#!/usr/bin/env python3 import math import numpy as np from openpilot.common.numpy_fast import clip, interp from openpilot.common.params import Params from cereal import car import cereal.messaging as messaging from openpilot.common.conversions import Conversions as CV from openpilot.common.filter_simple import FirstOrderFilter from openpilot.common.realtime import DT_MDL from openpilot.selfdrive.modeld.constants import ModelConstants from openpilot.selfdrive.controls.lib.sunnypilot.common import Source from openpilot.selfdrive.controls.lib.sunnypilot.speed_limit_controller import SpeedLimitController from openpilot.selfdrive.car.interfaces import ACCEL_MIN, ACCEL_MAX from openpilot.selfdrive.controls.lib.longcontrol import LongCtrlState from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import LongitudinalMpc from openpilot.selfdrive.controls.lib.longitudinal_mpc_lib.long_mpc import T_IDXS as T_IDXS_MPC from openpilot.selfdrive.controls.lib.drive_helpers import V_CRUISE_MAX, CONTROL_N, get_speed_error from openpilot.selfdrive.controls.lib.vision_turn_controller import VisionTurnController from openpilot.selfdrive.controls.lib.turn_speed_controller import TurnSpeedController from openpilot.selfdrive.controls.lib.dynamic_experimental_controller import DynamicExperimentalController from openpilot.selfdrive.controls.lib.events import Events from openpilot.common.swaglog import cloudlog LON_MPC_STEP = 0.2 # first step is 0.2s A_CRUISE_MIN = -1.2 A_CRUISE_MAX_VALS = [1.6, 1.2, 0.8, 0.6] A_CRUISE_MAX_BP = [0., 10.0, 25., 40.] # Lookup table for turns _A_TOTAL_MAX_V = [1.7, 3.2] _A_TOTAL_MAX_BP = [20., 40.] EventName = car.CarEvent.EventName def get_max_accel(v_ego): return interp(v_ego, A_CRUISE_MAX_BP, A_CRUISE_MAX_VALS) 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 """ # FIXME: This function to calculate lateral accel is incorrect and should use the VehicleModel # The lookup table for turns should also be updated if we do this 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.)) return [a_target[0], min(a_target[1], a_x_allowed)] class LongitudinalPlanner: def __init__(self, CP, init_v=0.0, init_a=0.0, dt=DT_MDL): self.CP = CP self.mpc = LongitudinalMpc(dt=dt) self.fcw = False self.dt = dt self.a_desired = init_a self.v_desired_filter = FirstOrderFilter(init_v, 2.0, self.dt) self.v_model_error = 0.0 self.v_desired_trajectory = np.zeros(CONTROL_N) self.a_desired_trajectory = np.zeros(CONTROL_N) self.j_desired_trajectory = np.zeros(CONTROL_N) self.solverExecutionTime = 0.0 self.params = Params() self.param_read_counter = 0 self.read_param() self.cruise_source = 'cruise' self.vision_turn_controller = VisionTurnController(CP) self.speed_limit_controller = SpeedLimitController(CP) self.events = Events() self.turn_speed_controller = TurnSpeedController() self.dynamic_experimental_controller = DynamicExperimentalController() def read_param(self): try: self.dynamic_experimental_controller.set_enabled(self.params.get_bool("DynamicExperimentalControl")) except AttributeError: self.dynamic_experimental_controller = DynamicExperimentalController() @staticmethod def parse_model(model_msg, model_error): if (len(model_msg.position.x) == ModelConstants.IDX_N and len(model_msg.velocity.x) == ModelConstants.IDX_N and len(model_msg.acceleration.x) == ModelConstants.IDX_N): x = np.interp(T_IDXS_MPC, ModelConstants.T_IDXS, model_msg.position.x) - model_error * T_IDXS_MPC v = np.interp(T_IDXS_MPC, ModelConstants.T_IDXS, model_msg.velocity.x) - model_error