sunnypilot v2026.002.000

version: sunnypilot v2026.002.000 (staging)
date: 2026-07-21T07:44:02
master commit: 2c334ede443d7391d27575af8c854a095ba702a8

openpilot/selfdrive/controls/tests/test_following_distance.py

@@ -0,0 +1,46 @@
+import pytest
+import itertools
+from openpilot.common.parameterized import parameterized_class
+
+from openpilot.cereal import log
+
+from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import get_safe_obstacle_distance, get_stopped_equivalence_factor, get_T_FOLLOW
+from openpilot.selfdrive.test.longitudinal_maneuvers.maneuver import Maneuver
+
+
+def desired_follow_distance(v_ego, v_lead, t_follow=None):
+  if t_follow is None:
+    t_follow = get_T_FOLLOW()
+  return get_safe_obstacle_distance(v_ego, t_follow) - get_stopped_equivalence_factor(v_lead)
+
+def run_following_distance_simulation(v_lead, t_end=100.0, e2e=False, personality=0):
+  man = Maneuver(
+    '',
+    duration=t_end,
+    initial_speed=float(v_lead),
+    lead_relevancy=True,
+    initial_distance_lead=100,
+    speed_lead_values=[v_lead],
+    breakpoints=[0.],
+    e2e=e2e,
+    personality=personality,
+  )
+  valid, output = man.evaluate()
+  assert valid
+  return output[-1,2] - output[-1,1]
+
+
+@parameterized_class(("e2e", "personality", "speed"), itertools.product(
+                      [True, False], # e2e
+                      [log.LongitudinalPersonality.relaxed, # personality
+                       log.LongitudinalPersonality.standard,
+                       log.LongitudinalPersonality.aggressive],
+                      [0,10,35])) # speed
+class TestFollowingDistance:
+  def test_following_distance(self):
+    v_lead = float(self.speed)
+    simulation_steady_state = run_following_distance_simulation(v_lead, e2e=self.e2e, personality=self.personality)
+    correct_steady_state = desired_follow_distance(v_lead, v_lead, get_T_FOLLOW(self.personality))
+    err_ratio = 0.2 if self.e2e else 0.1
+    abs_err_margin = 0.5 if v_lead > 0.0 else 1.15
+    assert simulation_steady_state == pytest.approx(correct_steady_state, abs=err_ratio * correct_steady_state + abs_err_margin)

openpilot/selfdrive/controls/tests/test_latcontrol.py

@@ -0,0 +1,56 @@
+from openpilot.common.parameterized import parameterized
+
+from openpilot.cereal import log
+from opendbc.car.structs import car
+from opendbc.car.car_helpers import interfaces
+from opendbc.car.honda.values import CAR as HONDA
+from opendbc.car.toyota.values import CAR as TOYOTA
+from opendbc.car.nissan.values import CAR as NISSAN
+from opendbc.car.gm.values import CAR as GM
+from opendbc.car.vehicle_model import VehicleModel
+from openpilot.common.realtime import DT_CTRL
+from openpilot.selfdrive.car.helpers import convert_to_capnp
+from openpilot.selfdrive.controls.lib.latcontrol_pid import LatControlPID
+from openpilot.selfdrive.controls.lib.latcontrol_torque import LatControlTorque
+from openpilot.selfdrive.controls.lib.latcontrol_angle import LatControlAngle
+from openpilot.selfdrive.locationd.helpers import Pose
+from openpilot.common.mock.generators import generate_livePose
+from openpilot.sunnypilot.selfdrive.car import interfaces as sunnypilot_interfaces
+
+
+class TestLatControl:
+
+  @parameterized.expand([(HONDA.HONDA_CIVIC, LatControlPID), (TOYOTA.TOYOTA_RAV4, LatControlTorque),
+                         (NISSAN.NISSAN_LEAF, LatControlAngle), (GM.CHEVROLET_BOLT_EUV, LatControlTorque)])
+  def test_saturation(self, car_name, controller):
+    CarInterface = interfaces[car_name]
+    CP = CarInterface.get_non_essential_params(car_name)
+    CP_SP = CarInterface.get_non_essential_params_sp(CP, car_name)
+    CI = CarInterface(CP, CP_SP)
+    sunnypilot_interfaces.setup_interfaces(CI)
+    CP_SP = convert_to_capnp(CP_SP)
+    VM = VehicleModel(CP)
+
+    controller = controller(CP.as_reader(), CP_SP.as_reader(), CI, DT_CTRL)
+
+    CS = car.CarState.new_message()
+    CS.vEgo = 30
+    CS.steeringPressed = False
+
+    params = log.LiveParametersData.new_message()
+
+    lp = generate_livePose()
+    pose = Pose.from_live_pose(lp.livePose)
+
+    # Saturate for curvature limited and controller limited
+    for _ in range(1000):
+      _, _, lac_log = controller.update(True, CS, VM, params, False, 0, pose, True, 0.2)
+    assert lac_log.saturated
+
+    for _ in range(1000):
+      _, _, lac_log = controller.update(True, CS, VM, params, False, 0, pose, False, 0.2)
+    assert not lac_log.saturated
+
+    for _ in range(1000):
+      _, _, lac_log = controller.update(True, CS, VM, params, False, 1, pose, False, 0.2)
+    assert lac_log.saturated

