def parse_model(self, md):
lane_lines = md.laneLines
if len(lane_lines) == 4 and len(lane_lines[0].t) == TRAJECTORY_SIZE:
self.ll_t = (np.array(lane_lines[1].t) +
np.array(lane_lines[2].t)) / 2
# left and right ll x is the same
self.ll_x = lane_lines[1].x
# only offset left and right lane lines; offsetting path does not make sense
cameraOffset = ntune_common_get(
"cameraOffset"
) + 0.08 if self.wide_camera else ntune_common_get("cameraOffset")
self.lll_y = np.array(lane_lines[1].y) - cameraOffset
self.rll_y = np.array(lane_lines[2].y) - cameraOffset
self.lll_prob = md.laneLineProbs[1]
self.rll_prob = md.laneLineProbs[2]
self.lll_std = md.laneLineStds[1]
self.rll_std = md.laneLineStds[2]
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]
def get_lag_adjusted_curvature(CP, v_ego, psis, curvatures, curvature_rates):
if len(psis) != CONTROL_N:
psis = [0.0] * CONTROL_N
curvatures = [0.0] * CONTROL_N
curvature_rates = [0.0] * CONTROL_N
v_ego = max(v_ego, 0.1)
# TODO this needs more thought, use .2s extra for now to estimate other delays
delay = ntune_common_get('steerActuatorDelay') + .2
# MPC can plan to turn the wheel and turn back before t_delay. This means
# in high delay cases some corrections never even get commanded. So just use
# psi to calculate a simple linearization of desired curvature
current_curvature_desired = curvatures[0]
psi = interp(delay, T_IDXS[:CONTROL_N], psis)
average_curvature_desired = psi / (v_ego * delay)
desired_curvature = 2 * average_curvature_desired - current_curvature_desired
# This is the "desired rate of the setpoint" not an actual desired rate
desired_curvature_rate = curvature_rates[0]
max_curvature_rate = MAX_LATERAL_JERK / (v_ego**2)
safe_desired_curvature_rate = clip(desired_curvature_rate,
-max_curvature_rate, max_curvature_rate)
safe_desired_curvature = clip(
desired_curvature,
current_curvature_desired - max_curvature_rate * DT_MDL,
current_curvature_desired + max_curvature_rate * DT_MDL)
return safe_desired_curvature, safe_desired_curvature_rate
def get_lag_adjusted_curvature(CP, v_ego, psis, curvatures, curvature_rates):
if len(psis) != CONTROL_N:
psis = [0.0 for i in range(CONTROL_N)]
curvatures = [0.0 for i in range(CONTROL_N)]
curvature_rates = [0.0 for i in range(CONTROL_N)]
# TODO this needs more thought, use .2s extra for now to estimate other delays
delay = ntune_common_get('steerActuatorDelay') + .2
current_curvature = curvatures[0]
psi = interp(delay, T_IDXS[:CONTROL_N], psis)
desired_curvature_rate = curvature_rates[0]
# MPC can plan to turn the wheel and turn back before t_delay. This means
# in high delay cases some corrections never even get commanded. So just use
# psi to calculate a simple linearization of desired curvature
curvature_diff_from_psi = psi / (max(v_ego, 1e-1) *
delay) - current_curvature
desired_curvature = current_curvature + 2 * curvature_diff_from_psi
max_curvature_rate = interp(v_ego, MAX_CURVATURE_RATE_SPEEDS,
MAX_CURVATURE_RATES)
safe_desired_curvature_rate = clip(desired_curvature_rate,
-max_curvature_rate, max_curvature_rate)
safe_desired_curvature = clip(
desired_curvature, current_curvature - max_curvature_rate * DT_MDL,
current_curvature + max_curvature_rate * DT_MDL)
return safe_desired_curvature, safe_desired_curvature_rate
def publish_logs(self, CS, start_time, actuators, lac_log):
"""Send actuators and hud commands to the car, send controlsstate and MPC logging"""
CC = car.CarControl.new_message()
CC.enabled = self.enabled
CC.active = self.active
CC.actuators = actuators
orientation_value = self.sm['liveLocationKalman'].orientationNED.value
if len(orientation_value) > 2:
CC.roll = orientation_value[0]
CC.pitch = orientation_value[1]
CC.cruiseControl.cancel = self.CP.pcmCruise and not self.enabled and CS.cruiseState.enabled
if self.joystick_mode and self.sm.rcv_frame[
'testJoystick'] > 0 and self.sm['testJoystick'].buttons[0]:
CC.cruiseControl.cancel = True
hudControl = CC.hudControl
