firestar5683
207 lines
10 KiB
Python
207 lines
10 KiB
Python
import math
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import numpy as np
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from collections import deque
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from cereal import log
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from opendbc.car.gm.values import CAR as GM_CAR
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from opendbc.car.lateral import get_friction
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from openpilot.common.constants import ACCELERATION_DUE_TO_GRAVITY, CV
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from openpilot.common.filter_simple import FirstOrderFilter
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from openpilot.common.pid import PIDController
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from openpilot.selfdrive.controls.lib.drive_helpers import MIN_SPEED
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from openpilot.selfdrive.controls.lib.latcontrol import LatControl
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# At higher speeds (25+mph) we can assume:
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# Lateral acceleration achieved by a specific car correlates to
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# torque applied to the steering rack. It does not correlate to
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# wheel slip, or to speed.
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# This controller applies torque to achieve desired lateral
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# accelerations. To compensate for the low speed effects the
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# proportional gain is increased at low speeds by the PID controller.
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# Additionally, there is friction in the steering wheel that needs
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# to be overcome to move it at all, this is compensated for too.
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KP = 0.7
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KI = 0.35
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INTERP_SPEEDS = [1, 1.5, 2.0, 3.0, 5, 7.5, 10, 15, 30]
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KP_INTERP = [250, 120, 65, 30, 11.5, 5.5, 3.5, 2.0, KP]
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LOW_SPEED_X = [0, 10, 20, 30]
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LOW_SPEED_Y = [12, 10.5, 8, 5]
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MAX_LAT_JERK_UP = 2.5 # m/s^3
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LP_FILTER_CUTOFF_HZ = 1.2
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JERK_LOOKAHEAD_SECONDS = 0.19
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JERK_GAIN = 0.22
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LAT_ACCEL_REQUEST_BUFFER_SECONDS = 1.0
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VERSION = 2
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DEBUG_TORQUE_TUNE = False
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FF_SCALE_BLEND_LAT_ACCEL = 0.05
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DEADZONE_BOOST_LAT_ACCEL = 0.15
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UNWIND_D_DES_THRESHOLD = -1.0
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UNWIND_LAT_ACCEL_NEAR_ZERO = 0.3
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MIN_LATERAL_CONTROL_SPEED = 0.3
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BOLT_2022_2023_CARS = (
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GM_CAR.CHEVROLET_BOLT_ACC_2022_2023,
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GM_CAR.CHEVROLET_BOLT_ACC_2022_2023_PEDAL,
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GM_CAR.CHEVROLET_BOLT_CC_2022_2023,
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)
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BOLT_2018_2021_CARS = (
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GM_CAR.CHEVROLET_BOLT_CC_2018_2021,
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)
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BOLT_2017_CARS = (
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GM_CAR.CHEVROLET_BOLT_CC_2017,
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)
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BOLT_CARS = BOLT_2022_2023_CARS + BOLT_2018_2021_CARS + BOLT_2017_CARS
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def get_friction_threshold(v_ego: float) -> float:
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# Keep the speed-scaled friction threshold behavior.
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return float(np.interp(v_ego, [1 * CV.MPH_TO_MS, 20 * CV.MPH_TO_MS, 75 * CV.MPH_TO_MS], [0.16, 0.19, 0.27]))
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class LatControlTorque(LatControl):
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def __init__(self, CP, CI, dt):
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super().__init__(CP, CI, dt)
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self.torque_params = CP.lateralTuning.torque.as_builder()
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self.torque_from_lateral_accel = CI.torque_from_lateral_accel()
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self.lateral_accel_from_torque = CI.lateral_accel_from_torque()
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self.pid = PIDController([INTERP_SPEEDS, KP_INTERP], KI, rate=1/self.dt)
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self.update_limits()
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self.steering_angle_deadzone_deg = self.torque_params.steeringAngleDeadzoneDeg
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self.lat_accel_request_buffer_len = int(LAT_ACCEL_REQUEST_BUFFER_SECONDS / self.dt)
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self.lat_accel_request_buffer = deque([0.] * self.lat_accel_request_buffer_len, maxlen=self.lat_accel_request_buffer_len)
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self.lookahead_frames = int(JERK_LOOKAHEAD_SECONDS / self.dt)
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self.jerk_filter = FirstOrderFilter(0.0, 1 / (2 * np.pi * LP_FILTER_CUTOFF_HZ), self.dt)
