#!/usr/bin/env python import zmq import math import numpy as np from collections import defaultdict from common.params import Params from common.realtime import sec_since_boot from common.numpy_fast import interp import selfdrive.messaging as messaging from selfdrive.swaglog import cloudlog from selfdrive.config import Conversions as CV from selfdrive.services import service_list from selfdrive.controls.lib.drive_helpers import create_event, MPC_COST_LONG, EventTypes as ET from selfdrive.controls.lib.longitudinal_mpc import libmpc_py from selfdrive.controls.lib.speed_smoother import speed_smoother from selfdrive.controls.lib.longcontrol import LongCtrlState, MIN_CAN_SPEED from selfdrive.controls.lib.radar_helpers import _LEAD_ACCEL_TAU NO_CURVATURE_SPEED = 200. * CV.MPH_TO_MS _DT_MPC = 0.2 # 5Hz MAX_SPEED_ERROR = 2.0 AWARENESS_DECEL = -0.2 # car smoothly decel at .2m/s^2 when user is distracted # lookup tables VS speed to determine min and max accels in cruise # make sure these accelerations are smaller than mpc limits _A_CRUISE_MIN_V = [-1.0, -.8, -.67, -.5, -.30] _A_CRUISE_MIN_BP = [ 0., 5., 10., 20., 40.] # need fast accel at very low speed for stop and go # make sure these accelerations are smaller than mpc limits _A_CRUISE_MAX_V = [1.1, 1.1, .8, .5, .3] _A_CRUISE_MAX_V_FOLLOWING = [1.6, 1.6, 1.2, .7, .3] _A_CRUISE_MAX_BP = [0., 5., 10., 20., 40.] # Lookup table for turns _A_TOTAL_MAX_V = [1.5, 1.9, 3.2] _A_TOTAL_MAX_BP = [0., 20., 40.] _FCW_A_ACT_V = [-3., -2.] _FCW_A_ACT_BP = [0., 30.] def calc_cruise_accel_limits(v_ego, following): a_cruise_min = interp(v_ego, _A_CRUISE_MIN_BP, _A_CRUISE_MIN_V) if following: a_cruise_max = interp(v_ego, _A_CRUISE_MAX_BP, _A_CRUISE_MAX_V_FOLLOWING) else: a_cruise_max = interp(v_ego, _A_CRUISE_MAX_BP, _A_CRUISE_MAX_V) return np.vstack([a_cruise_min, a_cruise_max]) def limit_accel_in_turns(v_ego, angle_steers, a_target, CP): """ This function returns a limited long acceleration allowed, depending on the existing lateral acceleration this should avoid accelerating when losing the target in turns """ a_total_max = interp(v_ego, _A_TOTAL_MAX_BP, _A_TOTAL_MAX_V) a_y = v_ego**2 * angle_steers * CV.DEG_TO_RAD / (CP.steerRatio * CP.wheelbase) a_x_allowed = math.sqrt(max(a_total_max**2 - a_y**2, 0.)) a_target[1] = min(a_target[1], a_x_allowed) return a_target class FCWChecker(object): def __init__(self): self.reset_lead(0.0) def reset_lead(self, cur_time): self.last_fcw_a = 0.0 self.v_lead_max = 0.0 self.lead_seen_t = cur_time self.last_fcw_time = 0.0 self.last_min_a = 0.0 self.counters = defaultdict(lambda: 0) @staticmethod def calc_ttc(v_ego, a_ego, x_lead, v_lead, a_lead): max_ttc = 5.0 v_rel = v_ego - v_lead a_rel = a_ego - a_lead # assuming that closing gap ARel comes from lead vehicle decel, # then limit ARel so that v_lead will get to zero in no sooner than t_decel. # This helps underweighting ARel when v_lead is close to zero. t_decel = 2. a_rel = np.minimum(a_rel, v_lead / t_decel) # delta of the quadratic equation to solve for ttc delta = v_rel**2 + 2 * x_lead * a_rel # assign an arbitrary high ttc value if there is no solution to ttc if delta < 0.1 or (np.sqrt(delta) + v_rel < 0.1): ttc = max_ttc else: ttc = np.minimum(2 * x_lead / (np.sqrt(delta) + v_rel), max_ttc) return ttc def update(self, mpc_solution, cur_time, v_ego, a_ego, x_lead, v_lead, a_lead, y_lead, vlat_lead, fcw_lead, blinkers): mpc_solution_a = list(mpc_solution[0].a_ego) self.last_min_a = min(mpc_solution_a) self.v_lead_max = max(self.v_lead_max, v_lead) if (fcw_lead > 0.99): ttc = self.calc_ttc(v_ego, a_ego, x_lead, v_lead, a_lead) self.counters['v_ego'] = self.counters['v_ego'] + 1 if v_ego > 5.0 else 0 self.counters['ttc'] = self.counters['ttc'] + 1 if ttc < 2.5 else 0 self.counters['v_lead_max'] = self.counters['v_lead_max'] + 1 if self.v_lead_max > 2.5 else 0 self.counters['v_ego_lead'] = self.counters['v_ego_lead'] + 1 if v_ego > v_lead else 0 self.counters['lead_seen'] = self.counters['lead_seen'] + 0.33 self.counters['y_lead'] = self.counters['y_lead'] + 1 if abs(y_lead) < 1.0 else 0 self.counters['vlat_lead'] = self.counters['vlat_lead'] + 1 if abs(vlat_lead) < 0.4 else 0 self.counters['blinkers'] = self.counters['blinkers'] + 10.0 / (20 * 3.0) if not blinkers else 0 a_thr = interp(v_lead, _FCW_A_ACT_BP, _FCW_A_ACT_V) a_delta = min(mpc_solution_a[:15]) - min(0.0, a_ego) fcw_allowed = all(c >= 10 for c in self.counters.values()) if (self.last_min_a < -3.0 or a_delta < a_thr) and fcw_allowed and self.last_fcw_time + 5.0 < cur_time: self.last_fcw_time = cur_time self.last_fcw_a = self.last_min_a return True return False class LongitudinalMpc(object): def __init__(self, mpc_id, live_longitudinal_mpc): self.live_longitudinal_mpc = live_longitudinal_mpc self.mpc_id = mpc_id self.setup_mpc() self.v_mpc = 0.0 self.v_mpc_future = 0.0 self.a_mpc = 0.0 self.v_cruise = 0.0 self.prev_lead_status = False self.prev_lead_x = 0.0 self.new_lead = False self.last_cloudlog_t = 0.0 def send_mpc_solution(self, qp_iterations, calculation_time): qp_iterations = max(0, qp_iterations) dat = messaging.new_message() dat.init('liveLongitudinalMpc') dat.liveLongitudinalMpc.xEgo = list(self.mpc_solution[0].x_ego) dat.liveLongitudinalMpc.vEgo = list(self.mpc_solution[0].v_ego) dat.liveLongitudinalMpc.aEgo = list(self.mpc_solution[0].a_ego) dat.liveLongitudinalMpc.xLead = list(self.mpc_solution[0].x_l) dat.liveLongitudinalMpc.vLead = list(self.mpc_solution[0].v_l) dat.liveLongitudinalMpc.cost = self.mpc_solution[0].cost dat.liveLongitudinalMpc.aLeadTau = self.a_lead_tau dat.liveLongitudinalMpc.qpIterations = qp_iterations dat.liveLongitudinalMpc.mpcId = self.mpc_id dat.liveLongitudinalMpc.calculationTime = calculation_time self.live_longitudinal_mpc.send(dat.to_bytes()) def setup_mpc(self): ffi, self.libmpc = libmpc_py.get_libmpc(self.mpc_id) self.libmpc.init(MPC_COST_LONG.TTC, MPC_COST_LONG.DISTANCE, MPC_COST_LONG.ACCELERATION, MPC_COST_LONG.JERK) self.mpc_solution = ffi.new("log_t *") self.cur_state = ffi.new("state_t *") self.cur_state[0].v_ego = 0 self.cur_state[0].a_ego = 0 self.a_lead_tau = _LEAD_ACCEL_TAU def