Esempio n. 1
0
    def __init__(self,
                 scenario_params: ScenarioParameters,
                 ctrl_params: CtrlParameters,
                 carla_synchronous: tuple,
                 eval_env: Environment,
                 eval_stg: Trajectron,
                 motion_planner_cls: MidlevelAgent,
                 scene_builder_cls: TrajectronPlusPlusSceneBuilder,
                 n_simulations=2):
        self.client, self.world, self.carla_map, self.traffic_manager = carla_synchronous
        self.scenario_params = scenario_params
        self.ctrl_params = ctrl_params
        self.eval_env = eval_env
        self.eval_stg = eval_stg
        self.motion_planner_cls = motion_planner_cls
        self.scene_builder_cls = scene_builder_cls
        self.n_simulations = n_simulations

        self.map_reader = NaiveMapQuerier(self.world,
                                          self.carla_map,
                                          debug=True)
        self.online_config = OnlineConfig(record_interval=10,
                                          node_type=self.eval_env.NodeType)

        # Mock vehicles
        self.spawn_points = self.carla_map.get_spawn_points()
        self.blueprints = get_all_vehicle_blueprints(self.world)
        self.blueprint_audi_a2 = self.world.get_blueprint_library().find(
            'vehicle.audi.a2')
Esempio n. 2
0
def test_1_npc_appear(carla_Town03_synchronous):
    """Test case where NPC appears before EGO vehicle after awhile.
    """
    client, world, carla_map, traffic_manager = carla_Town03_synchronous
    ego_vehicle = None
    other_vehicles = []
    data_collector = None

    n_burn_frames = 180
    save_frequency = 40
    record_interval = 5
    scene_interval = 30
    try:
        # Mock vehicles
        spawn_points = carla_map.get_spawn_points()
        blueprint = world.get_blueprint_library().find('vehicle.audi.a2')
        spawn_point = spawn_points[251]
        ego_vehicle = world.spawn_actor(blueprint, spawn_point)
        ego_vehicle.set_autopilot(True, traffic_manager.get_port())

        other_vehicle_ids = []
        blueprints = get_all_vehicle_blueprints(world)
        for idx in [164]:
            blueprint = np.random.choice(blueprints)
            spawn_point = spawn_points[idx]
            other_vehicle = world.spawn_actor(blueprint, spawn_point)
            other_vehicle.set_autopilot(True, traffic_manager.get_port())
            other_vehicles.append(other_vehicle)
            other_vehicle_ids.append(other_vehicle.id)

        # Setup data collector
        map_reader = NaiveMapQuerier(world, carla_map, debug=True)
        scene_config = SceneConfig(scene_interval=scene_interval,
                                   record_interval=record_interval)
        data_collector = DataCollector(ego_vehicle,
                                       map_reader,
                                       other_vehicle_ids,
                                       scene_builder_cls=TESTSceneBuilder,
                                       scene_config=scene_config,
                                       save_frequency=save_frequency,
                                       n_burn_frames=n_burn_frames,
                                       debug=True)
        data_collector.start_sensor()
        assert data_collector.sensor_is_listening

        # Run simulation for X steps
        for idx in range(n_burn_frames + record_interval *
                         (save_frequency - 1)):
            frame = world.tick()
            data_collector.capture_step(frame)

    finally:
        if data_collector:
            data_collector.destroy()
        if ego_vehicle:
            ego_vehicle.destroy()
        for other_vehicle in other_vehicles:
            other_vehicle.destroy()
Esempio n. 3
0
def test_no_npcs(carla_Town03_synchronous):
    client, world, carla_map, traffic_manager = carla_Town03_synchronous
    ego_vehicle = None
    data_collector = None

    n_burn_frames = 60
    save_frequency = 30
    record_interval = 5
    scene_interval = 20
    try:
        # Mock vehicles
        blueprint = world.get_blueprint_library().find('vehicle.audi.a2')
        spawn_point = carla_map.get_spawn_points()[0]
        ego_vehicle = world.spawn_actor(blueprint, spawn_point)
        ego_vehicle.set_autopilot(True, traffic_manager.get_port())

        # Setup data collector
        map_reader = NaiveMapQuerier(world, carla_map, debug=True)
        scene_config = SceneConfig(scene_interval=scene_interval,
                                   record_interval=record_interval)
        data_collector = DataCollector(ego_vehicle,
                                       map_reader, [],
                                       scene_builder_cls=TESTSceneBuilder,
                                       scene_config=scene_config,
                                       save_frequency=save_frequency,
                                       n_burn_frames=n_burn_frames,
                                       debug=True)
        data_collector.start_sensor()
        assert data_collector.sensor_is_listening

