openpilot_comma/selfdrive/controls/lib/latcontrol_torque.py

import math

from cereal import log
from common.numpy_fast import interp
from selfdrive.controls.lib.latcontrol import LatControl, MIN_STEER_SPEED
from selfdrive.controls.lib.pid import PIDController
from selfdrive.controls.lib.vehicle_model import ACCELERATION_DUE_TO_GRAVITY

# At higher speeds (25+mph) we can assume:
# Lateral acceleration achieved by a specific car correlates to
# torque applied to the steering rack. It does not correlate to
# wheel slip, or to speed.

# This controller applies torque to achieve desired lateral
# accelerations. To compensate for the low speed effects we
# use a LOW_SPEED_FACTOR in the error. Additionally, there is
# friction in the steering wheel that needs to be overcome to
# move it at all, this is compensated for too.


LOW_SPEED_FACTOR = 200
JERK_THRESHOLD = 0.2


def set_torque_tune(tune, MAX_LAT_ACCEL=2.5, FRICTION=.1):
  tune.init('torque')
  tune.torque.useSteeringAngle = True
  tune.torque.kp = 1.0 / MAX_LAT_ACCEL
  tune.torque.kf = 1.0 / MAX_LAT_ACCEL
  tune.torque.ki = 0.1 / MAX_LAT_ACCEL
  tune.torque.friction = FRICTION


class LatControlTorque(LatControl):
  def __init__(self, CP, CI):
    super().__init__(CP, CI)
    self.pid = PIDController(CP.lateralTuning.torque.kp, CP.lateralTuning.torque.ki,
                             k_f=CP.lateralTuning.torque.kf, pos_limit=self.steer_max, neg_limit=-self.steer_max)
    self.get_steer_feedforward = CI.get_steer_feedforward_function()
    self.use_steering_angle = CP.lateralTuning.torque.useSteeringAngle
    self.friction = CP.lateralTuning.torque.friction
    self.kf = CP.lateralTuning.torque.kf

  def reset(self):
    super().reset()
    self.pid.reset()

  def update(self, active, CS, VM, params, last_actuators, desired_curvature, desired_curvature_rate, llk):
    pid_log = log.ControlsState.LateralTorqueState.new_message()

    if CS.vEgo < MIN_STEER_SPEED or not active:
      output_torque = 0.0
      pid_log.active = False
    else:
      if self.use_steering_angle:
        actual_curvature = -VM.calc_curvature(math.radians(CS.steeringAngleDeg - params.angleOffsetDeg), CS.vEgo, params.roll)
      else:
        actual_curvature_vm = -VM.calc_curvature(math.radians(CS.steeringAngleDeg - params.angleOffsetDeg), CS.vEgo, params.roll)
        actual_curvature_llk = llk.angularVelocityCalibrated.value[2] / CS.vEgo
        actual_curvature = interp(CS.vEgo, [2.0, 5.0], [actual_curvature_vm, actual_curvature_llk])
      desired_lateral_accel = desired_curvature * CS.vEgo ** 2
      desired_lateral_jerk = desired_curvature_rate * CS.vEgo ** 2
      actual_lateral_accel = actual_curvature * CS.vEgo ** 2

      setpoint = desired_lateral_accel + LOW_SPEED_FACTOR * desired_curvature
      measurement = actual_lateral_accel + LOW_SPEED_FACTOR * actual_curvature
      error = setpoint - measurement
      pid_log.error = error

      ff = desired_lateral_accel - params.roll * ACCELERATION_DUE_TO_GRAVITY
      # convert friction into lateral accel units for feedforward
      friction_compensation = interp(desired_lateral_jerk, [-JERK_THRESHOLD, JERK_THRESHOLD], [-self.friction, self.friction])
      ff += friction_compensation / self.kf
      freeze_integrator = CS.steeringRateLimited or CS.steeringPressed or CS.vEgo < 5
      output_torque = self.pid.update(error,
                                      feedforward=ff,
                                      speed=CS.vEgo,
                                      freeze_integrator=freeze_integrator)

      pid_log.active = True
      pid_log.p = self.pid.p
      pid_log.i = self.pid.i
      pid_log.d = self.pid.d
      pid_log.f = self.pid.f
      pid_log.output = -output_torque
      pid_log.saturated = self._check_saturation(self.steer_max - abs(output_torque) < 1e-3, CS)
      pid_log.actualLateralAccel = actual_lateral_accel
      pid_log.desiredLateralAccel = desired_lateral_accel

    # TODO left is positive in this convention
    return -output_torque, 0.0, pid_log