make_sm(v_ego=20.0, velocity=flat_velocity(20.0), hard_brake=True, lead_present=False)
-    controller.update(sm)
-    assert controller.mode() == "blended"
-
-  def test_hard_brake_override_inert_while_lead_present(self):
-    controller = make_controller()
-    sm = make_sm(v_ego=20.0, velocity=flat_velocity(20.0), hard_brake=True,
-                 lead_present=True, lead_probs=[1.0, 1.0, 1.0])
-    controller.update(sm)
-    assert controller.mode() == "acc"
-
-  def test_degraded_model_does_not_blend(self):
-    controller = make_controller()
-    sm = make_sm(v_ego=20.0, velocity=decel_velocity(20.0, -3.0), frame_drop_perc=60.0)
-    for _ in range(30):
-      controller.update(sm)
-    assert controller.mode() == "acc"
-
-  def test_short_plan_arrays_do_not_blend(self):
-    controller = make_controller()
-    sm = make_sm(v_ego=20.0, velocity=[20.0] * 5)
-    for _ in range(30):
-      controller.update(sm)
-    assert controller.mode() == "acc"
-
-  def test_disabled_param_holds_acc(self):
-    controller = make_controller(enabled=False)
-    sm = make_sm(v_ego=20.0, velocity=decel_velocity(20.0, -3.0))
-    for _ in range(30):
-      controller.update(sm)
-    assert controller.mode() == "acc"
-
-
-class TestModeHysteresis(OpenpilotTestCase):
-  def test_entry_requires_enter_frames(self):
-    h = ModeHysteresis()
-    for _ in range(ENTER_FRAMES - 1):
-      assert h.update(want_blended=True, override=False, veto=False) == "acc"
-    assert h.update(want_blended=True, override=False, veto=False) == "blended"
-
-  def test_override_beats_veto(self):
-    h = ModeHysteresis()
-    assert h.update(want_blended=False, override=True, veto=True) == "blended"
-
-  def test_veto_forces_acc_even_when_reason_active(self):
-    h = ModeHysteresis()
-    for _ in range(ENTER_FRAMES + 5):
-      assert h.update(want_blended=True, override=False, veto=True) == "acc"
-
-  def test_counter_accumulates_under_veto_then_releases_instantly(self):
-    h = ModeHysteresis()
-    for _ in range(ENTER_FRAMES + 5):
-      h.update(want_blended=True, override=False, veto=True)
-    assert h.mode == "acc"
-    assert h.update(want_blended=True, override=False, veto=False) == "blended"
-
-  def test_exit_requires_min_dwell_and_sustained_absence(self):
-    h = ModeHysteresis()
-    for _ in range(ENTER_FRAMES):
-      h.update(want_blended=True, override=False, veto=False)
-    assert h.mode == "blended"
-    for _ in range(MIN_BLENDED_FRAMES - 1):
-      assert h.update(want_blended=False, override=False, veto=False) == "blended"
-    assert h.update(want_blended=False, override=False, veto=False) == "acc"
-
-  def test_no_flapping_on_alternating_reason(self):
-    h = ModeHysteresis()
-    changes = 0
-    prev = h.mode
-    for i in range(200):
-      mode = h.update(want_blended=i % 2 == 0, override=False, veto=False)
-      changes += mode != prev
-      prev = mode
-    assert changes == 0
-
-
-class TestShouldBlend(OpenpilotTestCase):
-  def test_slowdown_detected_triggers(self):
-    assert should_blend(DecSignals(decel_intent=1.0))
-    assert not should_blend(DecSignals(decel_intent=0.0))
-
-  def test_curve_exclusion_suppresses_slowdown(self):
-    assert not should_blend(DecSignals(decel_intent=0.7, curve_detected=True))
-
-  def test_curve_exclusion_does_not_override_saturated_decel_intent(self):
-    assert should_blend(DecSignals(decel_intent=1.0, curve_detected=True))
-
-  def test_degraded_model_suppresses_model_based_reasons(self):
-    s = DecSignals(decel_intent=1.0, model_trust=0.0)
-    assert not should_blend(s)
-
-  def test_creep_bypasses_everything(self):
-    assert should_blend(DecSignals(model_trust=0.0, creeping=True))

openpilot/sunnypilot/selfdrive/controls/lib/lead_departure_controller.py

@@ -1,116 +0,0 @@
-"""
-Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
-
-This file is part of sunnypilot and is licensed under the MIT License.
-See the LICENSE.md file in the root directory for more details.
-"""
-
-from collections import deque
-import math
-from typing import Any
-
-from openpilot.cereal import log
-from openpilot.selfdrive.controls.lib.longcontrol import LongCtrlState
-
-
-LEAD_DEPARTURE_MIN_SPEED = 0.6
-LEAD_DEPARTURE_CONFIRM_FRAMES = 3
-LEAD_DEPARTURE_MIN_DISTANCE = 0.03
-LEAD_DEPARTURE_MAX_EGO_SPEED = 0.3
-
-MpcPlanSource = log.LongitudinalPlan.LongitudinalPlanSource
-
-
-class LeadDepartureController:
-  def __init__(self, enabled: bool):
-    self.enabled = enabled
-    self._track_id: int | None = None
-    self._distances: deque[float] = deque(maxlen=LEAD_DEPARTURE_CONFIRM_FRAMES)
-    self._active = False
-
-  @property
-  def active(self) -> bool:
-    return self._active
-
-  def reset(self) -> None:
-    self._track_id = None
-    self._distances.clear()
-    self._active = False
-
-  @staticmethod
-  def _selected_lead(radar_state: Any, source: Any) -> Any | None:
-    if source == MpcPlanSource.lead0:
-      return radar_state.leadOne
-    if source == MpcPlanSource.lead1:
-      return radar_state.leadTwo
-    return None
-
-  @staticmethod
-  def _radar_has_errors(radar_state: Any) -> bool:
-    errors = radar_state.radarErrors
-    return errors.canError or errors.radarFault or errors.wrongConfig or errors.radarUnavailableTemporary
-
-  def update(self, sm: Any, source: Any, a_target: float, should_stop: bool, reset: bool, radar_valid: bool) -> bool:
-    CS = sm['carState']
-    CC = sm['carControl']
-    controls_state = sm['controlsState']
-    radar_state = sm['radarState']
-
-    blocked = (
-      not self.enabled
-      or reset
-      or not CC.longActive
-      or CC.cruiseControl.override
-      or CS.gasPressed
-      or CS.brakePressed
-      or controls_state.forceDecel
-      or controls_state.longControlState == LongCtrlState.off
-      or not radar_valid
-      or self._radar_has_errors(radar_state)
-    )
-    if blocked or not math.isfinite(CS.vEgo) or CS.vEgo >= LEAD_DEPARTURE_MAX_EGO_SPEED or not math.isfinite(a_target):
-      self.reset()
-      return should_stop
-
-    lead = self._selected_lead(radar_state, source)
-    lead_valid = (
-      lead is not None
-      and lead.present
-      and lead.radar
-      and lead.radarTrackId >= 0
-      and all(math.isfinite(value) for value in (lead.dRel, lead.vLeadK, lead.vRel, lead.aLeadK))
-      and lead.dRel > 0.0
-      and lead.vLeadK >= LEAD_DEPARTURE_MIN_SPEED
-      and lead.vRel >= LEAD_DEPARTURE_MIN_SPEED
-      and lead.aLeadK >= 0.0
-      and a_target >= 0.0
-    )
-    if not lead_valid:
-      self.reset()
-      return should_stop
-
-    track_id = int(lead.radarTrackId)
-    if self._active:
-      if track_id != self._track_id:
-        self.reset()
-        return should_stop
-      return False
-
-    if not should_stop:
-      self.reset()
-      return False
-
-    if controls_state.longControlState != LongCtrlState.stopping:
-      self.reset()
-      return should_stop
-
-    if track_id != self._track_id:
-      self._track_id = track_id
-      self._distances.clear()
-    self._distances.append(float(lead.dRel))
-
-    if len(self._distances) == LEAD_DEPARTURE_CONFIRM_FRAMES and self._distances[-1] - self._distances[0] >= LEAD_DEPARTURE_MIN_DISTANCE:
-      self._active = True
-      return False
-
-    return should_stop

openpilot/sunnypilot/selfdrive/controls/lib/longitudinal_planner.py

@@ -5,36 +5,26 @@ This file is part of sunnypilot and is licensed under the MIT License.
 See the LICENSE.md file in the root directory for more details.
 """
 
-import math
-
-from openpilot.cereal import messaging, custom, log
+from openpilot.cereal import messaging, custom
 from opendbc.car import structs
 from openpilot.common.constants import CV
 from openpilot.selfdrive.car.cruise import V_CRUISE_MAX
-from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import get_T_FOLLOW
-from openpilot.sunnypilot.selfdrive.controls.lib.accel_controller.accel_controller import AccelController
 from openpilot.sunnypilot.selfdrive.controls.lib.dec.dec import DynamicExperimentalController
 from openpilot.sunnypilot.selfdrive.controls.lib.e2e_alerts_helper import E2EAlertsHelper
-from openpilot.sunnypilot.selfdrive.controls.lib.lead_departure_controller import LeadDepartureController
 from openpilot.sunnypilot.selfdrive.controls.lib.smart_cruise_control.smart_cruise_control import SmartCruiseControl
 from openpilot.sunnypilot.selfdrive.controls.lib.speed_limit.speed_limit_assist import SpeedLimitAssist
 from openpilot.sunnypilot.selfdrive.controls.lib.speed_limit.speed_limit_resolver import SpeedLimitResolver
-from openpilot.sunnypilot.selfdrive.controls.lib.throttle_intent_controller import ThrottleIntentController
 from openpilot.sunnypilot.selfdrive.selfdrived.events import EventsSP
 from openpilot.sunnypilot.models.helpers import get_active_bundle
 
 DecState = custom.LongitudinalPlanSP.DynamicExperimentalControl.DynamicExperimentalControlState
 LongitudinalPlanSource = custom.LongitudinalPlanSP.LongitudinalPlanSource
-MpcPlanSource = log.LongitudinalPlan.LongitudinalPlanSource
 
 
 class LongitudinalPlannerSP:
   def __init__(self, CP: structs.CarParams, CP_SP: structs.CarParamsSP, mpc):
-    self.accel_controller = AccelController()
-    self.accel_controller_active = False
-    self.throttle_intent_controller = ThrottleIntentController(mpc.dt)
-    self.lead_departure_controller = LeadDepartureController(CP.openpilotLongitudinalControl and CP.autoResumeSng and not CP.notCar)
     self.events_sp = EventsSP()
+    self.resolver = SpeedLimitResolver()
     self.dec = DynamicExperimentalController(CP, mpc)
     self.scc = SmartCruiseControl()
     self.resolver = SpeedLimitResolver()
@@ -53,55 +43,6 @@ class LongitudinalPlannerSP:
 
     return experimental_mode and self.dec.mode() == "blended"
 
-  def get_max_accel_override(self, v_ego: float, v_target: float, e2e: bool) -> float | None:
-    self.accel_controller_active = bool(self.accel_controller.is_enabled() and (e2e or self.allow_throttle))
-    if not self.accel_controller_active:
-      return None
-    target = v_target if self.source == LongitudinalPlanSource.cruise else None
-    return self.accel_controller.get_max_accel(v_ego, target)
-
-  def get_cruise_target_override(self, v_ego: float, v_target: float, e2e: bool) -> float:
-    if not self.accel_controller.is_enabled() or self.source != LongitudinalPlanSource.cruise or not (e2e or self.allow_throttle):
-      return v_target
-    return self.accel_controller.get_cruise_target(v_ego, v_target)
-
-  def update_allow_throttle(self, throttle_prob: float, low_speed_override: bool, threshold: float) -> bool:
-    return self.throttle_intent_controller.update(throttle_prob, low_speed_override=low_speed_override, threshold=threshold)
-
-  def _has_valid_selected_lead(self, sm: messaging.SubMaster, source: MpcPlanSource) -> bool:
-    radar_valid = sm.valid.get('radarState', False) and getattr(sm, 'alive', {}).get('radarState', False)
-    return radar_valid and ((source == MpcPlanSource.lead0 and sm['radarState'].leadOne.present) or
-                            (source == MpcPlanSource.lead1 and sm['radarState'].leadTwo.present))
-
-  def arbitrate_cruise_candidate(self, sm: messaging.SubMaster, gated: float, ungated: float,
-                                 mpc_accel: float, mpc_source: MpcPlanSource, *, allow_throttle: bool,
-                                 e2e: bool, force_decel: bool) -> float:
-    finite = all(math.isfinite(value) for value in (gated, ungated, mpc_accel))
-    coast_gate_changed_source = gated < mpc_accel <= ungated
-    cruise_accel = gated
-    if (finite and not allow_throttle and not e2e and not force_decel
-        and self._has_valid_selected_lead(sm, mpc_source) and coast_gate_changed_source):
-      cruise_accel = ungated
-
-    lead_valid = (self.accel_controller.is_enabled() and self.source == LongitudinalPlanSource.cruise
-                  and self._has_valid_selected_lead(sm, mpc_source))
-    if not lead_valid or force_decel:
-      return cruise_accel
-
-    lead = sm['radarState'].leadOne if mpc_source == MpcPlanSource.lead0 else sm['radarState'].leadTwo
-    return self.accel_controller.get_lead_accel(
-      sm['carState'].vEgo, lead.dRel, lead.vRel, lead.aLeadK, cruise_accel, self.output_a_target,
-      get_T_FOLLOW(sm['selfdriveState'].personality),
-    )
-
-  def update_lead_departure(self, sm: messaging.SubMaster, a_target: float, should_stop: bool, reset: bool) -> tuple[float, bool]:
-    radar_valid = sm.valid.get('radarState', False) and getattr(sm, 'alive', {}).get('radarState', False)
-    should_stop = self.lead_departure_controller.update(sm, self.mpc.source, a_target, should_stop, reset, radar_valid)
-    if self.lead_departure_controller.active:
-      lead = sm['radarState'].leadOne if self.mpc.source == MpcPlanSource.lead0 else sm['radarState'].leadTwo
-      a_target = self.accel_controller.get_lead_departure_accel(sm['carState'].vEgo, lead.vLeadK, lead.aLeadK, a_target)
-    return a_target, should_stop
-
   def update_targets(self, sm: messaging.SubMaster, v_ego: float, a_ego: float, v_cruise: float) -> tuple[float, float]:
     CS = sm['carState']
     v_cruise_cluster_kph = min(CS.vCruiseCluster, V_CRUISE_MAX)
@@ -133,12 +74,9 @@ class LongitudinalPlannerSP:
     return self.output_v_target, self.output_a_target
 
   def update(self, sm: messaging.SubMaster) -> None:
-    self.accel_controller.update()
     self.events_sp.clear()
-    self.e2e_alerts_helper.update(sm, self.events_sp)
-
-  def update_dec(self, sm: messaging.SubMaster) -> None:
     self.dec.update(sm)
+    self.e2e_alerts_helper.update(sm, self.events_sp)
 
   def publish_longitudinal_plan_sp(self, sm: messaging.SubMaster, pm: messaging.PubMaster) -> None:
     plan_sp_send = messaging.new_message('longitudinalPlanSP')
@@ -156,15 +94,6 @@ class LongitudinalPlannerSP:
     dec.state = DecState.blended if self.dec.mode() == 'blended' else DecState.acc
     dec.enabled = self.dec.enabled()
     dec.active = self.dec.active()
-    dec.decelIntent = float(self.dec.signals.decel_intent)
-    dec.curveDetected = bool(self.dec.signals.curve_detected)
-    dec.wantBlended = bool(self.dec.want_blended)
-    dec.leadVeto = bool(self.dec.lead_veto)
-
-    accel_controller = longitudinalPlanSP.accelController
-    accel_controller.enabled = bool(self.accel_controller.is_enabled())
-    accel_controller.active = bool(self.accel_controller_active)
-    accel_controller.profile = int(self.accel_controller.profile)
 
     # Smart Cruise Control
     smartCruiseControl = longitudinalPlanSP.smartCruiseControl

openpilot/sunnypilot/selfdrive/controls/lib/smart_cruise_control/tests/test_vision_controller.py

@@ -4,8 +4,6 @@ Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
 This file is part of sunnypilot and is licensed under the MIT License.
 See the LICENSE.md file in the root directory for more details.
 """
-
-from types import SimpleNamespace
 from typing import Any
 
 import numpy as np
@@ -17,23 +15,8 @@ from openpilot.common.params import Params
 from openpilot.common.realtime import DT_MDL
 from openpilot.selfdrive.car.cruise import V_CRUISE_UNSET
 from openpilot.selfdrive.modeld.constants import ModelConstants
-from openpilot.sunnypilot.selfdrive.controls.lib.longitudinal_planner import LongitudinalPlannerSP, LongitudinalPlanSource
 from openpilot.sunnypilot.selfdrive.controls.lib.smart_cruise_control import MIN_V
-
-from openpilot.sunnypilot.selfdrive.controls.lib.smart_cruise_control.vision_controller import (
-  _A_LAT_REG_MAX,
-  _BELOW_EGO_TARGET_RELEASE_RATE,
-  _ENTERING_PRED_LAT_ACC_TH,
-  _MIN_ACTIVATION_SPEED,
-  _RELIEF_CONFIRMATION_FRAMES,
-  _TARGET_RELEASE_CONFIRMATION_FRAMES,
-  _TARGET_RELEASE_RATE,
-  _TARGET_TIGHTEN_CONFIRMATION_FRAMES,
-  _TARGET_TIGHTEN_RATE,
-  _TURNING_LAT_ACC_TH,
-  _URGENT_PRED_LAT_ACC_TH,
-  SmartCruiseControlVision,
-)
+from openpilot.sunnypilot.selfdrive.controls.lib.smart_cruise_control.vision_controller import SmartCruiseControlVision, _ENTERING_PRED_LAT_ACC_TH
 from openpilot.common.test import OpenpilotTestCase
 
 VisionState = custom.LongitudinalPlanSP.SmartCruiseControl.VisionState
@@ -124,6 +107,7 @@ def generate_controlsState():
 
 
 class TestSmartCruiseControlVision(OpenpilotTestCase):
+
   def setup_method(self):
     self.params = Params()
     self.reset_params()
@@ -137,377 +121,36 @@ class TestSmartCruiseControlVision(OpenpilotTestCase):
   def reset_params(self):
     self.params.put_bool("SmartCruiseControlVision", True, block=True)
 