        # Run simulation for X steps
        for idx in range(n_burn_frames + record_interval *
                         (save_frequency - 1)):
            frame = world.tick()
            data_collector.capture_step(frame)

    finally:
        if data_collector:
            data_collector.destroy()
        if ego_vehicle:
            ego_vehicle.destroy()
def scenario(scenario_params, variables, eval_env, eval_stg):
    ego_spawn_idx, other_spawn_ids, n_burn_interval, controls, \
            goal, carla_synchronous = scenario_params
    prediction_horizon, control_horizon, n_predictions, n_coincide = variables
    ego_vehicle = None
    agent = None
    other_vehicles = []
    client, world, carla_map, traffic_manager = carla_synchronous

    try:
        map_reader = NaiveMapQuerier(world, carla_map, debug=True)
        online_config = OnlineConfig(node_type=eval_env.NodeType)

        spawn_points = carla_map.get_spawn_points()
        spawn_point = spawn_points[ego_spawn_idx]
        blueprint = world.get_blueprint_library().find('vehicle.audi.a2')
        ego_vehicle = world.spawn_actor(blueprint, spawn_point)

        other_vehicle_ids = []
        blueprints = get_all_vehicle_blueprints(world)
        for idx in other_spawn_ids:
            blueprint = np.random.choice(blueprints)
            spawn_point = spawn_points[idx]
            other_vehicle = world.spawn_actor(blueprint, spawn_point)
            other_vehicle.set_autopilot(True, traffic_manager.get_port())
            other_vehicles.append(other_vehicle)
            other_vehicle_ids.append(other_vehicle.id)

        world.tick()
        agent = MidlevelAgent(ego_vehicle,
                              map_reader,
                              other_vehicle_ids,
                              eval_stg,
                              n_burn_interval=n_burn_interval,
                              control_horizon=control_horizon,
                              prediction_horizon=prediction_horizon,
                              n_predictions=n_predictions,
                              n_coincide=n_coincide,
                              scene_builder_cls=TrajectronPlusPlusSceneBuilder,
                              scene_config=online_config)
        agent.start_sensor()
        assert agent.sensor_is_listening
        if goal:
            agent.set_goal(goal.x, goal.y, is_relative=True)
        """Move the spectator to the ego vehicle.
        The positioning is a little off"""
        state = agent.get_vehicle_state()
        goal = agent.get_goal()
        world.get_spectator().set_transform(
            carla.Transform(
                carla.Location(x=state[0] + goal.x,
                               y=state[1] - goal.y,
                               z=state[2] + 50), carla.Rotation(pitch=-90)))

        n_burn_frames = n_burn_interval * online_config.record_interval
        control_frames = n_coincide * online_config.record_interval - 1
        for idx in range(n_burn_frames + control_frames):
            control = None
            for ctrl in controls:
                if ctrl.interval[0] <= idx and idx <= ctrl.interval[1]:
                    control = ctrl.control
                    break
            frame = world.tick()
            agent.run_step(frame, control=control)

    finally:
        if agent:
            agent.destroy()
        if ego_vehicle:
            ego_vehicle.destroy()
        for other_vehicle in other_vehicles:
            other_vehicle.destroy()

    time.sleep(1)
Esempio n. 5
0
def scenario(scenario_params, agent_constructor, ctrl_params,
             carla_synchronous, eval_env, eval_stg):
    ego_vehicle = None
    agent = None
    other_vehicles = []
    client, world, carla_map, traffic_manager = carla_synchronous

    try:
        map_reader = NaiveMapQuerier(world, carla_map, debug=True)
        online_config = OnlineConfig(node_type=eval_env.NodeType)

        # Mock vehicles
        spawn_points = carla_map.get_spawn_points()
        blueprints = get_all_vehicle_blueprints(world)
        spawn_indices = [scenario_params.ego_spawn_idx
                         ] + scenario_params.other_spawn_ids
        other_vehicle_ids = []
        for k, spawn_idx in enumerate(spawn_indices):
            if k == 0:
                blueprint = world.get_blueprint_library().find(
                    'vehicle.audi.a2')
            else:
                blueprint = np.random.choice(blueprints)
            spawn_point = spawn_points[spawn_idx]
            spawn_point = shift_spawn_point(carla_map, k,
                                            scenario_params.spawn_shifts,
                                            spawn_point)
            # Prevent collision with road.
            spawn_point.location += carla.Location(0, 0, 0.5)
            vehicle = world.spawn_actor(blueprint, spawn_point)
            if k == 0:
                ego_vehicle = vehicle
            else:
                vehicle.set_autopilot(True, traffic_manager.get_port())
                other_vehicles.append(vehicle)
                other_vehicle_ids.append(vehicle.id)

