cleanup unused radar fields (#38346)

* cleanup unused radar fields

* bump opendbc

* this is nice for debugging

* bring that back too

* bring these back

* more revert

openpilot/cereal/log.capnp

@@ -704,8 +704,7 @@ struct UsbState {
 }
 
 struct RadarState @0x9a185389d6fdd05f {
-  mdMonoTime @6 :UInt64;
-  carStateMonoTime @11 :UInt64;
+  mdMonoTime @6 :UInt64;  # for debugging
   radarErrors @13 :Car.RadarData.Error;
 
   leadOne @3 :LeadData;
@@ -715,21 +714,21 @@ struct RadarState @0x9a185389d6fdd05f {
     dRel @0 :Float32;
     yRel @1 :Float32;
     vRel @2 :Float32;
-    aRel @3 :Float32;
     vLead @4 :Float32;
-    dPath @6 :Float32;
-    vLat @7 :Float32;
-    vLeadK @8 :Float32;
-    aLeadK @9 :Float32;
-    fcw @10 :Bool;
+    vLeadK @8 :Float32;  # kalman-filtered lead speed
+    aLeadK @9 :Float32;  # kalman-filtered lead accel
     present @11 :Bool;
     aLeadTau @12 :Float32;
     modelProb @13 :Float32;
-    radar @14 :Bool;
-    radarTrackId @15 :Int32 = -1;
+    radar @14 :Bool;  # true if lead is radar-matched (vs vision-only)
+    radarTrackId @15 :Int32 = -1;  # for debugging
 
     deprecated :group {
+      aRel @3 :Float32;
       aLead @5 :Float32;
+      dPath @6 :Float32;
+      vLat @7 :Float32;
+      fcw @10 :Bool;
     }
   }
 
@@ -742,6 +741,7 @@ struct RadarState @0x9a185389d6fdd05f {
     calPerc @9 :Int8;
     canMonoTimes @10 :List(UInt64);
     cumLagMs @5 :Float32;
+    carStateMonoTime @11 :UInt64;
     radarErrors @12 :List(Car.RadarData.ErrorDEPRECATED);
   }
 }
@@ -1041,7 +1041,6 @@ struct ModelDataV2 {
   roadEdgeStds @14 :List(Float32);
 
   # predicted lead cars
-  leads @11 :List(LeadDataV2);
   leadsV3 @18 :List(LeadDataV3);
 
   meta @12 :MetaData;
@@ -1051,8 +1050,9 @@ struct ModelDataV2 {
   action @26: Action;
 
   lateralPlannerSolutionDEPRECATED @25: Deprecated.LateralPlannerSolution;
+  leadsDEPRECATED @11 :List(LeadDataV2DEPRECATED);
 
-  struct LeadDataV2 {
+  struct LeadDataV2DEPRECATED {
     prob @0 :Float32; # probability that car is your lead at time t
     t @1 :Float32;
 

openpilot/selfdrive/controls/radard.py

@@ -23,7 +23,6 @@ SPEED, ACCEL = 0, 1     # Kalman filter states enum
 # stationary qualification parameters
 V_EGO_STATIONARY = 4.   # no stationary object flag below this speed
 
-RADAR_TO_CENTER = 2.7   # (deprecated) RADAR is ~ 2.7m ahead from center of car
 RADAR_TO_CAMERA = 1.52  # RADAR is ~ 1.5m ahead from center of mesh frame
 
 
@@ -59,13 +58,12 @@ class Track:
     self.K_K = kalman_params.K
     self.kf = KF1D([[v_lead], [0.0]], self.K_A, self.K_C, self.K_K)
 
-  def update(self, d_rel: float, y_rel: float, v_rel: float, v_lead: float, measured: float):
+  def update(self, d_rel: float, y_rel: float, v_rel: float, v_lead: float):
     # relative values, copy
     self.dRel = d_rel   # LONG_DIST
     self.yRel = y_rel   # -LAT_DIST
     self.vRel = v_rel   # REL_SPEED
     self.vLead = v_lead
-    self.measured = measured   # measured or estimate
 
