mirror of
https://github.com/firestar5683/StarPilot.git
synced 2026-11-07 04:53:47 +08:00
firestar5683
172 lines
10 KiB
Python
172 lines
10 KiB
Python
from openpilot.starpilot.flm import torque_stages as auto_stages
|
|
import math
|
|
import numpy as np
|
|
from collections import deque
|
|
|
|
from openpilot.cereal import log
|
|
from opendbc.car import structs
|
|
from opendbc.car.hyundai.values import CAR, HyundaiFlags
|
|
from opendbc.car.lateral import FRICTION_THRESHOLD, get_friction
|
|
from openpilot.common.constants import ACCELERATION_DUE_TO_GRAVITY, CV
|
|
from openpilot.common.filter_simple import FirstOrderFilter
|
|
from openpilot.selfdrive.controls.lib.latcontrol import LatControl
|
|
from openpilot.common.pid import PIDController
|
|
from openpilot.starpilot.lateral.controller_selection import ControllerMode, default_selection, policy_for
|
|
from openpilot.starpilot.lateral.torque_extension import apply_turn_assist, create_extension, create_turn_assist
|
|
from openpilot.starpilot.flm import live as flm
|
|
|
|
# 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 the
|
|
# proportional gain is increased at low speeds by the PID controller.
|
|
# Additionally, there is friction in the steering wheel that needs
|
|
# to be overcome to move it at all, this is compensated for too.
|
|
|
|
KP = 0.8
|
|
KI = 0.15
|
|
|
|
INTERP_SPEEDS = [1, 1.5, 2.0, 3.0, 5, 7.5, 10, 15, 30]
|
|
KP_INTERP = [250, 120, 65, 30, 11.5, 5.5, 3.5, 2.0, KP]
|
|
|
|
LP_FILTER_CUTOFF_HZ = 1.2
|
|
JERK_LOOKAHEAD_SECONDS = 0.19
|
|
JERK_GAIN = 0.3
|
|
LAT_ACCEL_REQUEST_BUFFER_SECONDS = 1.0
|
|
VERSION = 1
|
|
|
|
class LatControlTorque(LatControl):
|
|
def __init__(self, CP, CI, dt, *, controller_mode: ControllerMode | None = None, turn_assist: bool = False):
|
|
super().__init__(CP, CI, dt)
|
|
self.hkg_canfd_torque = bool(CP.brand == 'hyundai' and CP.flags & HyundaiFlags.CANFD and
|
|
CP.carFingerprint != CAR.HYUNDAI_IONIQ_6 and
|
|
CP.steerControlType == structs.CarParams.SteerControlType.torque and
|
|
not CP.flags & HyundaiFlags.CANFD_ANGLE_STEERING and
|
|
not (CP.notCar or CP.passive or CP.dashcamOnly))
|
|
self.controller_mode = default_selection(CP).mode if controller_mode is None else ControllerMode(controller_mode)
|
|
self.controller_policy = policy_for(CP)
|
|
if self.controller_mode == ControllerMode.STARPILOT and self.controller_policy is None:
|
|
raise ValueError('No StarPilot torque policy for CarParams')
|
|
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([INTERP_SPEEDS, KP_INTERP], KI, rate=1/self.dt)
|
|
self.update_limits()
|
|
self.steering_angle_deadzone_deg = self.torque_params.steeringAngleDeadzoneDeg
|
|
self.lat_accel_request_buffer_len = int(LAT_ACCEL_REQUEST_BUFFER_SECONDS / self.dt)
|
|
self.lat_accel_request_buffer = deque([0.] * self.lat_accel_request_buffer_len , maxlen=self.lat_accel_request_buffer_len)
|
|
self.lookahead_frames = int(JERK_LOOKAHEAD_SECONDS / self.dt)
|
|
self.jerk_filter = FirstOrderFilter(0.0, 1 / (2 * np.pi * LP_FILTER_CUTOFF_HZ), self.dt)
|
|
self.turn_assist = create_turn_assist(CP, turn_assist)
|
|
self.starpilot_extension = create_extension(self, CP, self.controller_mode, self.controller_policy, turn_assist=turn_assist)
|
|
self.flm_source = flm.GmLiveSource(CP, self.controller_mode)
|
|
self.flm_surface = None
|
|
from openpilot.starpilot.flm.runtime_adapter_registry import baseline_values
|
|
self.native_learning_baseline = baseline_values(self)
|
|
self.native_learning_refinement = None
|
|
self.native_learning_provenance = ()
|
|
self.native_learning_last_tick = 0
|
|
self.native_learning_source = None
|
|
|
|
def update_torque_parameters(self, latAccelFactor, latAccelOffset, friction):
|
|
if self.starpilot_extension is not None:
|
|
latAccelFactor, latAccelOffset, friction = self.starpilot_extension.transform_torque_parameters(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 friction(self, error, deadzone, threshold, CS, setpoint):
|
|
if self.hkg_canfd_torque and not CS.steeringPressed:
|
|
weight = np.interp(CS.vEgo, [50 * CV.MPH_TO_MS, 65 * CV.MPH_TO_MS], [0.0, 1.0])
|
|
weight *= np.interp(abs(setpoint), [0.25, 0.65], [1.0, 0.0])
|
|
threshold += max(np.interp(CS.vEgo, [65 * CV.MPH_TO_MS, 75 * CV.MPH_TO_MS], [0.65, 0.78]) - threshold, 0.0) * weight
|
|
error = math.copysign(max(abs(error) - 0.04 * weight, 0.0), error)
|
|
return get_friction(error, deadzone, threshold, self.torque_params)
|
|
|
|
def update(self, active, CS, VM, params, steer_limited_by_safety, desired_curvature, curvature_limited, lat_delay):