        world.tick()
        agent = agent_constructor(
            ego_vehicle,
            map_reader,
            other_vehicle_ids,
            eval_stg,
            n_burn_interval=scenario_params.n_burn_interval,
            control_horizon=ctrl_params.control_horizon,
            prediction_horizon=ctrl_params.prediction_horizon,
            n_predictions=ctrl_params.n_predictions,
            n_coincide=ctrl_params.n_coincide,
            scene_builder_cls=TrajectronPlusPlusSceneBuilder,
            log_agent=False,
            log_cplex=False,
            plot_scenario=True,
            plot_simulation=True,
            scene_config=online_config)
        agent.start_sensor()
        assert agent.sensor_is_listening
        if scenario_params.goal:
            agent.set_goal(scenario_params.goal.x,
                           scenario_params.goal.y,
                           is_relative=scenario_params.goal.is_relative)
        """Move the spectator to the ego vehicle.
        The positioning is a little off"""
        state = agent.get_vehicle_state()
        goal = agent.get_goal()
        if goal.is_relative:
            location = carla.Location(x=state[0] + goal.x,
                                      y=state[1] - goal.y,
                                      z=state[2] + 50)
        else:
            location = carla.Location(x=state[0] + (state[0] - goal.x) / 2.,
                                      y=state[1] - (state[1] + goal.y) / 2.,
                                      z=state[2] + 50)
        world.get_spectator().set_transform(
            carla.Transform(location, carla.Rotation(pitch=-90)))

        n_burn_frames = scenario_params.n_burn_interval * online_config.record_interval
        if scenario_params.loop_type == LoopEnum.CLOSED_LOOP:
            run_frames = scenario_params.run_interval * online_config.record_interval
        elif isinstance(agent, OAAgent):
            run_frames = ctrl_params.control_horizon * online_config.record_interval - 1
        else:
            run_frames = ctrl_params.n_coincide * online_config.record_interval - 1
        for idx in range(n_burn_frames + run_frames):
            control = None
            for ctrl in scenario_params.controls:
                if ctrl.interval[0] <= idx and idx <= ctrl.interval[1]:
                    control = ctrl.control
                    break
            frame = world.tick()
            agent.run_step(frame, control=control)

    finally:
        if agent:
            agent.destroy()
        if ego_vehicle:
            ego_vehicle.destroy()
        for other_vehicle in other_vehicles:
            other_vehicle.destroy()

    time.sleep(1)
def scenario(scenario_params, ctrl_params, carla_synchronous, eval_env,
             eval_stg):
    ego_vehicle = None
    agent = None
    spectator_camera = None
    other_vehicles = []
    record_spectator = False
    client, world, carla_map, traffic_manager = carla_synchronous

    try:
        map_reader = NaiveMapQuerier(world, carla_map, debug=True)
        online_config = OnlineConfig(record_interval=10,
                                     node_type=eval_env.NodeType)

        # Mock vehicles
        spawn_points = carla_map.get_spawn_points()
        blueprints = get_all_vehicle_blueprints(world)
        spawn_indices = [scenario_params.ego_spawn_idx
                         ] + scenario_params.other_spawn_ids
        other_vehicle_ids = []
        for k, spawn_idx in enumerate(spawn_indices):
            if k == 0:
                blueprint = world.get_blueprint_library().find(
                    'vehicle.audi.a2')
            else:
                blueprint = np.random.choice(blueprints)
            spawn_point = spawn_points[spawn_idx]
            spawn_point = shift_spawn_point(carla_map, k,
                                            scenario_params.spawn_shifts,
                                            spawn_point)
            # Prevent collision with road.
            spawn_point.location += carla.Location(0, 0, 0.5)
            vehicle = world.spawn_actor(blueprint, spawn_point)
            if k == 0:
                ego_vehicle = vehicle
            else:
                vehicle.set_autopilot(True, traffic_manager.get_port())
                if scenario_params.ignore_signs:
                    traffic_manager.ignore_signs_percentage(vehicle, 100.)
                if scenario_params.ignore_lights:
                    traffic_manager.ignore_lights_percentage(vehicle, 100.)
                if scenario_params.ignore_vehicles:
                    traffic_manager.ignore_vehicles_percentage(vehicle, 100.)
                if not scenario_params.auto_lane_change:
                    traffic_manager.auto_lane_change(vehicle, False)
                other_vehicles.append(vehicle)
                other_vehicle_ids.append(vehicle.id)

        frame = world.tick()
        agent = MidlevelAgent(
            ego_vehicle,
            map_reader,
            other_vehicle_ids,
            eval_stg,
            n_burn_interval=scenario_params.n_burn_interval,
            control_horizon=ctrl_params.control_horizon,
            prediction_horizon=ctrl_params.prediction_horizon,
            step_horizon=ctrl_params.step_horizon,
            n_predictions=ctrl_params.n_predictions,
            scene_builder_cls=TrajectronPlusPlusSceneBuilder,
            turn_choices=scenario_params.turn_choices,
            max_distance=scenario_params.max_distance,
            plot_boundary=False,
            log_agent=False,
            log_cplex=False,
            plot_scenario=True,
            plot_simulation=True,
            plot_overapprox=False,
            scene_config=online_config)
        agent.start_sensor()
        assert agent.sensor_is_listening
        """Move the spectator to the ego vehicle.
        The positioning is a little off"""
        state = agent.get_vehicle_state()
        goal = agent.get_goal()
        goal_x, goal_y = goal.x, -goal.y
        if goal.is_relative:
            location = carla.Location(x=state[0] + goal_x / 2.,
                                      y=state[1] - goal_y / 2.,
                                      z=state[2] + 50)
        else:
            location = carla.Location(x=(state[0] + goal_x) / 2.,
                                      y=(state[1] + goal_y) / 2.,
                                      z=state[2] + 50)
        # configure the spectator
        world.get_spectator().set_transform(
            carla.Transform(location,
                            carla.Rotation(pitch=-70, yaw=-90, roll=20)))
        record_spectator = False
        if record_spectator:
            # attach camera to spectator
            spectator_camera = attach_camera_to_spectator(world, frame)

