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252 lines
9.7 KiB
252 lines
9.7 KiB
#!/usr/bin/env python3
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import math
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import numpy as np
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from common.params import Params
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from common.numpy_fast import interp
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import cereal.messaging as messaging
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from cereal import car
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from common.realtime import sec_since_boot
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from selfdrive.swaglog import cloudlog
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from selfdrive.config import Conversions as CV
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from selfdrive.controls.lib.speed_smoother import speed_smoother
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from selfdrive.controls.lib.longcontrol import LongCtrlState, MIN_CAN_SPEED
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from selfdrive.controls.lib.fcw import FCWChecker
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from selfdrive.controls.lib.long_mpc import LongitudinalMpc
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MAX_SPEED = 255.0
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LON_MPC_STEP = 0.2 # first step is 0.2s
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MAX_SPEED_ERROR = 2.0
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AWARENESS_DECEL = -0.2 # car smoothly decel at .2m/s^2 when user is distracted
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# lookup tables VS speed to determine min and max accels in cruise
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# make sure these accelerations are smaller than mpc limits
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_A_CRUISE_MIN_V = [-1.0, -.8, -.67, -.5, -.30]
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_A_CRUISE_MIN_BP = [ 0., 5., 10., 20., 40.]
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# need fast accel at very low speed for stop and go
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# make sure these accelerations are smaller than mpc limits
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_A_CRUISE_MAX_V = [1.2, 1.2, 0.65, .4]
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_A_CRUISE_MAX_V_FOLLOWING = [1.6, 1.6, 0.65, .4]
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_A_CRUISE_MAX_BP = [0., 6.4, 22.5, 40.]
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# Lookup table for turns
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_A_TOTAL_MAX_V = [1.7, 3.2]
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_A_TOTAL_MAX_BP = [20., 40.]
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# 75th percentile
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SPEED_PERCENTILE_IDX = 7
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def calc_cruise_accel_limits(v_ego, following):
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a_cruise_min = interp(v_ego, _A_CRUISE_MIN_BP, _A_CRUISE_MIN_V)
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if following:
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a_cruise_max = interp(v_ego, _A_CRUISE_MAX_BP, _A_CRUISE_MAX_V_FOLLOWING)
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else:
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a_cruise_max = interp(v_ego, _A_CRUISE_MAX_BP, _A_CRUISE_MAX_V)
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return np.vstack([a_cruise_min, a_cruise_max])
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def limit_accel_in_turns(v_ego, angle_steers, a_target, CP):
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"""
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This function returns a limited long acceleration allowed, depending on the existing lateral acceleration
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this should avoid accelerating when losing the target in turns
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"""
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a_total_max = interp(v_ego, _A_TOTAL_MAX_BP, _A_TOTAL_MAX_V)
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a_y = v_ego**2 * angle_steers * CV.DEG_TO_RAD / (CP.steerRatio * CP.wheelbase)
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a_x_allowed = math.sqrt(max(a_total_max**2 - a_y**2, 0.))