hudControl.setSpeed = float(self.v_cruise_kph * CV.KPH_TO_MS)
hudControl.speedVisible = self.enabled
hudControl.lanesVisible = self.enabled
hudControl.leadVisible = self.sm['longitudinalPlan'].hasLead
right_lane_visible = self.sm['lateralPlan'].rProb > 0.5
left_lane_visible = self.sm['lateralPlan'].lProb > 0.5
if self.sm.frame % 100 == 0:
self.right_lane_visible = right_lane_visible
self.left_lane_visible = left_lane_visible
CC.hudControl.rightLaneVisible = self.right_lane_visible
CC.hudControl.leftLaneVisible = self.left_lane_visible
recent_blinker = (self.sm.frame - self.last_blinker_frame
) * DT_CTRL < 5.0 # 5s blinker cooldown
ldw_allowed = self.is_ldw_enabled and CS.vEgo > LDW_MIN_SPEED and not recent_blinker \
and not self.active and self.sm['liveCalibration'].calStatus == Calibration.CALIBRATED
model_v2 = self.sm['modelV2']
desire_prediction = model_v2.meta.desirePrediction
if len(desire_prediction) and ldw_allowed:
right_lane_visible = self.sm['lateralPlan'].rProb > 0.5
left_lane_visible = self.sm['lateralPlan'].lProb > 0.5
l_lane_change_prob = desire_prediction[Desire.laneChangeLeft - 1]
r_lane_change_prob = desire_prediction[Desire.laneChangeRight - 1]
lane_lines = model_v2.laneLines
cameraOffset = ntune_common_get(
"cameraOffset"
) + 0.08 if self.wide_camera else ntune_common_get("cameraOffset")
l_lane_close = left_lane_visible and (lane_lines[1].y[0] >
-(1.08 + cameraOffset))
r_lane_close = right_lane_visible and (lane_lines[2].y[0] <
(1.08 - cameraOffset))
hudControl.leftLaneDepart = bool(
l_lane_change_prob > LANE_DEPARTURE_THRESHOLD and l_lane_close)
hudControl.rightLaneDepart = bool(
r_lane_change_prob > LANE_DEPARTURE_THRESHOLD and r_lane_close)
if hudControl.rightLaneDepart or hudControl.leftLaneDepart:
self.events.add(EventName.ldw)
clear_event_types = set()
if ET.WARNING not in self.current_alert_types:
clear_event_types.add(ET.WARNING)
if self.enabled:
clear_event_types.add(ET.NO_ENTRY)
alerts = self.events.create_alerts(
self.current_alert_types,
[self.CP, self.sm, self.is_metric, self.soft_disable_timer])
self.AM.add_many(self.sm.frame, alerts)
current_alert = self.AM.process_alerts(self.sm.frame,
clear_event_types)
if current_alert:
hudControl.visualAlert = current_alert.visual_alert
if not self.read_only and self.initialized:
# send car controls over can
self.last_actuators, can_sends = self.CI.apply(CC, self)
self.pm.send(
'sendcan',
can_list_to_can_capnp(can_sends,
msgtype='sendcan',
valid=CS.canValid))
CC.actuatorsOutput = self.last_actuators
force_decel = (self.sm['driverMonitoringState'].awarenessStatus < 0.) or \
(self.state == State.softDisabling)
# Curvature & Steering angle
params = self.sm['liveParameters']
steer_angle_without_offset = math.radians(CS.steeringAngleDeg -
params.angleOffsetDeg)
curvature = -self.VM.calc_curvature(steer_angle_without_offset,
CS.vEgo, params.roll)
# controlsState
dat = messaging.new_message('controlsState')
dat.valid = CS.canValid
controlsState = dat.controlsState
if current_alert:
controlsState.alertText1 = current_alert.alert_text_1
controlsState.alertText2 = current_alert.alert_text_2
controlsState.alertSize = current_alert.alert_size
controlsState.alertStatus = current_alert.alert_status
controlsState.alertBlinkingRate = current_alert.alert_rate
controlsState.alertType = current_alert.alert_type
controlsState.alertSound = current_alert.audible_alert
controlsState.canMonoTimes = list(CS.canMonoTimes)
controlsState.longitudinalPlanMonoTime = self.sm.logMonoTime[
'longitudinalPlan']
controlsState.lateralPlanMonoTime = self.sm.logMonoTime['lateralPlan']
controlsState.enabled = self.enabled
controlsState.active = self.active
controlsState.curvature = curvature
controlsState.state = self.state
controlsState.engageable = not self.events.any(ET.NO_ENTRY)
controlsState.longControlState = self.LoC.long_control_state
controlsState.vPid = float(self.LoC.v_pid)
controlsState.vCruise = float(
self.applyMaxSpeed if self.CP.
