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269 lines
13 KiB
Python
Executable File
269 lines
13 KiB
Python
Executable File
#!/usr/bin/env python3
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from math import fabs, exp
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import numpy as np
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from opendbc.car import get_safety_config, structs
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from opendbc.car.common.conversions import Conversions as CV
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from opendbc.car.gm.carcontroller import CarController
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from opendbc.car.gm.carstate import CarState
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from opendbc.car.gm.radar_interface import RadarInterface, RADAR_HEADER_MSG, CAMERA_DATA_HEADER_MSG
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from opendbc.car.gm.values import CAR, CarControllerParams, EV_CAR, CAMERA_ACC_CAR, SDGM_CAR, ALT_ACCS, CanBus, GMSafetyFlags
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from opendbc.car.interfaces import CarInterfaceBase, TorqueFromLateralAccelCallbackType, LateralAccelFromTorqueCallbackType
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from opendbc.sunnypilot.car.gm.interface_ext import CarInterfaceExt
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from opendbc.sunnypilot.car.gm.values_ext import GMFlagsSP, GMSafetyFlagsSP
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TransmissionType = structs.CarParams.TransmissionType
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NetworkLocation = structs.CarParams.NetworkLocation
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# sunnypilot-specific torque parameters for Bolt cars that actually use the d parameter
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NON_LINEAR_TORQUE_PARAMS_SP = {
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CAR.CHEVROLET_BOLT_NON_ACC: [2.24, 1.1, 0.28, -0.07],
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CAR.CHEVROLET_BOLT_NON_ACC_1ST_GEN: [1.8, 1.1, 0.3, -0.045],
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}
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NON_LINEAR_TORQUE_PARAMS = {
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CAR.CHEVROLET_BOLT_EUV: [2.6531724862969748, 1.0, 0.1919764879840985, 0.009054123646805178],
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CAR.GMC_ACADIA: [4.78003305, 1.0, 0.3122, 0.05591772],
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CAR.CHEVROLET_SILVERADO: [3.29974374, 1.0, 0.25571356, 0.0465122],
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**NON_LINEAR_TORQUE_PARAMS_SP,
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}
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class CarInterface(CarInterfaceBase, CarInterfaceExt):
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CarState = CarState
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CarController = CarController
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RadarInterface = RadarInterface
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DRIVABLE_GEARS = (structs.CarState.GearShifter.sport, structs.CarState.GearShifter.low,
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structs.CarState.GearShifter.eco, structs.CarState.GearShifter.manumatic)
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def __init__(self, CP, CP_SP):
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CarInterfaceBase.__init__(self, CP, CP_SP)
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CarInterfaceExt.__init__(self, CP, CarInterfaceBase)
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@staticmethod
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def get_pid_accel_limits(CP, CP_SP, current_speed, cruise_speed):
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return CarControllerParams.ACCEL_MIN, CarControllerParams.ACCEL_MAX
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# Determined by iteratively plotting and minimizing error for f(angle, speed) = steer.
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@staticmethod
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def get_steer_feedforward_volt(desired_angle, v_ego):
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desired_angle *= 0.02904609
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sigmoid = desired_angle / (1 + fabs(desired_angle))
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return 0.10006696 * sigmoid * (v_ego + 3.12485927)
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def get_steer_feedforward_function(self):
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if self.CP.carFingerprint == CAR.CHEVROLET_VOLT:
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return self.get_steer_feedforward_volt
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else:
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return CarInterfaceBase.get_steer_feedforward_default
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def get_lataccel_torque_siglin(self) -> tuple[list[float], np.ndarray]:
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def torque_from_lateral_accel_siglin_func(lateral_acceleration: float) -> float:
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# The "lat_accel vs torque" relationship is assumed to be the sum of "sigmoid + linear" curves
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# An important thing to consider is that the slope at 0 should be > 0 (ideally >1)
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# This has big effect on the stability about 0 (noise when going straight)
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non_linear_torque_params = NON_LINEAR_TORQUE_PARAMS.get(self.CP.carFingerprint)
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assert non_linear_torque_params, "The params are not defined"
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a, b, c, d = non_linear_torque_params
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sig_input = a * lateral_acceleration
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sig = np.sign(sig_input) * (1 / (1 + exp(-fabs(sig_input))) - 0.5)
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steer_torque = (sig * b) + (lateral_acceleration * c) + d
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return float(steer_torque)
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lataccel_values = np.arange(-5.0, 5.0, 0.01)
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torque_values = [torque_from_lateral_accel_siglin_func(x) for x in lataccel_values]
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assert min(torque_values) < -1 and max(torque_values) > 1, "The torque values should cover the range [-1, 1]"
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return torque_values, lataccel_values
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def torque_from_lateral_accel(self) -> TorqueFromLateralAccelCallbackType:
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if self.CP.carFingerprint in NON_LINEAR_TORQUE_PARAMS:
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torque_values, lataccel_values = self.get_lataccel_torque_siglin()
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def torque_from_lateral_accel_siglin(lateral_acceleration: float, torque_params: structs.CarParams.LateralTorqueTuning):
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return np.interp(lateral_acceleration, lataccel_values, torque_values)
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return torque_from_lateral_accel_siglin
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else:
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return self.torque_from_lateral_accel_linear
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def lateral_accel_from_torque(self) -> LateralAccelFromTorqueCallbackType:
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if self.CP.carFingerprint in NON_LINEAR_TORQUE_PARAMS:
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torque_values, lataccel_values = self.get_lataccel_torque_siglin()
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def lateral_accel_from_torque_siglin(torque: float, torque_params: structs.CarParams.LateralTorqueTuning):
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return np.interp(torque, torque_values, lataccel_values)
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return lateral_accel_from_torque_siglin
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else:
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return self.lateral_accel_from_torque_linear
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@staticmethod
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def _get_params(ret: structs.CarParams, candidate, fingerprint, car_fw, alpha_long, is_release, docs) -> structs.CarParams:
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ret.brand = "gm"
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ret.safetyConfigs = [get_safety_config(structs.CarParams.SafetyModel.gm)]
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ret.autoResumeSng = False
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ret.enableBsm = 0x142 in fingerprint[CanBus.POWERTRAIN]
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if candidate in EV_CAR:
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ret.transmissionType = TransmissionType.direct
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ret.safetyConfigs[0].safetyParam |= GMSafetyFlags.EV.value
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else:
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ret.transmissionType = TransmissionType.automatic
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ret.longitudinalTuning.kiBP = [5., 35.]
