def update(self, sm, pm, CP, VM):
v_ego = sm['carState'].vEgo
angle_steers = sm['carState'].steeringAngle
active = sm['controlsState'].active
angle_offset = sm['liveParameters'].angleOffset
steerRateCost = ntune_get('steerRateCost')
if self.steer_rate_cost_prev != steerRateCost:
self.steer_rate_cost_prev = steerRateCost
self.libmpc.init(MPC_COST_LAT.PATH, MPC_COST_LAT.LANE,
MPC_COST_LAT.HEADING, steerRateCost)
self.cur_state[0].delta = math.radians(angle_steers -
angle_offset) / VM.sR
# Run MPC
self.angle_steers_des_prev = self.angle_steers_des_mpc
# Update vehicle model
x = max(sm['liveParameters'].stiffnessFactor, 0.1)
if ntune_isEnabled('useLiveSteerRatio'):
sr = max(sm['liveParameters'].steerRatio, 0.1)
else:
sr = max(ntune_get('steerRatio'), 0.1)
VM.update_params(x, sr)
curvature_factor = VM.curvature_factor(v_ego)
self.LP.parse_model(sm['model'])
# Lane change logic
one_blinker = sm['carState'].leftBlinker != sm['carState'].rightBlinker
below_lane_change_speed = v_ego < LANE_CHANGE_SPEED_MIN
if sm['carState'].leftBlinker:
self.lane_change_direction = LaneChangeDirection.left
elif sm['carState'].rightBlinker:
self.lane_change_direction = LaneChangeDirection.right
if (not active) or (self.lane_change_timer > LANE_CHANGE_TIME_MAX) or (
not one_blinker) or (not self.lane_change_enabled):
self.lane_change_state = LaneChangeState.off
self.lane_change_direction = LaneChangeDirection.none
else:
torque_applied = sm['carState'].steeringPressed and \
((sm['carState'].steeringTorque > 0 and self.lane_change_direction == LaneChangeDirection.left) or
(sm['carState'].steeringTorque < 0 and self.lane_change_direction == LaneChangeDirection.right)) or \
self.auto_lane_change_enabled and \
(AUTO_LCA_START_TIME+0.25) > self.auto_lane_change_timer > AUTO_LCA_START_TIME
blindspot_detected = (
(sm['carState'].leftBlindspot
and self.lane_change_direction == LaneChangeDirection.left) or
(sm['carState'].rightBlindspot
and self.lane_change_direction == LaneChangeDirection.right))
lane_change_prob = self.LP.l_lane_change_prob + self.LP.r_lane_change_prob
# State transitions
# off
if self.lane_change_state == LaneChangeState.off and one_blinker and not self.prev_one_blinker and not below_lane_change_speed:
self.lane_change_state = LaneChangeState.preLaneChange
self.lane_change_ll_prob = 1.0
# pre
elif self.lane_change_state == LaneChangeState.preLaneChange:
if not one_blinker or below_lane_change_speed:
self.lane_change_state = LaneChangeState.off
elif torque_applied and (not blindspot_detected
or self.prev_torque_applied):
self.lane_change_state = LaneChangeState.laneChangeStarting
elif torque_applied and blindspot_detected and self.auto_lane_change_timer != 10.0:
self.auto_lane_change_timer = 10.0
elif not torque_applied and self.auto_lane_change_timer == 10.0 and not self.prev_torque_applied:
self.prev_torque_applied = True
# starting
elif self.lane_change_state == LaneChangeState.laneChangeStarting:
# fade out over .5s
self.lane_change_ll_prob = max(
self.lane_change_ll_prob - 2 * DT_MDL, 0.0)
# 98% certainty
if lane_change_prob < 0.02 and self.lane_change_ll_prob < 0.01:
self.lane_change_state = LaneChangeState.laneChangeFinishing
# finishing
elif self.lane_change_state == LaneChangeState.laneChangeFinishing:
# fade in laneline over 1s
self.lane_change_ll_prob = min(