openpilotLongitudinalControl else self.v_cruise_kph)
controlsState.upAccelCmd = float(self.LoC.pid.p)
controlsState.uiAccelCmd = float(self.LoC.pid.i)
controlsState.ufAccelCmd = float(self.LoC.pid.f)
controlsState.cumLagMs = -self.rk.remaining * 1000.
controlsState.startMonoTime = int(start_time * 1e9)
controlsState.forceDecel = bool(force_decel)
controlsState.canErrorCounter = self.can_rcv_error_counter
controlsState.angleSteers = steer_angle_without_offset * CV.RAD_TO_DEG
controlsState.applyAccel = self.apply_accel
controlsState.aReqValue = self.aReqValue
controlsState.aReqValueMin = self.aReqValueMin
controlsState.aReqValueMax = self.aReqValueMax
controlsState.sccStockCamAct = self.sccStockCamAct
controlsState.sccStockCamStatus = self.sccStockCamStatus
controlsState.steerRatio = self.VM.sR
controlsState.steerRateCost = ntune_common_get('steerRateCost')
controlsState.steerActuatorDelay = ntune_common_get(
'steerActuatorDelay')
controlsState.sccGasFactor = ntune_scc_get('sccGasFactor')
controlsState.sccBrakeFactor = ntune_scc_get('sccBrakeFactor')
controlsState.sccCurvatureFactor = ntune_scc_get('sccCurvatureFactor')
lat_tuning = self.CP.lateralTuning.which()
if self.joystick_mode:
controlsState.lateralControlState.debugState = lac_log
elif self.CP.steerControlType == car.CarParams.SteerControlType.angle:
controlsState.lateralControlState.angleState = lac_log
elif lat_tuning == 'pid':
controlsState.lateralControlState.pidState = lac_log
elif lat_tuning == 'lqr':
controlsState.lateralControlState.lqrState = lac_log
elif lat_tuning == 'indi':
controlsState.lateralControlState.indiState = lac_log
self.pm.send('controlsState', dat)
# carState
car_events = self.events.to_msg()
cs_send = messaging.new_message('carState')
cs_send.valid = CS.canValid
cs_send.carState = CS
cs_send.carState.events = car_events
self.pm.send('carState', cs_send)
# carEvents - logged every second or on change
if (self.sm.frame % int(1. / DT_CTRL)
== 0) or (self.events.names != self.events_prev):
ce_send = messaging.new_message('carEvents', len(self.events))
ce_send.carEvents = car_events
self.pm.send('carEvents', ce_send)
self.events_prev = self.events.names.copy()
# carParams - logged every 50 seconds (> 1 per segment)
if (self.sm.frame % int(50. / DT_CTRL) == 0):
cp_send = messaging.new_message('carParams')
cp_send.carParams = self.CP
self.pm.send('carParams', cp_send)
# carControl
cc_send = messaging.new_message('carControl')
cc_send.valid = CS.canValid
cc_send.carControl = CC
self.pm.send('carControl', cc_send)
# copy CarControl to pass to CarInterface on the next iteration
self.CC = CC
def state_control(self, CS):
"""Given the state, this function returns an actuators packet"""
# Update VehicleModel
params = self.sm['liveParameters']
x = max(params.stiffnessFactor, 0.1)
#sr = max(params.steerRatio, 0.1)
if ntune_common_enabled('useLiveSteerRatio'):
sr = max(params.steerRatio, 0.1)
else:
sr = max(ntune_common_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()
actuators.longControlState = self.LoC.long_control_state
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)
if not CS.cruiseState.enabledAcc:
self.LoC.reset(v_pid=CS.vEgo)
if not self.joystick_mode:
# accel PID loop
pid_accel_limits = self.CI.get_pid_accel_limits(