set_cur_state(self, v, a): self.cur_state[0].v_ego = v self.cur_state[0].a_ego = a def update(self, CS, lead, v_cruise_setpoint): v_ego = CS.carState.vEgo # Setup current mpc state self.cur_state[0].x_ego = 0.0 if lead is not None and lead.status: x_lead = lead.dRel v_lead = max(0.0, lead.vLead) a_lead = lead.aLeadK if (v_lead < 0.1 or -a_lead / 2.0 > v_lead): v_lead = 0.0 a_lead = 0.0 self.a_lead_tau = max(lead.aLeadTau, (a_lead**2 * math.pi) / (2 * (v_lead + 0.01)**2)) self.new_lead = False if not self.prev_lead_status or abs(x_lead - self.prev_lead_x) > 2.5: self.libmpc.init_with_simulation(self.v_mpc, x_lead, v_lead, a_lead, self.a_lead_tau) self.new_lead = True self.prev_lead_status = True self.prev_lead_x = x_lead self.cur_state[0].x_l = x_lead self.cur_state[0].v_l = v_lead else: self.prev_lead_status = False # Fake a fast lead car, so mpc keeps running self.cur_state[0].x_l = 50.0 self.cur_state[0].v_l = v_ego + 10.0 a_lead = 0.0 self.a_lead_tau = _LEAD_ACCEL_TAU # Calculate mpc t = sec_since_boot() n_its = self.libmpc.run_mpc(self.cur_state, self.mpc_solution, self.a_lead_tau, a_lead) duration = int((sec_since_boot() - t) * 1e9) self.send_mpc_solution(n_its, duration) # Get solution. MPC timestep is 0.2 s, so interpolation to 0.05 s is needed self.v_mpc = self.mpc_solution[0].v_ego[1] self.a_mpc = self.mpc_solution[0].a_ego[1] self.v_mpc_future = self.mpc_solution[0].v_ego[10] # Reset if NaN or goes through lead car dls = np.array(list(self.mpc_solution[0].x_l)) - np.array(list(self.mpc_solution[0].x_ego)) crashing = min(dls) < -50.0 nans = np.any(np.isnan(list(self.mpc_solution[0].v_ego))) backwards = min(list(self.mpc_solution[0].v_ego)) < -0.01 if ((backwards or crashing) and self.prev_lead_status) or nans: if t > self.last_cloudlog_t + 5.0: self.last_cloudlog_t = t cloudlog.warning("Longitudinal mpc %d reset - backwards: %s crashing: %s nan: %s" % ( self.mpc_id, backwards, crashing, nans)) self.libmpc.init(MPC_COST_LONG.TTC, MPC_COST_LONG.DISTANCE, MPC_COST_LONG.ACCELERATION, MPC_COST_LONG.JERK) self.cur_state[0].v_ego = v_ego self.cur_state[0].a_ego = 0.0 self.v_mpc = v_ego self.a_mpc = CS.carState.aEgo self.prev_lead_status = False class Planner(object): def __init__(self, CP, fcw_enabled): context = zmq.Context() self.CP = CP self.poller = zmq.Poller() self.plan = messaging.pub_sock(context, service_list['plan'].port) self.live_longitudinal_mpc = messaging.pub_sock(context, service_list['liveLongitudinalMpc'].port) self.radar_errors = [] self.mpc1 = LongitudinalMpc(1, self.live_longitudinal_mpc) self.mpc2 = LongitudinalMpc(2, self.live_longitudinal_mpc) self.v_acc_start = 0.0 self.a_acc_start = 0.0 self.v_acc = 0.0 self.v_acc_future = 0.0 self.a_acc = 0.0 self.v_cruise = 0.0 self.a_cruise = 0.0 self.lead_1 = None self.lead_2 = None self.longitudinalPlanSource = 'cruise' self.fcw = False self.fcw_checker = FCWChecker() self.fcw_enabled = fcw_enabled self.params = Params() self.v_curvature = NO_CURVATURE_SPEED self.v_speedlimit = NO_CURVATURE_SPEED self.decel_for_turn = False self.map_valid = False def