dragonpilot/selfdrive/controls/lib/planner.py

#!/usr/bin/env python
import os
import zmq

import numpy as np
import math
from collections import defaultdict

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, EventTypes as ET
from selfdrive.controls.lib.pathplanner import PathPlanner
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

_DT = 0.01    # 100Hz
_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
_DEBUG = False
_LEAD_ACCEL_TAU = 1.5

GPS_PLANNER_ADDR = "192.168.5.1"

# 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., .8, .5, .3]
_A_CRUISE_MAX_V_FOLLOWING = [1.5, 1.5, 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.]

# max acceleration allowed in acc, which happens in restart
A_ACC_MAX = max(_A_CRUISE_MAX_V_FOLLOWING)


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
  """
  deg_to_rad = np.pi / 180.  # from can reading to rad

  a_total_max = interp(v_ego, _A_TOTAL_MAX_BP, _A_TOTAL_MAX_V)
  a_y = v_ego**2 * angle_steers * 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[1:])
    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[1:15]) - 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.aLead = list(self.mpc_solution[0].a_l)
    dat.liveLongitudinalMpc.aLeadTau = self.l
    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()

    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.l = _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):
    # 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

      # Learn if constant acceleration
      if abs(a_lead) < 0.5:
        self.l = _LEAD_ACCEL_TAU
      else:
        self.l *= 0.9

      l = max(self.l, -a_lead / (v_lead + 0.01))
      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, l)
        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
      self.cur_state[0].a_l = a_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 = CS.vEgo + 10.0
      self.cur_state[0].a_l = 0.0
      l = _LEAD_ACCEL_TAU

    # Calculate mpc
    t = sec_since_boot()
    n_its = self.libmpc.run_mpc(self.cur_state, self.mpc_solution, l)
    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)[1:]) - np.array(list(self.mpc_solution[0].x_ego)[1:])
    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)[1:]) < -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()
      self.cur_state[0].v_ego = CS.vEgo
      self.cur_state[0].a_ego = 0.0
      self.v_mpc = CS.vEgo
      self.a_mpc = CS.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.live20 = messaging.sub_sock(context, service_list['live20'].port, conflate=True, poller=self.poller)
    self.model = messaging.sub_sock(context, service_list['model'].port, conflate=True, poller=self.poller)

    if os.environ.get('GPS_PLANNER_ACTIVE', False):
      self.gps_planner_plan = messaging.sub_sock(context, service_list['gpsPlannerPlan'].port, conflate=True, poller=self.poller, addr=GPS_PLANNER_ADDR)
    else:
      self.gps_planner_plan = None

    self.plan = messaging.pub_sock(context, service_list['plan'].port)
    self.live_longitudinal_mpc = messaging.pub_sock(context, service_list['liveLongitudinalMpc'].port)

    self.last_md_ts = 0
    self.last_l20_ts = 0
    self.last_model = 0.
    self.last_l20 = 0.
    self.model_dead = True
    self.radar_dead = True
    self.radar_errors = []

    self.PP = PathPlanner()
    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.acc_start_time = sec_since_boot()
    self.v_acc = 0.0
    self.v_acc_sol = 0.0
    self.v_acc_future = 0.0
    self.a_acc = 0.0
    self.a_acc_sol = 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.last_gps_planner_plan = None
    self.gps_planner_active = 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)

      if _DEBUG:
        print "D_SOL", solutions, slowest, self.v_acc_sol, self.a_acc_sol
        print "D_V", self.mpc1.v_mpc, self.mpc2.v_mpc, self.v_cruise
        print "D_A", self.mpc1.a_mpc, self.mpc2.a_mpc, self.a_cruise

      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])

  # this runs whenever we get a packet that can change the plan
  def update(self, CS, LoC, v_cruise_kph, user_distracted):
    cur_time = sec_since_boot()
    v_cruise_setpoint = v_cruise_kph * CV.KPH_TO_MS

    md = None
    l20 = None
    gps_planner_plan = None

    for socket, event in self.poller.poll(0):
      if socket is self.model:
        md = messaging.recv_one(socket)
      elif socket is self.live20:
        l20 = messaging.recv_one(socket)
      elif socket is self.gps_planner_plan:
        gps_planner_plan = messaging.recv_one(socket)

    if gps_planner_plan is not None:
      self.last_gps_planner_plan = gps_planner_plan

    if md is not None:
      self.last_md_ts = md.logMonoTime
      self.last_model = cur_time
      self.model_dead = False

      self.PP.update(CS.vEgo, md)