self.lane_change_ll_prob + DT_MDL, 1.0)
if one_blinker and self.lane_change_ll_prob > 0.99:
self.lane_change_state = LaneChangeState.preLaneChange
elif self.lane_change_ll_prob > 0.99:
self.lane_change_state = LaneChangeState.off
if self.lane_change_state in [
LaneChangeState.off, LaneChangeState.preLaneChange
]:
self.lane_change_timer = 0.0
else:
self.lane_change_timer += DT_MDL
if self.lane_change_state == LaneChangeState.off:
self.auto_lane_change_timer = 0.0
self.prev_torque_applied = False
elif self.auto_lane_change_timer < (
AUTO_LCA_START_TIME +
0.25): # stop afer 3 sec resume from 10 when torque applied
self.auto_lane_change_timer += DT_MDL
self.prev_one_blinker = one_blinker
desire = DESIRES[self.lane_change_direction][self.lane_change_state]
# Turn off lanes during lane change
if desire == log.PathPlan.Desire.laneChangeRight or desire == log.PathPlan.Desire.laneChangeLeft:
self.LP.l_prob *= self.lane_change_ll_prob
self.LP.r_prob *= self.lane_change_ll_prob
self.LP.update_d_poly(v_ego)
steerActuatorDelay = ntune_get('steerActuatorDelay')
# account for actuation delay
self.cur_state = calc_states_after_delay(self.cur_state, v_ego,
angle_steers - angle_offset,
curvature_factor, VM.sR,
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,
list(self.LP.l_poly), list(self.LP.r_poly),
list(self.LP.d_poly), self.LP.l_prob,
self.LP.r_prob, curvature_factor, v_ego_mpc,
self.LP.lane_width)
# reset to current steer angle if not active or overriding
if active:
delta_desired = self.mpc_solution[0].delta[1]
rate_desired = math.degrees(self.mpc_solution[0].rate[0] * VM.sR)
else:
delta_desired = math.radians(angle_steers - angle_offset) / VM.sR
rate_desired = 0.0
self.cur_state[0].delta = delta_desired
self.angle_steers_des_mpc = float(
math.degrees(delta_desired * VM.sR) + angle_offset)
# Check for infeasable MPC solution
mpc_nans = any(math.isnan(x) for x in self.mpc_solution[0].delta)
t = sec_since_boot()
if mpc_nans:
self.libmpc.init(MPC_COST_LAT.PATH, MPC_COST_LAT.LANE,
MPC_COST_LAT.HEADING, steerRateCost)
self.cur_state[0].delta = math.radians(angle_steers -
angle_offset) / VM.sR
if t > self.last_cloudlog_t + 5.0:
self.last_cloudlog_t = t
cloudlog.warning("Lateral mpc - nan: True")
if self.mpc_solution[
0].cost > 20000. or mpc_nans: # TODO: find a better way to detect when MPC did not converge
self.solution_invalid_cnt += 1
else:
self.solution_invalid_cnt = 0
plan_solution_valid = self.solution_invalid_cnt < 3
plan_send = messaging.new_message('pathPlan')
plan_send.valid = sm.all_alive_and_valid(service_list=[
'carState', 'controlsState', 'liveParameters', 'model'
])
plan_send.pathPlan.laneWidth = float(self.LP.lane_width)
plan_send.pathPlan.dPoly = [float(x) for x in self.LP.d_poly]
plan_send.pathPlan.lPoly = [float(x) for x in self.LP.l_poly]
plan_send.pathPlan.lProb = float(self.LP.l_prob)
plan_send.pathPlan.rPoly = [float(x) for x in self.LP.r_poly]
plan_send.pathPlan.rProb = float(self.LP.r_prob)
plan_send.pathPlan.angleSteers = float(self.angle_steers_des_mpc)
plan_send.pathPlan.rateSteers = float(rate_desired)
plan_send.pathPlan.angleOffset = float(
sm['liveParameters'].angleOffset)
plan_send.pathPlan.mpcSolutionValid = bool(plan_solution_valid)
plan_send.pathPlan.paramsValid = bool(sm['liveParameters'].valid)