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if candidate in (CAMERA_ACC_CAR | SDGM_CAR):
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ret.alphaLongitudinalAvailable = candidate not in SDGM_CAR
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ret.networkLocation = NetworkLocation.fwdCamera
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ret.radarUnavailable = True # no radar
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ret.pcmCruise = True
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ret.safetyConfigs[0].safetyParam |= GMSafetyFlags.HW_CAM.value
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ret.minEnableSpeed = -1 if candidate in SDGM_CAR else 5 * CV.KPH_TO_MS
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ret.minSteerSpeed = 10 * CV.KPH_TO_MS
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# Tuning for experimental long
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ret.longitudinalTuning.kiV = [2.0, 1.5]
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ret.stoppingDecelRate = 2.0 # reach brake quickly after enabling
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ret.vEgoStopping = 0.25
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ret.vEgoStarting = 0.25
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if alpha_long:
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ret.pcmCruise = False
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ret.openpilotLongitudinalControl = True
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ret.safetyConfigs[0].safetyParam |= GMSafetyFlags.HW_CAM_LONG.value
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if candidate in ALT_ACCS:
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ret.alphaLongitudinalAvailable = False
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ret.openpilotLongitudinalControl = False
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ret.minEnableSpeed = -1. # engage speed is decided by PCM
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else: # ASCM, OBD-II harness
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ret.openpilotLongitudinalControl = True
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ret.networkLocation = NetworkLocation.gateway
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# LRR messages can take up to a few seconds to start sending after ignition, check camera data as well which starts earlier
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ret.radarUnavailable = RADAR_HEADER_MSG not in fingerprint[CanBus.OBSTACLE] and CAMERA_DATA_HEADER_MSG not in fingerprint[CanBus.OBSTACLE] and not docs
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ret.pcmCruise = False # stock non-adaptive cruise control is kept off
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# supports stop and go, but initial engage must (conservatively) be above 18mph
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ret.minEnableSpeed = 18 * CV.MPH_TO_MS
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ret.minSteerSpeed = 7 * CV.MPH_TO_MS
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# Tuning
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ret.longitudinalTuning.kiV = [2.4, 1.5]
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# These cars have been put into dashcam only due to both a lack of users and test coverage.
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# These cars likely still work fine. Once a user confirms each car works and a test route is
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# added to opendbc/car/tests/routes.py, we can remove it from this list.
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ret.dashcamOnly = candidate in {CAR.CADILLAC_ATS, CAR.HOLDEN_ASTRA, CAR.CHEVROLET_MALIBU, CAR.BUICK_REGAL} or \
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(ret.networkLocation == NetworkLocation.gateway and ret.radarUnavailable)
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# Start with a baseline tuning for all GM vehicles. Override tuning as needed in each model section below.
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ret.lateralTuning.pid.kiBP, ret.lateralTuning.pid.kpBP = [[0.], [0.]]
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ret.lateralTuning.pid.kpV, ret.lateralTuning.pid.kiV = [[0.2], [0.00]]
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ret.lateralTuning.pid.kf = 0.00004 # full torque for 20 deg at 80mph means 0.00007818594
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ret.steerActuatorDelay = 0.1 # Default delay, not measured yet
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ret.steerLimitTimer = 0.4
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ret.longitudinalActuatorDelay = 0.5 # large delay to initially start braking
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if candidate == CAR.CHEVROLET_VOLT:
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ret.lateralTuning.pid.kpBP = [0., 40.]
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ret.lateralTuning.pid.kpV = [0., 0.17]
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ret.lateralTuning.pid.kiBP = [0.]
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ret.lateralTuning.pid.kiV = [0.]