     # computed velocity and accelerations
     if self.cnt > 0:
@@ -92,7 +90,6 @@ class Track:
       "aLeadK": float(self.aLeadK),
       "aLeadTau": float(self.aLeadTau.x),
       "present": True,
-      "fcw": self.is_potential_fcw(model_prob),
       "modelProb": model_prob,
       "radar": True,
       "radarTrackId": self.identifier,
@@ -103,9 +100,6 @@ class Track:
     # Radar points closer than 0.75, are almost always glitches on toyota radars
     return abs(self.yRel) < 1.0 and (v_ego < V_EGO_STATIONARY) and (0.75 < self.dRel < 25)
 
-  def is_potential_fcw(self, model_prob: float):
-    return model_prob > .9
-
   def __str__(self):
     ret = f"x: {self.dRel:4.1f}  y: {self.yRel:4.1f}  v: {self.vRel:4.1f}  a: {self.aLeadK:4.1f}"
     return ret
@@ -149,7 +143,6 @@ def get_RadarState_from_vision(lead_msg: capnp._DynamicStructReader, v_ego: floa
     "vLeadK": float(v_ego + lead_v_rel_pred),
     "aLeadK": float(lead_msg.a[0]),
     "aLeadTau": 0.3,
-    "fcw": False,
     "modelProb": float(lead_prob),
     "present": True,
     "radar": False,
@@ -209,7 +202,7 @@ class RadarD:
       self.v_ego_hist.append(self.v_ego)
       self.last_v_ego_frame = sm.recv_frame['carState']
 
-    ar_pts = {pt.trackId: [pt.dRel, pt.yRel, pt.vRel, pt.measured] for pt in rr.points}
+    ar_pts = {pt.trackId: [pt.dRel, pt.yRel, pt.vRel] for pt in rr.points}
 
     # *** remove missing points from meta data ***
     for ids in list(self.tracks.keys()):
@@ -226,14 +219,13 @@ class RadarD:
       # create the track if it doesn't exist or it's a new track
       if ids not in self.tracks:
         self.tracks[ids] = Track(ids, v_lead, self.kalman_params)
-      self.tracks[ids].update(rpt[0], rpt[1], rpt[2], v_lead, rpt[3])
+      self.tracks[ids].update(rpt[0], rpt[1], rpt[2], v_lead)
 
     # *** publish radarState ***
     self.radar_state_valid = sm.all_checks()
     self.radar_state = log.RadarState.new_message()
     self.radar_state.mdMonoTime = sm.logMonoTime['modelV2']
     self.radar_state.radarErrors = rr.errors
-    self.radar_state.carStateMonoTime = sm.logMonoTime['carState']
 
     if len(sm['modelV2'].velocity.x):
       model_v_ego = sm['modelV2'].velocity.x[0]

openpilot/selfdrive/test/longitudinal_maneuvers/plant.py

@@ -89,7 +89,6 @@ class Plant:
     lead.dRel = float(d_rel)
     lead.yRel = 0.0
     lead.vRel = float(v_rel)
-    lead.aRel = float(a_lead - self.acceleration)
     lead.vLead = float(v_lead)
     lead.vLeadK = float(v_lead)
     lead.aLeadK = float(a_lead)
@@ -97,6 +96,7 @@ class Plant:
     lead.aLeadTau = float(_LEAD_ACCEL_TAU)
     lead.present = status
     lead.modelProb = float(prob_lead)
+    lead.radar = True
     if not self.only_lead2:
       radar.radarState.leadOne = lead
     radar.radarState.leadTwo = lead

openpilot/selfdrive/test/process_replay/migration.py

@@ -175,8 +175,6 @@ def migrate_liveTracks(msgs):
       pt.dRel = track.dRel
       pt.yRel = track.yRel
       pt.vRel = track.vRel
-      pt.aRel = track.aRel
-      pt.measured = True
       pts.append(pt)
 
     new_msg.liveTracks.points = pts

openpilot/tools/replay/lib/ui_helpers.py

@@ -201,7 +201,7 @@ def maybe_update_radar_points(lt, lid_overlay):
   if lt is not None:
     ar_pts = {}
     for track in lt:
-      ar_pts[track.trackId] = [track.dRel, track.yRel, track.vRel, track.aRel]
+      ar_pts[track.trackId] = [track.dRel, track.yRel, track.vRel]
   for pt in ar_pts.values():
     # negative here since radar is left positive
     px, py = to_topdown_pt(pt[0], -pt[1])