-  def assert_approx(self, actual, expected):
-    self.assertAlmostEqual(actual, expected, delta=max(1e-12, abs(expected) * 1e-6))
-
-  def set_lat_accels(self, current: float, predicted: float, v_ego: float = 20.0, model_speed: float = 20.0) -> None:
-    self.sm['controlsState'].curvature = current / v_ego**2
-    self.sm['modelV2'].velocity.x = [model_speed] * len(ModelConstants.T_IDXS)
-    self.sm['modelV2'].orientationRate.z = [predicted / model_speed] * len(ModelConstants.T_IDXS)
-
-  def update_lat_accels(
-    self, current: float, predicted: float, cruise: float = 30.0, a_ego: float = 0.0, v_ego: float = 20.0, model_speed: float = 20.0
-  ) -> None:
-    self.set_lat_accels(current, predicted, v_ego, model_speed)
-    self.scc_v.update(self.sm, True, False, v_ego, a_ego, cruise)
-
-  def enter_curve(self, predicted: float = 2.2) -> None:
-    self.update_lat_accels(0.5, predicted)
-    self.update_lat_accels(0.5, predicted)
-    assert self.scc_v.state == VisionState.entering
-
   def test_initial_state(self):
     assert self.scc_v.state == VisionState.disabled
     assert not self.scc_v.is_active
     assert self.scc_v.output_v_target == V_CRUISE_UNSET
-    assert self.scc_v.output_a_target == 0.0
+    assert self.scc_v.output_a_target == 0.
 
   def test_system_disabled(self):
     self.params.put_bool("SmartCruiseControlVision", False, block=True)
     self.scc_v.enabled = self.params.get_bool("SmartCruiseControlVision")
 
-    for _ in range(int(10.0 / DT_MDL)):
-      self.scc_v.update(self.sm, True, False, 0.0, 0.0, 0.0)
+    for _ in range(int(10. / DT_MDL)):
+      self.scc_v.update(self.sm, True, False, 0., 0., 0.)
     assert self.scc_v.state == VisionState.disabled
     assert not self.scc_v.is_active
 
   def test_disabled(self):
-    for _ in range(int(10.0 / DT_MDL)):
-      self.scc_v.update(self.sm, False, False, 0.0, 0.0, 0.0)
+    for _ in range(int(10. / DT_MDL)):
+      self.scc_v.update(self.sm, False, False, 0., 0., 0.)
     assert self.scc_v.state == VisionState.disabled
 
   def test_transition_disabled_to_enabled(self):
-    for _ in range(int(10.0 / DT_MDL)):
-      self.scc_v.update(self.sm, True, False, 0.0, 0.0, 0.0)
+    for _ in range(int(10. / DT_MDL)):
+      self.scc_v.update(self.sm, True, False, 0., 0., 0.)
     assert self.scc_v.state == VisionState.enabled
 
-  def test_unconfirmed_release_holds_but_urgent_reentry_tightens(self):
-    self.enter_curve()
-    targets = [self.scc_v.output_v_target]
-
-    self.update_lat_accels(2.0, 2.2, a_ego=-0.8)
-    assert self.scc_v.state == VisionState.turning
-    assert self.scc_v.output_a_target == -0.8
-    turning_demand = self.scc_v._v_demand()
-    targets.append(self.scc_v.output_v_target)
-
-    self.update_lat_accels(1.2, 1.2, a_ego=0.3)
-    assert self.scc_v.state == VisionState.leaving
-    assert self.scc_v.output_a_target == 0.3
-    targets.append(self.scc_v.output_v_target)
-
-    self.update_lat_accels(1.0, 3.0, a_ego=-1.2)
-    assert self.scc_v.state == VisionState.entering
-    assert self.scc_v.output_a_target == -1.2
-    reentry_demand = self.scc_v._v_demand()
-    targets.append(self.scc_v.output_v_target)
-
-    entering, turning, leaving, reentering = targets
-    assert turning < entering
-    self.assert_approx(turning, turning_demand)
-    self.assert_approx(leaving, turning)
-    assert reentering < leaving
-    self.assert_approx(reentering, reentry_demand)
-
-  def test_new_curve_interrupts_confirmed_release_immediately(self):
-    self.enter_curve()
-    for _ in range(_RELIEF_CONFIRMATION_FRAMES + 1):
-      self.update_lat_accels(0.8, 0.8)
-    releasing_v_target = self.scc_v.output_v_target
-    assert self.scc_v.state == VisionState.leaving
-
-    self.update_lat_accels(0.8, 3.0, a_ego=-0.7)
-    assert self.scc_v.state == VisionState.entering
-    assert self.scc_v.output_v_target < releasing_v_target
-    assert self.scc_v.output_a_target == -0.7
-
-  @parameterized.expand([(-2.0,), (-0.5,), (0.0,), (0.8,)])
-  def test_planner_acceleration_passes_through_exactly(self, planner_accel):
-    self.enter_curve()
-    self.update_lat_accels(0.5, 2.2, a_ego=planner_accel)
-    assert self.scc_v.output_a_target == planner_accel
-
-  def test_planner_acceleration_passes_through_all_states(self):
-    cases = (
-      (False, False, 0.5, 2.2, -0.2, VisionState.disabled),
-      (True, False, 0.5, 0.8, 0.1, VisionState.enabled),
-      (True, False, 0.5, 2.2, -0.4, VisionState.entering),
-      (True, False, 2.0, 2.2, -0.8, VisionState.turning),
-      (True, False, 1.2, 1.2, 0.3, VisionState.leaving),
-      (True, True, 1.2, 1.2, 0.6, VisionState.overriding),
-    )
-    for long_enabled, override, current, predicted, planner_accel, state in cases:
-      self.set_lat_accels(current, predicted)
-      self.scc_v.update(self.sm, long_enabled, override, 20.0, planner_accel, 30.0)
-      assert self.scc_v.state == state
-      assert self.scc_v.output_a_target == planner_accel
-
-  def test_jitter_requires_confirmed_relief_then_releases_smoothly(self):
-    self.enter_curve()
-    previous_v_target = self.scc_v.output_v_target
-
-    for frame in range(_RELIEF_CONFIRMATION_FRAMES * 2):
-      self.update_lat_accels(1.0, 1.05 if frame % 2 == 0 else 1.15)
-      assert self.scc_v.state == VisionState.entering
-      assert self.scc_v.output_v_target >= previous_v_target
-      assert self.scc_v.output_v_target - previous_v_target <= _BELOW_EGO_TARGET_RELEASE_RATE * DT_MDL + 1e-9
-      previous_v_target = self.scc_v.output_v_target
-
-    for _ in range(_RELIEF_CONFIRMATION_FRAMES):
-      self.update_lat_accels(1.15, 0.8)
-      assert self.scc_v.state == VisionState.entering
-      assert 0.0 <= self.scc_v.output_v_target - previous_v_target <= _BELOW_EGO_TARGET_RELEASE_RATE * DT_MDL + 1e-9
-      previous_v_target = self.scc_v.output_v_target
-
-    release_cruise = 30.0
-    for _ in range(_RELIEF_CONFIRMATION_FRAMES - 1):
-      self.update_lat_accels(0.8, 0.8, release_cruise)
-      assert self.scc_v.state == VisionState.entering
-      assert 0.0 <= self.scc_v.output_v_target - previous_v_target <= _BELOW_EGO_TARGET_RELEASE_RATE * DT_MDL + 1e-9
-      previous_v_target = self.scc_v.output_v_target
-
-    active_v_targets = [previous_v_target]
-    for _ in range(int((release_cruise - previous_v_target) / (_TARGET_RELEASE_RATE * DT_MDL)) + 10):
-      self.update_lat_accels(0.8, 0.8, release_cruise)
-      if not self.scc_v.is_active:
-        break
-      assert self.scc_v.state == VisionState.leaving
-      assert self.scc_v.output_v_target != V_CRUISE_UNSET
-      active_v_targets.append(self.scc_v.output_v_target)
-
-    assert self.scc_v.state == VisionState.enabled
-    assert self.scc_v.output_v_target == V_CRUISE_UNSET
-    self.assert_approx(active_v_targets[-1], release_cruise)
-    assert np.all((np.diff(active_v_targets) >= 0.0) & (np.diff(active_v_targets) <= _BELOW_EGO_TARGET_RELEASE_RATE * DT_MDL + 1e-9))
-
-  def test_target_release_waits_for_relief_above_ego_speed(self):
-    self.enter_curve()
-    held_v_target = self.scc_v.output_v_target
-    self.assert_approx(held_v_target, self.scc_v.v_ego)
-
-    for _ in range(_RELIEF_CONFIRMATION_FRAMES + _TARGET_RELEASE_CONFIRMATION_FRAMES - 2):
-      self.update_lat_accels(0.8, 0.8)
-      self.assert_approx(self.scc_v.output_v_target, held_v_target)
-
-    self.update_lat_accels(0.8, 0.8)
-    rise = self.scc_v.output_v_target - held_v_target
-    assert 0.0 < rise <= _TARGET_RELEASE_RATE * DT_MDL + 1e-9
-
-  def test_curve_target_is_independent_of_ego_speed(self):
-    model_speed = 24.0
-    predicted_yaw_rate = 0.12
-    predicted_lat_accel = model_speed * predicted_yaw_rate
-    expected_v_target = (_A_LAT_REG_MAX / (predicted_yaw_rate / model_speed)) ** 0.5
-    targets = []
-
-    for v_ego in (18.0, 28.0):
-      controller = SmartCruiseControlVision()
-      self.set_lat_accels(0.5, predicted_lat_accel, v_ego, model_speed)
-      controller.update(self.sm, True, False, v_ego, 0.0, 30.0)
-      controller.update(self.sm, True, False, v_ego, 0.0, 30.0)
-      assert controller.state == VisionState.entering
-      targets.append(controller.v_target)
-
-    self.assert_approx(targets[0], expected_v_target)
-    self.assert_approx(targets[1], expected_v_target)
-
-  def test_curve_target_respects_minimum_speed_floor(self):
-    model_speed = 10.0
-    predicted_yaw_rate = 2.0
-    self.set_lat_accels(0.5, model_speed * predicted_yaw_rate, model_speed=model_speed)
-    self.scc_v.update(self.sm, True, False, 20.0, 0.0, 30.0)
-    self.scc_v.update(self.sm, True, False, 20.0, 0.0, 30.0)
-
-    assert self.scc_v.state == VisionState.entering
-    assert self.scc_v.v_target < MIN_V
-    self.assert_approx(self.scc_v.output_v_target, MIN_V)
-
-  @parameterized.expand(
-    [([], []), ([np.nan] * len(ModelConstants.T_IDXS), [np.nan] * len(ModelConstants.T_IDXS)), ([20.0] * 5, [0.1] * 3)],
-    names=["velocities", "yaw_rates"],
-  )
-  def test_model_vector_edges_remain_finite(self, velocities, yaw_rates):
-    self.sm['modelV2'].velocity.x = velocities
-    self.sm['modelV2'].orientationRate.z = yaw_rates
-    self.scc_v.update(self.sm, True, False, 20.0, 0.0, 30.0)
-    self.scc_v.update(self.sm, True, False, 20.0, 0.0, 30.0)
-
-    assert all(
-      np.isfinite(value)
-      for value in (
-        self.scc_v.current_lat_acc,
-        self.scc_v.max_pred_lat_acc,
-        self.scc_v.v_target,
-        self.scc_v.output_v_target,
-        self.scc_v.output_a_target,
-      )
-    )
-
-  @parameterized.expand([(5.75,), (9.9,), (_MIN_ACTIVATION_SPEED,)])
-  def test_vision_control_does_not_steal_launch(self, launch_speed):
-    self.set_lat_accels(0.5, 3.0, launch_speed)
-    self.scc_v.update(self.sm, True, False, launch_speed, 0.0, 30.0)
-    self.scc_v.update(self.sm, True, False, launch_speed, 0.0, 30.0)
-
-    assert launch_speed <= _MIN_ACTIVATION_SPEED
-    assert self.scc_v.state == VisionState.enabled
-    assert not self.scc_v.is_active
-    assert self.scc_v.output_v_target == V_CRUISE_UNSET
-
-  def test_vision_control_can_activate_above_launch_range(self):
-    speed = _MIN_ACTIVATION_SPEED + 0.01
-    self.set_lat_accels(0.5, 3.0, speed)
-    self.scc_v.update(self.sm, True, False, speed, 0.0, 30.0)
-    self.scc_v.update(self.sm, True, False, speed, 0.0, 30.0)
-
-    assert self.scc_v.state == VisionState.entering
-    assert self.scc_v.is_active
-
-  def test_nonurgent_activation_has_no_target_cliff(self):
-    v_ego = _MIN_ACTIVATION_SPEED + 0.01
-    model_speed = 8.0
-    self.update_lat_accels(0.5, 2.0, v_ego=v_ego, model_speed=model_speed)
-    self.update_lat_accels(0.5, 2.0, v_ego=v_ego, model_speed=model_speed)
-
-    self.assert_approx(self.scc_v.v_target, 8.0)
-    self.assert_approx(self.scc_v.output_v_target, v_ego)
-
-  def test_nonurgent_tightening_is_confirmed_and_rate_limited(self):
-    self.enter_curve()
-    initial_v_target = self.scc_v.output_v_target
-
-    for _ in range(_TARGET_TIGHTEN_CONFIRMATION_FRAMES - 1):
-      self.update_lat_accels(0.5, 2.8)
-      self.assert_approx(self.scc_v.output_v_target, initial_v_target)
-
-    self.update_lat_accels(0.5, 2.8)
-    drop = initial_v_target - self.scc_v.output_v_target
-    assert 0.0 < drop <= _TARGET_TIGHTEN_RATE * DT_MDL + 1e-9
-
-  def test_one_frame_curve_prediction_does_not_pulse_target(self):
-    self.enter_curve()
-    for _ in range(10):
-      self.update_lat_accels(0.5, 2.2)
-    stable_v_target = self.scc_v.output_v_target
-
-    self.update_lat_accels(0.5, 2.8)
-    self.assert_approx(self.scc_v.output_v_target, stable_v_target)
-    self.update_lat_accels(0.5, 2.2)
-
-    self.assert_approx(self.scc_v.output_v_target, stable_v_target)
-
-  def test_one_frame_release_does_not_reverse_target(self):
-    self.enter_curve(_URGENT_PRED_LAT_ACC_TH)
-    stable_v_target = self.scc_v.output_v_target
-
-    self.update_lat_accels(0.5, 2.2)
-    self.assert_approx(self.scc_v.output_v_target, stable_v_target)
-    self.update_lat_accels(0.5, _URGENT_PRED_LAT_ACC_TH)
-
-    self.assert_approx(self.scc_v.output_v_target, stable_v_target)
-
-  def test_urgent_predicted_curve_is_not_delayed(self):
-    self.enter_curve()
-    self.update_lat_accels(0.5, _URGENT_PRED_LAT_ACC_TH)
-
-    self.assert_approx(self.scc_v.output_v_target, self.scc_v._v_demand())
-
-  def test_current_curve_is_not_delayed(self):
-    self.enter_curve()
-    self.update_lat_accels(_TURNING_LAT_ACC_TH, 2.8)
-
-    self.assert_approx(self.scc_v.output_v_target, self.scc_v._v_demand())
-
-  def test_sequential_curve_confirms_release_and_tightens_urgently(self):
-    self.enter_curve(3.0)
-    for _ in range(20):
-      self.update_lat_accels(0.5, 3.0)
-    restrictive_v_target = self.scc_v.output_v_target
-
-    self.update_lat_accels(0.5, 1.4, a_ego=0.4)
-    assert self.scc_v.state == VisionState.entering
-    self.assert_approx(self.scc_v.output_v_target, restrictive_v_target)
-    assert self.scc_v.output_a_target == 0.4
-
-    for _ in range(_TARGET_RELEASE_CONFIRMATION_FRAMES - 2):
-      self.update_lat_accels(0.5, 1.4)
-      self.assert_approx(self.scc_v.output_v_target, restrictive_v_target)
-
-    self.update_lat_accels(0.5, 1.4)
-    released_v_target = self.scc_v.output_v_target
-    assert 0.0 < released_v_target - restrictive_v_target <= _BELOW_EGO_TARGET_RELEASE_RATE * DT_MDL + 1e-9
-
-    self.update_lat_accels(0.5, 3.0, a_ego=-0.6)
-    assert self.scc_v.state == VisionState.entering
-    self.assert_approx(self.scc_v.output_v_target, restrictive_v_target)
-    assert self.scc_v.output_a_target == -0.6
-
-    for _ in range(4):
-      self.update_lat_accels(0.5, 1.4)
-      self.assert_approx(self.scc_v.output_v_target, restrictive_v_target)
-      self.update_lat_accels(0.5, 3.0)
-      self.assert_approx(self.scc_v.output_v_target, restrictive_v_target)
-
-  def test_acceleration_is_continuous_through_planner_arbitration(self):
-    car_control = messaging.new_message('carControl')
-    car_control.carControl.enabled = True
-    car_control.carControl.cruiseControl.override = False
-    self.sm['carControl'] = car_control.carControl
-    self.sm['carState'].vCruiseCluster = 108.0
-
-    planner: Any = LongitudinalPlannerSP.__new__(LongitudinalPlannerSP)
-    planner.scc = SimpleNamespace(
-      vision=self.scc_v,
-      map=SimpleNamespace(output_v_target=V_CRUISE_UNSET, output_a_target=0.0),
-      update=lambda sm, enabled, override, v_ego, a_ego, v_cruise: self.scc_v.update(sm, enabled, override, v_ego, a_ego, v_cruise),
-    )
-    planner.resolver = SimpleNamespace(
-      speed_limit_valid=False,
-      speed_limit_last_valid=False,
-      speed_limit=0.0,
-      speed_limit_final_last=0.0,
-      distance=0.0,
-      update=lambda _v_ego, _sm: None,
-    )
-    planner.sla = SimpleNamespace(
-      output_v_target=V_CRUISE_UNSET,
-      output_a_target=0.0,
-      update=lambda *_args: None,
-    )
-    planner.events_sp = SimpleNamespace()
-
-    self.set_lat_accels(0.5, 2.2)
-    planner.update_targets(self.sm, 20.0, -0.8, 30.0)
-    planner.update_targets(self.sm, 20.0, -0.8, 30.0)
-    assert planner.source == LongitudinalPlanSource.sccVision
-    assert planner.output_a_target == -0.8
-
-    for planner_accel in (-2.0, 0.5, -0.2):
-      planner.update_targets(self.sm, 20.0, planner_accel, 30.0)
-      assert planner.source == LongitudinalPlanSource.sccVision
-      assert planner.output_a_target == planner_accel
-
-    self.set_lat_accels(0.8, 0.8)
-    for _ in range(int(30.0 / (_TARGET_RELEASE_RATE * DT_MDL)) + 10):
-      planner.update_targets(self.sm, 20.0, 0.4, 30.0)
-      assert planner.output_a_target == 0.4
-      if planner.source == LongitudinalPlanSource.cruise:
-        break
-    else:
-      self.fail("SCC Vision did not release to cruise")
-
-    planner.update_targets(self.sm, 20.0, 0.4, 30.0)
-    assert self.scc_v.state == VisionState.enabled
-    assert planner.source == LongitudinalPlanSource.cruise
-
-  @parameterized.expand(
-    [
+  @parameterized.expand([
       ("p97_just_above_threshold", True),
       ("single_spike_filtered", False),
       ("persistent_high_values", True),
-    ],
-    names=["case", "should_enter"],
-  )
+    ], names=["case", "should_enter"])
   def test_max_pred_lat_acc_uses_p97_and_threshold(self, case, should_enter):
     n = len(ModelConstants.T_IDXS)
     th = float(_ENTERING_PRED_LAT_ACC_TH)

openpilot/sunnypilot/selfdrive/controls/lib/smart_cruise_control/tests/test_vision_controller_closed_loop.py

