def create_from_config(self, config_param_object, road_corridor):
track_file_name = config_param_object["TrackFilename", "Path to track file (csv)",
"bark/runtime/tests/data/interaction_dataset_dummy_track.csv"]
track_ids = config_param_object["TrackIds", "IDs of the vehicle tracks to import.", [1]]
start_time = config_param_object["StartTs", "Timestamp when to start the scenario (ms)", 0]
end_time = config_param_object["EndTs","Timestamp when to end the scenario (ms)", None]
wheel_base = config_param_object["WheelBase", "Wheelbase assumed for shape calculation", 2.7]
agent_geometries = []
agent_states = []
lane_positions = []
tracks = []
for track_id in track_ids:
tracks_read = dataset_reader.read_tracks(track_file_name)
track = tracks_read[track_id]
if start_time is None:
start_time = track.time_stamp_ms_first
if end_time is None:
end_time = track.time_stamp_ms_last
numpy_state = InitStateFromTrack(track, start_time)
agent_state = numpy_state.reshape(5).tolist()
agent_states.append(agent_state)
shape = ShapeFromTrack(track, wheel_base)
agent_geometries.append(shape)
tracks.append(track)
lane_positions_agent = self.find_lane_positions(numpy_state, road_corridor)
lane_positions.append(lane_positions_agent)
assert(len(agent_states) == len(agent_geometries))
return agent_states, agent_geometries, {"track_ids": track_ids, "tracks" : tracks, \
"agent_ids" : track_ids, "start_time" : start_time, "end_time" : end_time, \
"agent_lane_positions" : lane_positions}, config_param_object
def get_init_state(self, track, start_time):
return InitStateFromTrack(track, start_time)