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return [a_target[0], min(a_target[1], a_x_allowed)]
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class Planner():
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def __init__(self, CP):
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self.CP = CP
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self.mpc1 = LongitudinalMpc(1)
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self.mpc2 = LongitudinalMpc(2)
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self.v_acc_start = 0.0
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self.a_acc_start = 0.0
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self.v_acc = 0.0
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self.v_acc_future = 0.0
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self.a_acc = 0.0
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self.v_cruise = 0.0
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self.a_cruise = 0.0
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self.v_model = 0.0
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self.a_model = 0.0
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self.longitudinalPlanSource = 'cruise'
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self.fcw_checker = FCWChecker()
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self.path_x = np.arange(192)
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self.params = Params()
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self.first_loop = True
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def choose_solution(self, v_cruise_setpoint, enabled):
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if enabled:
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solutions = {'model': self.v_model, 'cruise': self.v_cruise}
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if self.mpc1.prev_lead_status:
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solutions['mpc1'] = self.mpc1.v_mpc
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if self.mpc2.prev_lead_status:
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solutions['mpc2'] = self.mpc2.v_mpc
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slowest = min(solutions, key=solutions.get)
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self.longitudinalPlanSource = slowest
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# Choose lowest of MPC and cruise
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if slowest == 'mpc1':
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self.v_acc = self.mpc1.v_mpc
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self.a_acc = self.mpc1.a_mpc
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elif slowest == 'mpc2':
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self.v_acc = self.mpc2.v_mpc
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self.a_acc = self.mpc2.a_mpc
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elif slowest == 'cruise':
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self.v_acc = self.v_cruise
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self.a_acc = self.a_cruise
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elif slowest == 'model':
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self.v_acc = self.v_model
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self.a_acc = self.a_model
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self.v_acc_future = min([self.mpc1.v_mpc_future, self.mpc2.v_mpc_future, v_cruise_setpoint])
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def update(self, sm, pm, CP, VM, PP):
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"""Gets called when new radarState is available"""
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cur_time = sec_since_boot()
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v_ego = sm['carState'].vEgo
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long_control_state = sm['controlsState'].longControlState
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v_cruise_kph = sm['controlsState'].vCruise
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force_slow_decel = sm['controlsState'].forceDecel
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v_cruise_setpoint = v_cruise_kph * CV.KPH_TO_MS
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lead_1 = sm['radarState'].leadOne
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lead_2 = sm['radarState'].leadTwo
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enabled = (long_control_state == LongCtrlState.pid) or (long_control_state == LongCtrlState.stopping)
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following = lead_1.status and lead_1.dRel < 45.0 and lead_1.vLeadK > v_ego and lead_1.aLeadK > 0.0
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if len(sm['model'].path.poly):
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path = list(sm['model'].path.poly)
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# Curvature of polynomial https://en.wikipedia.org/wiki/Curvature#Curvature_of_the_graph_of_a_function
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# y = a x^3 + b x^2 + c x + d, y' = 3 a x^2 + 2 b x + c, y'' = 6 a x + 2 b
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# k = y'' / (1 + y'^2)^1.5
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# TODO: compute max speed without using a list of points and without numpy
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y_p = 3 * path[0] * self.path_x**2 + 2 * path[1] * self.path_x + path[2]
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y_pp = 6 * path[0] * self.path_x + 2 * path[1]
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curv = y_pp / (1. + y_p**2)**1.5
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a_y_max = 2.975 - v_ego * 0.0375 # ~1.85 @ 75mph, ~2.6 @ 25mph
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v_curvature = np.sqrt(a_y_max / np.clip(np.abs(curv), 1e-4, None))
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model_speed = np.min(v_curvature)
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model_speed = max(20.0 * CV.MPH_TO_MS, model_speed) # Don't slow down below 20mph
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else:
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model_speed = MAX_SPEED
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# Calculate speed for normal cruise control
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if enabled and not self.first_loop:
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accel_limits = [float(x) for x in calc_cruise_accel_limits(v_ego, following)]
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jerk_limits = [min(-0.1, accel_limits[0]), max(0.1, accel_limits[1])] # TODO: make a separate lookup for jerk tuning
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accel_limits_turns = limit_accel_in_turns(v_ego, sm['carState'].steeringAngle, accel_limits, self.CP)
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if force_slow_decel:
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# if required so, force a smooth deceleration
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accel_limits_turns[1] = min(accel_limits_turns[1], AWARENESS_DECEL)
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accel_limits_turns[0] = min(accel_limits_turns[0], accel_limits_turns[1])
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self.v_cruise, self.a_cruise = speed_smoother(self.v_acc_start, self.a_acc_start,
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v_cruise_setpoint,
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accel_limits_turns[1], accel_limits_turns[0],
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jerk_limits[1], jerk_limits[0],
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LON_MPC_STEP)
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self.v_model, self.a_model = speed_smoother(self.v_acc_start, self.a_acc_start,
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model_speed,
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2*accel_limits[1], accel_limits[0],
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2*jerk_limits[1], jerk_limits[0],
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LON_MPC_STEP)
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# cruise speed can't be negative even is user is distracted
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self.v_cruise = max(self.v_cruise, 0.)
