You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
122 lines
5.1 KiB
122 lines
5.1 KiB
import numpy as np
|
|
from common.realtime import sec_since_boot, DT_MDL
|
|
from common.numpy_fast import interp
|
|
from system.swaglog import cloudlog
|
|
from selfdrive.controls.lib.lateral_mpc_lib.lat_mpc import LateralMpc
|
|
from selfdrive.controls.lib.lateral_mpc_lib.lat_mpc import N as LAT_MPC_N
|
|
from selfdrive.controls.lib.drive_helpers import CONTROL_N
|
|
from selfdrive.controls.lib.desire_helper import DesireHelper
|
|
import cereal.messaging as messaging
|
|
from cereal import log
|
|
|
|
TRAJECTORY_SIZE = 33
|
|
CAMERA_OFFSET = 0.04
|
|
|
|
class LateralPlanner:
|
|
def __init__(self, CP):
|
|
self.DH = DesireHelper()
|
|
|
|
# Vehicle model parameters used to calculate lateral movement of car
|
|
self.factor1 = CP.wheelbase - CP.centerToFront
|
|
self.factor2 = (CP.centerToFront * CP.mass) / (CP.wheelbase * CP.tireStiffnessRear)
|
|
self.last_cloudlog_t = 0
|
|
self.solution_invalid_cnt = 0
|
|
|
|
self.path_xyz = np.zeros((TRAJECTORY_SIZE, 3))
|
|
self.plan_yaw = np.zeros((TRAJECTORY_SIZE,))
|
|
self.plan_yaw_rate = np.zeros((TRAJECTORY_SIZE,))
|
|
self.t_idxs = np.arange(TRAJECTORY_SIZE)
|
|
self.y_pts = np.zeros(TRAJECTORY_SIZE)
|
|
|
|
self.lat_mpc = LateralMpc()
|
|
self.reset_mpc(np.zeros(4))
|
|
|
|
def reset_mpc(self, x0=np.zeros(4)):
|
|
self.x0 = x0
|
|
self.lat_mpc.reset(x0=self.x0)
|
|
|
|
def update(self, sm):
|
|
v_ego = sm['carState'].vEgo
|
|
measured_curvature = sm['controlsState'].curvature
|
|
|
|
# Parse model predictions
|
|
md = sm['modelV2']
|
|
if len(md.position.x) == TRAJECTORY_SIZE and len(md.orientation.x) == TRAJECTORY_SIZE:
|
|
self.path_xyz = np.column_stack([md.position.x, md.position.y, md.position.z])
|
|
self.t_idxs = np.array(md.position.t)
|
|
self.plan_yaw = np.array(md.orientation.z)
|
|
self.plan_yaw_rate = np.array(md.orientationRate.z)
|
|
|
|
# Lane change logic
|
|
desire_state = md.meta.desireState
|
|
if len(desire_state):
|
|
self.l_lane_change_prob = desire_state[log.LateralPlan.Desire.laneChangeLeft]
|
|
self.r_lane_change_prob = desire_state[log.LateralPlan.Desire.laneChangeRight]
|
|
lane_change_prob = self.l_lane_change_prob + self.r_lane_change_prob
|
|
self.DH.update(sm['carState'], sm['carControl'].latActive, lane_change_prob)
|
|
|
|
d_path_xyz = self.path_xyz
|
|
# Heading cost is useful at low speed, otherwise end of plan can be off-heading
|
|
heading_cost = interp(v_ego, [5.0, 10.0], [1.0, 0.15])
|
|
self.lat_mpc.set_weights(1.0, heading_cost, 0.0, .075)
|
|
|
|
y_pts = np.interp(v_ego * self.t_idxs[:LAT_MPC_N + 1], np.linalg.norm(d_path_xyz, axis=1), d_path_xyz[:, 1])
|
|
heading_pts = np.interp(v_ego * self.t_idxs[:LAT_MPC_N + 1], np.linalg.norm(self.path_xyz, axis=1), self.plan_yaw)
|
|
yaw_rate_pts = np.interp(v_ego * self.t_idxs[:LAT_MPC_N + 1], np.linalg.norm(self.path_xyz, axis=1), self.plan_yaw_rate)
|
|
self.y_pts = y_pts
|
|
|
|
assert len(y_pts) == LAT_MPC_N + 1
|
|
assert len(heading_pts) == LAT_MPC_N + 1
|
|
assert len(yaw_rate_pts) == LAT_MPC_N + 1
|
|
lateral_factor = max(0, self.factor1 - (self.factor2 * v_ego**2))
|
|
p = np.array([v_ego, lateral_factor])
|
|
self.lat_mpc.run(self.x0,
|
|
p,
|
|
y_pts,
|
|
heading_pts,
|
|
yaw_rate_pts)
|
|
# init state for next iteration
|
|
# mpc.u_sol is the desired second derivative of psi given x0 curv state.
|
|
# with x0[3] = measured_yaw_rate, this would be the actual desired yaw rate.
|
|
# instead, interpolate x_sol so that x0[3] is the desired yaw rate for lat_control.
|
|
self.x0[3] = interp(DT_MDL, self.t_idxs[:LAT_MPC_N + 1], self.lat_mpc.x_sol[:, 3])
|
|
|
|
# Check for infeasible MPC solution
|
|
mpc_nans = np.isnan(self.lat_mpc.x_sol[:, 3]).any()
|
|
t = sec_since_boot()
|
|
if mpc_nans or self.lat_mpc.solution_status != 0:
|
|
self.reset_mpc()
|
|
self.x0[3] = measured_curvature
|
|
if t > self.last_cloudlog_t + 5.0:
|
|
self.last_cloudlog_t = t
|
|
cloudlog.warning("Lateral mpc - nan: True")
|
|
|
|
if self.lat_mpc.cost > 20000. or mpc_nans:
|
|
self.solution_invalid_cnt += 1
|
|
else:
|
|
self.solution_invalid_cnt = 0
|
|
|
|
def publish(self, sm, pm):
|
|
plan_solution_valid = self.solution_invalid_cnt < 2
|
|
plan_send = messaging.new_message('lateralPlan')
|
|
plan_send.valid = sm.all_checks(service_list=['carState', 'controlsState', 'modelV2'])
|
|
|
|
lateralPlan = plan_send.lateralPlan
|
|
lateralPlan.modelMonoTime = sm.logMonoTime['modelV2']
|
|
lateralPlan.dPathPoints = self.y_pts.tolist()
|
|
lateralPlan.psis = self.lat_mpc.x_sol[0:CONTROL_N, 2].tolist()
|
|
|
|
# clip speed for curv calculation at 1m/s, to prevent low speed extremes
|
|
clipped_speed = max(1.0, sm['carState'].vEgo)
|
|
lateralPlan.curvatures = (self.lat_mpc.x_sol[0:CONTROL_N, 3]/clipped_speed).tolist()
|
|
lateralPlan.curvatureRates = [float(x/clipped_speed) for x in self.lat_mpc.u_sol[0:CONTROL_N - 1]] + [0.0]
|
|
|
|
lateralPlan.mpcSolutionValid = bool(plan_solution_valid)
|
|
lateralPlan.solverExecutionTime = self.lat_mpc.solve_time
|
|
|
|
lateralPlan.desire = self.DH.desire
|
|
lateralPlan.useLaneLines = False
|
|
lateralPlan.laneChangeState = self.DH.lane_change_state
|
|
lateralPlan.laneChangeDirection = self.DH.lane_change_direction
|
|
|
|
pm.send('lateralPlan', plan_send)
|
|
|