a = np.interp(T_IDXS_MPC, ModelConstants.T_IDXS, model_msg.acceleration.x) j = np.zeros(len(T_IDXS_MPC)) else: x = np.zeros(len(T_IDXS_MPC)) v = np.zeros(len(T_IDXS_MPC)) a = np.zeros(len(T_IDXS_MPC)) j = np.zeros(len(T_IDXS_MPC)) return x, v, a, j def update(self, sm): if self.param_read_counter % 50 == 0: self.read_param() self.param_read_counter += 1 if self.dynamic_experimental_controller.is_enabled() and sm['controlsState'].experimentalMode: self.mpc.mode = self.dynamic_experimental_controller.get_mpc_mode(self.CP.radarUnavailable, sm['carState'], sm['radarState'].leadOne, sm['modelV2'], sm['controlsState'], sm['navInstruction'].maneuverDistance) else: self.mpc.mode = 'blended' if sm['controlsState'].experimentalMode else 'acc' v_ego = sm['carState'].vEgo v_cruise_kph = min(sm['controlsState'].vCruise, V_CRUISE_MAX) v_cruise = v_cruise_kph * CV.KPH_TO_MS long_control_off = sm['controlsState'].longControlState == LongCtrlState.off force_slow_decel = sm['controlsState'].forceDecel # Reset current state when not engaged, or user is controlling the speed reset_state = long_control_off if self.CP.openpilotLongitudinalControl else not sm['carControl'].hudControl.speedVisible # No change cost when user is controlling the speed, or when standstill prev_accel_constraint = not (reset_state or sm['carState'].standstill) if self.mpc.mode == 'acc': accel_limits = [A_CRUISE_MIN, get_max_accel(v_ego)] accel_limits_turns = limit_accel_in_turns(v_ego, sm['carState'].steeringAngleDeg, accel_limits, self.CP) else: accel_limits = [ACCEL_MIN, ACCEL_MAX] accel_limits_turns = [ACCEL_MIN, ACCEL_MAX] if reset_state: self.v_desired_filter.x = v_ego # Clip aEgo to cruise limits to prevent large accelerations when becoming active self.a_desired = clip(sm['carState'].aEgo, accel_limits[0], accel_limits[1]) # Prevent divergence, smooth in current v_ego self.v_desired_filter.x = max(0.0, self.v_desired_filter.update(v_ego)) # Compute model v_ego error self.v_model_error = get_speed_error(sm['modelV2'], v_ego) if force_slow_decel: v_cruise = 0.0 # Get active solutions for custom long mpc. v_cruise = self.cruise_solutions( not reset_state and (self.CP.openpilotLongitudinalControl or not self.CP.pcmCruiseSpeed), self.v_desired_filter.x, self.a_desired, v_cruise, sm) # clip limits, cannot init MPC outside of bounds accel_limits_turns[0] = min(accel_limits_turns[0], self.a_desired + 0.05) accel_limits_turns[1] = max(accel_limits_turns[1], self.a_desired - 0.05) self.mpc.set_weights(prev_accel_constraint, personality=sm['controlsState'].personality) self.mpc.set_accel_limits(accel_limits_turns[0], accel_limits_turns[1]) self.mpc.set_cur_state(self.v_desired_filter.x, self.a_desired) x, v, a, j = self.parse_model(sm['modelV2'], self.v_model_error) self.mpc.update(sm['radarState'], v_cruise, x, v, a, j, personality=sm['controlsState'].personality) self.v_desired_trajectory_full = np.interp(ModelConstants.T_IDXS, T_IDXS_MPC, self.mpc.v_solution) self.a_desired_trajectory_full = np.interp(ModelConstants.T_IDXS, T_IDXS_MPC, self.mpc.a_solution) self.v_desired_trajectory = self.v_desired_trajectory_full[:CONTROL_N] self.a_desired_trajectory = self.a_desired_trajectory_full[:CONTROL_N] self.j_desired_trajectory = np.interp(ModelConstants.T_IDXS[:CONTROL_N], T_IDXS_MPC[:-1], self.mpc.j_solution) # TODO counter is only needed because radar is glitchy, remove once radar is gone self.fcw = self.mpc.crash_cnt > 2 and not sm['carState'].standstill