@@ -1,110 +0,0 @@
-"""
-Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
-
-This file is part of sunnypilot and is licensed under the MIT License.
-See the LICENSE.md file in the root directory for more details.
-"""
-
-import gc
-from contextlib import ExitStack
-from unittest import mock
-
-import numpy as np
-
-from openpilot.common.test import OpenpilotTestCase
-from openpilot.selfdrive.test.longitudinal_maneuvers.plant import Plant
-from openpilot.sunnypilot.selfdrive.controls.lib.longitudinal_planner import LongitudinalPlanSource
-from openpilot.sunnypilot.selfdrive.controls.lib.smart_cruise_control.vision_controller import _A_LAT_REG_MAX
-
-
-def _run_constant_curve(*, scc_enabled: bool, cruise: float, duration: float = 70.0) -> dict[str, np.ndarray]:
-  gc.collect()
-  curvature = 0.005
-  plant = Plant(lead_relevancy=False, speed=30.0)
-  planner = plant.planner
-  planner.dec._enabled = False
-  planner.scc.map.enabled = False
-  planner.scc.vision.enabled = scc_enabled
-  solver_failures = 0
-
-  with ExitStack() as patches:
-    patches.enter_context(mock.patch.object(planner.dec, "_read_params", return_value=None))
-    patches.enter_context(mock.patch.object(planner.scc.map, "update_params", return_value=None))
-    patches.enter_context(mock.patch.object(planner.scc.vision, "_update_params", return_value=None))
-
-    original_mpc_reset = planner.mpc.reset
-
-    def record_mpc_reset(*args, **kwargs):
-      nonlocal solver_failures
-      solver_failures += int(planner.mpc.solution_status != 0)
-      return original_mpc_reset(*args, **kwargs)
-
-    patches.enter_context(mock.patch.object(planner.mpc, "reset", side_effect=record_mpc_reset))
-
-    if scc_enabled:
-      original_update_calculations = planner.scc.vision._update_calculations
-
-      def inject_constant_curvature(sm):
-        velocities = np.asarray(sm['modelV2'].velocity.x, dtype=float)
-        sm['modelV2'].orientationRate.z = (curvature * velocities).tolist()
-        sm['controlsState'].curvature = curvature
-        original_update_calculations(sm)
-
-      patches.enter_context(mock.patch.object(planner.scc.vision, "_update_calculations", side_effect=inject_constant_curvature))
-
-    original_update = planner.update
-
-    def enable_longitudinal(sm):
-      sm['carControl'].enabled = True
-      sm['carControl'].longActive = True
-      original_update(sm)
-
-    patches.enter_context(mock.patch.object(planner, "update", side_effect=enable_longitudinal))
-    rows = []
-    while plant.current_time < duration:
-      output = plant.step(v_cruise=cruise)
-      rows.append(
-        (
-          plant.current_time,
-          output['speed'],
-          output['should_stop'],
-          planner.scc.vision.is_active,
-          planner.source == LongitudinalPlanSource.sccVision,
-          planner.scc.vision.output_v_target,
-        )
-      )
-
-  data = np.asarray(rows, dtype=float)
-  gc.collect()
-  return {
-    'time': data[:, 0],
-    'speed': data[:, 1],
-    'should_stop': data[:, 2],
-    'active': data[:, 3],
-    'scc_source': data[:, 4],
-    'target': data[:, 5],
-    'solver_failures': np.asarray(solver_failures),
-  }
-
-
-class TestVisionControllerClosedLoop(OpenpilotTestCase):
-  def test_constant_curve_recovers_like_stock_speed_cap(self):
-    target = (_A_LAT_REG_MAX / 0.005) ** 0.5
-    scc = _run_constant_curve(scc_enabled=True, cruise=30.0)
-    stock = _run_constant_curve(scc_enabled=False, cruise=target)
-    scc_final = scc['speed'][scc['time'] >= 60.0]
-    stock_final = stock['speed'][stock['time'] >= 60.0]
-
-    # The generated solver can report platform-specific failures for the
-    # synthetic no-lead plant. The feature must not make that stock baseline
-    # worse; requiring an absolute zero would hide a harness difference as a
-    # controller regression.
-    assert scc['solver_failures'] <= stock['solver_failures']
-    assert not scc['should_stop'].any()
-    assert np.all(scc['active'][scc['time'] >= 60.0])
-    assert np.all(scc['scc_source'][scc['time'] >= 60.0])
-    assert np.allclose(scc['target'][scc['time'] >= 60.0], target)
-    assert scc_final.min() >= target - 1.0
-    assert abs(scc_final.mean() - stock_final.mean()) < 0.5
-    assert abs(scc_final.min() - stock_final.min()) < 1.0
-    assert abs(scc_final.max() - stock_final.max()) < 1.0

openpilot/sunnypilot/selfdrive/controls/lib/smart_cruise_control/vision_controller.py

@@ -23,21 +23,25 @@ _ENTERING_PRED_LAT_ACC_TH = 1.3  # Predicted Lat Acc threshold to trigger enteri
 _ABORT_ENTERING_PRED_LAT_ACC_TH = 1.1  # Predicted Lat Acc threshold to abort entering state if speed drops.
 
 _TURNING_LAT_ACC_TH = 1.6  # Lat Acc threshold to trigger turning state.
-_URGENT_PRED_LAT_ACC_TH = 3.  # Predicted Lat Acc threshold that requires an immediate speed reduction.
 
 _LEAVING_LAT_ACC_TH = 1.3  # Lat Acc threshold to trigger leaving turn state.
 _FINISH_LAT_ACC_TH = 1.1  # Lat Acc threshold to trigger the end of the turn cycle.
 
 _A_LAT_REG_MAX = 2.  # Maximum lateral acceleration
 
-_RELIEF_CONFIRMATION_FRAMES = max(1, int(round(0.5 / DT_MDL)))
-_TARGET_TIGHTEN_CONFIRMATION_FRAMES = max(1, int(round(0.1 / DT_MDL)))
-_TARGET_RELEASE_CONFIRMATION_FRAMES = max(1, int(round(0.15 / DT_MDL)))
-_TARGET_TIGHTEN_RATE = 5.  # m/s^2
-_TARGET_RELEASE_RATE = 1.  # m/s^2
-_BELOW_EGO_TARGET_RELEASE_RATE = 3.  # m/s^2
-_MIN_PRED_SPEED = 1.  # m/s
-_MIN_ACTIVATION_SPEED = 10.  # m/s
+_NO_OVERSHOOT_TIME_HORIZON = 4.  # s. Time to use for velocity desired based on a_target when not overshooting.
+
+# Lookup table for the minimum smooth deceleration during the ENTERING state
+# depending on the actual maximum absolute lateral acceleration predicted on the turn ahead.
+_ENTERING_SMOOTH_DECEL_V = [-0.2, -1.]  # min decel value allowed on ENTERING state
+_ENTERING_SMOOTH_DECEL_BP = [1.3, 3.]  # absolute value of lat acc ahead
+
+# Lookup table for the acceleration for the TURNING state
+# depending on the current lateral acceleration of the vehicle.
+_TURNING_ACC_V = [0.5, 0., -0.4]  # acc value
+_TURNING_ACC_BP = [1.5, 2.3, 3.]  # absolute value of current lat acc
+
+_LEAVING_ACC = 0.5  # Conformable acceleration to regain speed while leaving a turn.
 
 
 class SmartCruiseControlVision:
@@ -61,62 +65,14 @@ class SmartCruiseControlVision:
     self.state = VisionState.disabled
     self.current_lat_acc = 0.
     self.max_pred_lat_acc = 0.
-    self.relief_frames = 0
-    self.tighten_frames = 0
-    self.release_frames = 0
-
-  def _v_demand(self) -> float:
-    return max(MIN_V, min(self.v_target, self.v_cruise_setpoint))
-
-  def _curve_is_urgent(self) -> bool:
-    return self.current_lat_acc >= _TURNING_LAT_ACC_TH or self.max_pred_lat_acc >= _URGENT_PRED_LAT_ACC_TH
-
-  def _filtered_v_target(self) -> float:
-    demand = self._v_demand()
-
-    if self.output_v_target == V_CRUISE_UNSET:
-      self.tighten_frames = 0
-      self.release_frames = 0
-      if self._curve_is_urgent():
-        return demand
-      return max(demand, min(self.v_ego, self.v_cruise_setpoint))
-
-    if demand < self.output_v_target:
-      self.release_frames = 0
-      if self._curve_is_urgent():
-        self.tighten_frames = 0
-        return demand
-
-      self.tighten_frames += 1
-      if self.tighten_frames < _TARGET_TIGHTEN_CONFIRMATION_FRAMES:
-        return self.output_v_target
-      return max(demand, self.output_v_target - _TARGET_TIGHTEN_RATE * DT_MDL)
-
-    self.tighten_frames = 0
-    releasing_brake = self.output_v_target < min(self.v_ego, demand)
-    if not releasing_brake and self.relief_frames < _RELIEF_CONFIRMATION_FRAMES:
-      self.release_frames = 0
-      return self.output_v_target
-
-    if demand > self.output_v_target:
-      self.release_frames += 1
-      if self.release_frames < _TARGET_RELEASE_CONFIRMATION_FRAMES:
-        return self.output_v_target
-    else:
-      self.release_frames = 0
-
-    release_rate = _BELOW_EGO_TARGET_RELEASE_RATE if releasing_brake else _TARGET_RELEASE_RATE
-    return min(demand, self.output_v_target + release_rate * DT_MDL)
 
   def get_a_target_from_control(self) -> float:
-    return self.a_ego
+    return self.a_target
 
   def get_v_target_from_control(self) -> float:
     if self.is_active:
-      return self._filtered_v_target()
+      return max(self.v_target, MIN_V) + self.a_target * _NO_OVERSHOOT_TIME_HORIZON
 
-    self.tighten_frames = 0
-    self.release_frames = 0
     return V_CRUISE_UNSET
 
   def _update_params(self) -> None:
@@ -126,27 +82,25 @@ class SmartCruiseControlVision:
   def _update_calculations(self, sm: messaging.SubMaster) -> None:
     if not self.long_enabled:
       return
+    else:
+      rate_plan = np.array(np.abs(sm['modelV2'].orientationRate.z))
+      vel_plan = np.array(sm['modelV2'].velocity.x)
 
-    rate_plan = np.asarray(np.abs(sm['modelV2'].orientationRate.z), dtype=float)
-    vel_plan = np.asarray(sm['modelV2'].velocity.x, dtype=float)
-    size = min(len(rate_plan), len(vel_plan))
-    rate_plan, vel_plan = rate_plan[:size], vel_plan[:size]
-    valid = np.isfinite(rate_plan) & np.isfinite(vel_plan) & (vel_plan >= _MIN_PRED_SPEED)
+      self.current_lat_acc = self.v_ego ** 2 * abs(sm['controlsState'].curvature)
 
-    self.current_lat_acc = self.v_ego ** 2 * abs(sm['controlsState'].curvature)
-    self.max_pred_lat_acc = 0.
-    self.v_target = V_CRUISE_UNSET
-    if np.any(valid):
-      self.max_pred_lat_acc = float(np.percentile(rate_plan[valid] * vel_plan[valid], 97))
-      max_pred_curvature = float(np.percentile(rate_plan[valid] / vel_plan[valid], 97))
-      if max_pred_curvature > 0.:
-        self.v_target = min(float((_A_LAT_REG_MAX / max_pred_curvature) ** 0.5), V_CRUISE_UNSET)
+      # get the maximum lat accel from the model
+      predicted_lat_accels = rate_plan * vel_plan
+      self.max_pred_lat_acc = np.percentile(predicted_lat_accels, 97)
+
+      # get the maximum curve based on the current velocity
+      v_ego = max(self.v_ego, 0.1)  # ensure a value greater than 0 for calculations
+      max_curve = self.max_pred_lat_acc / (v_ego**2)
+
+      # Get the target velocity for the maximum curve
+      self.v_target = (_A_LAT_REG_MAX / max_curve) ** 0.5
 
   def _update_state_machine(self) -> tuple[bool, bool]:
     # ENABLED, ENTERING, TURNING, LEAVING, OVERRIDING
-    relief = self.current_lat_acc < _FINISH_LAT_ACC_TH and self.max_pred_lat_acc < _ABORT_ENTERING_PRED_LAT_ACC_TH
-    self.relief_frames = self.relief_frames + 1 if self.state in ACTIVE_STATES and relief else 0
-
     if self.state != VisionState.disabled:
       # longitudinal and feature disable always have priority in a non-disabled state
       if not self.long_enabled or not self.enabled:
@@ -158,7 +112,7 @@ class SmartCruiseControlVision:
         # ENABLED
         if self.state == VisionState.enabled:
           # Do not enter a turn control cycle if the speed is low.
-          if self.v_ego <= _MIN_ACTIVATION_SPEED:
+          if self.v_ego <= MIN_V:
             pass
           # If significant lateral acceleration is predicted ahead, then move to Entering turn state.
           elif self.max_pred_lat_acc >= _ENTERING_PRED_LAT_ACC_TH:
@@ -174,26 +128,23 @@ class SmartCruiseControlVision:
           # Transition to Turning if current lateral acceleration is over the threshold.
           if self.current_lat_acc >= _TURNING_LAT_ACC_TH:
             self.state = VisionState.turning
-          # Begin releasing only after both current and predicted lateral acceleration stay clear.
-          elif self.relief_frames >= _RELIEF_CONFIRMATION_FRAMES:
-            self.state = VisionState.leaving
+          # Abort if the predicted lateral acceleration drops
+          elif self.max_pred_lat_acc < _ABORT_ENTERING_PRED_LAT_ACC_TH:
+            self.state = VisionState.enabled
 
         # TURNING
         elif self.state == VisionState.turning:
-          # Transition out of Turning if current lateral acceleration drops below a threshold.
+          # Transition to Leaving if current lateral acceleration drops below a threshold.
           if self.current_lat_acc <= _LEAVING_LAT_ACC_TH:
-            self.state = VisionState.entering if self.max_pred_lat_acc >= _ENTERING_PRED_LAT_ACC_TH else VisionState.leaving
+            self.state = VisionState.leaving
 
         # LEAVING
         elif self.state == VisionState.leaving:
           # Transition back to Turning if current lateral acceleration goes back over the threshold.
           if self.current_lat_acc >= _TURNING_LAT_ACC_TH:
             self.state = VisionState.turning
-          # Start a new turn cycle immediately if another curve is predicted.
-          elif self.max_pred_lat_acc >= _ENTERING_PRED_LAT_ACC_TH:
-            self.state = VisionState.entering
-          # Finish after confirmed relief and a gradual release to the cruise setpoint.
-          elif self.relief_frames >= _RELIEF_CONFIRMATION_FRAMES and self.output_v_target >= self.v_cruise_setpoint:
+          # Finish if current lateral acceleration goes below a threshold.
+          elif self.current_lat_acc < _FINISH_LAT_ACC_TH:
             self.state = VisionState.enabled
 
     # DISABLED
@@ -206,11 +157,32 @@ class SmartCruiseControlVision:
 
     enabled = self.state in ENABLED_STATES
     active = self.state in ACTIVE_STATES
-    if not active:
-      self.relief_frames = 0
 
     return enabled, active
 
+  def _update_solution(self) -> float:
+    # DISABLED, ENABLED, OVERRIDING
+    if self.state not in ACTIVE_STATES:
+      # when not overshooting, calculate v_turn as the speed at the prediction horizon when following
+      # the smooth deceleration.
+      a_target = self.a_ego
+    # ENTERING
+    elif self.state == VisionState.entering:
+      # when not overshooting, target a smooth deceleration in preparation for a sharp turn to come.
+      a_target = np.interp(self.max_pred_lat_acc, _ENTERING_SMOOTH_DECEL_BP, _ENTERING_SMOOTH_DECEL_V)
+    # TURNING
+    elif self.state == VisionState.turning:
+      # When turning, we provide a target acceleration that is comfortable for the lateral acceleration felt.
+      a_target = np.interp(self.current_lat_acc, _TURNING_ACC_BP, _TURNING_ACC_V)
+    # LEAVING
+    elif self.state == VisionState.leaving:
+      # When leaving, we provide a comfortable acceleration to regain speed.
+      a_target = _LEAVING_ACC
+    else:
+      raise NotImplementedError(f"SCC-V state not supported: {self.state}")
+
+    return a_target
+
   def update(self, sm: messaging.SubMaster, long_enabled: bool, long_override: bool, v_ego: float, a_ego: float,
              v_cruise_setpoint: float) -> None:
     self.long_enabled = long_enabled
@@ -223,7 +195,7 @@ class SmartCruiseControlVision:
     self._update_calculations(sm)
 
     self.is_enabled, self.is_active = self._update_state_machine()
-    self.a_target = self.a_ego
+    self.a_target = self._update_solution()
 
     self.output_v_target = self.get_v_target_from_control()
     self.output_a_target = self.get_a_target_from_control()

openpilot/sunnypilot/selfdrive/controls/lib/tests/test_lead_departure_controller.py