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else:
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starting = long_control_state == LongCtrlState.starting
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a_ego = min(sm['carState'].aEgo, 0.0)
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reset_speed = MIN_CAN_SPEED if starting else v_ego
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reset_accel = self.CP.startAccel if starting else a_ego
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self.v_acc = reset_speed
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self.a_acc = reset_accel
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self.v_acc_start = reset_speed
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self.a_acc_start = reset_accel
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self.v_cruise = reset_speed
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self.a_cruise = reset_accel
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self.mpc1.set_cur_state(self.v_acc_start, self.a_acc_start)
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self.mpc2.set_cur_state(self.v_acc_start, self.a_acc_start)
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self.mpc1.update(pm, sm['carState'], lead_1, v_cruise_setpoint)
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self.mpc2.update(pm, sm['carState'], lead_2, v_cruise_setpoint)
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self.choose_solution(v_cruise_setpoint, enabled)
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# determine fcw
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if self.mpc1.new_lead:
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self.fcw_checker.reset_lead(cur_time)
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blinkers = sm['carState'].leftBlinker or sm['carState'].rightBlinker
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fcw = self.fcw_checker.update(self.mpc1.mpc_solution, cur_time,
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sm['controlsState'].active,
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v_ego, sm['carState'].aEgo,
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lead_1.dRel, lead_1.vLead, lead_1.aLeadK,
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lead_1.yRel, lead_1.vLat,
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lead_1.fcw, blinkers) and not sm['carState'].brakePressed
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if fcw:
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cloudlog.info("FCW triggered %s", self.fcw_checker.counters)
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radar_dead = not sm.alive['radarState']
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radar_errors = list(sm['radarState'].radarErrors)
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radar_fault = car.RadarData.Error.fault in radar_errors
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radar_can_error = car.RadarData.Error.canError in radar_errors
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# **** send the plan ****
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plan_send = messaging.new_message('plan')
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plan_send.valid = sm.all_alive_and_valid(service_list=['carState', 'controlsState', 'radarState'])
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plan_send.plan.mdMonoTime = sm.logMonoTime['model']
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plan_send.plan.radarStateMonoTime = sm.logMonoTime['radarState']
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# longitudal plan
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plan_send.plan.vCruise = float(self.v_cruise)
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plan_send.plan.aCruise = float(self.a_cruise)
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plan_send.plan.vStart = float(self.v_acc_start)
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plan_send.plan.aStart = float(self.a_acc_start)
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plan_send.plan.vTarget = float(self.v_acc)
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plan_send.plan.aTarget = float(self.a_acc)
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plan_send.plan.vTargetFuture = float(self.v_acc_future)
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plan_send.plan.hasLead = self.mpc1.prev_lead_status
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plan_send.plan.longitudinalPlanSource = self.longitudinalPlanSource
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radar_valid = not (radar_dead or radar_fault)
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plan_send.plan.radarValid = bool(radar_valid)
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plan_send.plan.radarCanError = bool(radar_can_error)
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plan_send.plan.processingDelay = (plan_send.logMonoTime / 1e9) - sm.rcv_time['radarState']
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# Send out fcw
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plan_send.plan.fcw = fcw
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pm.send('plan', plan_send)
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# Interpolate 0.05 seconds and save as starting point for next iteration
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a_acc_sol = self.a_acc_start + (CP.radarTimeStep / LON_MPC_STEP) * (self.a_acc - self.a_acc_start)
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v_acc_sol = self.v_acc_start + CP.radarTimeStep * (a_acc_sol + self.a_acc_start) / 2.0
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self.v_acc_start = v_acc_sol
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self.a_acc_start = a_acc_sol
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self.first_loop = False
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