        n_burn_frames = scenario_params.n_burn_interval * online_config.record_interval
        if ctrl_params.loop_type == LoopEnum.CLOSED_LOOP:
            run_frames = scenario_params.run_interval * online_config.record_interval
        else:
            run_frames = ctrl_params.control_horizon * online_config.record_interval - 1
        for idx in range(n_burn_frames + run_frames):
            control = None
            for ctrl in scenario_params.controls:
                if ctrl.interval[0] <= idx and idx <= ctrl.interval[1]:
                    control = ctrl.control
                    break
            frame = world.tick()
            agent.run_step(frame, control=control)

    finally:
        if spectator_camera:
            spectator_camera.destroy()
        if agent:
            agent.destroy()
        if ego_vehicle:
            ego_vehicle.destroy()
        for other_vehicle in other_vehicles:
            other_vehicle.destroy()

        if record_spectator == True:
            time.sleep(5)
        else:
            time.sleep(1)
Esempio n. 7
0
    def run(self):
        ego_vehicle = None
        agent = None
        spectator_camera = None
        other_vehicles = []
        record_spectator = False

        try:
            map_reader = NaiveMapQuerier(self.world,
                                         self.carla_map,
                                         debug=True)
            online_config = OnlineConfig(record_interval=10,
                                         node_type=self.eval_env.NodeType)

            # Mock vehicles
            spawn_points = self.carla_map.get_spawn_points()
            blueprints = get_all_vehicle_blueprints(self.world)
            spawn_indices = [self.scenario_params.ego_spawn_idx
                             ] + self.scenario_params.other_spawn_ids
            other_vehicle_ids = []
            for k, spawn_idx in enumerate(spawn_indices):
                if k == 0:
                    blueprint = self.world.get_blueprint_library().find(
                        'vehicle.audi.a2')
                else:
                    blueprint = np.random.choice(blueprints)
                spawn_point = spawn_points[spawn_idx]
                spawn_point = shift_spawn_point(
                    self.carla_map, k, self.scenario_params.spawn_shifts,
                    spawn_point)
                # Prevent collision with road.
                spawn_point.location += carla.Location(0, 0, 0.5)
                vehicle = self.world.spawn_actor(blueprint, spawn_point)
                if k == 0:
                    ego_vehicle = vehicle
                else:
                    vehicle.set_autopilot(True,
                                          self.traffic_manager.get_port())
                    if self.scenario_params.ignore_signs:
                        self.traffic_manager.ignore_signs_percentage(
                            vehicle, 100.)
                    if self.scenario_params.ignore_lights:
                        self.traffic_manager.ignore_lights_percentage(
                            vehicle, 100.)
                    if self.scenario_params.ignore_vehicles:
                        self.traffic_manager.ignore_vehicles_percentage(
                            vehicle, 100.)
                    if not self.scenario_params.auto_lane_change:
                        self.traffic_manager.auto_lane_change(vehicle, False)
                    other_vehicles.append(vehicle)
                    other_vehicle_ids.append(vehicle.id)

            frame = self.world.tick()
            agent = self.motion_planner_cls(
                ego_vehicle,
                map_reader,
                other_vehicle_ids,
                self.eval_stg,
                scene_builder_cls=self.scene_builder_cls,
                scene_config=online_config,
                **self.scenario_params,
                **self.ctrl_params,
                **self.DEBUG_SETTINGS,
            )
            agent.start_sensor()
            assert agent.sensor_is_listening
            """Setup vehicle routes"""
            if "CARLANAME" in os.environ and os.environ[
                    "CARLANAME"] == "carla-0.9.13":
                for k, vehicle in enumerate(other_vehicles):
                    route = None
                    try:
                        route = self.scenario_params.other_routes[k]
                        len(route)
                    except (TypeError, IndexError) as e:
                        continue
                    self.traffic_manager.set_route(vehicle, route)
            else:
                logging.info("Skipping setting up OV routes.")
            """Move the spectator to the ego vehicle.
            The positioning is a little off"""
            state = agent.get_vehicle_state()
            goal = agent.get_goal()
            goal_x, goal_y = goal.x, -goal.y
            if goal.is_relative:
                location = carla.Location(x=state[0] + goal_x / 2.,
                                          y=state[1] - goal_y / 2.,
                                          z=state[2] + 50)
            else:
                location = carla.Location(x=(state[0] + goal_x) / 2.,
                                          y=(state[1] + goal_y) / 2.,
                                          z=state[2] + 50)
            # configure the spectator
            self.world.get_spectator().set_transform(
                carla.Transform(location,
                                carla.Rotation(pitch=-70, yaw=-90, roll=20)))
            record_spectator = False
            if record_spectator:
                # attach camera to spectator
                spectator_camera = attach_camera_to_spectator(
                    self.world, frame)

