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89 lines
3.7 KiB
89 lines
3.7 KiB
import math
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from cereal import log
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from common.numpy_fast import interp
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from selfdrive.controls.lib.latcontrol import LatControl, MIN_STEER_SPEED
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from selfdrive.controls.lib.pid import PIDController
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from selfdrive.controls.lib.vehicle_model import ACCELERATION_DUE_TO_GRAVITY
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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_FACTOR = 200
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JERK_THRESHOLD = 0.2
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def set_torque_tune(tune, MAX_LAT_ACCEL=2.5, FRICTION=.1):
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tune.init('torque')
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tune.torque.useSteeringAngle = True
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tune.torque.kp = 1.0 / MAX_LAT_ACCEL
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tune.torque.kf = 1.0 / MAX_LAT_ACCEL
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tune.torque.ki = 0.1 / MAX_LAT_ACCEL
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tune.torque.friction = FRICTION
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class LatControlTorque(LatControl):
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def __init__(self, CP, CI):
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super().__init__(CP, CI)
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self.pid = PIDController(CP.lateralTuning.torque.kp, CP.lateralTuning.torque.ki,
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k_f=CP.lateralTuning.torque.kf, pos_limit=self.steer_max, neg_limit=-self.steer_max)
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self.get_steer_feedforward = CI.get_steer_feedforward_function()
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self.use_steering_angle = CP.lateralTuning.torque.useSteeringAngle
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self.friction = CP.lateralTuning.torque.friction
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self.kf = CP.lateralTuning.torque.kf
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def reset(self):
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super().reset()
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self.pid.reset()
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def update(self, active, CS, VM, params, last_actuators, desired_curvature, desired_curvature_rate, llk):
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pid_log = log.ControlsState.LateralTorqueState.new_message()
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if CS.vEgo < MIN_STEER_SPEED or 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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if self.use_steering_angle:
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actual_curvature = -VM.calc_curvature(math.radians(CS.steeringAngleDeg - params.angleOffsetDeg), CS.vEgo, params.roll)
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else:
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actual_curvature = llk.angularVelocityCalibrated.value[2] / CS.vEgo
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desired_lateral_accel = desired_curvature * CS.vEgo ** 2
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desired_lateral_jerk = desired_curvature_rate * CS.vEgo ** 2
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actual_lateral_accel = actual_curvature * CS.vEgo ** 2
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setpoint = desired_lateral_accel + LOW_SPEED_FACTOR * desired_curvature
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measurement = actual_lateral_accel + LOW_SPEED_FACTOR * actual_curvature
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error = setpoint - measurement
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pid_log.error = error
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ff = desired_lateral_accel - params.roll * ACCELERATION_DUE_TO_GRAVITY
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# convert friction into lateral accel units for feedforward
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friction_compensation = interp(desired_lateral_jerk, [-JERK_THRESHOLD, JERK_THRESHOLD], [-self.friction, self.friction])
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ff += friction_compensation / self.kf
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freeze_integrator = CS.steeringRateLimited or CS.steeringPressed or CS.vEgo < 5
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output_torque = self.pid.update(error,
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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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pid_log.active = True
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pid_log.p = self.pid.p
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pid_log.i = self.pid.i
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pid_log.d = self.pid.d
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pid_log.f = self.pid.f
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pid_log.output = -output_torque
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pid_log.saturated = self._check_saturation(self.steer_max - abs(output_torque) < 1e-3, CS)
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pid_log.actualLateralAccel = actual_lateral_accel
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pid_log.desiredLateralAccel = desired_lateral_accel
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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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