@@ -1,313 +0,0 @@
-"""
-Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
-
-This file is part of sunnypilot and is licensed under the MIT License.
-See the LICENSE.md file in the root directory for more details.
-"""
-
-from types import SimpleNamespace
-from unittest import mock
-
-from openpilot.cereal import log
-from openpilot.common.params import Params
-from openpilot.common.realtime import DT_MDL
-from openpilot.common.test import OpenpilotTestCase
-from openpilot.selfdrive.controls.lib.longcontrol import LongCtrlState
-from openpilot.sunnypilot.selfdrive.controls.lib.accel_controller.accel_controller import AccelProfile
-from openpilot.sunnypilot.selfdrive.controls.lib.lead_departure_controller import LEAD_DEPARTURE_MIN_SPEED, LeadDepartureController
-from openpilot.sunnypilot.selfdrive.test.longitudinal_maneuvers.plant import PRIUS_TSS2_ROUTE_MODEL, PlantSP
-
-
-MpcPlanSource = log.LongitudinalPlan.LongitudinalPlanSource
-
-
-def make_lead(*, d_rel: float = 4.0, v_lead: float = 0.7, v_rel: float = 0.7, a_lead: float = 0.0,
-              present: bool = True, radar: bool = True, track_id: int = 7):
-  return SimpleNamespace(dRel=d_rel, vLeadK=v_lead, vRel=v_rel, aLeadK=a_lead, present=present, radar=radar, radarTrackId=track_id)
-
-
-def make_sm(
-  *,
-  lead_one=None,
-  lead_two=None,
-  v_ego: float = 0.0,
-  long_active: bool = True,
-  long_state=LongCtrlState.stopping,
-  gas: bool = False,
-  brake: bool = False,
-  override: bool = False,
-  force_decel: bool = False,
-  radar_error: str | None = None,
-):
-  errors = SimpleNamespace(canError=False, radarFault=False, wrongConfig=False, radarUnavailableTemporary=False)
-  if radar_error is not None:
-    setattr(errors, radar_error, True)
-  return {
-    'carState': SimpleNamespace(vEgo=v_ego, gasPressed=gas, brakePressed=brake),
-    'carControl': SimpleNamespace(longActive=long_active, cruiseControl=SimpleNamespace(override=override)),
-    'controlsState': SimpleNamespace(longControlState=long_state, forceDecel=force_decel),
-    'radarState': SimpleNamespace(leadOne=lead_one or make_lead(), leadTwo=lead_two or make_lead(track_id=8), radarErrors=errors),
-  }
-
-
-def update(controller, sm, *, source=MpcPlanSource.lead0, a_target: float = 0.05, should_stop: bool = True, reset: bool = False, radar_valid: bool = True):
-  return controller.update(sm, source, a_target, should_stop, reset, radar_valid)
-
-
-def activate(controller: LeadDepartureController):
-  assert update(controller, make_sm(lead_one=make_lead(d_rel=4.00)))
-  assert update(controller, make_sm(lead_one=make_lead(d_rel=4.01)))
-  assert not update(controller, make_sm(lead_one=make_lead(d_rel=4.04)))
-  assert controller.active
-
-
-def run_closed_loop(controller_enabled: bool, gap: float, lead_speed, duration: float, model_should_stop: bool | None = None,
-                    profile_enabled: bool = False):
-  params = Params()
-  params.put_bool("AccelPersonalityEnabled", profile_enabled, block=True)
-  params.put("AccelPersonality", AccelProfile.eco, block=True)
-
-  def observe_lead(_t, _name, truth):
-    truth.update(radar=True, radarTrackId=7)
-    return truth
-
-  def model_action(_t, _v_ego, _a_ego):
-    return 0.0, bool(model_should_stop)
-
-  plant = PlantSP(
-    lead_relevancy=True,
-    speed=0.0,
-    distance_lead=gap,
-    lead_observation_fn=observe_lead,
-    actuator_model=PRIUS_TSS2_ROUTE_MODEL,
-    run_long_control=True,
-    e2e=model_should_stop is not None,
-    model_action_fn=model_action if model_should_stop is not None else None,
-  )
-  plant.v_lead_prev = lead_speed(0.0)
-  plant.planner.lead_departure_controller.enabled = controller_enabled
-
-  original_update = plant.planner.update
-
-  def long_active_update(sm):
-    sm['carControl'].longActive = True
-    original_update(sm)
-
-  solver_resets = 0
-  original_reset = plant.planner.mpc.reset
-
-  def counted_reset(*args, **kwargs):
-    nonlocal solver_resets
-    if plant.planner.mpc.solution_status != 0:
-      solver_resets += 1
-    return original_reset(*args, **kwargs)
-
-  rows = []
-  active = []
-  with (
-    mock.patch.object(plant.planner, 'get_max_accel_override', return_value=None),
-    mock.patch.object(plant.planner, 'update', side_effect=long_active_update),
-    mock.patch.object(plant.planner.mpc, 'reset', side_effect=counted_reset),
-  ):
-    for _ in range(round(duration / DT_MDL)):
-      t = plant.current_time
-      result = plant.step(v_lead=lead_speed(t), v_cruise=8.0)
-      rows.append(
-        (t, result['speed'], result['distance'], result['distance_lead'] - result['distance'], result['actuator_command'], result['should_stop'], result['fcw'],
-         result['a_target'], plant.applied_actuator_command)
-      )
-      active.append(plant.planner.lead_departure_controller.active)
-
-  return rows, active, solver_resets
-
-
-def first_delay(rows, cue: float, column: int, predicate):
-  return next(row[0] - cue for row in rows if row[0] >= cue and predicate(row[column]))
-
-
-class TestLeadDepartureController(OpenpilotTestCase):
-  def test_requires_three_coherent_radar_frames(self):
-    controller = LeadDepartureController(True)
-    assert update(controller, make_sm(lead_one=make_lead(d_rel=4.00)))
-    assert update(controller, make_sm(lead_one=make_lead(d_rel=4.01)))
-    assert not update(controller, make_sm(lead_one=make_lead(d_rel=4.04)))
-    assert controller.active
-
-  def test_distance_confirmation_uses_a_sliding_three_frame_window(self):
-    controller = LeadDepartureController(True)
-    for d_rel in (4.00, 4.01, 4.02, 4.03):
-      assert update(controller, make_sm(lead_one=make_lead(d_rel=d_rel)))
-    assert not controller.active
-
-    assert not update(controller, make_sm(lead_one=make_lead(d_rel=4.06)))
-    assert controller.active
-
-  def test_persistent_false_speed_cue_with_static_range_never_arms(self):
-    controller = LeadDepartureController(True)
-    for _ in range(10):
-      assert update(controller, make_sm(lead_one=make_lead(d_rel=4.0)))
-    assert not controller.active
-
-  def test_slow_lead_creep_never_arms(self):
-    controller = LeadDepartureController(True)
-    for frame in range(20):
-      lead = make_lead(d_rel=4.0 + frame * 0.03, v_lead=LEAD_DEPARTURE_MIN_SPEED - 0.05, v_rel=LEAD_DEPARTURE_MIN_SPEED - 0.05)
-      assert update(controller, make_sm(lead_one=lead))
-    assert not controller.active
-
-  def test_same_track_can_move_between_lead_slots(self):
-    controller = LeadDepartureController(True)
-    assert update(controller, make_sm(lead_one=make_lead(d_rel=4.00)), source=MpcPlanSource.lead0)
-    assert update(controller, make_sm(lead_two=make_lead(d_rel=4.01)), source=MpcPlanSource.lead1)
-    assert not update(controller, make_sm(lead_one=make_lead(d_rel=4.04)), source=MpcPlanSource.lead0)
-
-  def test_different_track_restarts_confirmation(self):
-    controller = LeadDepartureController(True)
-    assert update(controller, make_sm(lead_one=make_lead(d_rel=4.00, track_id=7)))
-    assert update(controller, make_sm(lead_one=make_lead(d_rel=4.02, track_id=7)))
-    assert update(controller, make_sm(lead_one=make_lead(d_rel=4.20, track_id=9)))
-    assert update(controller, make_sm(lead_one=make_lead(d_rel=4.22, track_id=9)))
-    assert not update(controller, make_sm(lead_one=make_lead(d_rel=4.24, track_id=9)))
-
-  def test_active_release_latches_through_native_threshold_churn(self):
-    controller = LeadDepartureController(True)
-    activate(controller)
-    sm = make_sm(lead_one=make_lead(d_rel=4.10), long_state=LongCtrlState.pid)
-    assert not update(controller, sm, a_target=0.12, should_stop=False)
-    assert not update(controller, sm, a_target=0.05, should_stop=True)
-    assert controller.active
-
-  def test_active_release_latches_across_same_track_source_churn(self):
-    controller = LeadDepartureController(True)
-    activate(controller)
-    sm = make_sm(lead_two=make_lead(d_rel=4.10), long_state=LongCtrlState.pid)
-    assert not update(controller, sm, source=MpcPlanSource.lead1)
-    assert controller.active
-
-  def test_active_release_cancels_on_invalid_state(self):
-    cases = (
-      ('lead lost', make_sm(lead_one=make_lead(present=False))),
-      ('vision lead', make_sm(lead_one=make_lead(radar=False))),
-      ('track changed', make_sm(lead_one=make_lead(track_id=9))),
-      ('lead too slow', make_sm(lead_one=make_lead(v_lead=LEAD_DEPARTURE_MIN_SPEED - 0.01))),
-      ('relative speed too low', make_sm(lead_one=make_lead(v_rel=LEAD_DEPARTURE_MIN_SPEED - 0.01))),
-      ('lead braking', make_sm(lead_one=make_lead(a_lead=-0.01))),
-      ('gas', make_sm(gas=True)),
-      ('brake', make_sm(brake=True)),
-      ('override', make_sm(override=True)),
-      ('force decel', make_sm(force_decel=True)),
-      ('long inactive', make_sm(long_active=False)),
-      ('long control off', make_sm(long_state=LongCtrlState.off)),
-      ('ego rolling', make_sm(v_ego=0.3)),
-      ('radar CAN error', make_sm(radar_error='canError')),
-      ('radar fault', make_sm(radar_error='radarFault')),
-      ('radar config', make_sm(radar_error='wrongConfig')),
-      ('radar unavailable', make_sm(radar_error='radarUnavailableTemporary')),
-    )
-    for name, sm in cases:
-      with self.subTest(name=name):
-        controller = LeadDepartureController(True)
-        activate(controller)
-        assert update(controller, sm)
-        assert not controller.active
-
-  def test_active_release_cancels_on_invalid_update_input(self):
-    cases = (('negative target', -0.01, False, True), ('reset', 0.05, True, True), ('radar invalid', 0.05, False, False))
-    for name, a_target, reset, radar_valid in cases:
-      with self.subTest(name=name):
-        controller = LeadDepartureController(True)
-        activate(controller)
-        assert update(controller, make_sm(), a_target=a_target, reset=reset, radar_valid=radar_valid)
-        assert not controller.active
-
-  def test_inactive_controller_arms_only_from_native_stop_and_stopping_state(self):
-    controller = LeadDepartureController(True)
-    for d_rel in (4.00, 4.02, 4.04):
-      assert not update(controller, make_sm(lead_one=make_lead(d_rel=d_rel)), should_stop=False)
-    for d_rel in (4.00, 4.02, 4.04):
-      assert update(controller, make_sm(lead_one=make_lead(d_rel=d_rel), long_state=LongCtrlState.pid))
-    assert not controller.active
-
-  def test_capability_gate_disables_controller(self):
-    controller = LeadDepartureController(False)
-    for d_rel in (4.00, 4.02, 4.04):
-      assert update(controller, make_sm(lead_one=make_lead(d_rel=d_rel)))
-    assert not controller.active
-
-  def test_closed_loop_departure_releases_earlier_without_a_safety_regression(self):
-    lead_accel = 0.31
-    cue = 1.0 + 0.4 / lead_accel
-
-    def lead_speed(t):
-      return 0.0 if t < 1.0 else min(5.0, lead_accel * (t - 1.0))
-
-    stock, stock_active, stock_resets = run_closed_loop(False, 3.81, lead_speed, 8.0)
-    controller, controller_active, controller_resets = run_closed_loop(True, 3.81, lead_speed, 8.0)
-
-    stock_release = first_delay(stock, cue, 5, lambda should_stop: not should_stop)
-    controller_release = first_delay(controller, cue, 5, lambda should_stop: not should_stop)
-    stock_motion = first_delay(stock, cue, 1, lambda speed: speed > 0.01)
-    controller_motion = first_delay(controller, cue, 1, lambda speed: speed > 0.01)
-    stock_v01 = first_delay(stock, cue, 1, lambda speed: speed > 0.1)
-    controller_v01 = first_delay(controller, cue, 1, lambda speed: speed > 0.1)
-
-    assert any(controller_active) and not any(stock_active)
-    assert stock_resets == controller_resets == 0
-    assert not any(row[6] for row in stock + controller)
-    assert controller_release <= stock_release - 0.5
-    assert stock_motion - controller_motion >= DT_MDL
-    assert stock_v01 - controller_v01 >= DT_MDL
-    assert min(row[3] for row in controller) >= min(row[3] for row in stock)
-    assert max(abs(right[4] - left[4]) for left, right in zip(controller, controller[1:], strict=False)) <= max(
-      abs(right[4] - left[4]) for left, right in zip(stock, stock[1:], strict=False)
-    )
-
-  def test_model_stop_remains_authoritative(self):
-    def lead_speed(t):
-      return 0.0 if t < 1.0 else min(5.0, 0.8 * (t - 1.0))
-
-    rows, active, solver_resets = run_closed_loop(True, 4.0, lead_speed, 6.0, model_should_stop=True, profile_enabled=True)
-
-    assert any(active)
-    assert solver_resets == 0
-    assert all(row[5] for row in rows)
-    assert all(row[1] == 0.0 and row[2] == 0.0 for row in rows)
-    assert not any(row[6] for row in rows)
-
-  def test_stationary_lead_remains_stock_identical(self):
-    stock, stock_active, stock_resets = run_closed_loop(False, 8.0, lambda _t: 0.0, 12.0)
-    controller, controller_active, controller_resets = run_closed_loop(True, 8.0, lambda _t: 0.0, 12.0)
-
-    assert stock == controller
-    assert not any(stock_active) and not any(controller_active)
-    assert stock_resets == controller_resets == 0
-
-  def test_profile_breakaway_assist_moves_with_a_creeping_lead(self):
-    def lead_speed(t):
-      return min(1.1, 0.66 + 0.4 * t)
-
-    baseline, baseline_active, baseline_resets = run_closed_loop(True, 2.8, lead_speed, 8.0)
-    assisted, assisted_active, assisted_resets = run_closed_loop(True, 2.8, lead_speed, 8.0, profile_enabled=True)
-
-    baseline_motion = next((row[0] for row in baseline if row[1] > 0.01), float("inf"))
-    assisted_motion = next(row[0] for row in assisted if row[1] > 0.01)
-    assert any(baseline_active) and any(assisted_active)
-    assert baseline_resets == assisted_resets == 0
-    assert assisted_motion <= 1.0
-    assert baseline_motion - assisted_motion >= 1.0
-    assert min(row[3] for row in assisted) >= min(row[3] for row in baseline) - 1e-9
-    assert not any(row[6] for row in baseline + assisted)
-    assert max(abs(right[8] - left[8]) for left, right in zip(assisted, assisted[1:], strict=False)) <= 4.0 * DT_MDL + 1e-9
-
-  def test_departure_assist_yields_when_the_lead_brakes(self):
-    def lead_speed(t):
-      return 0.8 if t < 0.8 else max(0.0, 0.8 - 4.0 * (t - 0.8))
-
-    rows, active, solver_resets = run_closed_loop(True, 2.8, lead_speed, 5.0, profile_enabled=True)
-
-    assert any(active)
-    assert solver_resets == 0
-    assert min(row[3] for row in rows) > 2.0
-    assert not any(row[6] for row in rows)
-    assert rows[-1][1] == 0.0
-    assert min(row[7] for row in rows if row[0] >= 0.8) < 0.0

openpilot/sunnypilot/selfdrive/controls/lib/tests/test_throttle_intent_arbitration.py

@@ -1,144 +0,0 @@
-"""
-Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
-
-This file is part of sunnypilot and is licensed under the MIT License.
-See the LICENSE.md file in the root directory for more details.
-"""
-
-from types import SimpleNamespace
-from typing import cast
-
-from openpilot.cereal import messaging, custom, log
-from openpilot.common.realtime import DT_MDL
-from openpilot.common.test import OpenpilotTestCase
-from openpilot.selfdrive.controls.lib.longitudinal_planner import get_coast_accel, get_cruise_accel
-from openpilot.sunnypilot.selfdrive.controls.lib.accel_controller.accel_controller import AccelController
-from openpilot.sunnypilot.selfdrive.controls.lib.longitudinal_planner import LongitudinalPlannerSP
-
-PlanSource = log.LongitudinalPlan.LongitudinalPlanSource
-SunnyPlanSource = custom.LongitudinalPlanSP.LongitudinalPlanSource
-
-
-class FakeSubMaster(dict):
-  def __init__(self, lead_one: bool = True, lead_two: bool = False, *, valid: bool = True, alive: bool = True):
-    lead = {'dRel': 120.8, 'vRel': -16.4, 'aLeadK': -1.7}
-    super().__init__(radarState=SimpleNamespace(
-      leadOne=SimpleNamespace(present=lead_one, **lead),
-      leadTwo=SimpleNamespace(present=lead_two, **lead),
-    ), carState=SimpleNamespace(vEgo=17.3),
-      selfdriveState=SimpleNamespace(personality=log.LongitudinalPersonality.standard))
-    self.valid = {'radarState': valid}
-    self.alive = {'radarState': alive}
-
-
-def arbitrate(sm, mpc_accel=0.19, gated_cruise=-0.26, ungated_cruise=0.5, source=PlanSource.lead0,
-              allow_throttle=False, e2e=False, force_decel=False, lead_comfort=False, previous_accel=0.0):
-  planner = make_planner(lead_comfort, previous_accel)
-  return planner.arbitrate_cruise_candidate(
-    cast(messaging.SubMaster, sm), gated_cruise, ungated_cruise, mpc_accel, source,
-    allow_throttle=allow_throttle, e2e=e2e, force_decel=force_decel,
-  )
-
-
-def make_planner(lead_comfort: bool = False, previous_accel: float = 0.0):
-  planner = object.__new__(LongitudinalPlannerSP)
-  planner.accel_controller = AccelController()
-  planner.accel_controller._enabled = lead_comfort
-  planner.source = SunnyPlanSource.cruise
-  planner.output_a_target = previous_accel
-  return planner
-
-
-class TestThrottleIntentArbitration(OpenpilotTestCase):
-  def test_coast_gate_cannot_add_braking_a_valid_lead_does_not_need(self):
-    selected = arbitrate(FakeSubMaster())
-    self.assertEqual(selected, 0.5)
-    self.assertEqual(min(selected, 0.19), 0.19)
-
-  def test_counterfactual_must_select_the_lead(self):
-    self.assertEqual(arbitrate(FakeSubMaster(), ungated_cruise=0.1), -0.26)
-
-  def test_legitimate_cruise_braking_is_preserved(self):
-    self.assertEqual(arbitrate(FakeSubMaster(), gated_cruise=-0.5, ungated_cruise=-0.5), -0.5)
-
-  def test_hard_lead_braking_remains_authoritative(self):
-    selected = arbitrate(FakeSubMaster(), mpc_accel=-0.6)
-    self.assertEqual(selected, -0.26)
-    self.assertEqual(min(selected, -0.6), -0.6)
-
-  def test_lead_comfort_is_only_an_extra_braking_candidate(self):
-    for sm, source in ((FakeSubMaster(), PlanSource.lead0), (FakeSubMaster(False, True), PlanSource.lead1)):
-      cruise = arbitrate(sm, mpc_accel=0.5, gated_cruise=0.5, ungated_cruise=0.5, source=source,
-                         allow_throttle=True, lead_comfort=True, previous_accel=0.2)
-      self.assertLess(cruise, 0.2)
-      self.assertEqual(min(cruise, -1.2), -1.2)
-
-  def test_lead_comfort_requires_a_live_selected_lead(self):
-    for sm, source in ((FakeSubMaster(valid=False), PlanSource.lead0),
-                       (FakeSubMaster(alive=False), PlanSource.lead0),
-                       (FakeSubMaster(lead_one=False), PlanSource.lead0),
-                       (FakeSubMaster(lead_one=True, lead_two=False), PlanSource.lead1)):
-      with self.subTest(source=source):
-        self.assertEqual(arbitrate(sm, gated_cruise=0.5, ungated_cruise=0.5, source=source,
-                                   allow_throttle=True, lead_comfort=True), 0.5)
-
-  def test_policy_requires_live_valid_selected_lead(self):
-    cases = (
-      FakeSubMaster(valid=False),
-      FakeSubMaster(alive=False),
-      FakeSubMaster(lead_one=False),
-      FakeSubMaster(lead_one=True, lead_two=False),
-    )
-    sources = (PlanSource.lead0, PlanSource.lead0, PlanSource.lead0, PlanSource.lead1)
-    for sm, source in zip(cases, sources, strict=True):
-      with self.subTest(source=source, valid=sm.valid, alive=sm.alive):
-        self.assertEqual(arbitrate(sm, source=source), -0.26)
-
-  def test_second_lead_is_supported(self):
-    self.assertEqual(arbitrate(FakeSubMaster(False, True), source=PlanSource.lead1), 0.5)
-
-  def test_bypass_modes_are_stock_identical(self):
-    for allow_throttle, e2e, force_decel in ((True, False, False), (False, True, False), (False, False, True)):
-      with self.subTest(allow_throttle=allow_throttle, e2e=e2e, force_decel=force_decel):
-        selected = arbitrate(FakeSubMaster(), allow_throttle=allow_throttle, e2e=e2e, force_decel=force_decel)
-        self.assertEqual(selected, -0.26)
-
-  def test_nonfinite_inputs_do_not_bypass_gate(self):
-    for gated, ungated, mpc_accel in ((float('nan'), 0.5, 0.2),
-                                      (-0.26, float('inf'), 0.2),
-                                      (-0.26, 0.5, float('nan'))):
-      with self.subTest(gated=gated, ungated=ungated, mpc_accel=mpc_accel):
-        selected = arbitrate(FakeSubMaster(), mpc_accel, gated, ungated)
-        if gated != gated:
-          self.assertNotEqual(selected, selected)
-        else:
-          self.assertEqual(selected, gated)
-
-  def test_5c4_shape_keeps_positive_lead_authoritative_until_it_brakes(self):
-    class CarParams:
-      steerRatio = 15.0
-      wheelbase = 2.7
-
-    planner = make_planner()
-    sm = FakeSubMaster()
-    v_ego = 6.9
-    v_cruise = 30.0
-    accel_coast = get_coast_accel(-0.007)
-    cruise_accel = 0.185
-    mpc_trace = (0.18, 0.175, 0.165, 0.126, 0.06, -0.10, -0.30)
-    outputs = []
-
-    for mpc_accel in mpc_trace:
-      previous_cruise_accel = cruise_accel
-      gated = get_cruise_accel(False, v_cruise, v_ego, previous_cruise_accel, 0.0,
-                                CarParams(), DT_MDL, accel_coast, False, 1.45)
-      ungated = get_cruise_accel(False, v_cruise, v_ego, previous_cruise_accel, 0.0,
-                                  CarParams(), DT_MDL, accel_coast, True, 1.45)
-      cruise_accel = planner.arbitrate_cruise_candidate(
-        cast(messaging.SubMaster, sm), gated, ungated, mpc_accel, PlanSource.lead0,
-        allow_throttle=False, e2e=False, force_decel=False,
-      )
-      outputs.append(min(cruise_accel, mpc_accel))
-      self.assertLessEqual(abs(cruise_accel - previous_cruise_accel), 0.07)
-
-    self.assertEqual(outputs, list(mpc_trace))

