long: preserve smooth stoppingdeacelrate.

openpilot/selfdrive/controls/lib/longcontrol.py

@@ -4,6 +4,7 @@ from openpilot.common.realtime import DT_CTRL
 from openpilot.selfdrive.controls.lib.drive_helpers import CONTROL_N
 from openpilot.common.pid import PIDController
 from openpilot.selfdrive.modeld.constants import ModelConstants
+from openpilot.sunnypilot.selfdrive.controls.lib.longcontrol import LongControlSP
 
 CONTROL_N_T_IDX = ModelConstants.T_IDXS[:CONTROL_N]
 
@@ -39,7 +40,7 @@ def long_control_state_trans(CP_SP, active, long_control_state,
 
   return long_control_state
 
-class LongControl:
+class LongControl(LongControlSP):
   def __init__(self, CP, CP_SP):
     self.CP = CP
     self.CP_SP = CP_SP
@@ -66,7 +67,7 @@ class LongControl:
 
     elif self.long_control_state == LongCtrlState.stopping:
       output_accel = self.last_output_accel
-      if output_accel > self.CP.stopAccel:
+      if output_accel > self.CP.stopAccel and not LongControlSP.should_hold_stopping(self, CS, a_target):
         output_accel = min(output_accel, 0.0)
         # TODO: can we just go straight to stopAccel?
         output_accel -= 1.0 * DT_CTRL  # m/s^2/s while trying to stop

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

@@ -6,78 +6,180 @@ from opendbc.car.ford.values import CAR as FORD
 from opendbc.car.gm.values import CAR as GM
 from opendbc.car.honda.values import CAR as HONDA
 from opendbc.car.hyundai.values import CAR as HYUNDAI
+from opendbc.car.rivian.values import CAR as RIVIAN
 from opendbc.car.toyota.values import CAR as TOYOTA
-from openpilot.selfdrive.controls.lib.drive_helpers import get_accel_from_plan
-from openpilot.selfdrive.controls.lib.longcontrol import LongControl, LongCtrlState, long_control_state_trans
+from opendbc.car.volkswagen.values import CAR as VOLKSWAGEN
+from openpilot.selfdrive.controls.lib.drive_helpers import should_stop
+from openpilot.selfdrive.controls.lib.longcontrol import LongControl, LongCtrlState
+from openpilot.sunnypilot.selfdrive.controls.lib.longcontrol import LongControlSP
 
 
-VEHICLES = [
-  pytest.param(TOYOTA.TOYOTA_RAV4_TSS2, (True, False, 0.0, -2.0, 0.25, 0.25, 0.3), id="toyota-rav4-tss2"),
-  pytest.param(HONDA.HONDA_ACCORD, (True, False, 0.0, -2.0, 0.5, 0.5, 0.8), id="honda-accord"),
-  pytest.param(GM.CHEVROLET_BOLT_EUV, (True, False, 0.0, -2.0, 0.25, 0.25, 2.0), id="gm-bolt-euv"),
-  pytest.param(HYUNDAI.HYUNDAI_SONATA, (True, True, 1.0, -2.0, 0.1, 0.5, 0.8), id="hyundai-sonata"),
-  pytest.param(FORD.FORD_ESCAPE_MK4, (True, False, 0.0, -2.0, 0.5, 0.5, 0.8), id="ford-escape"),
-]
+VEHICLES = (TOYOTA.TOYOTA_RAV4_TSS2, HONDA.HONDA_ACCORD, HONDA.HONDA_CIVIC_2022, GM.CHEVROLET_BOLT_EUV,
+            HYUNDAI.HYUNDAI_SONATA, FORD.FORD_ESCAPE_MK4, VOLKSWAGEN.VOLKSWAGEN_ARTEON_MK1, RIVIAN.RIVIAN_R1)
+ROUTE_STOP_ONSETS = (
+  (0.290, -0.497, -0.270, -0.302), (0.464, -0.223, -0.264, -0.292), (0.467, -0.582, -0.316, -0.359),
+  (0.530, -0.311, -0.309, -0.333), (0.581, -0.467, -0.312, -0.352), (0.398, -0.557, -0.311, -0.348),
+  (0.517, -0.290, -0.301, -0.327), (0.312, -0.420, -0.271, -0.304), (0.474, -0.509, -0.303, -0.347),
+  (0.241, -0.554, -0.573, -0.617), (0.292, -0.154, -0.302, -0.326),
+)
 
 
 def get_car_params(candidate):
   fingerprint = gen_empty_fingerprint()
   interface = interfaces[candidate]
   CP = interface.get_params(candidate, fingerprint, [], True, False, False)
-  CP_SP = interface.get_params_sp(CP, candidate, fingerprint, [], True, False, False)
-  return CP, CP_SP
+  return CP, interface.get_params_sp(CP, candidate, fingerprint, [], True, False, False)
 