choose_solution(self, v_cruise_setpoint, enabled): if enabled: solutions = {'cruise': self.v_cruise} if self.mpc1.prev_lead_status: solutions['mpc1'] = self.mpc1.v_mpc if self.mpc2.prev_lead_status: solutions['mpc2'] = self.mpc2.v_mpc slowest = min(solutions, key=solutions.get) self.longitudinalPlanSource = slowest # Choose lowest of MPC and cruise if slowest == 'mpc1': self.v_acc = self.mpc1.v_mpc self.a_acc = self.mpc1.a_mpc elif slowest == 'mpc2': self.v_acc = self.mpc2.v_mpc self.a_acc = self.mpc2.a_mpc elif slowest == 'cruise': self.v_acc = self.v_cruise self.a_acc = self.a_cruise self.v_acc_future = min([self.mpc1.v_mpc_future, self.mpc2.v_mpc_future, v_cruise_setpoint]) def update(self, CS, CP, VM, PP, live20, live100, md, live_map_data): """Gets called when new live20 is available""" cur_time = live20.logMonoTime / 1e9 v_ego = CS.carState.vEgo long_control_state = live100.live100.longControlState v_cruise_kph = live100.live100.vCruise force_slow_decel = live100.live100.forceDecel v_cruise_setpoint = v_cruise_kph * CV.KPH_TO_MS self.last_md_ts = md.logMonoTime self.radar_errors = list(live20.live20.radarErrors) self.lead_1 = live20.live20.leadOne self.lead_2 = live20.live20.leadTwo enabled = (long_control_state == LongCtrlState.pid) or (long_control_state == LongCtrlState.stopping) following = self.lead_1.status and self.lead_1.dRel < 45.0 and self.lead_1.vLeadK > v_ego and self.lead_1.aLeadK > 0.0 self.v_speedlimit = NO_CURVATURE_SPEED self.v_curvature = NO_CURVATURE_SPEED self.map_valid = live_map_data.liveMapData.mapValid # Speed limit and curvature set_speed_limit_active = self.params.get("LimitSetSpeed") == "1" and self.params.get("SpeedLimitOffset") is not None if set_speed_limit_active: if live_map_data.liveMapData.speedLimitValid: speed_limit = live_map_data.liveMapData.speedLimit offset = float(self.params.get("SpeedLimitOffset")) self.v_speedlimit = speed_limit + offset if live_map_data.liveMapData.curvatureValid: curvature = abs(live_map_data.liveMapData.curvature) a_y_max = 2.975 - v_ego * 0.0375 # ~1.85 @ 75mph, ~2.6 @ 25mph v_curvature = math.sqrt(a_y_max / max(1e-4, curvature)) self.v_curvature = min(NO_CURVATURE_SPEED, v_curvature) self.decel_for_turn = bool(self.v_curvature < min([v_cruise_setpoint, self.v_speedlimit, v_ego + 1.])) v_cruise_setpoint = min([v_cruise_setpoint, self.v_curvature, self.v_speedlimit]) # Calculate speed for normal cruise control if enabled: accel_limits = map(float, calc_cruise_accel_limits(v_ego, following)) jerk_limits = [min(-0.1, accel_limits[0]), max(0.1, accel_limits[1])] # TODO: make a separate lookup for jerk tuning accel_limits = limit_accel_in_turns(v_ego, CS.carState.steeringAngle, accel_limits, self.CP) if force_slow_decel: # if required so, force a smooth deceleration accel_limits[1] = min(accel_limits[1], AWARENESS_DECEL) accel_limits[0] = min(accel_limits[0], accel_limits[1]) # Change accel limits based on time remaining to turn if self.decel_for_turn: time_to_turn = max(1.0, live_map_data.liveMapData.distToTurn / max(self.v_cruise, 1.)) required_decel = min(0, (self.v_curvature - self.v_cruise) / time_to_turn) accel_limits[0] = max(accel_limits[0], required_decel) self.v_cruise, self.a_cruise = speed_smoother(self.v_acc_start, self.a_acc_start, v_cruise_setpoint, accel_limits[1], accel_limits[0], jerk_limits[1], jerk_limits[0], _DT_MPC) # cruise speed can't be negative even is user is distracted self.v_cruise = max(self.v_cruise, 0.) else: starting = long_control_state == LongCtrlState.starting a_ego = min(CS.carState.aEgo, 0.0) reset_speed = MIN_CAN_SPEED if starting else v_ego reset_accel = self.CP.startAccel if starting else a_ego self.v_acc = reset_speed self.a_acc = reset_accel self.v_acc_start = reset_speed self.a_acc_start = reset_accel self.v_cruise = reset_speed self.a_cruise = reset_accel self.mpc1.set_cur_state(self.v_acc_start, self.a_acc_start) self.mpc2.set_cur_state(self.v_acc_start, self.a_acc_start) self.mpc1.update(CS, self.lead_1, v_cruise_setpoint) self.mpc2.update(CS, self.lead_2, v_cruise_setpoint) self.choose_solution(v_cruise_setpoint, enabled) # determine fcw if self.mpc1.new_lead: self.fcw_checker.reset_lead(cur_time) blinkers = CS.carState.leftBlinker or CS.carState.rightBlinker self.fcw = self.fcw_checker.update(self.mpc1.mpc_solution, cur_time, v_ego, CS.carState.aEgo, self.lead_1.dRel, self.lead_1.vLead, self.lead_1.aLeadK, self.lead_1.yRel, self.lead_1.vLat, self.lead_1.fcw, blinkers) and not CS.carState.brakePressed if self.fcw: cloudlog.info("FCW triggered %s", self.fcw_checker.counters) model_dead = cur_time - (md.logMonoTime / 1e9) > 0.5 # **** send the plan **** plan_send = messaging.new_message() plan_send.init('plan') # TODO: Move all these events to controlsd. This has nothing to do with planning events = [] if model_dead: events.append(create_event('modelCommIssue', [ET.NO_ENTRY, ET.IMMEDIATE_DISABLE])) if 'fault' in self.radar_errors: events.append(create_event('radarFault', [ET.NO_ENTRY, ET.SOFT_DISABLE])) plan_send.plan.events = events plan_send.plan.mdMonoTime = md.logMonoTime plan_send.plan.l20MonoTime = live20.logMonoTime # longitudal plan plan_send.plan.vCruise = self.v_cruise plan_send.plan.aCruise = self.a_cruise plan_send.plan.vStart = self.v_acc_start plan_send.plan.aStart = self.a_acc_start plan_send.plan.vTarget = self.v_acc plan_send.plan.aTarget = self.a_acc plan_send.plan.vTargetFuture = self.v_acc_future plan_send.plan.hasLead = self.mpc1.prev_lead_status plan_send.plan.longitudinalPlanSource = self.longitudinalPlanSource plan_send.plan.vCurvature = self.v_curvature plan_send.plan.decelForTurn = self.decel_for_turn plan_send.plan.mapValid = self.map_valid # Send out fcw fcw = self.fcw and (self.fcw_enabled or long_control_state != LongCtrlState.off) plan_send.plan.fcw = fcw self.plan.send(plan_send.to_bytes()) # Interpolate 0.05 seconds and save as starting point for next iteration dt = 0.05 # s a_acc_sol = self.a_acc_start + (dt / _DT_MPC) * (self.a_acc - self.a_acc_start) v_acc_sol = self.v_acc_start + dt * (a_acc_sol + self.a_acc_start) / 2.0 self.v_acc_start = v_acc_sol self.a_acc_start = a_acc_sol