openpilot/selfdrive/controls/tests/test_latcontrol_torque_buffer.py

@@ -0,0 +1,48 @@
+from openpilot.common.parameterized import parameterized
+
+from openpilot.cereal import log
+from opendbc.car.structs import car
+from opendbc.car.car_helpers import interfaces
+from opendbc.car.toyota.values import CAR as TOYOTA
+from opendbc.car.vehicle_model import VehicleModel
+from openpilot.common.realtime import DT_CTRL
+from openpilot.selfdrive.controls.lib.latcontrol_torque import LatControlTorque, LAT_ACCEL_REQUEST_BUFFER_SECONDS
+
+from openpilot.selfdrive.car.helpers import convert_to_capnp
+from openpilot.selfdrive.locationd.helpers import Pose
+from openpilot.common.mock.generators import generate_livePose
+from openpilot.sunnypilot.selfdrive.car import interfaces as sunnypilot_interfaces
+
+def get_controller(car_name):
+  CarInterface = interfaces[car_name]
+  CP = CarInterface.get_non_essential_params(car_name)
+  CP_SP = CarInterface.get_non_essential_params_sp(CP, car_name)
+  CI = CarInterface(CP, CP_SP)
+  sunnypilot_interfaces.setup_interfaces(CI)
+  CP_SP = convert_to_capnp(CP_SP)
+  VM = VehicleModel(CP)
+  controller = LatControlTorque(CP.as_reader(), CP_SP.as_reader(), CI, DT_CTRL)
+  return controller, VM
+
+class TestLatControlTorqueBuffer:
+
+  @parameterized.expand([(TOYOTA.TOYOTA_COROLLA_TSS2,)])
+  def test_request_buffer_consistency(self, car_name):
+    buffer_steps = int(LAT_ACCEL_REQUEST_BUFFER_SECONDS / DT_CTRL)
+    controller, VM = get_controller(car_name)
+
+    CS = car.CarState.new_message()
+    CS.vEgo = 30
+    CS.steeringPressed = False
+    params = log.LiveParametersData.new_message()
+
+    lp = generate_livePose()
+    pose = Pose.from_live_pose(lp.livePose)
+
+    for _ in range(buffer_steps):
+      controller.update(True, CS, VM, params, False, 0.001, pose, False, 0.2)
+    assert all(val != 0 for val in controller.lat_accel_request_buffer)
+
+    for _ in range(buffer_steps):
+      controller.update(False, CS, VM, params, False, 0.0, pose, False, 0.2)
+    assert all(val == 0 for val in controller.lat_accel_request_buffer)

openpilot/selfdrive/controls/tests/test_leads.py

@@ -0,0 +1,31 @@
+import openpilot.cereal.messaging as messaging
+
+from opendbc.car.toyota.values import CAR as TOYOTA
+from openpilot.selfdrive.test.process_replay import replay_process_with_name
+
+
+class TestLeads:
+  def test_radar_fault(self):
+    # if there's no radar-related can traffic, radard should either not respond or respond with an error
+    # this is tightly coupled with underlying car radar_interface implementation, but it's a good sanity check
+    def single_iter_pkg():
+      # single iter package, with meaningless cans and empty carState/modelV2
+      msgs = []
+      for _ in range(500):
+        can = messaging.new_message("can", 1)
+        cs = messaging.new_message("carState")
+        cp = messaging.new_message("carParams")
+        msgs.append(can.as_reader())
+        msgs.append(cs.as_reader())
+        msgs.append(cp.as_reader())
+      model = messaging.new_message("modelV2")
+      msgs.append(model.as_reader())
+
+      return msgs
+
+    msgs = [m for _ in range(3) for m in single_iter_pkg()]
+    out = replay_process_with_name("card", msgs, fingerprint=TOYOTA.TOYOTA_COROLLA_TSS2)
+    states = [m for m in out if m.which() == "liveTracks"]
+    failures = [not state.valid for state in states]
+
+    assert len(states) == 0 or all(failures)

