openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for over 200 supported car makes and models.
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import math
import numpy as np
from collections import deque
from cereal import log
from opendbc.car.lateral import FRICTION_THRESHOLD, get_friction
from openpilot.common.constants import ACCELERATION_DUE_TO_GRAVITY
from openpilot.selfdrive.controls.lib.drive_helpers import MIN_SPEED
from openpilot.selfdrive.controls.lib.latcontrol import LatControl
from openpilot.common.pid import PIDController
# 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_X = [0, 10, 20, 30]
LOW_SPEED_Y = [15, 13, 10, 5]
class LatControlTorque(LatControl):
def __init__(self, CP, CI, dt):
super().__init__(CP, CI, dt)
self.torque_params = CP.lateralTuning.torque.as_builder()
self.torque_from_lateral_accel = CI.torque_from_lateral_accel()
self.lateral_accel_from_torque = CI.lateral_accel_from_torque()
self.pid = PIDController(self.torque_params.kp, self.torque_params.ki,
k_f=self.torque_params.kf, rate=1/self.dt)
self.update_limits()
self.steering_angle_deadzone_deg = self.torque_params.steeringAngleDeadzoneDeg
self.LATACCEL_REQUEST_BUFFER_NUM_FRAMES = int(1 / self.dt)
self.requested_lateral_accel_buffer = deque([0.] * self.LATACCEL_REQUEST_BUFFER_NUM_FRAMES , maxlen=self.LATACCEL_REQUEST_BUFFER_NUM_FRAMES)
def update_live_torque_params(self, latAccelFactor, latAccelOffset, friction):
self.torque_params.latAccelFactor = latAccelFactor
self.torque_params.latAccelOffset = latAccelOffset
self.torque_params.friction = friction
self.update_limits()
def update_limits(self):
self.pid.set_limits(self.lateral_accel_from_torque(self.steer_max, self.torque_params),
self.lateral_accel_from_torque(-self.steer_max, self.torque_params))
def update(self, active, CS, VM, params, steer_limited_by_safety, desired_curvature, curvature_limited, lat_delay):
pid_log = log.ControlsState.LateralTorqueState.new_message()
if not active:
output_torque = 0.0
pid_log.active = False
else:
actual_curvature = -VM.calc_curvature(math.radians(CS.steeringAngleDeg - params.angleOffsetDeg), CS.vEgo, params.roll)
roll_compensation = params.roll * ACCELERATION_DUE_TO_GRAVITY
curvature_deadzone = abs(VM.calc_curvature(math.radians(self.steering_angle_deadzone_deg), CS.vEgo, 0.0))
delay_frames = int(np.clip(lat_delay / self.dt, 1, self.LATACCEL_REQUEST_BUFFER_NUM_FRAMES))
expected_lateral_accel = self.requested_lateral_accel_buffer[-delay_frames]
# TODO factor out lateral jerk from error to later replace it with delay independent alternative
future_desired_lateral_accel = desired_curvature * CS.vEgo ** 2
self.requested_lateral_accel_buffer.append(future_desired_lateral_accel)
gravity_adjusted_future_lateral_accel = future_desired_lateral_accel - roll_compensation
desired_lateral_jerk = (future_desired_lateral_accel - expected_lateral_accel) / lat_delay
actual_lateral_accel = actual_curvature * CS.vEgo ** 2
lateral_accel_deadzone = curvature_deadzone * CS.vEgo ** 2
low_speed_factor = np.interp(CS.vEgo, LOW_SPEED_X, LOW_SPEED_Y)**2 / (np.clip(CS.vEgo, MIN_SPEED, np.inf) ** 2)
setpoint = lat_delay * desired_lateral_jerk + expected_lateral_accel
measurement = actual_lateral_accel
error = setpoint - measurement
error_lsf = error + low_speed_factor * error
# do error correction in lateral acceleration space, convert at end to handle non-linear torque responses correctly
pid_log.error = float(error_lsf)
ff = gravity_adjusted_future_lateral_accel
# latAccelOffset corrects roll compensation bias from device roll misalignment relative to car roll
ff -= self.torque_params.latAccelOffset
# TODO jerk is weighted by lat_delay for legacy reasons, but should be made independent of it
ff += get_friction(error, lateral_accel_deadzone, FRICTION_THRESHOLD, self.torque_params)
freeze_integrator = steer_limited_by_safety or CS.steeringPressed or CS.vEgo < 5
output_lataccel = self.pid.update(pid_log.error,
feedforward=ff,
speed=CS.vEgo,
freeze_integrator=freeze_integrator)
output_torque = self.torque_from_lateral_accel(output_lataccel, self.torque_params)
pid_log.active = True
pid_log.p = float(self.pid.p)
pid_log.i = float(self.pid.i)
pid_log.d = float(self.pid.d)
pid_log.f = float(self.pid.f)
pid_log.output = float(-output_torque) # TODO: log lat accel?
pid_log.actualLateralAccel = float(actual_lateral_accel)
pid_log.desiredLateralAccel = float(expected_lateral_accel)
pid_log.saturated = bool(self._check_saturation(self.steer_max - abs(output_torque) < 1e-3, CS, steer_limited_by_safety, curvature_limited))
# TODO left is positive in this convention
return -output_torque, 0.0, pid_log