openpilot/sunnypilot/selfdrive/controls/lib/tests/test_throttle_intent_controller.py

@@ -1,104 +0,0 @@
-"""
-Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
-
-This file is part of sunnypilot and is licensed under the MIT License.
-See the LICENSE.md file in the root directory for more details.
-"""
-
-import math
-
-from openpilot.common.test import OpenpilotTestCase
-from openpilot.sunnypilot.selfdrive.controls.lib.throttle_intent_controller import ThrottleIntentController
-
-
-class TestAllowThrottle(OpenpilotTestCase):
-  def setUp(self):
-    self.controller = ThrottleIntentController()
-
-  def update(self, throttle_prob: float, low_speed_override: bool = False) -> bool:
-    return self.controller.update(throttle_prob, low_speed_override=low_speed_override, threshold=0.4)
-
-  def test_short_probability_dip(self):
-    self.assertTrue(self.update(1.0))
-    self.assertTrue(self.update(0.0))
-    self.assertTrue(self.update(0.0))
-    self.assertTrue(self.update(0.0))
-
-  def test_probability_chatter(self):
-    self.assertTrue(self.update(1.0))
-    for _ in range(100):
-      self.assertTrue(self.update(0.39))
-      self.assertTrue(self.update(0.46))
-
-    self.controller = ThrottleIntentController()
-    for _ in range(10):
-      self.update(0.0)
-    self.assertFalse(self.update(0.0))
-    for _ in range(100):
-      self.assertFalse(self.update(0.39))
-      self.assertFalse(self.update(0.46))
-
-  def test_sustained_probability_changes(self):
-    self.assertTrue(self.update(1.0))
-    states = [self.update(0.0) for _ in range(8)]
-    self.assertTrue(all(states[:-1]))
-    self.assertFalse(states[-1])
-
-    for _ in range(20):
-      self.assertFalse(self.update(0.0))
-    self.assertEqual([self.update(1.0) for _ in range(2)], [False, True])
-
-  def test_threshold_boundaries(self):
-    for _ in range(6):
-      state = self.update(0.4)
-    self.assertFalse(state)
-    self.controller.prob_filter.x = 0.44
-    self.controller.prob_filter.initialized = True
-    self.assertFalse(self.update(0.44))
-    self.controller.prob_filter.x = 0.46
-    self.assertTrue(self.update(0.46))
-
-  def test_low_speed_override(self):
-    for _ in range(20):
-      self.assertTrue(self.update(0.0, True))
-
-    self.assertTrue(self.update(1.0))
-    self.assertTrue(self.update(math.nan, True))
-    self.assertEqual(self.controller.prob_filter.x, 0.45)
-    self.assertTrue(self.controller.prob_filter.initialized)
-    self.assertTrue(self.update(1.0))
-    for _ in range(20):
-      self.assertTrue(self.update(0.0, True))
-    states = [self.update(0.0) for _ in range(6)]
-    self.assertTrue(all(states[:-1]))
-    self.assertFalse(states[-1])
-
-  def test_nonfinite_probability(self):
-    self.assertTrue(self.update(1.0))
-    for value in (math.inf, -math.inf, math.nan):
-      self.assertFalse(self.update(value))
-      self.assertTrue(math.isfinite(self.controller.prob_filter.x))
-
-    self.assertFalse(self.update(1.0))
-    self.assertTrue(self.update(1.0))
-
-  def test_route_probability_trace(self):
-    probabilities = (0.941, 0.093, 0.070, 0.429, 0.430, 0.083, 0.509, 0.068)
-    states = [self.update(probability) for probability in probabilities]
-    self.assertTrue(all(states))
-
-  def test_sustained_low_probability_still_disables_throttle(self):
-    self.assertTrue(self.update(1.0))
-    states = [self.update(0.0) for _ in range(20)]
-    self.assertFalse(all(states))
-    self.assertFalse(states[-1])
-
-  def test_filter_updates_once(self):
-    self.assertTrue(self.update(1.0))
-    self.assertTrue(self.update(0.0))
-    self.assertAlmostEqual(self.controller.prob_filter.x, 2.0 / 3.0)
-
-  def test_disable_dwell_uses_wall_time(self):
-    self.controller = ThrottleIntentController(dt=0.1)
-    states = [self.update(0.0) for _ in range(3)]
-    self.assertEqual(states, [True, True, False])

openpilot/sunnypilot/selfdrive/controls/lib/throttle_intent_controller.py

@@ -1,53 +0,0 @@
-"""
-Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
-
-This file is part of sunnypilot and is licensed under the MIT License.
-See the LICENSE.md file in the root directory for more details.
-"""
-
-import math
-
-from openpilot.common.filter_simple import FirstOrderFilter
-from openpilot.common.realtime import DT_MDL
-
-THROTTLE_PROB_FILTER_RC = 0.10
-THROTTLE_PROB_HYSTERESIS = 0.05
-THROTTLE_DISABLE_TIME = 0.30
-
-
-class ThrottleIntentController:
-  def __init__(self, dt: float = DT_MDL):
-    self.disable_frames = max(1, math.ceil(THROTTLE_DISABLE_TIME / dt))
-    self.allow_throttle = True
-    self.disallow_frames = 0
-    self.prob_filter = FirstOrderFilter(0.0, THROTTLE_PROB_FILTER_RC, dt, initialized=False)
-
-  def update(self, throttle_prob: float, *, low_speed_override: bool, threshold: float) -> bool:
-    if low_speed_override:
-      self.allow_throttle = True
-      self.disallow_frames = 0
-      self.prob_filter.x = threshold + THROTTLE_PROB_HYSTERESIS
-      self.prob_filter.initialized = True
-      return True
-
-    if not math.isfinite(throttle_prob):
-      self.allow_throttle = False
-      self.disallow_frames = 0
-      self.prob_filter.x = 0.0
-      self.prob_filter.initialized = True
-      return False
-
-    filtered_throttle_prob = self.prob_filter.update(throttle_prob)
-    if self.allow_throttle:
-      if filtered_throttle_prob <= threshold:
-        self.disallow_frames += 1
-        if self.disallow_frames >= self.disable_frames:
-          self.allow_throttle = False
-          self.disallow_frames = 0
-      else:
-        self.disallow_frames = 0
-    elif filtered_throttle_prob > threshold + THROTTLE_PROB_HYSTERESIS:
-      self.allow_throttle = True
-      self.disallow_frames = 0
-
-    return self.allow_throttle

openpilot/sunnypilot/selfdrive/locationd/tests/test_locationd.py

@@ -83,9 +83,14 @@ class TestLocationdProc(OpenpilotTestCase):
       self.pm.send(msg.which(), msg)
       if msg.which() == "cameraOdometry":
         self.pm.wait_for_readers_to_update(msg.which(), timeout=1, dt=0.005)
-    time.sleep(1)  # wait for async params write
+    for _ in range(50):
+      val = self.params.get('LastGPSPositionLLK')
+      if val is not None:
+        break
+      time.sleep(0.1)
 
-    lastGPS = json.loads(self.params.get('LastGPSPositionLLK'))
+    self.assertIsNotNone(val, "LastGPSPositionLLK not written within 5s")
+    lastGPS = json.loads(val)
     self.assertAlmostEqual(lastGPS['latitude'], self.lat, delta=0.001)
     self.assertAlmostEqual(lastGPS['longitude'], self.lon, delta=0.001)
     self.assertAlmostEqual(lastGPS['altitude'], self.alt, delta=0.001)