            n_burn_frames = self.scenario_params.n_burn_interval * online_config.record_interval
            if self.ctrl_params.loop_type == LoopEnum.CLOSED_LOOP:
                run_frames = self.scenario_params.run_interval * online_config.record_interval
            else:
                run_frames = self.ctrl_params.control_horizon * online_config.record_interval - 1
            for idx in range(n_burn_frames + run_frames):
                control = None
                for ctrl in self.scenario_params.controls:
                    if ctrl.interval[0] <= idx and idx <= ctrl.interval[1]:
                        control = ctrl.control
                        break
                frame = self.world.tick()
                agent.run_step(frame, control=control)

        finally:
            if spectator_camera:
                spectator_camera.destroy()
            if agent:
                agent.destroy()
            if ego_vehicle:
                ego_vehicle.destroy()
            for other_vehicle in other_vehicles:
                other_vehicle.destroy()

            if record_spectator == True:
                time.sleep(5)
            else:
                time.sleep(1)
Esempio n. 8
0
def test_2_data_collectors(carla_Town03_synchronous):
    """Test case where NPCs move away from the EGO vehicle and disappear.
    """
    client, world, carla_map, traffic_manager = carla_Town03_synchronous
    vehicles = []
    data_collectors = []

    n_burn_frames = 40
    save_frequency = 40
    record_interval = 5
    scene_interval = 30
    try:
        # Mock vehicles
        spawn_points = carla_map.get_spawn_points()
        vehicle_ids = []
        blueprints = get_all_vehicle_blueprints(world)
        for idx in [7, 187, 122, 221]:
            blueprint = np.random.choice(blueprints)
            spawn_point = spawn_points[idx]
            vehicle = world.spawn_actor(blueprint, spawn_point)
            vehicle.set_autopilot(True, traffic_manager.get_port())
            vehicles.append(vehicle)
            vehicle_ids.append(vehicle.id)

        # Setup data collector
        map_reader = NaiveMapQuerier(world, carla_map, debug=True)
        scene_config = SceneConfig(scene_interval=scene_interval,
                                   record_interval=record_interval)
        data_collector = DataCollector(vehicles[0],
                                       map_reader,
                                       vehicle_ids[1:],
                                       scene_builder_cls=TESTSceneBuilder,
                                       scene_config=scene_config,
                                       save_frequency=save_frequency,
                                       n_burn_frames=n_burn_frames,
                                       debug=True)
        data_collector.start_sensor()
        data_collectors.append(data_collector)
        data_collector = DataCollector(vehicles[1],
                                       map_reader,
                                       vehicle_ids[:1] + vehicle_ids[2:],
                                       scene_builder_cls=TESTSceneBuilder,
                                       scene_config=scene_config,
                                       save_frequency=save_frequency,
                                       n_burn_frames=n_burn_frames,
                                       debug=True)
        data_collector.start_sensor()
        data_collectors.append(data_collector)

        # Run simulation for X steps
        for idx in range(n_burn_frames + record_interval *
                         (save_frequency - 1)):
            frame = world.tick()
            for data_collector in data_collectors:
                data_collector.capture_step(frame)

    finally:
        for data_collector in data_collectors:
            data_collector.destroy()
        for vehicle in vehicles:
            vehicle.destroy()
Esempio n. 9
0
    def run(self):
        ego_vehicle = None
        agent = None
        other_vehicles = []

        try:
            map_reader = NaiveMapQuerier(self.world,
                                         self.carla_map,
                                         debug=True)
            online_config = OnlineConfig(record_interval=10,
                                         node_type=self.eval_env.NodeType)

            # Mock vehicles
            spawn_points = self.carla_map.get_spawn_points()
            blueprints = get_all_vehicle_blueprints(self.world)
            spawn_indices = [self.scenario_params.ego_spawn_idx
                             ] + self.scenario_params.other_spawn_ids
            other_vehicle_ids = []
            for k, spawn_idx in enumerate(spawn_indices):
                if k == 0:
                    blueprint = self.world.get_blueprint_library().find(
                        'vehicle.audi.a2')
                else:
                    blueprint = np.random.choice(blueprints)
                spawn_point = spawn_points[spawn_idx]
                spawn_point = shift_spawn_point(
                    self.carla_map, k, self.scenario_params.spawn_shifts,
                    spawn_point)
                # Prevent collision with road.
                spawn_point.location += carla.Location(0, 0, 0.5)
                vehicle = self.world.spawn_actor(blueprint, spawn_point)
                if k == 0:
                    ego_vehicle = vehicle
                else:
                    other_vehicles.append(vehicle)
                    other_vehicle_ids.append(vehicle.id)
                vehicle.set_autopilot(True, self.traffic_manager.get_port())
                # if self.scenario_params.ignore_signs:
                #     self.traffic_manager.ignore_signs_percentage(vehicle, 100.)
                if self.scenario_params.ignore_lights:
                    self.traffic_manager.ignore_lights_percentage(
                        vehicle, 100.)
                # if self.scenario_params.ignore_vehicles:
                #     self.traffic_manager.ignore_vehicles_percentage(vehicle, 100.)
                if not self.scenario_params.auto_lane_change:
                    self.traffic_manager.auto_lane_change(vehicle, False)