self.CP, CS.vEgo, self.v_cruise_kph * CV.KPH_TO_MS)
t_since_plan = (self.sm.frame -
self.sm.rcv_frame['longitudinalPlan']) * DT_CTRL
actuators.accel = self.LoC.update(
self.active and CS.cruiseState.enabledAcc, CS, self.CP,
long_plan, pid_accel_limits, t_since_plan,
self.sm['radarState'])
# Steering PID loop and lateral MPC
lat_active = self.active and not CS.steerWarning and not CS.steerError and CS.vEgo > self.CP.minSteerSpeed
t_since_plan = (self.sm.frame -
self.sm.rcv_frame['lateralPlan']) * DT_CTRL
desired_curvature, desired_curvature_rate = get_lag_adjusted_curvature(
self.CP, CS.vEgo, lat_plan.psis, lat_plan.curvatures,
lat_plan.curvatureRates, t_since_plan)
actuators.steer, actuators.steeringAngleDeg, lac_log = self.LaC.update(
lat_active, CS, self.CP, self.VM, params, self.last_actuators,
desired_curvature, desired_curvature_rate)
else:
lac_log = log.ControlsState.LateralDebugState.new_message()
if self.sm.rcv_frame['testJoystick'] > 0 and self.active:
actuators.accel = 4.0 * clip(self.sm['testJoystick'].axes[0],
-1, 1)
steer = clip(self.sm['testJoystick'].axes[1], -1, 1)
# max angle is 45 for angle-based cars
actuators.steer, actuators.steeringAngleDeg = steer, steer * 45.
lac_log.active = True
lac_log.steeringAngleDeg = CS.steeringAngleDeg
lac_log.output = steer
lac_log.saturated = abs(steer) >= 0.9
# Send a "steering required alert" if saturation count has reached the limit
if lac_log.active and lac_log.saturated and not CS.steeringPressed:
dpath_points = lat_plan.dPathPoints
if len(dpath_points):
# Check if we deviated from the path
# TODO use desired vs actual curvature
left_deviation = actuators.steer > 0 and dpath_points[0] < -0.20
right_deviation = actuators.steer < 0 and dpath_points[0] > 0.20
if left_deviation or right_deviation:
self.events.add(EventName.steerSaturated)
# Ensure no NaNs/Infs
for p in ACTUATOR_FIELDS:
attr = getattr(actuators, p)
if not isinstance(attr, Number):
continue
if not math.isfinite(attr):
cloudlog.error(
f"actuators.{p} not finite {actuators.to_dict()}")
setattr(actuators, p, 0.0)
return actuators, lac_log
def update(self, sm):
v_ego = sm['carState'].vEgo
active = sm['controlsState'].active
measured_curvature = sm['controlsState'].curvature
md = sm['modelV2']
self.LP.parse_model(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 = list(md.orientation.z)
if len(md.position.xStd) == TRAJECTORY_SIZE:
self.path_xyz_stds = np.column_stack([md.position.xStd, md.position.yStd, md.position.zStd])
# Lane change logic
one_blinker = sm['carState'].leftBlinker != sm['carState'].rightBlinker
below_lane_change_speed = v_ego < LANE_CHANGE_SPEED_MIN
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:
if sm['carState'].leftBlinker:
self.lane_change_direction = LaneChangeDirection.left
elif sm['carState'].rightBlinker:
self.lane_change_direction = LaneChangeDirection.right
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
# LaneChangeState.laneChangeStarting
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
# LaneChangeState.laneChangeFinishing
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 self.lane_change_ll_prob > 0.99:
self.lane_change_direction = LaneChangeDirection.none
if one_blinker:
self.lane_change_state = LaneChangeState.preLaneChange