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self.previous_measurement = 0.0
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self.measurement_rate_filter = FirstOrderFilter(0.0, 1 / (2 * np.pi * (MAX_LAT_JERK_UP - 0.5)), self.dt)
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self.low_speed_reset_threshold = max(CP.minSteerSpeed, MIN_LATERAL_CONTROL_SPEED)
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self.steer_release_i_decay = 0.8
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self.prev_steering_pressed = False
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self.debug_counter = 0
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self.prev_desired_lateral_accel = 0.0
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self.is_bolt = CP.carFingerprint in BOLT_CARS
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self.is_bolt_2022_2023 = CP.carFingerprint in BOLT_2022_2023_CARS
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self.is_bolt_2018_2021 = CP.carFingerprint in BOLT_2018_2021_CARS
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self.is_bolt_2017 = CP.carFingerprint in BOLT_2017_CARS
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self.use_bolt_ff_scaling = self.is_bolt_2022_2023 or self.is_bolt_2018_2021 or self.is_bolt_2017
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self.use_bolt_ki_multiplier = self.use_bolt_ff_scaling
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self.torque_ff_scale_pos = 1.0
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self.torque_ff_scale_neg = 1.0
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self.torque_deadzone_boost = float(getattr(self.torque_params, "kfDEPRECATED", 0.0))
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self.torque_ki_mult = 1.0
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if self.is_bolt:
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kp_scale = getattr(self.torque_params, "kp", getattr(self.torque_params, "kpDEPRECATED", 1.0))
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ki_scale = getattr(self.torque_params, "ki", getattr(self.torque_params, "kiDEPRECATED", 1.0))
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kd_scale = getattr(self.torque_params, "kd", getattr(self.torque_params, "kdDEPRECATED", 1.0))
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self.torque_ff_scale_pos = float(kp_scale)
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self.torque_ff_scale_neg = float(ki_scale)
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self.torque_ki_mult = float(kd_scale)
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if self.use_bolt_ki_multiplier and self.torque_ki_mult > 0.0 and self.torque_ki_mult != 1.0:
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self.pid._k_i = [self.pid._k_i[0], [k * self.torque_ki_mult for k in self.pid._k_i[1]]]
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def update_live_torque_params(self, latAccelFactor, latAccelOffset, friction):
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self.torque_params.latAccelFactor = latAccelFactor
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self.torque_params.latAccelOffset = latAccelOffset
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self.torque_params.friction = friction
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self.update_limits()
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def update_limits(self):
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self.pid.set_limits(self.lateral_accel_from_torque(self.steer_max, self.torque_params),
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self.lateral_accel_from_torque(-self.steer_max, self.torque_params))
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def update(self, active, CS, VM, params, steer_limited_by_safety, desired_curvature, curvature_limited, lat_delay, calibrated_pose, model_data, starpilot_toggles):
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pid_log = log.ControlsState.LateralTorqueState.new_message()
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pid_log.version = VERSION
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if not active:
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output_torque = 0.0
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pid_log.active = False
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self.pid.reset()
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self.previous_measurement = 0.0
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self.measurement_rate_filter.x = 0.0
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self.lat_accel_request_buffer = deque([0.] * self.lat_accel_request_buffer_len, maxlen=self.lat_accel_request_buffer_len)
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self.prev_desired_lateral_accel = 0.0
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else:
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if self.prev_steering_pressed and not CS.steeringPressed:
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self.pid.i *= self.steer_release_i_decay
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measured_curvature = -VM.calc_curvature(math.radians(CS.steeringAngleDeg - params.angleOffsetDeg), CS.vEgo, params.roll)
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roll_compensation = params.roll * ACCELERATION_DUE_TO_GRAVITY
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curvature_deadzone = abs(VM.calc_curvature(math.radians(self.steering_angle_deadzone_deg), CS.vEgo, 0.0))
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lateral_accel_deadzone = curvature_deadzone * CS.vEgo ** 2
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delay_frames = int(np.clip(lat_delay / self.dt, 1, self.lat_accel_request_buffer_len))
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expected_lateral_accel = self.lat_accel_request_buffer[-delay_frames]
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future_desired_lateral_accel = desired_curvature * CS.vEgo ** 2
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self.lat_accel_request_buffer.append(future_desired_lateral_accel)
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raw_lateral_jerk = (future_desired_lateral_accel - expected_lateral_accel) / max(lat_delay, self.dt)
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raw_lateral_jerk = np.clip(raw_lateral_jerk, -MAX_LAT_JERK_UP, MAX_LAT_JERK_UP)