if self.fcw: cloudlog.info("FCW triggered") # Interpolate 0.05 seconds and save as starting point for next iteration a_prev = self.a_desired self.a_desired = float(interp(self.dt, ModelConstants.T_IDXS[:CONTROL_N], self.a_desired_trajectory)) self.v_desired_filter.x = self.v_desired_filter.x + self.dt * (self.a_desired + a_prev) / 2.0 self.e2e_events(sm) def publish(self, sm, pm): plan_send = messaging.new_message('longitudinalPlan') plan_send.valid = sm.all_checks(service_list=['carState', 'controlsState']) longitudinalPlan = plan_send.longitudinalPlan longitudinalPlan.modelMonoTime = sm.logMonoTime['modelV2'] longitudinalPlan.processingDelay = (plan_send.logMonoTime / 1e9) - sm.logMonoTime['modelV2'] longitudinalPlan.speeds = self.v_desired_trajectory.tolist() longitudinalPlan.accels = self.a_desired_trajectory.tolist() longitudinalPlan.jerks = self.j_desired_trajectory.tolist() longitudinalPlan.hasLead = sm['radarState'].leadOne.status longitudinalPlan.longitudinalPlanSource = self.mpc.source longitudinalPlan.fcw = self.fcw longitudinalPlan.solverExecutionTime = self.mpc.solve_time pm.send('longitudinalPlan', plan_send) plan_sp_send = messaging.new_message('longitudinalPlanSP') plan_sp_send.valid = sm.all_checks(service_list=['carState', 'controlsState']) longitudinalPlanSP = plan_sp_send.longitudinalPlanSP longitudinalPlanSP.longitudinalPlanSource = self.mpc.source if self.mpc.source != 'cruise' else self.cruise_source longitudinalPlanSP.e2eX = self.mpc.e2e_x.tolist() longitudinalPlanSP.visionTurnControllerState = self.vision_turn_controller.state longitudinalPlanSP.visionTurnSpeed = float(self.vision_turn_controller.v_target) longitudinalPlanSP.visionCurrentLatAcc = float(self.vision_turn_controller.current_lat_acc) longitudinalPlanSP.visionMaxPredLatAcc = float(self.vision_turn_controller.max_pred_lat_acc) longitudinalPlanSP.speedLimitControlState = self.speed_limit_controller.state longitudinalPlanSP.speedLimit = float(self.speed_limit_controller.speed_limit) longitudinalPlanSP.speedLimitOffset = float(self.speed_limit_controller.speed_limit_offset) longitudinalPlanSP.distToSpeedLimit = float(self.speed_limit_controller.distance) longitudinalPlanSP.isMapSpeedLimit = bool(self.speed_limit_controller.source not in (Source.none, Source.nav)) longitudinalPlanSP.events = self.events.to_msg() longitudinalPlanSP.turnSpeedControlState = self.turn_speed_controller.state longitudinalPlanSP.turnSpeed = float(self.turn_speed_controller.v_target) longitudinalPlanSP.e2eBlended = self.mpc.mode pm.send('longitudinalPlanSP', plan_sp_send) def cruise_solutions(self, enabled, v_ego, a_ego, v_cruise, sm): # Update controllers self.vision_turn_controller.update(enabled, v_ego, v_cruise, sm) self.events = Events() self.speed_limit_controller.update(enabled, v_ego, a_ego, sm, v_cruise, self.events) self.turn_speed_controller.update(enabled, v_ego, sm, v_cruise) v_tsc_target = self.vision_turn_controller.v_target if self.vision_turn_controller.is_active else 255 slc_target = self.speed_limit_controller.speed_limit_offseted if self.speed_limit_controller.is_active else 255 m_tsc_target = self.turn_speed_controller.v_target if self.turn_speed_controller.is_active else 255 # Pick solution with the lowest velocity target. v_solutions = min(v_cruise, v_tsc_target, slc_target, m_tsc_target) return v_solutions def e2e_events(self, sm): e2e_long_status = sm['e2eLongStateSP'].status if e2e_long_status in (1, 2): self.events.add(EventName.e2eLongStart)