Long planner: make work with training (#35043)

* revert useless

* update ref

selfdrive/controls/lib/longitudinal_planner.py

@@ -52,6 +52,7 @@ class LongitudinalPlanner:
   def __init__(self, CP, init_v=0.0, init_a=0.0, dt=DT_MDL):
     self.CP = CP
     self.mpc = LongitudinalMpc(dt=dt)
+    self.mpc.mode = 'acc'
     self.fcw = False
     self.dt = dt
     self.allow_throttle = True
@@ -89,7 +90,6 @@ class LongitudinalPlanner:
     return x, v, a, j, throttle_prob
 
   def update(self, sm):
-    self.mpc.mode = 'acc'
     self.mode = 'blended' if sm['selfdriveState'].experimentalMode else 'acc'
 
     if len(sm['carControl'].orientationNED) == 3:
@@ -97,7 +97,7 @@ class LongitudinalPlanner:
     else:
       accel_coast = ACCEL_MAX
 
-    v_ego = sm['modelV2'].velocity.x[0]
+    v_ego = sm['carState'].vEgo
     v_cruise_kph = min(sm['carState'].vCruise, V_CRUISE_MAX)
     v_cruise = v_cruise_kph * CV.KPH_TO_MS
     v_cruise_initialized = sm['carState'].vCruise != V_CRUISE_UNSET
@@ -129,7 +129,7 @@ class LongitudinalPlanner:
     self.v_desired_filter.x = max(0.0, self.v_desired_filter.update(v_ego))
     # Compute model v_ego error
     self.v_model_error = get_speed_error(sm['modelV2'], v_ego)
-    x, v, a, j, throttle_prob = self.parse_model(sm['modelV2'], 0)
+    x, v, a, j, throttle_prob = self.parse_model(sm['modelV2'], self.v_model_error)
     # Don't clip at low speeds since throttle_prob doesn't account for creep
     self.allow_throttle = throttle_prob > ALLOW_THROTTLE_THRESHOLD or v_ego <= MIN_ALLOW_THROTTLE_SPEED
 

selfdrive/test/process_replay/ref_commit

@@ -1 +1 @@
-0800e73b5d9c801f161b9559557c0559b0682fec
+fcc771b9ceb487a61035885acbd84e592fb316bf