openpilot/sunnypilot/selfdrive/test/longitudinal_maneuvers/plant.py

@@ -1,433 +0,0 @@
-"""
-Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
-
-This file is part of sunnypilot and is licensed under the MIT License.
-See the LICENSE.md file in the root directory for more details.
-"""
-
-from collections import deque
-from collections.abc import Callable
-from dataclasses import asdict, dataclass
-import math
-import time
-from typing import Any
-
-import numpy as np
-
-from openpilot.cereal import log, messaging
-from opendbc.car.interfaces import ACCEL_MAX, ACCEL_MIN
-from openpilot.common.realtime import DT_CTRL, DT_MDL, Ratekeeper
-from openpilot.selfdrive.modeld.constants import ModelConstants
-from openpilot.selfdrive.controls.lib.longcontrol import LongControl, LongCtrlState
-from openpilot.selfdrive.controls.lib.longitudinal_planner import LongitudinalPlanner
-from openpilot.selfdrive.controls.radard import _LEAD_ACCEL_TAU
-from openpilot.selfdrive.test.longitudinal_maneuvers.plant import Plant, PlannerSM
-
-
-LeadObservation = dict[str, Any]
-LeadObservationFn = Callable[[float, str, LeadObservation], LeadObservation | None]
-ModelActionFn = Callable[[float, float, float], tuple[float, bool]]
-EgoObservationFn = Callable[[float, float, float], tuple[float, float]]
-ModelPlanFn = Callable[[float, float, float], list[float]]
-ModelMetaFn = Callable[[float], tuple[list[float], bool, float]]
-LeadFutureProbsFn = Callable[[float], tuple[float, float, float]]
-PositionYFn = Callable[[float], list[float]]
-ExperimentalModeFn = Callable[[float], bool]
-
-
-@dataclass(frozen=True)
-class ActuatorModel:
-  planner_delay: float
-  transport_delay: float
-  actuator_lag: float
-  command_rate_limit: float
-  stopping_acceleration: float
-  standstill_breakaway_acceleration: float
-  standstill_breakaway_time: float
-
-  def __post_init__(self):
-    nonnegative_fields = {
-      "planner_delay": self.planner_delay,
-      "transport_delay": self.transport_delay,
-      "actuator_lag": self.actuator_lag,
-      "standstill_breakaway_acceleration": self.standstill_breakaway_acceleration,
-      "standstill_breakaway_time": self.standstill_breakaway_time,
-    }
-    if any(not math.isfinite(value) or value < 0.0 for value in nonnegative_fields.values()):
-      raise ValueError(f"ActuatorModel fields must be finite and non-negative: {nonnegative_fields}")
-    if not math.isfinite(self.command_rate_limit) or self.command_rate_limit <= 0.0:
-      raise ValueError("command_rate_limit must be finite and positive")
-    if not math.isfinite(self.stopping_acceleration) or self.stopping_acceleration > 0.0:
-      raise ValueError("stopping_acceleration must be finite and non-positive")
-
-
-# Conservative Prius TSS2 actuator model.
-PRIUS_TSS2_ROUTE_MODEL = ActuatorModel(
-  planner_delay=0.05,
-  transport_delay=0.0,
-  actuator_lag=0.20,
-  command_rate_limit=4.0,
-  stopping_acceleration=-2.0,
-  standstill_breakaway_acceleration=1.0,
-  standstill_breakaway_time=0.05,
-)
-
-
-class PlantSP(Plant):
-  """Closed-loop plant with configurable observations and actuator response."""
-
-  def __init__(
-    self,
-    lead_relevancy=False,
-    speed=0.0,
-    distance_lead=2.0,
-    enabled=True,
-    only_lead2=False,
-    only_radar=False,
-    e2e=False,
-    personality=0,
-    force_decel=False,
-    lead_observation_fn: LeadObservationFn | None = None,
-    model_action_fn: ModelActionFn | None = None,
-    ego_observation_fn: EgoObservationFn | None = None,
-    model_plan_fn: ModelPlanFn | None = None,
-    model_meta_fn: ModelMetaFn | None = None,
-    lead_future_probs_fn: LeadFutureProbsFn | None = None,
-    position_y_fn: PositionYFn | None = None,
-    experimental_mode_fn: ExperimentalModeFn | None = None,
-    actuator_delay: float | None = None,
-    actuator_lag: float = 0.0,
-    actuator_model: ActuatorModel | None = None,
-    run_long_control: bool = False,
-  ):
-    if actuator_delay is not None and (not math.isfinite(actuator_delay) or actuator_delay < 0.0):
-      raise ValueError("actuator_delay must be finite and non-negative")
-    if not math.isfinite(actuator_lag) or actuator_lag < 0.0:
-      raise ValueError("actuator_lag must be finite and non-negative")
-
-    self.rate = 1.0 / DT_MDL
-
-    if not Plant.messaging_initialized:
-      Plant.radar = messaging.pub_sock('radarState')
-      Plant.controls_state = messaging.pub_sock('controlsState')
-      Plant.selfdrive_state = messaging.pub_sock('selfdriveState')
-      Plant.car_state = messaging.pub_sock('carState')
-      Plant.plan = messaging.sub_sock('longitudinalPlan')
-      Plant.messaging_initialized = True
-
-    self.v_lead_prev = 0.0
-
-    self.distance = 0.0
-    self.speed = speed
-    self.should_stop = False
-    self.acceleration = 0.0
-    self.a_target = 0.0
-    self.actuator_command = 0.0
-    self.applied_actuator_command = 0.0
-    self.breakaway_confirmed = False
-    self._breakaway_timer = 0.0
-
-    # lead car
-    self.lead_relevancy = lead_relevancy
-    self.distance_lead = distance_lead
-    self.enabled = enabled
-    self.only_lead2 = only_lead2
-    self.only_radar = only_radar
-    self.e2e = e2e
-    self.personality = personality
-    self.force_decel = force_decel
-    self.lead_observation_fn = lead_observation_fn
-    self.model_action_fn = model_action_fn
-    self.ego_observation_fn = ego_observation_fn
-    self.model_plan_fn = model_plan_fn
-    self.model_meta_fn = model_meta_fn
-    self.lead_future_probs_fn = lead_future_probs_fn
-    self.position_y_fn = position_y_fn
-    self.experimental_mode_fn = experimental_mode_fn
-    self.actuator_model = actuator_model
-    self.actuator_delay = actuator_model.planner_delay if actuator_model is not None else actuator_delay
-    self.transport_delay = actuator_model.transport_delay if actuator_model is not None else actuator_delay
-    self.actuator_lag = actuator_model.actuator_lag if actuator_model is not None else actuator_lag
-    self.publish_realized_a_ego = any((lead_observation_fn is not None, model_action_fn is not None, ego_observation_fn is not None,
-                                      actuator_delay is not None, actuator_lag > 0.0, actuator_model is not None, run_long_control))
-
-    self.rk = Ratekeeper(self.rate, print_delay_threshold=100.0)
-    self.ts = 1.0 / self.rate
-    time.sleep(0.1)
-    self.sm = messaging.SubMaster(['longitudinalPlan'])
-
-    from opendbc.car.honda.values import CAR
-    from opendbc.car.honda.interface import CarInterface
-
-    CP = CarInterface.get_non_essential_params(CAR.HONDA_CIVIC)
-    if self.actuator_delay is not None:
-      CP.longitudinalActuatorDelay = self.actuator_delay
-    CP_SP = CarInterface.get_non_essential_params_sp(CP, CAR.HONDA_CIVIC)
-    self.planner = LongitudinalPlanner(CP, CP_SP, init_v=self.speed)
-    self.long_control = LongControl(CP, CP_SP) if run_long_control else None
-
-    if self.actuator_model is not None and self.speed >= 0.01:
-      self.breakaway_confirmed = True
-    self.integration_dt = DT_CTRL if run_long_control else self.ts
-    delay_steps = 0 if self.transport_delay is None else round(self.transport_delay / self.integration_dt)
-    self._actuator_delay_queue = deque([self.acceleration] * delay_steps)
-
-  @staticmethod
-  def _lead_message(observation: LeadObservation):
-    lead = log.RadarState.LeadData.new_message()
-    for field, value in observation.items():
-      setattr(lead, field, value)
-    return lead
-
-  def _observe_lead(self, lead_name: str, truth: LeadObservation, present_by_default: bool) -> LeadObservation | None:
-    if self.lead_observation_fn is None:
-      return dict(truth) if present_by_default else None
-
-    observed = self.lead_observation_fn(self.current_time, lead_name, dict(truth))
-    if observed is None:
-      return None
-
-    complete_observation = dict(truth)
-    complete_observation.update(observed)
-    return complete_observation
-
-  def _update_actuator(self, command: float) -> tuple[float, float]:
-    if self._actuator_delay_queue:
-      self._actuator_delay_queue.append(command)
-      delayed_command = self._actuator_delay_queue.popleft()
-    else:
-      delayed_command = command
-
-    if self.actuator_model is not None:
-      max_command_delta = self.actuator_model.command_rate_limit * self.integration_dt
-      self.applied_actuator_command = float(np.clip(delayed_command,
-                                                   self.applied_actuator_command - max_command_delta,
-                                                   self.applied_actuator_command + max_command_delta))
-
-      if self.speed < 0.01:
-        if self.applied_actuator_command <= 0.0:
-          self.breakaway_confirmed = False
-          self._breakaway_timer = 0.0
-        elif not self.breakaway_confirmed:
-          breakaway_ready = self.applied_actuator_command + 1e-9 >= self.actuator_model.standstill_breakaway_acceleration
-          if breakaway_ready:
-            self._breakaway_timer += self.integration_dt
-          else:
-            self._breakaway_timer = 0.0
-
-          self.breakaway_confirmed = breakaway_ready and self._breakaway_timer + 1e-9 >= self.actuator_model.standstill_breakaway_time
-        if not self.breakaway_confirmed:
-          self.acceleration = 0.0
-          return delayed_command, self.acceleration
-      else:
-        self.breakaway_confirmed = True
-
-      response_command = self.applied_actuator_command
-    else:
-      self.applied_actuator_command = delayed_command
-      response_command = delayed_command
-
-    if self.actuator_lag > 0.0:
-      alpha = 1.0 - math.exp(-self.integration_dt / self.actuator_lag)
-      self.acceleration += alpha * (response_command - self.acceleration)
-    else:
-      self.acceleration = response_command
-    return delayed_command, self.acceleration
-
-  def _integrate_ego(self, dt: float, stop_at_standstill: bool = False) -> None:
-    self.speed += self.acceleration * dt
-    if self.speed <= 0.0 or stop_at_standstill and self.speed < 0.01 and self.actuator_command <= 0.0:
-      self.speed = self.acceleration = 0.0
-    self.distance += self.speed * dt
-
-  def step(self, v_lead=0.0, prob_lead=1.0, v_cruise=50.0, pitch=0.0, prob_throttle=1.0):
-    # ******** publish a fake model going straight and fake calibration ********
-    # note that this is worst case for MPC, since model will delay long mpc by one time step
-    radar = messaging.new_message('radarState')
-    control = messaging.new_message('controlsState')
-    ss = messaging.new_message('selfdriveState')
-    car_state = messaging.new_message('carState')
-    vehicle_parameters = messaging.new_message('vehicleParameters')
-    car_control = messaging.new_message('carControl')
-    model = messaging.new_message('modelV2')
-    car_state_sp = messaging.new_message('carStateSP')
-    live_map_data_sp = messaging.new_message('liveMapDataSP')
-    gps_data = messaging.new_message('gpsLocation')
-    a_lead = (v_lead - self.v_lead_prev) / self.ts
-    self.v_lead_prev = v_lead
-
-    if self.lead_relevancy:
-      d_rel = np.maximum(0.0, self.distance_lead - self.distance)
-      v_rel = v_lead - self.speed
-      if self.only_radar:
-        status = True
-      elif prob_lead > 0.5:
-        status = True
-      else:
-        status = False
-    else:
-      d_rel = 200.0
-      v_rel = 0.0
-      prob_lead = 0.0
-      status = False
-
-    truth_lead: LeadObservation = {
-      "dRel": float(d_rel),
-      "yRel": 0.0,
-      "vRel": float(v_rel),
-      "vLead": float(v_lead),
-      "vLeadK": float(v_lead),
-      "aLeadK": float(a_lead),
-      "present": bool(status),
-      # TODO use real radard logic for this
-      "aLeadTau": float(_LEAD_ACCEL_TAU),
-      "modelProb": float(prob_lead),
-      "radar": bool(self.only_radar),
-      "radarTrackId": -1,
-    }
-    lead_one_observation = self._observe_lead("leadOne", truth_lead, not self.only_lead2)
-    lead_two_observation = self._observe_lead("leadTwo", truth_lead, True)
-    if lead_one_observation is not None:
-      radar.radarState.leadOne = self._lead_message(lead_one_observation)
-    if lead_two_observation is not None:
-      radar.radarState.leadTwo = self._lead_message(lead_two_observation)
-
-    # Simulate model predicting slightly faster speed
-    # this is to ensure lead policy is effective when model
-    # does not predict slowdown in e2e mode
-    position = log.XYZTData.new_message()
-    position.x = [float(x) for x in (self.speed + 0.5) * np.array(ModelConstants.T_IDXS)]
-    if self.position_y_fn is None:
-      position.y = [0.0] * len(ModelConstants.T_IDXS)
-    else:
-      position.y = [float(y) for y in self.position_y_fn(self.current_time)]
-    model.modelV2.position = position
-    if self.model_action_fn is None:
-      model_acceleration, model_should_stop = self.acceleration + 0.5, False
-    else:
-      model_acceleration, model_should_stop = self.model_action_fn(self.current_time, self.speed, self.acceleration)
-    model.modelV2.action.desiredAcceleration = float(model_acceleration)
-    model.modelV2.action.shouldStop = bool(model_should_stop)
-    velocity = log.XYZTData.new_message()
-    if self.model_plan_fn is None:
-      velocity_plan = [float(x) for x in (self.speed + 0.5) * np.ones_like(ModelConstants.T_IDXS)]
-      velocity_plan[0] = float(self.speed)  # always start at current speed
-    else:
-      velocity_plan = [float(x) for x in self.model_plan_fn(self.current_time, self.speed, self.acceleration)]
-    velocity.x = velocity_plan
-    model.modelV2.velocity = velocity
-    acceleration = log.XYZTData.new_message()
-    acceleration.x = [float(x) for x in np.zeros_like(ModelConstants.T_IDXS)]
-    model.modelV2.acceleration = acceleration
-    model.modelV2.meta.disengagePredictions.gasPressProbs = [float(prob_throttle) for _ in range(6)]
-    if self.model_meta_fn is None:
-      brake3_probs, hard_brake_predicted, frame_drop_perc = [0.0] * 5, False, 0.0
-    else:
-      brake3_probs, hard_brake_predicted, frame_drop_perc = self.model_meta_fn(self.current_time)
-    model.modelV2.meta.disengagePredictions.brake3MetersPerSecondSquaredProbs = [float(p) for p in brake3_probs]
-    model.modelV2.meta.hardBrakePredicted = bool(hard_brake_predicted)
-    model.modelV2.frameDropPerc = float(frame_drop_perc)
-    if self.lead_future_probs_fn is not None:
-      model.modelV2.init('leadsV3', 3)
-      lead_future_probs = self.lead_future_probs_fn(self.current_time)
-      for i, (prob, prob_time) in enumerate(zip(lead_future_probs, (0.0, 2.0, 4.0), strict=True)):
-        model.modelV2.leadsV3[i].prob = float(prob)
-        model.modelV2.leadsV3[i].probTime = prob_time
-
-    control.controlsState.longControlState = self.long_control.long_control_state if self.long_control is not None else (
-      LongCtrlState.pid if self.enabled else LongCtrlState.off)
-    ss.selfdriveState.experimentalMode = self.e2e if self.experimental_mode_fn is None else bool(self.experimental_mode_fn(self.current_time))
-    ss.selfdriveState.personality = self.personality
-    control.controlsState.forceDecel = self.force_decel
-    true_v_ego = self.speed
-    true_a_ego = self.acceleration
-    published_v_ego = true_v_ego
-    published_a_ego = true_a_ego if self.publish_realized_a_ego else 0.0
-    if self.ego_observation_fn is not None:
-      published_v_ego, published_a_ego = self.ego_observation_fn(self.current_time, true_v_ego, true_a_ego)
-    car_state.carState.vEgo = float(published_v_ego)
-    car_state.carState.aEgo = float(published_a_ego)
-    car_state.carState.standstill = bool(self.speed < 0.01)
-    car_state.carState.vCruise = float(v_cruise * 3.6)
-    car_control.carControl.orientationNED = [0.0, float(pitch), 0.0]
-
-    # ******** get controlsState messages for plotting ***
-    sm = PlannerSM(self.rk.frame, {
-      'radarState': radar.radarState,
-      'carState': car_state.carState,
-      'carControl': car_control.carControl,
-      'controlsState': control.controlsState,
-      'selfdriveState': ss.selfdriveState,
-      'vehicleParameters': vehicle_parameters.vehicleParameters,
-      'modelV2': model.modelV2,
-      'carStateSP': car_state_sp.carStateSP,
-      'liveMapDataSP': live_map_data_sp.liveMapDataSP,
-      'gpsLocation': gps_data.gpsLocation,
-    })
-    self.planner.update(sm)
-    self.a_target = self.planner.output_a_target
-    if self.long_control is None:
-      self.actuator_command = self.a_target
-      if self.planner.output_should_stop:
-        stopping_acceleration = -0.5 if self.actuator_model is None else self.actuator_model.stopping_acceleration
-        self.actuator_command = min(stopping_acceleration, self.actuator_command)
-      self._update_actuator(self.actuator_command)
-      self._integrate_ego(self.ts)
-    else:
-      for _ in range(round(self.ts / DT_CTRL)):
-        car_state.carState.vEgo = self.speed
-        car_state.carState.aEgo = self.acceleration
-        car_state.carState.standstill = self.speed < 0.01
-        self.actuator_command = self.long_control.update(
-          self.enabled, car_state.carState, self.a_target, self.planner.output_should_stop, (ACCEL_MIN, ACCEL_MAX),
-        )
-        self._update_actuator(self.actuator_command)
-        self._integrate_ego(DT_CTRL, stop_at_standstill=True)
-    self.should_stop = self.planner.output_should_stop
-    fcw = self.planner.fcw
-    self.distance_lead = self.distance_lead + v_lead * self.ts
-
-    # *** radar model ***
-    if self.lead_relevancy:
-      d_rel = np.maximum(0.0, self.distance_lead - self.distance)
-      v_rel = v_lead - self.speed
-    else:
-      d_rel = 200.0
-      v_rel = 0.0
-
-    # print at 5hz
-    # if (self.rk.frame % (self.rate // 5)) == 0:
-    #   print("%2.2f sec   %6.2f m  %6.2f m/s  %6.2f m/s2   lead_rel: %6.2f m  %6.2f m/s"
-    #         % (self.current_time, self.distance, self.speed, self.acceleration, d_rel, v_rel))
-
-    # ******** update prevs ********
-    self.rk.monitor_time()
-
-    return {
-      "distance": self.distance,
-      "speed": self.speed,
-      "acceleration": self.acceleration,
-      "realized_acceleration": self.acceleration,
-      "a_target": self.a_target,
-      "actuator_command": self.actuator_command,
-      "published_a_ego": published_a_ego,
-      "published_v_ego": published_v_ego,
-      "should_stop": self.should_stop,
-      "long_control_state": (int(self.long_control.long_control_state) if self.long_control is not None
-                             else control.controlsState.longControlState.raw),
-      "distance_lead": self.distance_lead,
-      "fcw": fcw,
-      "mpc_source": self.planner.mpc.source,
-      "dec_mode": self.planner.dec.mode(),
-      "dec_want_blended": self.planner.dec.want_blended,
-      "dec_signals": asdict(self.planner.dec.signals),
-      "dec_lead_veto": self.planner.dec.lead_veto,
-      "controller_active": self.planner.accel_controller_active,
-      "model_action": {
-        "desiredAcceleration": float(model_acceleration),
-        "shouldStop": bool(model_should_stop),
-      },
-      "truth_lead": dict(truth_lead),
-      "lead_one_observation": None if lead_one_observation is None else dict(lead_one_observation),
-      "lead_two_observation": None if lead_two_observation is None else dict(lead_two_observation),
-    }

openpilot/sunnypilot/selfdrive/test/longitudinal_maneuvers/tests/test_dec_maneuvers.py

@@ -1,186 +0,0 @@
-import numpy as np
-
-from openpilot.common.params import Params
-from openpilot.common.realtime import DT_MDL
-from openpilot.common.test import OpenpilotTestCase
-from openpilot.selfdrive.modeld.constants import ModelConstants
-from openpilot.sunnypilot.selfdrive.controls.lib.dec.dec import ENTER_FRAMES, MIN_BLENDED_FRAMES
-from openpilot.sunnypilot.selfdrive.test.longitudinal_maneuvers.plant import PlantSP
-
-T_IDXS = np.array(ModelConstants.T_IDXS)
-
-
-def decel_plan(a):
-  def fn(_current_time, speed, _acceleration):
-    return [float(max(0.0, speed + a * t)) for t in T_IDXS]
-  return fn
-
-
-def flat_plan():
-  def fn(_current_time, speed, _acceleration):
-    return [float(speed)] * len(T_IDXS)
-  return fn
-
-
-def alternating_plan(a):
-  def fn(current_time, speed, _acceleration):
-    frame_a = a if round(current_time / DT_MDL) % 2 == 0 else 0.0
-    return [float(max(0.0, speed + frame_a * t)) for t in T_IDXS]
-  return fn
-
-
-def persistent_lead_probs(_current_time):
-  return (1.0, 0.95, 0.9)
-
-
-def _run(plant, steps, v_lead=0.0, v_cruise=50.0):
-  solver_failures = 0
-  original_reset = plant.planner.mpc.reset
-
-  def counting_reset(*args, **kw):
-    nonlocal solver_failures
-    if plant.planner.mpc.solution_status != 0:
-      solver_failures += 1
-    return original_reset(*args, **kw)
-
-  plant.planner.mpc.reset = counting_reset
-  return [plant.step(v_lead=v_lead, v_cruise=v_cruise) for _ in range(steps)], solver_failures
-
-
-def mode_changes(results):
-  modes = [r["dec_mode"] for r in results]
-  return sum(a != b for a, b in zip(modes, modes[1:], strict=False))
-
-
-class TestDecManeuvers(OpenpilotTestCase):
-  def setUp(self):
-    super().setUp()
-    self.params = Params()
-    self.params.put_bool("DynamicExperimentalControl", True, block=True)
-
-  def test_s1_lead_clears_with_underlying_slowdown_blends_quickly(self):
-    clear_t = 1.0
-
-    def lead_obs(current_time, _lead_name, truth):
-      return None if current_time >= clear_t else dict(truth)
-
-    plant = PlantSP(lead_relevancy=True, speed=20.0, distance_lead=40.0, e2e=True, only_radar=True,
-                     lead_observation_fn=lead_obs, model_plan_fn=decel_plan(-2.5),
-                     lead_future_probs_fn=persistent_lead_probs)
-    clear_frame = round(clear_t / DT_MDL)
-    results, _ = _run(plant, steps=clear_frame + ENTER_FRAMES + 5, v_lead=20.0, v_cruise=20.0)
-
-    assert all(r["dec_mode"] == "acc" for r in results[:clear_frame])
-    assert all(r["dec_lead_veto"] for r in results[:clear_frame])
-    post_clear = [r["dec_mode"] for r in results[clear_frame:clear_frame + ENTER_FRAMES + 2]]
-    assert "blended" in post_clear
-
-  def test_s1b_lead_clears_with_no_underlying_slowdown_stays_acc(self):
-    clear_t = 1.0
-
-    def lead_obs(current_time, _lead_name, truth):
-      return None if current_time >= clear_t else dict(truth)
-
-    plant = PlantSP(lead_relevancy=True, speed=20.0, distance_lead=40.0, e2e=True, only_radar=True,
-                     lead_observation_fn=lead_obs, model_plan_fn=flat_plan(),
-                     lead_future_probs_fn=persistent_lead_probs)
-    clear_frame = round(clear_t / DT_MDL)
-    results, _ = _run(plant, steps=clear_frame + MIN_BLENDED_FRAMES, v_lead=20.0, v_cruise=20.0)
-
-    assert all(r["dec_mode"] == "acc" for r in results)
-
-  def test_s2_steady_highway_following_never_blends(self):
-    v = 80.0 / 3.6
-    plant = PlantSP(lead_relevancy=True, speed=v, distance_lead=40.0, e2e=True, only_radar=True,
-                     model_plan_fn=flat_plan(), lead_future_probs_fn=persistent_lead_probs)
-    results, failures = _run(plant, steps=100, v_lead=v, v_cruise=v)
-
-    assert failures <= 1
-    assert all(r["dec_mode"] == "acc" for r in results)
-
-  def test_s3_low_speed_cruise_no_lead_never_blends(self):
-    v = 15.0 / 3.6
-    plant = PlantSP(lead_relevancy=False, speed=v, e2e=True, model_plan_fn=flat_plan())
-    results, _ = _run(plant, steps=100, v_cruise=v)
-
-    assert all(r["dec_mode"] == "acc" for r in results)
-
-  def test_s4_highway_slowdown_without_lead_blends(self):
-    v0 = 110.0 / 3.6
-    a = (70.0 / 3.6 - v0) / 6.0
-    plant = PlantSP(lead_relevancy=False, speed=v0, e2e=True, model_plan_fn=decel_plan(a))
-    results, _ = _run(plant, steps=10, v_cruise=v0)
-
-    assert any(r["dec_mode"] == "blended" for r in results)
-
-  def test_s5_stop_then_depart_with_lead_present_stays_acc_throughout(self):
-    def departing_lead(current_time):
-      return 0.0 if current_time < 1.0 else min(15.0, 3.0 * (current_time - 1.0))
-
-    plant = PlantSP(lead_relevancy=True, speed=0.0, distance_lead=6.0, e2e=True)
-    results = []
-    solver_failures = 0
-    original_reset = plant.planner.mpc.reset
-
-    def counting_reset(*args, **kw):
-      nonlocal solver_failures
-      if plant.planner.mpc.solution_status != 0:
-        solver_failures += 1
-      return original_reset(*args, **kw)
-
-    plant.planner.mpc.reset = counting_reset
-    for _ in range(200):
-      results.append(plant.step(v_lead=departing_lead(plant.current_time), v_cruise=15.0))
-
-    assert solver_failures <= 1
-    assert all(r["dec_mode"] == "acc" for r in results)
-    assert all(r["dec_lead_veto"] for r in results)
-
-  def test_s6_creep_cycles_behind_lead_stay_acc(self):
-    def creep_cycle_lead(current_time):
-      return 1.5 + 1.5 * np.sin(current_time * 2.0)
-
-    plant = PlantSP(lead_relevancy=True, speed=1.0, distance_lead=8.0, e2e=True, only_radar=True,
-                     model_plan_fn=flat_plan(), lead_future_probs_fn=persistent_lead_probs)
-    results = [plant.step(v_lead=creep_cycle_lead(plant.current_time), v_cruise=5.0) for _ in range(200)]
-
-    assert all(r["dec_mode"] == "acc" for r in results)
-
-  def test_s7_oscillating_near_threshold_demand_does_not_flap(self):
-    plant = PlantSP(lead_relevancy=False, speed=20.0, e2e=True, model_plan_fn=alternating_plan(-2.5))
-    results, _ = _run(plant, steps=200, v_cruise=20.0)
-
-    assert mode_changes(results) <= 2
-
-  def test_s8_degraded_model_holds_acc_through_a_slowdown(self):
-    def degraded_meta(_current_time):
-      return [0.0] * 5, False, 60.0
-
-    plant = PlantSP(lead_relevancy=False, speed=20.0, e2e=True, model_plan_fn=decel_plan(-3.0), model_meta_fn=degraded_meta)
-    results, _ = _run(plant, steps=30, v_cruise=20.0)
-
-    assert all(r["dec_mode"] == "acc" for r in results)
-
-  def test_s9_curve_exclusion_prevents_false_blend_on_a_bend(self):
-    plant = PlantSP(lead_relevancy=False, speed=20.0, e2e=True, model_plan_fn=decel_plan(-1.0),
-                     position_y_fn=lambda _t: [6.0] * len(T_IDXS))
-    results, _ = _run(plant, steps=30, v_cruise=20.0)
-
-    assert all(r["dec_mode"] == "acc" for r in results)
-
-  def test_s11_curve_does_not_interrupt_an_active_hard_stop(self):
-    plant = PlantSP(lead_relevancy=False, speed=20.0, e2e=True, model_plan_fn=decel_plan(-2.5),
-                     position_y_fn=lambda _t: [6.0] * len(T_IDXS))
-    results, _ = _run(plant, steps=10, v_cruise=20.0)
-
-    assert all(r["dec_mode"] == "blended" for r in results[ENTER_FRAMES - 1:])
-
-  def test_s10_hard_brake_override_inert_while_lead_present(self):
-    def hard_brake_meta(_current_time):
-      return [0.0] * 5, True, 0.0
-
-    plant = PlantSP(lead_relevancy=True, speed=20.0, distance_lead=40.0, e2e=True, only_radar=True,
-                     model_plan_fn=flat_plan(), model_meta_fn=hard_brake_meta, lead_future_probs_fn=persistent_lead_probs)
-    results, _ = _run(plant, steps=10, v_lead=20.0, v_cruise=20.0)
-
-    assert all(r["dec_mode"] == "acc" for r in results)

openpilot/sunnypilot/selfdrive/test/longitudinal_maneuvers/tests/test_plant_sp.py