 
-@pytest.mark.parametrize(("candidate", "expected"), VEHICLES)
-def test_real_vehicle_longcontrol_stop_and_start(candidate, expected):
+def make_car_state(v_ego=0.2, a_ego=0.0, standstill=False):
+  return structs.CarState(vEgo=float(v_ego), aEgo=float(a_ego), standstill=standstill)
+
+
+def make_control(candidate, initial_accel=-0.33):
   CP, CP_SP = get_car_params(candidate)
-  expected_long, expected_starting, *expected_tuning = expected
-
-  assert CP.openpilotLongitudinalControl is expected_long
-  assert CP.startingState is expected_starting
-  assert (CP.startAccel, CP.stopAccel, CP.vEgoStarting, CP.vEgoStopping, CP.stoppingDecelRate) == pytest.approx(expected_tuning)
-
-  stop_speeds = [CP.vEgoStopping - 0.01] * 2
-  drive_speeds = [CP.vEgoStopping + 0.01] * 2
-  _, should_stop = get_accel_from_plan(stop_speeds, [0.0, 0.0], [0.0, 1.0], vEgoStopping=CP.vEgoStopping)
-  _, should_drive = get_accel_from_plan(drive_speeds, [0.0, 0.0], [0.0, 1.0], vEgoStopping=CP.vEgoStopping)
-  assert should_stop
-  assert not should_drive
-
-  departure_state = long_control_state_trans(
-    CP,
-    CP_SP,
-    True,
-    LongCtrlState.stopping,
-    CP.vEgoStarting - 0.01,
-    should_drive,
-    brake_pressed=False,
-    cruise_standstill=False,
-  )
-  assert departure_state == (LongCtrlState.starting if CP.startingState else LongCtrlState.pid)
-  assert (
-    long_control_state_trans(
-      CP,
-      CP_SP,
-      True,
-      departure_state,
-      CP.vEgoStarting + 0.01,
-      should_drive,
-      brake_pressed=False,
-      cruise_standstill=False,
-    )
-    == LongCtrlState.pid
-  )
-
-  CS = structs.CarState()
-  CS.vEgo = 0.0
-  CS.aEgo = 0.0
   control = LongControl(CP, CP_SP)
+  control.long_control_state = LongCtrlState.pid
+  control.last_output_accel = initial_accel
+  return CP, control
 
-  stopping_accel = control.update(True, CS, 0.0, should_stop, (-3.0, 2.0))
+
+def stock_stopping_output(output_accel, stop_accel):
+  return min(output_accel, 0.0) - DT_CTRL if output_accel > stop_accel else output_accel
+
+
+def test_stop_threshold_remains_unchanged():
+  assert should_stop(0.24, 0.0)
+  assert not should_stop(0.26, 0.0)
+  assert not should_stop(0.24, 0.1)
+
+
+def test_longcontrol_uses_sunnypilot_extension():
+  assert LongControl.__bases__ == (LongControlSP,)
+
+
+@pytest.mark.parametrize("candidate", VEHICLES)
+@pytest.mark.parametrize(("v_ego", "a_ego", "a_target", "initial_accel"), ROUTE_STOP_ONSETS)
+def test_logged_stop_onsets_hold_the_existing_brake(candidate, v_ego, a_ego, a_target, initial_accel):
+  _, control = make_control(candidate, initial_accel)
+  output = control.update(True, make_car_state(v_ego, a_ego), a_target, True, (-3.5, 2.0))
   assert control.long_control_state == LongCtrlState.stopping
-  assert stopping_accel == pytest.approx(-CP.stoppingDecelRate * DT_CTRL)
+  assert output == pytest.approx(initial_accel)
 