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ret.lateralTuning.pid.kf = 1. # get_steer_feedforward_volt()
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ret.steerActuatorDelay = 0.2
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elif candidate == CAR.GMC_ACADIA:
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ret.minEnableSpeed = -1. # engage speed is decided by pcm
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ret.steerActuatorDelay = 0.2
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CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
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elif candidate == CAR.BUICK_LACROSSE:
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CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
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elif candidate == CAR.CADILLAC_ESCALADE:
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ret.minEnableSpeed = -1. # engage speed is decided by pcm
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CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
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elif candidate in (CAR.CADILLAC_ESCALADE_ESV, CAR.CADILLAC_ESCALADE_ESV_2019):
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ret.minEnableSpeed = -1. # engage speed is decided by pcm
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if candidate == CAR.CADILLAC_ESCALADE_ESV:
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ret.lateralTuning.pid.kiBP, ret.lateralTuning.pid.kpBP = [[10., 41.0], [10., 41.0]]
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ret.lateralTuning.pid.kpV, ret.lateralTuning.pid.kiV = [[0.13, 0.24], [0.01, 0.02]]
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ret.lateralTuning.pid.kf = 0.000045
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else:
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ret.steerActuatorDelay = 0.2
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CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
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elif candidate == CAR.CHEVROLET_BOLT_EUV:
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ret.steerActuatorDelay = 0.2
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CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
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elif candidate == CAR.CHEVROLET_SILVERADO:
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# On the Bolt, the ECM and camera independently check that you are either above 5 kph or at a stop
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# with foot on brake to allow engagement, but this platform only has that check in the camera.
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# TODO: check if this is split by EV/ICE with more platforms in the future
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if ret.openpilotLongitudinalControl:
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ret.minEnableSpeed = -1.
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CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
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elif candidate == CAR.CHEVROLET_EQUINOX:
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CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
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elif candidate == CAR.CHEVROLET_TRAILBLAZER:
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ret.steerActuatorDelay = 0.2
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CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
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elif candidate == CAR.CADILLAC_XT4:
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ret.steerActuatorDelay = 0.2
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ret.minSteerSpeed = 30 * CV.MPH_TO_MS
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CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
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elif candidate == CAR.CHEVROLET_VOLT_2019:
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ret.steerActuatorDelay = 0.2
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CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
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elif candidate == CAR.CHEVROLET_TRAVERSE:
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ret.steerActuatorDelay = 0.2
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CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
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elif candidate == CAR.GMC_YUKON:
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ret.steerActuatorDelay = 0.5
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CarInterfaceBase.configure_torque_tune(candidate, ret.lateralTuning)
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ret.dashcamOnly = True # Needs steerRatio, tireStiffness, and lat accel factor tuning
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return ret
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@staticmethod
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def _get_params_sp(stock_cp: structs.CarParams, ret: structs.CarParamsSP, candidate, fingerprint: dict[int, dict[int, int]],
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car_fw: list[structs.CarParams.CarFw], alpha_long: bool, is_release_sp: bool, docs: bool) -> structs.CarParamsSP:
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if candidate in (CAR.CHEVROLET_MALIBU_NON_ACC_9TH_GEN, CAR.CHEVROLET_BOLT_NON_ACC, CAR.CHEVROLET_BOLT_NON_ACC_1ST_GEN,
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CAR.CHEVROLET_BOLT_NON_ACC_2ND_GEN, CAR.CHEVROLET_TRAILBLAZER_NON_ACC_2ND_GEN):
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stock_cp.steerActuatorDelay = 0.2
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CarInterfaceBase.configure_torque_tune(candidate, stock_cp.lateralTuning)
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elif candidate in (CAR.CHEVROLET_EQUINOX_NON_ACC_3RD_GEN, ):
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CarInterfaceBase.configure_torque_tune(candidate, stock_cp.lateralTuning)
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# NON_ACC vehicles should use camera car speed thresholds
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if ret.flags & GMFlagsSP.NON_ACC:
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stock_cp.dashcamOnly = False
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stock_cp.alphaLongitudinalAvailable = False
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stock_cp.networkLocation = NetworkLocation.fwdCamera
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stock_cp.openpilotLongitudinalControl = False
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stock_cp.pcmCruise = True
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stock_cp.safetyConfigs[0].safetyParam |= GMSafetyFlags.HW_CAM.value
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ret.safetyParam |= GMSafetyFlagsSP.NON_ACC
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stock_cp.minEnableSpeed = 24 * CV.MPH_TO_MS # 24 mph
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stock_cp.minSteerSpeed = 3.0 # ~6 mph
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# dashcamOnly platforms: untested platforms, need user validations
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if candidate in (CAR.CHEVROLET_BOLT_NON_ACC_2ND_GEN, CAR.CHEVROLET_EQUINOX_NON_ACC_3RD_GEN,
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CAR.CHEVROLET_SUBURBAN_NON_ACC_11TH_GEN, CAR.CADILLAC_CT6_NON_ACC_1ST_GEN, CAR.CHEVROLET_TRAILBLAZER_NON_ACC_2ND_GEN,
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CAR.CADILLAC_XT5_NON_ACC_1ST_GEN):
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stock_cp.dashcamOnly = True
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return ret
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