            # Set up data collecting vehicle.
            frame = self.world.tick()
            agent = CapturingAgent(ego_vehicle,
                                   map_reader,
                                   other_vehicle_ids,
                                   self.eval_stg,
                                   scene_builder_cls=self.scene_builder_cls,
                                   scene_config=online_config,
                                   **self.scenario_params,
                                   **self.ctrl_params)
            agent.start_sensor()
            assert agent.sensor_is_listening

            # Set up autopilot routes
            for k, vehicle in enumerate([ego_vehicle] + other_vehicles):
                route = None
                try:
                    route = self.scenario_params.other_routes[k]
                    len(route)
                except (TypeError, IndexError):
                    continue
                try:
                    self.traffic_manager.set_route(vehicle, route)
                except AttributeError:
                    break

            locations = carlautil.to_locations_ndarray([ego_vehicle] +
                                                       other_vehicles)
            location = carlautil.ndarray_to_location(np.mean(locations,
                                                             axis=0))
            location += carla.Location(z=50)
            rotation = carla.Rotation(pitch=-90, yaw=0, roll=0)
            self.world.get_spectator().set_transform(
                carla.Transform(location, rotation))

            n_burn_frames = self.scenario_params.n_burn_interval * online_config.record_interval
            run_frames = self.scenario_params.run_interval * online_config.record_interval
            for idx in range(n_burn_frames + run_frames):
                frame = self.world.tick()
                agent.run_step(frame)

        finally:
            if agent:
                agent.destroy()
            if ego_vehicle:
                ego_vehicle.destroy()
            for other_vehicle in other_vehicles:
                other_vehicle.destroy()
            time.sleep(1)
Esempio n. 10
0
def scenario(scenario_params, agent_constructor, ctrl_params,
            carla_synchronous, eval_env):
    ego_vehicle = None
    agent = None
    client, world, carla_map, traffic_manager = carla_synchronous

    try:
        map_reader = NaiveMapQuerier(
                world, carla_map, debug=True)
        online_config = OnlineConfig(node_type=eval_env.NodeType)

        # Mock vehicles
        spawn_points = carla_map.get_spawn_points()
        blueprint = world.get_blueprint_library().find('vehicle.audi.a2')
        spawn_point = spawn_points[scenario_params.ego_spawn_idx]
        spawn_point = shift_spawn_point(carla_map,
                0, [scenario_params.spawn_shift], spawn_point)
        spawn_point.location += carla.Location(0, 0, 0.5)
        ego_vehicle = world.spawn_actor(blueprint, spawn_point)

        world.tick()
        agent = agent_constructor(
                ego_vehicle,
                map_reader,
                n_burn_interval=scenario_params.n_burn_interval,
                control_horizon=ctrl_params.control_horizon,
                step_horizon=ctrl_params.step_horizon,
                turn_choices=scenario_params.turn_choices,
                max_distance=scenario_params.max_distance,
                log_agent=False,
                log_cplex=False,
                plot_simulation=True,
                plot_boundary=False,
                road_boundary_constraints=True,
                scene_config=online_config)
        # if scenario_params.goal:
        #     agent.set_goal(scenario_params.goal.x, scenario_params.goal.y,
        #             is_relative=scenario_params.goal.is_relative)
        
        """Move the spectator to the ego vehicle.
        The positioning is a little off"""
        state = agent.get_vehicle_state()
        goal = agent.get_goal()
        goal_x, goal_y = goal.x, -goal.y
        if goal.is_relative:
            location = carla.Location(
                    x=state[0] + goal_x /2.,
                    y=state[1] - goal_y /2.,
                    z=state[2] + 50)
        else:
            location = carla.Location(
                    x=(state[0] + goal_x) /2.,
                    y=(state[1] + goal_y) /2.,
                    z=state[2] + 50)
        world.get_spectator().set_transform(
            carla.Transform(
                location,
                carla.Rotation(pitch=-90)
            )
        )