openpilot/selfdrive/controls/tests/test_longcontrol.py

@@ -0,0 +1,60 @@
+from openpilot.cereal import custom
+from opendbc.car.structs import car
+from openpilot.selfdrive.controls.lib.longcontrol import LongCtrlState, long_control_state_trans
+
+
+
+
+class TestLongControlStateTransition:
+
+  def test_stay_stopped(self):
+    CP = car.CarParams.new_message()
+    CP_SP = custom.CarParamsSP.new_message()
+    active = True
+    current_state = LongCtrlState.stopping
+    next_state = long_control_state_trans(CP, CP_SP, active, current_state, v_ego=0.1,
+                             should_stop=True, brake_pressed=False, cruise_standstill=False)
+    assert next_state == LongCtrlState.stopping
+    next_state = long_control_state_trans(CP, CP_SP, active, current_state, v_ego=0.1,
+                             should_stop=False, brake_pressed=True, cruise_standstill=False)
+    assert next_state == LongCtrlState.stopping
+    next_state = long_control_state_trans(CP, CP_SP, active, current_state, v_ego=0.1,
+                             should_stop=False, brake_pressed=False, cruise_standstill=True)
+    assert next_state == LongCtrlState.stopping
+    next_state = long_control_state_trans(CP, CP_SP, active, current_state, v_ego=1.0,
+                             should_stop=False, brake_pressed=False, cruise_standstill=False)
+    assert next_state == LongCtrlState.pid
+    active = False
+    next_state = long_control_state_trans(CP, CP_SP, active, current_state, v_ego=1.0,
+                             should_stop=False, brake_pressed=False, cruise_standstill=False)
+    assert next_state == LongCtrlState.off
+
+def test_engage():
+  CP = car.CarParams.new_message()
+  CP_SP = custom.CarParamsSP.new_message()
+  active = True
+  current_state = LongCtrlState.off
+  next_state = long_control_state_trans(CP, CP_SP, active, current_state, v_ego=0.1,
+                             should_stop=True, brake_pressed=False, cruise_standstill=False)
+  assert next_state == LongCtrlState.stopping
+  next_state = long_control_state_trans(CP, CP_SP, active, current_state, v_ego=0.1,
+                             should_stop=False, brake_pressed=True, cruise_standstill=False)
+  assert next_state == LongCtrlState.stopping
+  next_state = long_control_state_trans(CP, CP_SP, active, current_state, v_ego=0.1,
+                             should_stop=False, brake_pressed=False, cruise_standstill=True)
+  assert next_state == LongCtrlState.stopping
+  next_state = long_control_state_trans(CP, CP_SP, active, current_state, v_ego=0.1,
+                             should_stop=False, brake_pressed=False, cruise_standstill=False)
+  assert next_state == LongCtrlState.pid
+
+def test_starting():
+  CP = car.CarParams.new_message(startingState=True, vEgoStarting=0.5)
+  CP_SP = custom.CarParamsSP.new_message()
+  active = True
+  current_state = LongCtrlState.starting
+  next_state = long_control_state_trans(CP, CP_SP, active, current_state, v_ego=0.1,
+                             should_stop=False, brake_pressed=False, cruise_standstill=False)
+  assert next_state == LongCtrlState.starting
+  next_state = long_control_state_trans(CP, CP_SP, active, current_state, v_ego=1.0,
+                             should_stop=False, brake_pressed=False, cruise_standstill=False)
+  assert next_state == LongCtrlState.pid