plan_send.pathPlan.desire = desire
plan_send.pathPlan.laneChangeState = self.lane_change_state
plan_send.pathPlan.laneChangeDirection = self.lane_change_direction
plan_send.pathPlan.autoLaneChangeEnabled = self.auto_lane_change_enabled
plan_send.pathPlan.autoLaneChangeTimer = int(
AUTO_LCA_START_TIME) - int(self.auto_lane_change_timer)
plan_send.pathPlan.steerRatio = VM.sR
plan_send.pathPlan.steerRateCost = steerRateCost
plan_send.pathPlan.steerActuatorDelay = steerActuatorDelay
pm.send('pathPlan', plan_send)
if LOG_MPC:
dat = messaging.new_message('liveMpc')
dat.liveMpc.x = list(self.mpc_solution[0].x)
dat.liveMpc.y = list(self.mpc_solution[0].y)
dat.liveMpc.psi = list(self.mpc_solution[0].psi)
dat.liveMpc.delta = list(self.mpc_solution[0].delta)
dat.liveMpc.cost = self.mpc_solution[0].cost
pm.send('liveMpc', dat)
def state_control(self, CS):
"""Given the state, this function returns an actuators packet"""
# Neokii's live tune
# Update VehicleModel
params = self.sm['liveParameters']
x = max(params.stiffnessFactor, 0.1)
#sr = max(params.steerRatio, 0.1)
if ntune_isEnabled('useLiveSteerRatio'):
sr = max(self.sm['liveParameters'].steerRatio, 0.1)
else:
if self.CP.carName in [CAR.VOLT]:
sr = interp(abs(self.angle_steers_des), [5., 35.],
[13.5, 17.7])
else:
sr = max(ntune_get('steerRatio'), 0.1)
self.VM.update_params(x, sr)
lat_plan = self.sm['lateralPlan']
long_plan = self.sm['longitudinalPlan']
actuators = car.CarControl.Actuators.new_message()
if CS.leftBlinker or CS.rightBlinker:
self.last_blinker_frame = self.sm.frame
# State specific actions
if not self.active:
self.LaC.reset()
self.LoC.reset(v_pid=CS.vEgo)
long_plan_age = DT_CTRL * (self.sm.frame -
self.sm.rcv_frame['longitudinalPlan'])
# no greater than dt mpc + dt, to prevent too high extraps
dt = min(long_plan_age, LON_MPC_STEP + DT_CTRL) + DT_CTRL
a_acc_sol = long_plan.aStart + (dt / LON_MPC_STEP) * (
long_plan.aTarget - long_plan.aStart)
v_acc_sol = long_plan.vStart + dt * (a_acc_sol +
long_plan.aStart) / 2.0
# Gas/Brake PID loop
actuators.gas, actuators.brake = self.LoC.update(
self.active, CS, v_acc_sol, long_plan.vTargetFuture, a_acc_sol,
self.CP)
# Steering PID loop and lateral MPC
actuators.steer, actuators.steeringAngleDeg, lac_log = self.LaC.update(
self.active, CS, self.CP, self.VM, params, lat_plan)
# Check for difference between desired angle and angle for angle based control
angle_control_saturated = self.CP.steerControlType == car.CarParams.SteerControlType.angle and \
abs(actuators.steeringAngleDeg - CS.steeringAngleDeg) > STEER_ANGLE_SATURATION_THRESHOLD
if angle_control_saturated and not CS.steeringPressed and self.active:
self.saturated_count += 1
else:
self.saturated_count = 0
# Send a "steering required alert" if saturation count has reached the limit
if (lac_log.saturated and not CS.steeringPressed) or \
(self.saturated_count > STEER_ANGLE_SATURATION_TIMEOUT):
if len(lat_plan.dPathPoints):
# Check if we deviated from the path
left_deviation = actuators.steer > 0 and lat_plan.dPathPoints[
0] < -0.1
right_deviation = actuators.steer < 0 and lat_plan.dPathPoints[
0] > 0.1
# Bellow 2Lines' notations are for disable Alerts
# if left_deviation or right_deviation:
# self.events.add(EventName.steerSaturated)
return actuators, v_acc_sol, a_acc_sol, lac_log
