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 selfdrive.controls.lib.pid import PIController
from selfdrive.controls.lib.drive_helpers import MPC_COST_LAT
from selfdrive.controls.lib.lateral_mpc import libmpc_py
from common.numpy_fast import interp
from common.realtime import sec_since_boot
from selfdrive.swaglog import cloudlog
from cereal import car
_DT = 0.01 # 100Hz
_DT_MPC = 0.05 # 20Hz
def calc_states_after_delay(states, v_ego, steer_angle, curvature_factor, steer_ratio, delay):
states[0].x = v_ego * delay
states[0].psi = v_ego * curvature_factor * math.radians(steer_angle) / steer_ratio * delay
return states
def get_steer_max(CP, v_ego):
return interp(v_ego, CP.steerMaxBP, CP.steerMaxV)
class LatControl(object):
def __init__(self, CP):
self.pid = PIController((CP.steerKpBP, CP.steerKpV),
(CP.steerKiBP, CP.steerKiV),
k_f=CP.steerKf, pos_limit=1.0)
self.last_cloudlog_t = 0.0
self.setup_mpc(CP.steerRateCost)
def setup_mpc(self, steer_rate_cost):
self.libmpc = libmpc_py.libmpc
self.libmpc.init(MPC_COST_LAT.PATH, MPC_COST_LAT.LANE, MPC_COST_LAT.HEADING, steer_rate_cost)
self.mpc_solution = libmpc_py.ffi.new("log_t *")
self.cur_state = libmpc_py.ffi.new("state_t *")
self.mpc_updated = False
self.mpc_nans = False
self.cur_state[0].x = 0.0
self.cur_state[0].y = 0.0
self.cur_state[0].psi = 0.0
self.cur_state[0].delta = 0.0
self.last_mpc_ts = 0.0
self.angle_steers_des = 0.0
self.angle_steers_des_mpc = 0.0
self.angle_steers_des_prev = 0.0
self.angle_steers_des_time = 0.0
def reset(self):
self.pid.reset()
def update(self, active, v_ego, angle_steers, steer_override, d_poly, angle_offset, CP, VM, PL):
cur_time = sec_since_boot()
self.mpc_updated = False
# TODO: this creates issues in replay when rewinding time: mpc won't run
if self.last_mpc_ts < PL.last_md_ts:
self.last_mpc_ts = PL.last_md_ts
self.angle_steers_des_prev = self.angle_steers_des_mpc
curvature_factor = VM.curvature_factor(v_ego)
l_poly = libmpc_py.ffi.new("double[4]", list(PL.PP.l_poly))
r_poly = libmpc_py.ffi.new("double[4]", list(PL.PP.r_poly))
p_poly = libmpc_py.ffi.new("double[4]", list(PL.PP.p_poly))
# account for actuation delay
self.cur_state = calc_states_after_delay(self.cur_state, v_ego, angle_steers, curvature_factor, CP.steerRatio, CP.steerActuatorDelay)
v_ego_mpc = max(v_ego, 5.0) # avoid mpc roughness due to low speed
self.libmpc.run_mpc(self.cur_state, self.mpc_solution,
l_poly, r_poly, p_poly,
PL.PP.l_prob, PL.PP.r_prob, PL.PP.p_prob, curvature_factor, v_ego_mpc, PL.PP.lane_width)
# reset to current steer angle if not active or overriding
if active:
delta_desired = self.mpc_solution[0].delta[1]
else:
delta_desired = math.radians(angle_steers - angle_offset) / CP.steerRatio
self.cur_state[0].delta = delta_desired
self.angle_steers_des_mpc = float(math.degrees(delta_desired * CP.steerRatio) + angle_offset)
self.angle_steers_des_time = cur_time
self.mpc_updated = True
# Check for infeasable MPC solution
self.mpc_nans = np.any(np.isnan(list(self.mpc_solution[0].delta)))
t = sec_since_boot()
if self.mpc_nans:
self.libmpc.init(MPC_COST_LAT.PATH, MPC_COST_LAT.LANE, MPC_COST_LAT.HEADING, CP.steerRateCost)
self.cur_state[0].delta = math.radians(angle_steers) / CP.steerRatio
if t > self.last_cloudlog_t + 5.0:
self.last_cloudlog_t = t
cloudlog.warning("Lateral mpc - nan: True")
if v_ego < 0.3 or not active:
output_steer = 0.0
self.pid.reset()
else:
# TODO: ideally we should interp, but for tuning reasons we keep the mpc solution
# constant for 0.05s.
#dt = min(cur_time - self.angle_steers_des_time, _DT_MPC + _DT) + _DT # no greater than dt mpc + dt, to prevent too high extraps
#self.angle_steers_des = self.angle_steers_des_prev + (dt / _DT_MPC) * (self.angle_steers_des_mpc - self.angle_steers_des_prev)
self.angle_steers_des = self.angle_steers_des_mpc
steers_max = get_steer_max(CP, v_ego)
self.pid.pos_limit = steers_max
self.pid.neg_limit = -steers_max
steer_feedforward = self.angle_steers_des # feedforward desired angle
if CP.steerControlType == car.CarParams.SteerControlType.torque:
steer_feedforward *= v_ego**2 # proportional to realigning tire momentum (~ lateral accel)
deadzone = 0.0
output_steer = self.pid.update(self.angle_steers_des, angle_steers, check_saturation=(v_ego > 10), override=steer_override,
feedforward=steer_feedforward, speed=v_ego, deadzone=deadzone)
self.sat_flag = self.pid.saturated
return output_steer, float(self.angle_steers_des)