@@ -1,164 +0,0 @@
-from collections.abc import Callable
-import math
-from typing import cast
-
-from openpilot.common.parameterized import parameterized
-from openpilot.common.realtime import DT_MDL
-from openpilot.common.test import OpenpilotTestCase
-from openpilot.selfdrive.test.longitudinal_maneuvers.plant import Plant
-from openpilot.sunnypilot.selfdrive.test.longitudinal_maneuvers.plant import PlantSP
-
-STOCK_STEP_KEYS = ("distance", "speed", "acceleration", "should_stop", "distance_lead", "fcw")
-
-
-def departing_lead(current_time: float) -> float:
-  return 0.0 if current_time < 1.0 else min(2.0, 2.0 * (current_time - 1.0))
-
-
-def stopped_lead(_current_time: float) -> float:
-  return 0.0
-
-
-PARITY_SCENARIOS = {
-  "approach_stopped_lead": {"lead_relevancy": True, "speed": 15.0, "distance_lead": 60.0, "v_cruise": 20.0, "v_lead": stopped_lead, "steps": 80},
-  "stop_then_depart": {"lead_relevancy": True, "speed": 0.0, "distance_lead": 6.0, "v_cruise": 8.0, "v_lead": departing_lead, "steps": 120},
-}
-
-
-def _drive(cls, *, v_cruise: float, v_lead: Callable[[float], float], steps: int, **kwargs):
-  plant = cls(**kwargs)
-  plant.v_lead_prev = v_lead(0.0)
-  solver_failures = 0
-  original_reset = plant.planner.mpc.reset
-
-  def counting_reset(*args, **kw):
-    nonlocal solver_failures
-    if plant.planner.mpc.solution_status != 0:
-      solver_failures += 1
-    return original_reset(*args, **kw)
-
-  plant.planner.mpc.reset = counting_reset
-  results = []
-  for _ in range(steps):
-    lead_speed = v_lead(plant.current_time)
-    result = plant.step(v_lead=lead_speed, v_cruise=v_cruise)
-    results.append((result, plant.planner.mpc.source, plant.planner.output_a_target))
-  return results, solver_failures
-
-
-class TestPlantSP(OpenpilotTestCase):
-  @parameterized.expand(PARITY_SCENARIOS, names=("scenario",), ids=lambda scenario: scenario)
-  def test_plant_sp_matches_stock_plant_on_shared_kwargs(self, scenario: str):
-    kwargs = dict(PARITY_SCENARIOS[scenario])
-    v_cruise = cast(float, kwargs.pop("v_cruise"))
-    v_lead = cast(Callable[[float], float], kwargs.pop("v_lead"))
-    steps = cast(int, kwargs.pop("steps"))
-
-    stock_results, stock_failures = _drive(Plant, v_cruise=v_cruise, v_lead=v_lead, steps=steps, **kwargs)
-    sp_results, sp_failures = _drive(PlantSP, v_cruise=v_cruise, v_lead=v_lead, steps=steps, **kwargs)
-
-    assert stock_failures == 0, f"stock Plant solver failed {stock_failures} times in {scenario!r}"
-    assert sp_failures == 0, f"PlantSP solver failed {sp_failures} times in {scenario!r}"
-
-    for frame, ((stock_result, stock_source, stock_a_target), (sp_result, sp_source, sp_a_target)) in enumerate(
-      zip(stock_results, sp_results, strict=True),
-    ):
-      for key in STOCK_STEP_KEYS:
-        if isinstance(stock_result[key], float):
-          self.assertAlmostEqual(sp_result[key], stock_result[key], msg=f"{scenario} frame {frame} key {key}")
-        else:
-          assert sp_result[key] == stock_result[key], f"{scenario} frame {frame} key {key}"
-      assert sp_source == stock_source, f"{scenario} frame {frame} mpc.source"
-      self.assertAlmostEqual(sp_a_target, stock_a_target, msg=f"{scenario} frame {frame} output_a_target")
-
-    if scenario == "stop_then_depart":
-      departure_frame = round(1.0 / DT_MDL)
-      for results in (stock_results, sp_results):
-        assert all(result["speed"] < 0.01 for result, _, _ in results[:departure_frame])
-        assert results[departure_frame - 1][0]["should_stop"]
-        assert any(not result["should_stop"] for result, _, _ in results[departure_frame:])
-        assert any(result["speed"] > 0.05 for result, _, _ in results[departure_frame:])
-      stock_release = next(frame for frame, (result, _, _) in enumerate(stock_results)
-                           if frame >= departure_frame and not result["should_stop"])
-      sp_release = next(frame for frame, (result, _, _) in enumerate(sp_results)
-                        if frame >= departure_frame and not result["should_stop"])
-      stock_motion = next(frame for frame, (result, _, _) in enumerate(stock_results)
-                          if frame >= departure_frame and result["speed"] > 0.05)
-      sp_motion = next(frame for frame, (result, _, _) in enumerate(sp_results)
-                       if frame >= departure_frame and result["speed"] > 0.05)
-      assert sp_release == stock_release
-      assert sp_motion == stock_motion
-
-  def test_full_lead_observation_is_independent_from_truth(self):
-    callback_inputs = []
-
-    def observe_lead(current_time, lead_name, truth):
-      callback_inputs.append((current_time, lead_name, truth))
-      if lead_name == "leadOne":
-        return {
-          "dRel": 12.5,
-          "vRel": -4.0,
-          "vLead": 6.0,
-          "vLeadK": 5.5,
-          "aLeadK": -1.25,
-          "aLeadTau": 0.7,
-          "present": True,
-          "modelProb": 0.9,
-          "radarTrackId": 42,
-        }
-      return None
-
-    plant = PlantSP(lead_relevancy=True, speed=10.0, distance_lead=50.0, lead_observation_fn=observe_lead)
-    result = plant.step(v_lead=8.0)
-
-    assert [entry[1] for entry in callback_inputs] == ["leadOne", "leadTwo"]
-    self.assertAlmostEqual(callback_inputs[0][2]["dRel"], 50.0)
-    self.assertAlmostEqual(result["truth_lead"]["dRel"], 50.0)
-    self.assertAlmostEqual(result["lead_one_observation"]["dRel"], 12.5)
-    assert result["lead_one_observation"]["radarTrackId"] == 42
-    assert result["lead_two_observation"] is None
-    self.assertAlmostEqual(result["distance_lead"], 50.0 + 8.0 * DT_MDL)
-
-  def test_model_action_realized_acceleration_and_source_logging(self):
-    def model_action(current_time, v_ego, a_ego):
-      return -1.25, True
-
-    plant = PlantSP(speed=10.0, e2e=True, force_decel=True, model_action_fn=model_action, actuator_lag=0.5)
-    first = plant.step()
-    second = plant.step()
-
-    assert first["model_action"] == {"desiredAcceleration": -1.25, "shouldStop": True}
-    self.assertAlmostEqual(first["published_a_ego"], 0.0)
-    self.assertAlmostEqual(second["published_a_ego"], first["realized_acceleration"])
-    assert first["acceleration"] == first["realized_acceleration"]
-    assert abs(first["realized_acceleration"]) < abs(first["actuator_command"])
-    assert first["mpc_source"] is not None
-    assert first["dec_mode"] in ("acc", "blended")
-    assert "controller_active" in first
-    assert first["lead_one_observation"] is not None
-    assert first["truth_lead"] == first["lead_one_observation"]
-
-  def test_default_model_action_matches_stock_plant(self):
-    result = PlantSP(speed=10.0).step()
-
-    self.assertAlmostEqual(result["model_action"]["desiredAcceleration"], 0.5)
-    assert not result["model_action"]["shouldStop"]
-
-  def test_configurable_transport_delay_and_first_order_lag(self):
-    plant = PlantSP(speed=10.0, actuator_delay=2 * DT_MDL, actuator_lag=0.2)
-
-    self.assertAlmostEqual(plant.planner.CP.longitudinalActuatorDelay, 2 * DT_MDL)
-    delayed_commands = [plant._update_actuator(-1.0) for _ in range(3)]
-    assert [command for command, _ in delayed_commands[:2]] == [0.0, 0.0]
-
-    expected_acceleration = -(1.0 - math.exp(-DT_MDL / 0.2))
-    assert delayed_commands[2][0] == -1.0
-    self.assertAlmostEqual(delayed_commands[2][1], expected_acceleration)
-
-  @parameterized.expand(
-    [(-0.1, 0.0), (float("nan"), 0.0), (float("inf"), 0.0), (None, -0.1), (None, float("nan")), (None, float("inf"))],
-    names=("delay", "lag"),
-  )
-  def test_invalid_actuator_dynamics(self, delay, lag):
-    with self.assertRaises(ValueError):
-      PlantSP(actuator_delay=delay, actuator_lag=lag)

openpilot/sunnypilot/sunnylink/athena/sunnylinkd.py

@@ -28,7 +28,8 @@ from websocket import (ABNF, WebSocket, WebSocketException, WebSocketTimeoutExce
                        create_connection, WebSocketConnectionClosedException)
 
 import openpilot.cereal.messaging as messaging
-from openpilot.sunnypilot.models.default_model import get_default_model
+from openpilot.selfdrive.modeld.helpers import usbgpu_present, usbgpu_compiled
+from openpilot.sunnypilot.models.model_name import DEFAULT_MODEL, DEFAULT_BIG_MODEL
 from openpilot.sunnypilot.selfdrive.car.sync_sunnylink_params import update_car_list_param
 from openpilot.sunnypilot.sunnylink.api import SunnylinkApi
 from openpilot.sunnypilot.sunnylink.utils import sunnylink_need_register, sunnylink_ready, get_param_as_byte, save_param_from_base64_encoded_string
@@ -181,7 +182,10 @@ def getParamsMetadata() -> str:
     schema = generate_schema()
     schema["capabilities"] = generate_capabilities()
     schema["capability_labels"] = CAPABILITY_LABELS
-    schema["default_model"] = get_default_model()
+    # mirrors get_default_model() — ui_state unavailable in sunnylinkd process
+    show_big = (usbgpu_present() and usbgpu_compiled()
+                and (params.get_bool("UsbGpuActive") or params.get_bool("UsbGpuLoading") or params.get_bool("IsOffroad")))
+    schema["default_model"] = DEFAULT_BIG_MODEL if show_big else DEFAULT_MODEL
     raw = json.dumps(schema, separators=(",", ":")).encode("utf-8")
     return base64.b64encode(gzip.compress(raw)).decode("utf-8")
   except Exception:

openpilot/sunnypilot/sunnylink/settings_ui.json

@@ -652,53 +652,6 @@
                 }
               ]
             },
-            {
-              "key": "AccelPersonalityEnabled",
-              "widget": "toggle",
-              "title": "Enable Accel Controller",
-              "description": "Lets you choose how sunnypilot starts, catches up, and settles at the cruise speed. Emergency braking and stopping are unchanged.",
-              "visibility": [
-                {
-                  "type": "capability",
-                  "field": "has_longitudinal_control",
-                  "equals": true
-                }
-              ],
-              "enablement": [
-                {
-                  "type": "capability",
-                  "field": "has_longitudinal_control",
-                  "equals": true
-                }
-              ]
-            },
-            {
-              "key": "AccelPersonality",
-              "widget": "multiple_button",
-              "title": "Acceleration Profile",
-              "description": "Eco is gentlest, Normal balances a prompt start with smooth catch-up, and Sport is more responsive.",
-              "options": [
-                {
-                  "value": 0,
-                  "label": "Eco"
-                },
-                {
-                  "value": 1,
-                  "label": "Normal"
-                },
-                {
-                  "value": 2,
-                  "label": "Sport"
-                }
-              ],
-              "enablement": [
-                {
-                  "type": "capability",
-                  "field": "has_longitudinal_control",
-                  "equals": true
-                }
-              ]
-            },
             {
               "key": "IntelligentCruiseButtonManagement",
               "widget": "toggle",
@@ -2349,50 +2302,6 @@
       "title": "Toyota / Lexus Settings",
       "description": "",
       "items": [
-        {
-          "key": "ToyotaAutoHold",
-          "widget": "toggle",
-          "needs_onroad_cycle": true,
-          "title": "Toyota: Auto Brake Hold FOR TSS2 HYBRID CARS",
-          "enablement": [
-            {
-              "type": "not_engaged"
-            }
-          ]
-        },
-        {
-          "key": "ToyotaEnhancedBsm",
-          "widget": "toggle",
-          "needs_onroad_cycle": true,
-          "title": "Toyota: Prius TSS2 BSM and some tssp",
-          "enablement": [
-            {
-              "type": "not_engaged"
-            }
-          ]
-        },
-        {
-          "key": "ToyotaTSS2Long",
-          "widget": "toggle",
-          "needs_onroad_cycle": true,
-          "title": "Toyota: custom longitudinal for TSS2",
-          "enablement": [
-            {
-              "type": "not_engaged"
-            }
-          ]
-        },
-        {
-          "key": "ToyotaDriveMode",
-          "widget": "toggle",
-          "needs_onroad_cycle": true,
-          "title": "Enable drive mode btn link",
-          "enablement": [
-            {
-              "type": "not_engaged"
-            }
-          ]
-        },
         {
           "key": "ToyotaEnforceStockLongitudinal",
           "widget": "toggle",

openpilot/sunnypilot/sunnylink/settings_ui_src/pages/cruise.yaml

@@ -43,28 +43,6 @@ sections:
       label: Relaxed
     enablement:
     - $ref: '#/macros/longitudinal'
-  - key: AccelPersonalityEnabled
-    widget: toggle
-    title: Enable Accel Controller
-    description: Lets you choose how sunnypilot starts, catches up, and settles at the cruise speed. Emergency braking and stopping are
-      unchanged.
-    visibility:
-    - $ref: '#/macros/longitudinal'
-    enablement:
-    - $ref: '#/macros/longitudinal'
-  - key: AccelPersonality
-    widget: multiple_button
-    title: Acceleration Profile
-    description: Eco is gentlest, Normal balances a prompt start with smooth catch-up, and Sport is more responsive.
-    options:
-    - value: 0
-      label: Eco
-    - value: 1
-      label: Normal
-    - value: 2
-      label: Sport
-    enablement:
-    - $ref: '#/macros/longitudinal'
   - key: IntelligentCruiseButtonManagement
     widget: toggle
     title: Intelligent Cruise Button Management (ICBM) (Alpha)

openpilot/sunnypilot/sunnylink/settings_ui_src/pages/vehicle.yaml

@@ -82,30 +82,6 @@ sections:
   title: Toyota / Lexus Settings
   description: ''
   items:
-  - key: ToyotaAutoHold
-    widget: toggle
-    needs_onroad_cycle: true
-    title: 'Toyota: Auto Brake Hold FOR TSS2 HYBRID CARS'
-    enablement:
-    - $ref: '#/macros/not_engaged'
-  - key: ToyotaEnhancedBsm
-    widget: toggle
-    needs_onroad_cycle: true
-    title: 'Toyota: Prius TSS2 BSM and some tssp'
-    enablement:
-    - $ref: '#/macros/not_engaged'
-  - key: ToyotaTSS2Long
-    widget: toggle
-    needs_onroad_cycle: true
-    title: 'Toyota: custom longitudinal for TSS2'
-    enablement:
-    - $ref: '#/macros/not_engaged'
-  - key: ToyotaDriveMode
-    widget: toggle
-    needs_onroad_cycle: true
-    title: Enable drive mode btn link
-    enablement:
-    - $ref: '#/macros/not_engaged'
   - key: ToyotaEnforceStockLongitudinal
     widget: toggle
     needs_onroad_cycle: true

openpilot/sunnypilot/sunnylink/tests/test_capabilities.py

@@ -10,10 +10,9 @@ change and must be intentional. KNOWN_PROTOCOL_VERSIONS pins the set we
 explicitly support — when the constant is bumped, this list must be edited in
 the same commit so the bump shows up in code review.
 """
-
 from __future__ import annotations
 
-from openpilot.common.test import OpenpilotTestCase
+
 from openpilot.sunnypilot.sunnylink.capabilities import (
   CAPABILITY_DEFAULTS,
   CAPABILITY_FIELDS,
@@ -21,23 +20,13 @@ from openpilot.sunnypilot.sunnylink.capabilities import (
   PROTOCOL_VERSION,
   generate_capabilities,
 )
+from openpilot.common.test import OpenpilotTestCase
 
 
 KNOWN_PROTOCOL_VERSIONS = (1,)
 LATEST_KNOWN = max(KNOWN_PROTOCOL_VERSIONS)
 
