110 lines
5.7 KiB
Python
110 lines
5.7 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.lateral import FRICTION_THRESHOLD, get_friction
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from opendbc.car.tests.test_lateral_limits import MAX_LAT_JERK_UP
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from openpilot.common.constants import ACCELERATION_DUE_TO_GRAVITY
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from openpilot.common.filter_simple import FirstOrderFilter
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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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from openpilot.common.pid import PIDController
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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 we
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# use a LOW_SPEED_FACTOR in the error. Additionally, there is
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# friction in the steering wheel that needs to be overcome to
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# move it at all, this is compensated for too.
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LOW_SPEED_X = [0, 10, 20, 30]
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LOW_SPEED_Y = [15, 13, 10, 5]
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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(self.torque_params.kp, self.torque_params.ki,
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k_f=self.torque_params.kf, 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.LATACCEL_REQUEST_BUFFER_NUM_FRAMES = int(1 / self.dt)
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self.requested_lateral_accel_buffer = deque([0.] * self.LATACCEL_REQUEST_BUFFER_NUM_FRAMES , maxlen=self.LATACCEL_REQUEST_BUFFER_NUM_FRAMES)
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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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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):
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pid_log = log.ControlsState.LateralTorqueState.new_message()
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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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else:
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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.LATACCEL_REQUEST_BUFFER_NUM_FRAMES))
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expected_lateral_accel = self.requested_lateral_accel_buffer[-delay_frames]
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# TODO factor out lateral jerk from error to later replace it with delay independent alternative
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future_desired_lateral_accel = desired_curvature * CS.vEgo ** 2
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self.requested_lateral_accel_buffer.append(future_desired_lateral_accel)
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gravity_adjusted_future_lateral_accel = future_desired_lateral_accel - roll_compensation
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desired_lateral_jerk = (future_desired_lateral_accel - expected_lateral_accel) / lat_delay
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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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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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setpoint = lat_delay * desired_lateral_jerk + expected_lateral_accel
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error = setpoint - measurement
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error_lsf = error + low_speed_factor / self.torque_params.kp * error
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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_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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# TODO jerk is weighted by lat_delay for legacy reasons, but should be made independent of it
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ff += get_friction(error, lateral_accel_deadzone, FRICTION_THRESHOLD, self.torque_params)
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freeze_integrator = steer_limited_by_safety or CS.steeringPressed or CS.vEgo < 5
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output_lataccel = self.pid.update(pid_log.error,
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-measurement_rate,
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feedforward=ff,
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speed=CS.vEgo,
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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.saturated = bool(self._check_saturation(self.steer_max - abs(output_torque) < 1e-3, CS, steer_limited_by_safety, curvature_limited))
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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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