|
|
self.flm_surface = self.flm_source.sample(active=active, speed=CS.vEgo)
|
|
if self.starpilot_extension is not None:
|
|
result = self.starpilot_extension.update(active, CS, VM, params, steer_limited_by_safety,
|
|
desired_curvature, curvature_limited, lat_delay)
|
|
else:
|
|
result = self.update_standard(active, CS, VM, params, steer_limited_by_safety,
|
|
desired_curvature, curvature_limited, lat_delay)
|
|
return auto_stages.apply_selected_output(self, CS, VM, params, desired_curvature, result,
|
|
active=active, limited=steer_limited_by_safety or curvature_limited, curvature_limited=curvature_limited)
|
|
|
|
def update_standard(self, active, CS, VM, params, steer_limited_by_safety, desired_curvature, curvature_limited, lat_delay,
|
|
*, friction_policy=None):
|
|
pid_log = log.ControlsState.LateralTorqueState.new_message()
|
|
pid_log.version = VERSION
|
|
measured_curvature = -VM.calc_curvature(math.radians(CS.steeringAngleDeg - params.angleOffsetDeg), CS.vEgo, params.roll)
|
|
measurement = measured_curvature * CS.vEgo ** 2
|
|
future_desired_lateral_accel = desired_curvature * CS.vEgo ** 2
|
|
self.lat_accel_request_buffer.append(future_desired_lateral_accel)
|
|
|
|
roll_compensation = params.roll * ACCELERATION_DUE_TO_GRAVITY
|
|
curvature_deadzone = abs(VM.calc_curvature(math.radians(self.steering_angle_deadzone_deg + flm.deadband(self.flm_surface, CS.vEgo)), CS.vEgo, 0.0))
|
|
lateral_accel_deadzone = curvature_deadzone * CS.vEgo ** 2
|
|
lateral_accel_deadzone = auto_stages.apply_selected_deadzone(self, CS, VM, float(lateral_accel_deadzone), desired_curvature,
|
|
active=active, limited=steer_limited_by_safety or curvature_limited, curvature_limited=curvature_limited)
|
|
|
|
delay_frames = int(np.clip(lat_delay / self.dt + 1, 1, self.lat_accel_request_buffer_len))
|
|
expected_lateral_accel = self.lat_accel_request_buffer[-delay_frames]
|
|
setpoint = expected_lateral_accel
|
|
error = setpoint - measurement
|
|
|
|
lookahead_idx = int(np.clip(-delay_frames + self.lookahead_frames, -self.lat_accel_request_buffer_len+1, -2))
|
|
raw_lateral_jerk = (self.lat_accel_request_buffer[lookahead_idx+1] - self.lat_accel_request_buffer[lookahead_idx-1]) / (2 * self.dt)
|
|
desired_lateral_jerk = self.jerk_filter.update(raw_lateral_jerk)
|
|
gravity_adjusted_future_lateral_accel = future_desired_lateral_accel - roll_compensation
|
|
ff = gravity_adjusted_future_lateral_accel
|
|
# latAccelOffset corrects roll compensation bias from device roll misalignment relative to car roll
|
|
ff -= self.torque_params.latAccelOffset
|
|
threshold = flm.base_threshold(self.flm_surface, CS.vEgo, FRICTION_THRESHOLD)
|
|
ff, threshold = flm.stages(self.flm_surface, CS, setpoint, desired_lateral_jerk, ff, threshold)
|
|
if friction_policy is not None:
|
|
threshold = friction_policy.friction_threshold(CS.vEgo, setpoint, desired_lateral_jerk)
|
|
ff, threshold = auto_stages.apply_stages(self, CS, setpoint, desired_lateral_jerk, ff, threshold,
|
|
active=active, limited=steer_limited_by_safety or curvature_limited, curvature_limited=curvature_limited)
|
|
selected_friction = self.friction(error + JERK_GAIN * desired_lateral_jerk, lateral_accel_deadzone, threshold, CS, setpoint)
|
|
ff += auto_stages.apply_selected_friction(self, CS, setpoint, float(selected_friction),
|
|
active=active, limited=steer_limited_by_safety or curvature_limited, curvature_limited=curvature_limited)
|
|
|
|
if not active:
|
|
output_torque = 0.0
|
|
pid_log.active = False
|
|
else:
|
|
# do error correction in lateral acceleration space, convert at end to handle non-linear torque responses correctly
|
|
pid_log.error = float(error)
|
|
|
|
freeze_integrator = steer_limited_by_safety or CS.steeringPressed or CS.vEgo < 5
|
|
output_lataccel = self.pid.update(pid_log.error, speed=CS.vEgo, feedforward=ff, freeze_integrator=freeze_integrator)
|
|
output_torque = self.torque_from_lateral_accel(output_lataccel, self.torque_params)
|
|
|
|
output_torque = apply_turn_assist(self, CS, VM, params, desired_curvature, output_torque)
|
|
output_torque = flm.angle_assist(self.flm_surface, CS, VM, params, desired_curvature, setpoint, desired_lateral_jerk, output_torque)
|
|
|
|
if friction_policy is not None:
|
|
output_torque *= friction_policy.output_scale(setpoint, CS.vEgo)
|
|
|
|
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(measurement)
|
|
pid_log.desiredLateralAccel = float(setpoint)
|
|
pid_log.desiredLateralJerk = float(desired_lateral_jerk)
|
|
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
|