 
-class FakeParams:
-  def __init__(self, values=None):
-    self.values = values or {}
-
-  def get(self, key, *args, **kwargs):
-    return self.values.get(key)
-
-  def get_bool(self, key):
-    return bool(self.values.get(key, False))
-
-
 def caps():
   return generate_capabilities()
 
@@ -63,12 +52,14 @@ class TestProtocolVersion(OpenpilotTestCase):
   def test_protocol_version_is_known(self):
     """Sentinel against accidental bumps. Edit KNOWN_PROTOCOL_VERSIONS if intentional."""
     assert PROTOCOL_VERSION in KNOWN_PROTOCOL_VERSIONS, (
-      f"PROTOCOL_VERSION={PROTOCOL_VERSION} is not in KNOWN_PROTOCOL_VERSIONS={KNOWN_PROTOCOL_VERSIONS}. "
-      + "If this bump is intentional, add it to KNOWN_PROTOCOL_VERSIONS."
+      f"PROTOCOL_VERSION={PROTOCOL_VERSION} is not in KNOWN_PROTOCOL_VERSIONS={KNOWN_PROTOCOL_VERSIONS}. " +
+      "If this bump is intentional, add it to KNOWN_PROTOCOL_VERSIONS."
     )
 
   def test_protocol_version_matches_latest_known(self):
-    assert PROTOCOL_VERSION == LATEST_KNOWN, "Test invariant: PROTOCOL_VERSION must equal max(KNOWN_PROTOCOL_VERSIONS)."
+    assert PROTOCOL_VERSION == LATEST_KNOWN, (
+      "Test invariant: PROTOCOL_VERSION must equal max(KNOWN_PROTOCOL_VERSIONS)."
+    )
 
 
 class TestOpaquePerBrandFlags(OpenpilotTestCase):

openpilot/sunnypilot/sunnylink/tests/test_settings_changes.py

@@ -9,7 +9,6 @@ isolates one of the gating bugs that the design-overhaul branch fixes so a
 future regression is loud and obvious. These tests are intentionally narrow
 and additive — they do not replace the broader test_settings_schema.py.
 """
-
 from __future__ import annotations
 
 import json
@@ -25,13 +24,14 @@ from openpilot.sunnypilot.sunnylink.tools.generate_settings_schema import (
   _load_torque_versions,
   generate_schema,
 )
-from openpilot.sunnypilot.sunnylink.tools.validate_settings_ui import validate as validate_settings_ui
 from openpilot.common.test import OpenpilotTestCase
 
 
+SCHEMA_VALIDATOR_PATH = os.path.join(os.path.dirname(DEFINITION_PATH), "settings_ui.schema.json")
+
+
 def _walk_items(schema: dict[str, Any]):
   """Yield every item dict from the schema."""
-
   def _yield(item: dict[str, Any]):
     yield item
     for sub in item.get("sub_items", []):
@@ -149,13 +149,22 @@ class TestTestManeuversSection(OpenpilotTestCase):
     assert "is_sp_release" in vis_refs
     enablement = section.get("enablement") or []
     enable_refs = json.dumps(enablement)
-    assert "ShowAdvancedControls" in enable_refs, "test_maneuvers must gate ShowAdvancedControls via enablement"
+    assert "ShowAdvancedControls" in enable_refs, \
+      "test_maneuvers must gate ShowAdvancedControls via enablement"
 
 
 class TestValidator(OpenpilotTestCase):
   def test_validator_accepts_real_json(self):
-    """settings_ui.json passes the repository's production schema validator."""
-    self.assertTrue(validate_settings_ui(DEFINITION_PATH))
+    """settings_ui.json validates against settings_ui.schema.json."""
+    try:
+      import jsonschema
+    except ImportError:
+      self.skipTest("jsonschema not installed")
+    with open(DEFINITION_PATH) as f:
+      data = json.load(f)
+    with open(SCHEMA_VALIDATOR_PATH) as f:
+      validator = json.load(f)
+    jsonschema.validate(instance=data, schema=validator)
 
 
 class TestTorqueOptionGeneration(OpenpilotTestCase):
@@ -168,17 +177,16 @@ class TestTorqueOptionGeneration(OpenpilotTestCase):
     assert item.get("options") == expected
 
   def test_torque_versions_path_resolves(self):
-    assert os.path.exists(TORQUE_VERSIONS_PATH), f"latcontrol_torque_versions.json not found at {TORQUE_VERSIONS_PATH}"
+    assert os.path.exists(TORQUE_VERSIONS_PATH), (
+      f"latcontrol_torque_versions.json not found at {TORQUE_VERSIONS_PATH}"
+    )
 
 
 class TestReleaseBranchGates(OpenpilotTestCase):
-  @parameterized.expand(
-    [
-      "EnableGithubRunner",
-      "QuickBootToggle",
-    ],
-    names=["key"],
-  )
+  @parameterized.expand([
+    "EnableGithubRunner",
+    "QuickBootToggle",
+  ], names=["key"])
   def test_sp_dev_items_gate_on_is_sp_release(self, schema, key):
     """sunnypilot dev items must hide on sunnypilot release branches (is_sp_release gate)."""
     item = _find_item(schema, key)
@@ -200,14 +208,11 @@ class TestSpuriousOffroadGatesDropped(OpenpilotTestCase):
 
 
 class TestNotEngagedReplacement(OpenpilotTestCase):
-  @parameterized.expand(
-    [
-      "AlphaLongitudinalEnabled",
-      "ToyotaEnforceStockLongitudinal",
-      "ToyotaStopAndGoHack",
-    ],
-    names=["key"],
-  )
+  @parameterized.expand([
+    "AlphaLongitudinalEnabled",
+    "ToyotaEnforceStockLongitudinal",
+    "ToyotaStopAndGoHack",
+  ], names=["key"])
   def test_offroad_only_replaced_with_not_engaged(self, schema, key):
     """These items should use not_engaged, not offroad_only."""
     item = _find_item(schema, key)
@@ -215,5 +220,3 @@ class TestNotEngagedReplacement(OpenpilotTestCase):
     rule_types = _flatten_rule_types(item.get("enablement"))
     assert "offroad_only" not in rule_types, f"{key} still uses offroad_only"
     assert "not_engaged" in rule_types, f"{key} missing not_engaged"
-
-

openpilot/sunnypilot/sunnylink/tests/test_settings_schema.py

@@ -276,36 +276,13 @@ class TestKnownPanels(OpenpilotTestCase):
     enhanced_enable_keys = {r.get("key") for r in enhanced.get("enablement", []) if r.get("type") == "param"}
     assert "NeuralNetworkLateralControl" in enhanced_enable_keys
 
-  def test_accel_controller_profile_mapping_and_enablement(self, schema):
-    cruise = next(p for p in schema["panels"] if p["id"] == "cruise")
-    items = {item["key"]: item for item in _iter_panel_items(cruise)}
-
-    assert items["AccelPersonalityEnabled"]["widget"] == "toggle"
-    assert items["AccelPersonality"]["options"] == [
-      {"value": 0, "label": "Eco"},
-      {"value": 1, "label": "Normal"},
-      {"value": 2, "label": "Sport"},
-    ]
-    assert {
-      "type": "capability",
-      "field": "has_longitudinal_control",
-      "equals": True,
-    } in items["AccelPersonalityEnabled"]["enablement"]
-    assert {
-      "type": "capability",
-      "field": "has_longitudinal_control",
-      "equals": True,
-    } in items["AccelPersonality"]["enablement"]
-    profile_enable_keys = {rule.get("key") for rule in items["AccelPersonality"]["enablement"] if rule.get("type") == "param"}
-    assert "AccelPersonalityEnabled" not in profile_enable_keys
-
 
 class TestKnownVehicleSettings(OpenpilotTestCase):
   def test_hyundai_has_longitudinal_tuning(self, schema):
     keys = {i["key"] for i in _brand_items(schema["vehicle_settings"].get("hyundai"))}
     assert "HyundaiLongitudinalTuning" in keys
 
-  def test_toyota_has_enforce_stock_stop_go(self, schema):
+  def test_toyota_has_enforce_stock_and_stop_go(self, schema):
     keys = {i["key"] for i in _brand_items(schema["vehicle_settings"].get("toyota"))}
     assert "ToyotaEnforceStockLongitudinal" in keys
     assert "ToyotaStopAndGoHack" in keys

openpilot/system/ui/lib/scroll_panel2.py

@@ -45,9 +45,8 @@ class ScrollState(Enum):
 
 
 class GuiScrollPanel2:
-  def __init__(self, horizontal: bool = True, handle_out_of_bounds: bool = True) -> None:
+  def __init__(self, horizontal: bool = True) -> None:
     self._horizontal = horizontal
-    self._handle_out_of_bounds = handle_out_of_bounds
     self._state = ScrollState.STEADY
     self._offset: rl.Vector2 = rl.Vector2(0, 0)
     self._initial_click_event: MouseEvent | None = None
@@ -86,20 +85,6 @@ class GuiScrollPanel2:
     """Returns (max_offset, min_offset) for the given bounds and content size."""
     return 0.0, min(0.0, bounds_size - content_size)
 
-  def _clamp_offset(self, bounds_size: float, content_size: float) -> None:
-    if self._handle_out_of_bounds:
-      return
-
-    max_offset, min_offset = self._get_offset_bounds(bounds_size, content_size)
-    offset = self.get_offset()
-    clamped_offset = max(min_offset, min(max_offset, offset))
-    if clamped_offset == offset:
-      return
-
-    self.set_offset(clamped_offset)
-    if (clamped_offset == max_offset and self._velocity > 0) or (clamped_offset == min_offset and self._velocity < 0):
-      self._velocity = 0.0
-
   def _update_state(self, bounds_size: float, content_size: float, snap_target: float | None) -> None:
     """Runs per render frame, independent of mouse events. Updates auto-scrolling state and velocity."""
     max_offset, min_offset = self._get_offset_bounds(bounds_size, content_size)
@@ -153,8 +138,6 @@ class GuiScrollPanel2:
         factor = 1.0 - math.exp(-SNAP_RATE * dt)
         self.set_offset(self.get_offset() + dist * factor)
 
-    self._clamp_offset(bounds_size, content_size)
-
   def _handle_mouse_event(self, mouse_event: MouseEvent, bounds: rl.Rectangle, bounds_size: float,
                           content_size: float) -> None:
     max_offset, min_offset = self._get_offset_bounds(bounds_size, content_size)

openpilot/system/ui/widgets/scroller.py

@@ -75,6 +75,7 @@ class _Scroller(Widget):
     self._items: list[Widget] = []
     self._horizontal = horizontal
     self._snap_items = snap_items
+    assert not self._snap_items or self._horizontal, "Snapping is only supported for horizontal scrolling"
     self._spacing = spacing
     self._pad = pad
 
@@ -190,20 +191,12 @@ class _Scroller(Widget):
     snap_target: float | None = None
     if self._snap_items and visible_items and self._scrolling_to[0] is None:
       # TODO: this doesn't handle two small buttons at the edges well
-      center_pos = (self._rect.x + self._rect.width / 2) if self._horizontal else (self._rect.y + self._rect.height / 2)
-      closest_delta_pos = min(
-        (self._item_center_pos(item) - center_pos for item in visible_items),
-        key=abs,
-      )
+      center_pos = self._rect.x + self._rect.width / 2
+      closest_delta_pos = min((((item.rect.x + item.rect.width / 2) - center_pos) for item in visible_items), key=abs)
       snap_target = self.scroll_panel.get_offset() - closest_delta_pos
 
     return self.scroll_panel.update(self._rect, content_size, snap_target=snap_target)
 
-  def _item_center_pos(self, item: Widget) -> float:
-    if self._horizontal:
-      return item.rect.x + item.rect.width / 2
-    return item.rect.y + item.rect.height / 2
-
   @property
   def moving_items(self) -> bool:
     return len(self._move_animations) > 0 or len(self._move_lift) > 0

openpilot/tools/live/README.md

@@ -0,0 +1,198 @@
+# Live UI
+
+View a comma device's live sunnypilot UI over Wi-Fi. Replay, ADB, and USB are
+not used.
+
+| Mode | Output | Device bridge |
+| --- | --- | --- |
+| Mimic (default) | Local UI rendered from live device data | Required |
+| Exact (`--exact`) | Actual pixels shown on the device | Not required |
+
+Mimic mode does not directly require SSH, but the device bridge must be started
+somehow; the examples use SSH. Exact mode, touch control, and `--stop-exact`
+require key-based SSH access.
+
+Choose **mimic** when developing or inspecting the local UI with live device
+data. Choose **exact** when you need to see or control what is physically shown
+on the device.
+
+## Before the first run
+
+1. Replace `192.168.43.1` in the examples if your device uses a different IP.
+2. Connect the computer and device to networks that can reach each other.
+3. Run local commands from the sunnypilot repository root.
+4. For exact mode, verify non-interactive SSH access:
+
+   ```bash
+   ssh -o BatchMode=yes comma@192.168.43.1 true
+   ```
+
+The script automatically switches to the repository's `.venv` when present.
+
+## Mimic UI
+
+Mimic mode receives live cereal messages and encoded road-camera frames, then
+renders a new UI instance on the computer. It resembles the device UI but is
+not a pixel-for-pixel screen mirror.
+
+Build the messaging bridge once on the computer:
+
+```bash
+scons -u cereal/messaging/bridge
+```
+
+Use two terminals. In the first, start the bridge on the device and leave it
+running:
+
+```bash
+ssh comma@192.168.43.1
+./cereal/messaging/bridge
+```
+
+In the second terminal, start the local UI:
+
+```bash
+BIG=0 ./openpilot/tools/live/ui.py 192.168.43.1
+```
+
+`BIG` is inherited from your environment and is not forced by the tool.
+
+## Exact device screen
+
+Exact mode streams the actual device display. It does not need either
+messaging bridge:
+
+```bash
+./openpilot/tools/live/ui.py --exact 192.168.43.1
+```
+
+The tool runs a temporary capture helper through SSH using AGNOS's existing
+DRM broker. It does not install software or modify openpilot source on the
+device. Exact mode requires a compatible AGNOS DRM writeback connector and
+captures the post-processed display output when that mode is available.
+
+Exact mode is experimental. Some Qualcomm/AGNOS combinations can time out
+during DRM writeback, freezing both the mirrored window and physical device UI.
+This can happen without `--control`; mouse, keyboard, and shortcut forwarding
+are not required to trigger the capture failure.
+The tool stops its verified helper when capture stalls, but the kernel display
+state may require a full device reboot before exact mode can be tried again.
+Restarting openpilot alone does not reset the display driver.
+
+Set the capture rate from 1 to 60 FPS; the default is 15:
+
+```bash
+./openpilot/tools/live/ui.py --exact --exact-fps 30 192.168.43.1
+./openpilot/tools/live/ui.py --exact --exact-fps 60 192.168.43.1
+```
+
+Start with 15 or 30 FPS. Higher rates use more device CPU and Wi-Fi bandwidth.
+
+Use `SCALE` to resize the local window:
+
+```bash
+SCALE=2 ./openpilot/tools/live/ui.py --exact 192.168.43.1
+```
+
+Only one exact session can run at a time.
+
+## Touch control
+
+Touch control is available only with exact mode:
+
+```bash
+./openpilot/tools/live/ui.py --exact --control 192.168.43.1
+```
+
+Left-clicks and drags are forwarded to the physical touchscreen over SSH.
+These inputs affect the real device, including settings and confirmation
+buttons.
+
+When the device's on-screen keyboard is visible, type with the computer
+keyboard. Letters, numbers, symbols, Space, Backspace, and Return are converted
+to taps on the device keyboard.
+
+Exact control also provides simulator-style shortcuts:
+
+| Shortcut | Action |
+| --- | --- |
+| `↓` | Go back with a swipe-down gesture |
+| `←` | Swipe right |
+| `→` | Swipe left |
+| `Command`+`K` (macOS) or `Ctrl`+`K` (Linux/Windows) | Force keyboard forwarding on, or return to automatic detection |
+
+Hold an arrow key to repeat its gesture until the key is released.
+
+Escape has no action and does not close the program; use `Ctrl-C` or the window
+close button to exit. `Command`+`K`/`Ctrl`+`K` enables manual keyboard forwarding
+regardless of exact-screen resolution; touch locations scale to the captured
+screen. Automatic keyboard detection targets the 536x240 mici UI. Turn forced
+forwarding back off after typing so ordinary keys cannot produce unintended
+taps on incompatible keyboard layouts.
+
+## Connection status
+
+Status appears in the window title and terminal:
+
+- `connected`: mimic telemetry and camera frames, or exact screen frames, are
+  arriving.
+- `keyboard`: exact-mode keyboard forwarding is currently active. This appears
+  only while the device keyboard is detected or forwarding is forced on.
+- `no camera`: mimic telemetry is arriving, but road-camera frames are not.
+- `disconnected`: expected mimic-mode live data has stopped.
+
+At the default capture rate, exact mode reports a stopped screen stream in
+about one second. Lower `--exact-fps` values allow more time between frames.
+If Qualcomm DRM writeback stalls, exact mode immediately stops its verified
+device helper and exits to avoid leaving the physical display frozen.
+
+## Stop and clean up
+
+Press `Ctrl-C` or close the window. If an exact helper remains orphaned, run:
+
+```bash
+./openpilot/tools/live/ui.py --stop-exact 192.168.43.1
+```
+
+`--kill-exact` is an alias. Stop exact mode before restarting or rebuilding
+openpilot to avoid blocking the physical UI during a display transition.
+
+## Options
+
+```text
+--exact                 Show the actual device screen
+--control               Forward mouse and keyboard input; requires --exact
+--exact-fps FPS         Exact capture rate, 1-60 (default: 15)
+--stop-exact            Stop orphaned exact helpers
+--kill-exact            Alias for --stop-exact
+--ip ADDRESS            Alternative to the positional address
+```
+
+See the complete command help:
+
+```bash
+./openpilot/tools/live/ui.py --help
+```
+
+## Troubleshooting
+
+- **`cereal/messaging/bridge` is not built:** Run:
+
+  ```bash
+  scons -u cereal/messaging/bridge
+  ```
+
+- **Mimic is disconnected:** Confirm the device bridge is still running and
+  the IP is reachable.
+- **Mimic reports no camera:** Confirm the device is publishing
+  `roadEncodeData`. Camera display may also wait briefly for the next keyframe.
+- **Exact says another session is running:** Close the other exact window. If
+  none is open, run `--stop-exact`.
+- **Exact cannot connect:** Recheck key-based SSH and the device IP using the
+  command in "Before the first run."
+- **Exact stalls or the physical UI freezes:** Stop the exact window and run
+  `--stop-exact`. If the device UI remains unstable or exact immediately stalls
+  again, fully reboot the device; restarting openpilot is not sufficient. If
+  the problem returns after reboot, use mimic mode because continuous DRM
+  writeback is not reliable on that device/AGNOS combination. Removing
+  `--control` does not address this capture-layer failure.