-  departure_accel = control.update(True, CS, 0.0, should_drive, (-3.0, 2.0))
-  assert control.long_control_state == departure_state
-  assert departure_accel == pytest.approx(CP.startAccel)
+
+@pytest.mark.parametrize("candidate", VEHICLES)
+def test_urgent_braking_matches_the_stock_ramp(candidate):
+  CP, control = make_control(candidate)
+  CS = make_car_state(0.8, -0.1)
+  output = control.last_output_accel
+
+  for _ in range(round(1.0 / DT_CTRL)):
+    output = control.update(True, CS, -3.0, True, (-3.5, 2.0))
+
+  expected = -0.33
+  for _ in range(round(1.0 / DT_CTRL)):
+    expected = stock_stopping_output(expected, CP.stopAccel)
+  assert output == pytest.approx(expected)
+
+
+@pytest.mark.parametrize("candidate", VEHICLES)
+def test_stronger_planner_brake_matches_the_stock_ramp(candidate):
+  CP, control = make_control(candidate)
+  outputs = [control.update(True, make_car_state(0.3, -0.3), -1.0, True, (-3.5, 2.0)) for _ in range(10)]
+  expected = []
+  output = -0.33
+  for _ in range(10):
+    output = stock_stopping_output(output, CP.stopAccel)
+    expected.append(output)
+  assert outputs == pytest.approx(expected)
+
+
+@pytest.mark.parametrize("candidate", VEHICLES)
+def test_insufficient_deceleration_uses_the_stock_ramp_immediately(candidate):
+  CP, control = make_control(candidate)
+  output = control.update(True, make_car_state(0.6, -0.1), -0.1, True, (-3.5, 2.0))
+  assert output == pytest.approx(stock_stopping_output(-0.33, CP.stopAccel))
+
+
+def test_deceleration_noise_cannot_release_the_brake():
+  _, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2)
+  outputs = [control.update(True, make_car_state(0.3, -0.3 if frame % 2 else 0.0), -0.1, True, (-3.5, 2.0)) for frame in range(40)]
+  assert all(current <= previous for previous, current in zip(outputs[:-1], outputs[1:], strict=True))
+
+
+def test_planner_noise_cannot_release_the_brake():
+  _, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2)
+  outputs = [control.update(True, make_car_state(0.3, -0.3), -1.0 if frame % 2 else -0.1, True, (-3.5, 2.0)) for frame in range(40)]
+  assert all(current <= previous for previous, current in zip(outputs[:-1], outputs[1:], strict=True))
+
+
+@pytest.mark.parametrize(("v_ego", "a_ego", "a_target"), ((float("nan"), -0.3, -0.1), (0.3, float("nan"), -0.1), (0.3, -0.3, float("nan"))))
+def test_invalid_state_uses_the_stock_ramp(v_ego, a_ego, a_target):
+  CP, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2)
+  output = control.update(True, make_car_state(v_ego, a_ego), a_target, True, (-3.5, 2.0))
+  assert output == pytest.approx(stock_stopping_output(-0.33, CP.stopAccel))
+
+
+@pytest.mark.parametrize(("speed", "initial_accel", "grade_accel", "actuator_lag"), (
+  (0.24, 0.0, 0.0, 0.15), (0.464, -0.223, 0.0, 0.25), (0.53, -0.31, 0.0, 0.35),
+  (0.24, 0.0, 0.49, 0.15), (0.53, -0.31, 0.49, 0.25), (0.6, -0.3, 0.49, 0.35), (0.6, -0.3, 0.49, 0.5),
+))
+def test_smooth_stop_distance_is_bounded(speed, initial_accel, grade_accel, actuator_lag):
+  _, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2, initial_accel)
+  applied_accel = initial_accel
+  distance = 0.0
+
+  for _ in range(round(4.0 / DT_CTRL)):
+    command = control.update(True, make_car_state(speed, applied_accel), -0.1, True, (-3.5, 2.0))
+    applied_accel += DT_CTRL / actuator_lag * (command + grade_accel - applied_accel)
+    speed = max(0.0, speed + applied_accel * DT_CTRL)
+    distance += speed * DT_CTRL
+    if speed == 0.0:
+      break
+
+  assert speed == 0.0
+  assert distance < 1.0
+
+
+@pytest.mark.parametrize("candidate", VEHICLES)
+def test_standstill_uses_the_stock_ramp(candidate):
+  CP, control = make_control(candidate)
+  CS = make_car_state(0.0, 0.0, standstill=True)
+  outputs = [control.update(True, CS, 0.0, True, (-3.5, 2.0)) for _ in range(round(2.0 / DT_CTRL))]
+  expected = -0.33
+  for _ in range(round(2.0 / DT_CTRL)):
+    expected = stock_stopping_output(expected, CP.stopAccel)
+  assert outputs[0] == pytest.approx(stock_stopping_output(-0.33, CP.stopAccel))
+  assert outputs[-1] == pytest.approx(expected)
+
+
+@pytest.mark.parametrize(("v_ego", "a_ego", "standstill"), ((0.6, -0.1, False), (0.0, 0.0, True)))
+def test_stopping_never_releases_a_stronger_command(v_ego, a_ego, standstill):
+  _, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2, -3.0)
+  output = control.update(True, make_car_state(v_ego, a_ego, standstill), 0.0, True, (-3.5, 2.0))
+  assert output == pytest.approx(-3.0)
+
+
+def test_reported_standstill_while_moving_can_hold_the_brake():
+  _, control = make_control(GM.CHEVROLET_BOLT_EUV)
+  output = control.update(True, make_car_state(0.3, -0.3, standstill=True), -0.1, True, (-3.5, 2.0))
+  assert output == pytest.approx(-0.33)
+
+
+def test_stopping_removes_positive_acceleration_immediately():
+  _, control = make_control(HYUNDAI.HYUNDAI_SONATA, 0.2)
+  output = control.update(True, make_car_state(0.2, -0.2), -0.1, True, (-3.5, 2.0))
+  assert output == pytest.approx(-DT_CTRL)
+
+
+def test_rollback_uses_the_stock_ramp():
+  CP, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2)
+  output = control.update(True, make_car_state(-0.1, 0.1), -0.1, True, (-3.5, 2.0))
+  assert output == pytest.approx(stock_stopping_output(-0.33, CP.stopAccel))
+
+
+def test_departure_uses_the_stock_pid_path():
+  _, control = make_control(TOYOTA.TOYOTA_RAV4_TSS2)
+  control.long_control_state = LongCtrlState.stopping
+  output = control.update(True, make_car_state(0.0), 0.6, False, (-3.5, 2.0))
+  assert control.long_control_state == LongCtrlState.pid
+  assert output > 0.0