        n_burn_frames = scenario_params.n_burn_interval*online_config.record_interval
        if ctrl_params.loop_type == LoopEnum.CLOSED_LOOP:
            run_frames = scenario_params.run_interval*online_config.record_interval + 1
        else:
            run_frames = ctrl_params.control_horizon*online_config.record_interval + 1
        for idx in range(n_burn_frames + run_frames):
            control = None
            for ctrl in scenario_params.controls:
                if ctrl.interval[0] <= idx and idx <= ctrl.interval[1]:
                    control = ctrl.control
                    break
            frame = world.tick()
            agent.run_step(frame, control=control)
 
    finally:
        if agent:
            agent.destroy()
        if ego_vehicle:
            ego_vehicle.destroy()
    
    time.sleep(1)
def scenario(carla_synchronous, scenario_params):
    n_burn_frames, save_frequency, record_interval, scene_interval, \
            collector_spawn, npc_spawn, spawn_shifts = scenario_params
    client, world, carla_map, traffic_manager = carla_synchronous
    vehicles = []
    data_collectors = []
    env = Environment(node_type_list=['VEHICLE'],
                      standardization=standardization)
    scenes = []

    def add_scene(scene):
        scenes.append(scene)

    try:
        # Mock vehicles
        spawn_points = carla_map.get_spawn_points()
        blueprints = get_all_vehicle_blueprints(world)
        spawn_indices = collector_spawn + npc_spawn
        vehicle_ids = []
        for k, spawn_idx in enumerate(spawn_indices):
            blueprint = np.random.choice(blueprints)
            spawn_point = spawn_points[spawn_idx]
            spawn_point = shift_spawn_point(carla_map, k, spawn_shifts,
                                            spawn_point)
            # Prevent collision with road.
            spawn_point.location += carla.Location(0, 0, 0.5)
            # carlautil.debug_point(client, spawn_point.location, t=5.0)
            vehicle = world.spawn_actor(blueprint, spawn_point)
            vehicle.set_autopilot(True, traffic_manager.get_port())
            vehicles.append(vehicle)
            vehicle_ids.append(vehicle.id)

        # Setup data collector
        map_reader = NaiveMapQuerier(world, carla_map, debug=True)
        scene_config = SceneConfig(scene_interval=scene_interval,
                                   record_interval=record_interval,
                                   node_type=env.NodeType)
        n_data_collector = len(collector_spawn)
        for collector_idx in range(n_data_collector):
            other_vehicle_ids = vehicle_ids[:collector_idx] + vehicle_ids[
                collector_idx + 1:]
            data_collector = DataCollector(vehicles[collector_idx],
                                           map_reader,
                                           other_vehicle_ids,
                                           scene_builder_cls=TESTSceneBuilder,
                                           scene_config=scene_config,
                                           save_frequency=save_frequency,
                                           n_burn_frames=n_burn_frames,
                                           callback=add_scene,
                                           debug=True)
            data_collector.start_sensor()
            assert data_collector.sensor_is_listening
            data_collectors.append(data_collector)

        # Run simulation for X steps
        for idx in range(n_burn_frames + record_interval *
                         (save_frequency - 1)):
            frame = world.tick()
            for data_collector in data_collectors:
                data_collector.capture_step(frame)

        assert len(scenes) == n_data_collector
        for scene in scenes:
            plot_trajectron_scene('out', scene)

    finally:
        for data_collector in data_collectors:
            data_collector.destroy()
        for vehicle in vehicles:
            vehicle.destroy()
Esempio n. 12
0
def test_2_data_collectors(carla_Town03_synchronous):
    """Test case where NPCs move away from the EGO vehicle and disappear.
    """
    client, world, carla_map, traffic_manager = carla_Town03_synchronous
    vehicles = []
    data_collectors = []
    env = Environment(node_type_list=['VEHICLE'],
                      standardization=standardization)
    scenes = []

    def add_scene(scene):
        scenes.append(scene)

    n_burn_frames = 40
    save_frequency = 40
    record_interval = 5
    scene_interval = 30
    try:
        # Mock vehicles
        spawn_points = carla_map.get_spawn_points()
        vehicle_ids = []
        blueprints = get_all_vehicle_blueprints(world)
        for idx in [7, 187, 122, 221]:
            blueprint = np.random.choice(blueprints)
            spawn_point = spawn_points[idx]
            vehicle = world.spawn_actor(blueprint, spawn_point)
            vehicle.set_autopilot(True, traffic_manager.get_port())
            vehicles.append(vehicle)
            vehicle_ids.append(vehicle.id)

        # Setup data collector
        map_reader = NaiveMapQuerier(world, carla_map, debug=True)
        scene_config = SceneConfig(scene_interval=scene_interval,
                                   record_interval=record_interval)
        data_collector = DataCollector(vehicles[0],
                                       map_reader,
                                       vehicle_ids[1:],
                                       scene_builder_cls=TESTSceneBuilder,
                                       scene_config=scene_config,
                                       save_frequency=save_frequency,
                                       n_burn_frames=n_burn_frames,
                                       callback=add_scene,
                                       debug=True)
        data_collector.start_sensor()
        data_collectors.append(data_collector)
        data_collector = DataCollector(vehicles[1],
                                       map_reader,
                                       vehicle_ids[:1] + vehicle_ids[2:],
                                       scene_builder_cls=TESTSceneBuilder,
                                       scene_config=scene_config,
                                       save_frequency=save_frequency,
                                       n_burn_frames=n_burn_frames,
                                       callback=add_scene,
                                       debug=True)
        data_collector.start_sensor()
        data_collectors.append(data_collector)