openpilot/selfdrive/controls/tests/test_torqued_lat_accel_offset.py

@@ -0,0 +1,73 @@
+import numpy as np
+from openpilot.cereal import messaging
+from opendbc.car.structs import car
+from opendbc.car import ACCELERATION_DUE_TO_GRAVITY
+from opendbc.car import structs
+from opendbc.car.lateral import get_friction, FRICTION_THRESHOLD
+from openpilot.common.realtime import DT_MDL
+from openpilot.selfdrive.locationd.torqued import TorqueEstimator, MIN_BUCKET_POINTS, POINTS_PER_BUCKET, STEER_BUCKET_BOUNDS
+
+np.random.seed(0)
+
+LA_ERR_STD = 1.0
+INPUT_NOISE_STD = 0.08
+V_EGO = 30.0
+
+WARMUP_BUCKET_POINTS = (1.5*MIN_BUCKET_POINTS).astype(int)
+STRAIGHT_ROAD_LA_BOUNDS = (0.02, 0.03)
+
+ROLL_BIAS_DEG = 2.0
+ROLL_COMPENSATION_BIAS = ACCELERATION_DUE_TO_GRAVITY*float(np.sin(np.deg2rad(ROLL_BIAS_DEG)))
+TORQUE_TUNE = structs.CarParams.LateralTorqueTuning(latAccelFactor=2.0, latAccelOffset=0.0, friction=0.2)
+TORQUE_TUNE_BIASED = structs.CarParams.LateralTorqueTuning(latAccelFactor=2.0, latAccelOffset=-ROLL_COMPENSATION_BIAS, friction=0.2)
+
+def generate_inputs(torque_tune, la_err_std, input_noise_std=None):
+  rng = np.random.default_rng(0)
+  steer_torques = np.concat([rng.uniform(bnd[0], bnd[1], pts) for bnd, pts in zip(STEER_BUCKET_BOUNDS, WARMUP_BUCKET_POINTS, strict=True)])
+  la_errs = rng.normal(scale=la_err_std, size=steer_torques.size)
+  frictions = np.array([get_friction(la_err, 0.0, FRICTION_THRESHOLD, torque_tune) for la_err in la_errs])
+  lat_accels = torque_tune.latAccelFactor*steer_torques + torque_tune.latAccelOffset + frictions
+  if input_noise_std is not None:
+    steer_torques += rng.normal(scale=input_noise_std, size=steer_torques.size)
+    lat_accels += rng.normal(scale=input_noise_std, size=steer_torques.size)
+  return steer_torques, lat_accels
+
+def get_warmed_up_estimator(steer_torques, lat_accels):
+  est = TorqueEstimator(car.CarParams())
+  for steer_torque, lat_accel in zip(steer_torques, lat_accels, strict=True):
+    est.filtered_points.add_point(steer_torque, lat_accel)
+  return est
+
+def simulate_straight_road_msgs(est):
+  carControl = messaging.new_message('carControl').carControl
+  carOutput = messaging.new_message('carOutput').carOutput
+  carState = messaging.new_message('carState').carState
+  livePose = messaging.new_message('livePose').livePose
+  carControl.latActive = True
+  carState.vEgo = V_EGO
+  carState.steeringPressed = False
+  ts = DT_MDL*np.arange(2*POINTS_PER_BUCKET)
+  steer_torques = np.concat((np.linspace(-0.03, -0.02, POINTS_PER_BUCKET), np.linspace(0.02, 0.03, POINTS_PER_BUCKET)))
+  lat_accels = TORQUE_TUNE.latAccelFactor * steer_torques
+  for t, steer_torque, lat_accel in zip(ts, steer_torques, lat_accels, strict=True):
+    carOutput.actuatorsOutput.torque = float(-steer_torque)
+    livePose.orientationNED = {'x': float(np.deg2rad(ROLL_BIAS_DEG)), 'valid': True}
+    livePose.angularVelocityDevice = {'z': float(lat_accel / V_EGO), 'valid': True}
+    livePose.inputsOK, livePose.sensorsOK, livePose.posenetOK = True, True, True
+    livePose.timestamp = int(t * 1e9)
+    for which, msg in (('carControl', carControl), ('carOutput', carOutput), ('carState', carState), ('livePose', livePose)):
+      est.handle_log(t, which, msg)
+
+def test_estimated_offset():
+  steer_torques, lat_accels = generate_inputs(TORQUE_TUNE_BIASED, la_err_std=LA_ERR_STD, input_noise_std=INPUT_NOISE_STD)
+  est = get_warmed_up_estimator(steer_torques, lat_accels)
+  msg = est.get_msg()
+  # TODO add lataccelfactor and friction check when we have more accurate estimates
+  assert abs(msg.liveTorqueParameters.latAccelOffsetRaw - TORQUE_TUNE_BIASED.latAccelOffset) < 0.1
+
+def test_straight_road_roll_bias():
+  steer_torques, lat_accels = generate_inputs(TORQUE_TUNE, la_err_std=LA_ERR_STD, input_noise_std=INPUT_NOISE_STD)
+  est = get_warmed_up_estimator(steer_torques, lat_accels)
+  simulate_straight_road_msgs(est)
+  msg = est.get_msg()
+  assert (msg.liveTorqueParameters.latAccelOffsetRaw < -0.05) and np.isfinite(msg.liveTorqueParameters.latAccelOffsetRaw)