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

@@ -0,0 +1,16 @@
+"""
+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.
+"""
+
+STOPPING_DISTANCE = 0.75
+STOPPED_SPEED = 0.02
+STOPPING_TIME = 2.5
+
+
+class LongControlSP:
+  def should_hold_stopping(self, CS, a_target: float) -> bool:
+    return (self.last_output_accel <= 0.0 and a_target >= self.last_output_accel and CS.vEgo > STOPPED_SPEED and CS.aEgo < 0.0
+            and CS.vEgo <= -CS.aEgo * STOPPING_TIME and CS.vEgo ** 2 <= -2.0 * CS.aEgo * STOPPING_DISTANCE)

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

@@ -14,8 +14,7 @@ from typing import Any
 
 import numpy as np
 
-from openpilot.cereal import log
-import cereal.messaging as messaging
+from openpilot.cereal import log, messaging
 from openpilot.common.realtime import DT_MDL, Ratekeeper
 from openpilot.selfdrive.modeld.constants import ModelConstants
 from openpilot.selfdrive.controls.lib.longcontrol import LongCtrlState
@@ -251,14 +250,10 @@ class PlantSP(Plant):
       "dRel": float(d_rel),
       "yRel": 0.0,
       "vRel": float(v_rel),
-      "aRel": float(a_lead - self.acceleration),
       "vLead": float(v_lead),
-      "dPath": 0.0,
-      "vLat": 0.0,
       "vLeadK": float(v_lead),
       "aLeadK": float(a_lead),
-      "fcw": False,
-      "status": bool(status),
+      "present": bool(status),
       # TODO use real radard logic for this
       "aLeadTau": float(_LEAD_ACCEL_TAU),
       "modelProb": float(prob_lead),

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

@@ -1,5 +1,6 @@
 from collections.abc import Callable
 import math
+from typing import cast
 
 import pytest
 
@@ -14,15 +15,19 @@ 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": dict(lead_relevancy=True, speed=15.0, distance_lead=60.0, v_cruise=20.0, v_lead=0.0, steps=80),
-  "stop_then_depart": dict(lead_relevancy=True, speed=0.0, distance_lead=6.0, v_cruise=8.0, v_lead=departing_lead, steps=120),
+  "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: float | Callable[[float], float], steps: int, **kwargs):
+def _drive(cls, *, v_cruise: float, v_lead: Callable[[float], float], steps: int, **kwargs):
   plant = cls(**kwargs)
-  plant.v_lead_prev = float(v_lead(0.0)) if callable(v_lead) else float(v_lead)
+  plant.v_lead_prev = v_lead(0.0)
   solver_failures = 0
   original_reset = plant.planner.mpc.reset
 
@@ -35,16 +40,18 @@ def _drive(cls, *, v_cruise: float, v_lead: float | Callable[[float], float], st
   plant.planner.mpc.reset = counting_reset
   results = []
   for _ in range(steps):
-    lead_speed = float(v_lead(plant.current_time)) if callable(v_lead) else v_lead
+    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
 
 
 @pytest.mark.parametrize("scenario", PARITY_SCENARIOS, ids=list(PARITY_SCENARIOS))
-def test_plant_sp_matches_stock_plant_on_shared_kwargs(scenario):
+def test_plant_sp_matches_stock_plant_on_shared_kwargs(scenario: str):
   kwargs = dict(PARITY_SCENARIOS[scenario])
-  v_cruise, v_lead, steps = kwargs.pop("v_cruise"), kwargs.pop("v_lead"), kwargs.pop("steps")
+  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)
@@ -91,7 +98,7 @@ def test_full_lead_observation_is_independent_from_truth():
         "vLeadK": 5.5,
         "aLeadK": -1.25,
         "aLeadTau": 0.7,
-        "status": True,
+        "present": True,
         "modelProb": 0.9,
         "radarTrackId": 42,
       }