      if self.last_gps_planner_plan is not None:
        plan = self.last_gps_planner_plan.gpsPlannerPlan
        self.gps_planner_active = plan.valid
        if plan.valid:
          self.PP.d_poly = plan.poly
          self.PP.p_poly = plan.poly
          self.PP.c_poly = plan.poly
          self.PP.l_prob = 0.0
          self.PP.r_prob = 0.0
          self.PP.c_prob = 1.0

    if l20 is not None:
      self.last_l20_ts = l20.logMonoTime
      self.last_l20 = cur_time
      self.radar_dead = False
      self.radar_errors = list(l20.live20.radarErrors)

      self.v_acc_start = self.v_acc_sol
      self.a_acc_start = self.a_acc_sol
      self.acc_start_time = cur_time

      self.lead_1 = l20.live20.leadOne
      self.lead_2 = l20.live20.leadTwo

      enabled = (LoC.long_control_state == LongCtrlState.pid) or (LoC.long_control_state == LongCtrlState.stopping)
      following = self.lead_1.status and self.lead_1.dRel < 45.0 and self.lead_1.vLeadK > CS.vEgo and self.lead_1.aLeadK > 0.0

      # Calculate speed for normal cruise control
      if enabled:

        accel_limits = map(float, calc_cruise_accel_limits(CS.vEgo, following))
        # TODO: make a separate lookup for jerk tuning
        jerk_limits = [min(-0.1, accel_limits[0]), max(0.1, accel_limits[1])]
        accel_limits = limit_accel_in_turns(CS.vEgo, CS.steeringAngle, accel_limits, self.CP)
        if user_distracted:
          # if user is not responsive to awareness alerts, then start a smooth deceleration
          accel_limits[1] = min(accel_limits[1], AWARENESS_DECEL)
          accel_limits[0] = min(accel_limits[0], accel_limits[1])

        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 = LoC.long_control_state == LongCtrlState.starting
        a_ego = min(CS.aEgo, 0.0)
        reset_speed = MIN_CAN_SPEED if starting else CS.vEgo
        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.v_acc_sol = reset_speed
        self.a_acc_sol = 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.leftBlinker or CS.rightBlinker
      self.fcw = self.fcw_checker.update(self.mpc1.mpc_solution, cur_time, CS.vEgo, CS.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.brakePressed
      if self.fcw:
        cloudlog.info("FCW triggered %s", self.fcw_checker.counters)

    if cur_time - self.last_model > 0.5:
      self.model_dead = True

    if cur_time - self.last_l20 > 0.5:
      self.radar_dead = True
    # **** send the plan ****
    plan_send = messaging.new_message()
    plan_send.init('plan')

    events = []
    if self.model_dead:
      events.append(create_event('modelCommIssue', [ET.NO_ENTRY, ET.IMMEDIATE_DISABLE]))
    if self.radar_dead or 'commIssue' in self.radar_errors:
      events.append(create_event('radarCommIssue', [ET.NO_ENTRY, ET.IMMEDIATE_DISABLE]))
    if 'fault' in self.radar_errors:
      events.append(create_event('radarFault', [ET.NO_ENTRY, ET.IMMEDIATE_DISABLE]))

    # Interpolation of trajectory
    dt = min(cur_time - self.acc_start_time, _DT_MPC + _DT) + _DT  # no greater than dt mpc + dt, to prevent too high extraps
    self.a_acc_sol = self.a_acc_start + (dt / _DT_MPC) * (self.a_acc - self.a_acc_start)
    self.v_acc_sol = self.v_acc_start + dt * (self.a_acc_sol + self.a_acc_start) / 2.0

    plan_send.plan.events = events
    plan_send.plan.mdMonoTime = self.last_md_ts
    plan_send.plan.l20MonoTime = self.last_l20_ts

    # lateral plan
    plan_send.plan.lateralValid = not self.model_dead
    plan_send.plan.dPoly = map(float, self.PP.d_poly)
    plan_send.plan.laneWidth = float(self.PP.lane_width)

    # longitudal plan
    plan_send.plan.longitudinalValid = not self.radar_dead
    plan_send.plan.vCruise = self.v_cruise
    plan_send.plan.aCruise = self.a_cruise
    plan_send.plan.vTarget = self.v_acc_sol
    plan_send.plan.aTarget = self.a_acc_sol
    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.gpsPlannerActive = self.gps_planner_active

    # Send out fcw
    fcw = self.fcw and (self.fcw_enabled or LoC.long_control_state != LongCtrlState.off)
    plan_send.plan.fcw = fcw

    self.plan.send(plan_send.to_bytes())
    return plan_send