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desired_lateral_jerk = np.clip(self.jerk_filter.update(raw_lateral_jerk), -MAX_LAT_JERK_UP, MAX_LAT_JERK_UP)
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gravity_adjusted_future_lateral_accel = future_desired_lateral_accel - roll_compensation
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setpoint = expected_lateral_accel + desired_lateral_jerk * lat_delay
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desired_lateral_accel_rate = (setpoint - self.prev_desired_lateral_accel) / self.dt
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unwind_detected = (desired_lateral_accel_rate < UNWIND_D_DES_THRESHOLD and
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abs(setpoint) < UNWIND_LAT_ACCEL_NEAR_ZERO)
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self.prev_desired_lateral_accel = setpoint
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measurement = measured_curvature * CS.vEgo ** 2
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measurement_rate = self.measurement_rate_filter.update((measurement - self.previous_measurement) / self.dt)
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measurement_rate = np.clip(measurement_rate, -MAX_LAT_JERK_UP, MAX_LAT_JERK_UP)
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self.previous_measurement = measurement
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low_speed_factor = (np.interp(CS.vEgo, LOW_SPEED_X, LOW_SPEED_Y) / max(CS.vEgo, MIN_SPEED)) ** 2
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current_kp = np.interp(CS.vEgo, self.pid._k_p[0], self.pid._k_p[1])
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error = setpoint - measurement
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error_with_lsf = error * (1 + low_speed_factor / max(current_kp, 1e-3))
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# do error correction in lateral acceleration space, convert at end to handle non-linear torque responses correctly
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pid_log.error = float(error_with_lsf)
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ff = gravity_adjusted_future_lateral_accel
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# latAccelOffset corrects roll compensation bias from device roll misalignment relative to car roll
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ff -= self.torque_params.latAccelOffset
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ff_scale = 1.0
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if self.use_bolt_ff_scaling:
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ff_scale = np.interp(ff, [-FF_SCALE_BLEND_LAT_ACCEL, 0.0, FF_SCALE_BLEND_LAT_ACCEL],
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[self.torque_ff_scale_neg, 1.0, self.torque_ff_scale_pos])
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ff *= ff_scale
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ff += get_friction(error_with_lsf + JERK_GAIN * desired_lateral_jerk, lateral_accel_deadzone, get_friction_threshold(CS.vEgo), self.torque_params)
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deadzone_boost_active = False
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if self.torque_deadzone_boost > 0.0 and abs(gravity_adjusted_future_lateral_accel) < DEADZONE_BOOST_LAT_ACCEL:
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boost_scale = np.interp(abs(gravity_adjusted_future_lateral_accel), [0.0, DEADZONE_BOOST_LAT_ACCEL], [1.0, 0.0])
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ff += np.sign(gravity_adjusted_future_lateral_accel) * self.torque_deadzone_boost * boost_scale
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deadzone_boost_active = True
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if CS.vEgo < self.low_speed_reset_threshold:
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self.pid.reset()
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freeze_integrator = (steer_limited_by_safety or CS.steeringPressed or
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CS.vEgo < self.low_speed_reset_threshold or unwind_detected)
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output_lataccel = self.pid.update(pid_log.error, error_rate=-measurement_rate, speed=CS.vEgo, feedforward=ff, freeze_integrator=freeze_integrator)
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output_torque = self.torque_from_lateral_accel(output_lataccel, self.torque_params)
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pid_log.active = True
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pid_log.p = float(self.pid.p)
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pid_log.i = float(self.pid.i)
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pid_log.d = float(self.pid.d)
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pid_log.f = float(self.pid.f)
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pid_log.output = float(-output_torque) # TODO: log lat accel?
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pid_log.actualLateralAccel = float(measurement)
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pid_log.desiredLateralAccel = float(setpoint)
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pid_log.desiredLateralJerk = float(desired_lateral_jerk)
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pid_log.saturated = bool(self._check_saturation(self.steer_max - abs(output_torque) < 1e-3, CS, steer_limited_by_safety, curvature_limited))
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if DEBUG_TORQUE_TUNE and self.is_bolt:
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self.debug_counter += 1
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if self.debug_counter % 50 == 0:
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print(f"bolt_torque ff_scale={ff_scale:.3f} pos={self.torque_ff_scale_pos:.3f} "
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f"neg={self.torque_ff_scale_neg:.3f} deadzone_boost_active={deadzone_boost_active}")
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self.prev_steering_pressed = CS.steeringPressed
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# TODO left is positive in this convention
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return -output_torque, 0.0, pid_log
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