else:
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
self.desire = DESIRES[self.lane_change_direction][self.lane_change_state]
# Send keep pulse once per second during LaneChangeStart.preLaneChange
if self.lane_change_state in (LaneChangeState.off, LaneChangeState.laneChangeStarting):
self.keep_pulse_timer = 0.0
elif self.lane_change_state == LaneChangeState.preLaneChange:
self.keep_pulse_timer += DT_MDL
if self.keep_pulse_timer > 1.0:
self.keep_pulse_timer = 0.0
elif self.desire in (log.LateralPlan.Desire.keepLeft, log.LateralPlan.Desire.keepRight):
self.desire = log.LateralPlan.Desire.none
# Turn off lanes during lane change
if self.desire == log.LateralPlan.Desire.laneChangeRight or self.desire == log.LateralPlan.Desire.laneChangeLeft:
self.LP.lll_prob *= self.lane_change_ll_prob
self.LP.rll_prob *= self.lane_change_ll_prob
if self.use_lanelines:
d_path_xyz = self.LP.get_d_path(v_ego, self.t_idxs, self.path_xyz)
self.lat_mpc.set_weights(MPC_COST_LAT.PATH, MPC_COST_LAT.HEADING, ntune_common_get('steerRateCost'))
else:
d_path_xyz = self.path_xyz
path_cost = np.clip(abs(self.path_xyz[0, 1] / self.path_xyz_stds[0, 1]), 0.5, 1.5) * MPC_COST_LAT.PATH
# Heading cost is useful at low speed, otherwise end of plan can be off-heading
heading_cost = interp(v_ego, [5.0, 10.0], [MPC_COST_LAT.HEADING, 0.0])
self.lat_mpc.set_weights(path_cost, heading_cost, ntune_common_get('steerRateCost'))
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)
self.y_pts = y_pts
assert len(y_pts) == LAT_MPC_N + 1
assert len(heading_pts) == LAT_MPC_N + 1
# self.x0[4] = v_ego
p = np.array([v_ego, CAR_ROTATION_RADIUS])
self.lat_mpc.run(self.x0,
p,
y_pts,
heading_pts)
# init state for next
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 update(self, sm):
v_ego = sm['carState'].vEgo
measured_curvature = sm['controlsState'].curvature
# Parse model predictions
md = sm['modelV2']
self.LP.parse_model(md)
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 = list(md.orientation.z)
if len(md.position.xStd) == TRAJECTORY_SIZE:
self.path_xyz_stds = np.column_stack([md.position.xStd, md.position.yStd, md.position.zStd])
# Lane change logic
lane_change_prob = self.LP.l_lane_change_prob + self.LP.r_lane_change_prob
self.DH.update(sm['carState'], sm['controlsState'].active, lane_change_prob)
# Turn off lanes during lane change
if self.DH.desire == log.LateralPlan.Desire.laneChangeRight or self.DH.desire == log.LateralPlan.Desire.laneChangeLeft:
self.LP.lll_prob *= self.DH.lane_change_ll_prob
self.LP.rll_prob *= self.DH.lane_change_ll_prob
# Calculate final driving path and set MPC costs
if self.use_lanelines:
d_path_xyz = self.LP.get_d_path(v_ego, self.t_idxs, self.path_xyz)
else:
d_path_xyz = self.path_xyz
d_path_xyz[:, 1] += ntune_common_get('pathOffset')
self.lat_mpc.set_weights(MPC_COST_LAT.PATH, MPC_COST_LAT.HEADING, ntune_common_get('steerRateCost'))
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)
self.y_pts = y_pts
assert len(y_pts) == LAT_MPC_N + 1
assert len(heading_pts) == LAT_MPC_N + 1
# self.x0[4] = v_ego
p = np.array([v_ego, CAR_ROTATION_RADIUS])
self.lat_mpc.run(self.x0,
p,
y_pts,
heading_pts)
# init state for next
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