        # Run simulation for X steps
        for idx in range(n_burn_frames + record_interval *
                         (save_frequency - 1)):
            frame = world.tick()
            for data_collector in data_collectors:
                data_collector.capture_step(frame)

        assert len(scenes) == 2
        for scene in scenes:
            fig, ax = plt.subplots(figsize=(15, 15))
            # extent = (scene.x_min, scene.x_max, scene.y_min, scene.y_max)
            ax.imshow(scene.map['VEHICLE'].as_image(), origin='lower')
            spectral = cm.nipy_spectral(np.linspace(0, 1, len(scene.nodes)))
            for idx, node in enumerate(scene.nodes):
                # using values from scene.map['VEHICLE'].homography
                # to scale points
                xy = 3 * node.data.data[:, :2]
                ax.scatter(xy[:, 0], xy[:, 1], color=spectral[idx])
            ax.set_xlabel('x')
            ax.set_ylabel('y')
            ax.set_aspect('equal')
            fig.tight_layout()
            fn = f"{ scene.name.replace('/', '_') }.png"
            fp = os.path.join('out', fn)
            fig.savefig(fp)

    finally:
        for data_collector in data_collectors:
            data_collector.destroy()
        for vehicle in vehicles:
            vehicle.destroy()
Esempio n. 13
0
def test_1_npc_appear(carla_Town03_synchronous):
    """Test case where NPC appears before EGO vehicle after awhile.
    """
    client, world, carla_map, traffic_manager = carla_Town03_synchronous
    ego_vehicle = None
    other_vehicles = []
    data_collector = None
    env = Environment(node_type_list=['VEHICLE'],
                      standardization=standardization)
    scenes = []

    def add_scene(scene):
        scenes.append(scene)

    n_burn_frames = 160
    save_frequency = 40
    record_interval = 5
    scene_interval = 30
    try:
        # Mock vehicles
        spawn_points = carla_map.get_spawn_points()
        blueprint = world.get_blueprint_library().find('vehicle.audi.a2')
        spawn_point = spawn_points[251]
        ego_vehicle = world.spawn_actor(blueprint, spawn_point)
        ego_vehicle.set_autopilot(True, traffic_manager.get_port())

        other_vehicle_ids = []
        blueprints = get_all_vehicle_blueprints(world)
        for idx in [164]:
            blueprint = np.random.choice(blueprints)
            spawn_point = spawn_points[idx]
            other_vehicle = world.spawn_actor(blueprint, spawn_point)
            other_vehicle.set_autopilot(True, traffic_manager.get_port())
            other_vehicles.append(other_vehicle)
            other_vehicle_ids.append(other_vehicle.id)

        # Setup data collector
        map_reader = NaiveMapQuerier(world, carla_map, debug=True)
        scene_config = SceneConfig(scene_interval=scene_interval,
                                   record_interval=record_interval)
        data_collector = DataCollector(ego_vehicle,
                                       map_reader,
                                       other_vehicle_ids,
                                       scene_builder_cls=TESTSceneBuilder,
                                       scene_config=scene_config,
                                       save_frequency=save_frequency,
                                       n_burn_frames=n_burn_frames,
                                       callback=add_scene,
                                       debug=True)
        data_collector.start_sensor()
        assert data_collector.sensor_is_listening

        # Run simulation for X steps
        for idx in range(n_burn_frames + record_interval *
                         (save_frequency - 1)):
            frame = world.tick()
            data_collector.capture_step(frame)

        assert len(scenes) == 1
        scene = scenes[0]
        fig, ax = plt.subplots(figsize=(15, 15))
        # extent = (scene.x_min, scene.x_max, scene.y_min, scene.y_max)
        ax.imshow(scene.map['VEHICLE'].as_image(), origin='lower')
        spectral = cm.nipy_spectral(np.linspace(0, 1, len(scene.nodes)))
        for idx, node in enumerate(scene.nodes):
            # using values from scene.map['VEHICLE'].homography
            # to scale points
            xy = 3 * node.data.data[:, :2]
            ax.scatter(xy[:, 0], xy[:, 1], color=spectral[idx])
        ax.set_xlabel('x')
        ax.set_ylabel('y')
        ax.set_aspect('equal')
        fig.tight_layout()
        fn = f"{ scene.name.replace('/', '_') }.png"
        fp = os.path.join('out', fn)
        fig.savefig(fp)

    finally:
        if data_collector:
            data_collector.destroy()
        if ego_vehicle:
            ego_vehicle.destroy()
        for other_vehicle in other_vehicles:
            other_vehicle.destroy()