def create_source_config_agents(self, agent_states, agent_geometries,
behavior_models, execution_models,
dynamic_models, goal_definitions,
controlled_agent_ids, world, agent_params,
**kwargs):
num_agents = len(agent_states)
if any(
len(lst) != num_agents for lst in [
agent_geometries, behavior_models, execution_models,
dynamic_models, goal_definitions, controlled_agent_ids
]):
raise ValueError(
"Config readers did not return equal sized of lists")
agents = []
controlled_ids = []
for idx, agent_state in enumerate(agent_states):
bark_agent = Agent(np.array(agent_state), behavior_models[idx],
dynamic_models[idx], execution_models[idx],
agent_geometries[idx], agent_params,
goal_definitions[idx], world.map)
if "agent_ids" in kwargs:
bark_agent.SetAgentId(kwargs["agent_ids"][idx])
if controlled_agent_ids[idx]:
controlled_ids.append(kwargs["agent_ids"][idx])
else:
bark_agent.SetAgentId(idx)
if controlled_agent_ids[idx]:
controlled_ids.append(idx)
agents.append(bark_agent)
return agents, controlled_ids
def AgentFromTrackfile(self, track_params, param_server,
scenario_track_info, agent_id):
if scenario_track_info.GetEgoTrackInfo().GetTrackId() == agent_id:
agent_track_info = scenario_track_info.GetEgoTrackInfo()
elif agent_id in scenario_track_info.GetOtherTrackInfos().keys():
agent_track_info = scenario_track_info.GetOtherTrackInfos(
)[agent_id]
else:
raise ValueError("unknown agent id {}".format(agent_id))
fname = agent_track_info.GetFileName() # track_params["filename"]
track_id = agent_track_info.GetTrackId() # track_params["track_id"]
agent_id = agent_track_info.GetTrackId()
track = self.TrackFromTrackfile(fname, track_id)
start_time = scenario_track_info.GetStartTs()
end_time = scenario_track_info.GetEndTs()
behavior_model = track_params["behavior_model"]
model_converter = ModelJsonConversion()
if behavior_model is None:
# each agent need's its own param server
behavior = BehaviorFromTrack(
track, param_server.AddChild("agent{}".format(agent_id)),
start_time, end_time)
else:
behavior = behavior_model
try:
initial_state = InitStateFromTrack(track, start_time)
except:
raise ValueError(
"Could not retrieve initial state of agent {} at t={}.".format(
agent_id, start_time))
try:
dynamic_model = model_converter.convert_model(
track_params["dynamic_model"], param_server)
except:
raise ValueError("Could not create dynamic_model")
try:
execution_model = model_converter.convert_model(
track_params["execution_model"], param_server)
except:
raise ValueError("Could not retrieve execution_model")
try:
vehicle_shape = ShapeFromTrack(
track, param_server["DynamicModel"]["wheel_base", "Wheel base",
2.7])
except:
raise ValueError("Could not create vehicle_shape")
bark_agent = Agent(initial_state, behavior, dynamic_model,
execution_model, vehicle_shape,
param_server.AddChild("agent{}".format(agent_id)),
GoalDefinitionFromTrack(track, end_time),
track_params["map_interface"])
# set agent id from track
bark_agent.SetAgentId(track_id)
return bark_agent
def AgentFromTrackfile(self, track_params, param_server,
scenario_track_info, agent_id, goal_def):
if scenario_track_info.GetEgoTrackInfo().GetTrackId() == agent_id:
agent_track_info = scenario_track_info.GetEgoTrackInfo()
elif agent_id in scenario_track_info.GetOtherTrackInfos().keys():
agent_track_info = scenario_track_info.GetOtherTrackInfos(
)[agent_id]
else:
raise ValueError("unknown agent id {}".format(agent_id))
fname = agent_track_info.GetFileName() # track_params["filename"]
track_id = agent_track_info.GetTrackId() # track_params["track_id"]
agent_id = agent_track_info.GetTrackId()
track = self.TrackFromTrackfile(fname, track_id)
xy_offset = scenario_track_info.GetXYOffset()
# create behavior model from track, we use start time of scenario here
start_time = scenario_track_info.GetStartTimeMs()
end_time = scenario_track_info.GetEndTimeMs()
behavior_model = track_params["behavior_model"]
model_converter = ModelJsonConversion()
if behavior_model is None:
# each agent need's its own param server
behavior = BehaviorFromTrack(
track, param_server.AddChild("agent{}".format(agent_id)),
xy_offset, start_time, end_time)
else:
behavior = behavior_model
# retrieve initial state of valid agent
if agent_id in scenario_track_info._other_agents_track_infos:
start_time_init_state = max(
scenario_track_info._other_agents_track_infos[agent_id].
GetStartTimeMs(), start_time)
else:
start_time_init_state = start_time
try:
initial_state = InitStateFromTrack(track, xy_offset,
start_time_init_state)
except:
raise ValueError(
"Could not retrieve initial state of agent {} at t={}.".format(
agent_id, start_time_init_state))
if self._use_shape_from_track:
wb = WheelbaseFromTrack(track)
crad = ColRadiusFromTrack(track)
else:
wb = self._wb
crad = self._crad
param_server["DynamicModel"]["wheel_base"] = wb
try:
dynamic_model = model_converter.convert_model(
track_params["dynamic_model"], param_server)
except:
raise ValueError("Could not create dynamic_model")
try:
execution_model = model_converter.convert_model(
track_params["execution_model"], param_server)
except:
raise ValueError("Could not retrieve execution_model")
try:
if self._use_rectangle_shape:
vehicle_shape = GenerateCarRectangle(wb, crad)
else:
vehicle_shape = GenerateCarLimousine(wb, crad)
except:
raise ValueError("Could not create vehicle_shape")
if goal_def is None:
goal_def = GoalDefinitionFromTrack(track,
end_time,
xy_offset=xy_offset)
bark_agent = Agent(initial_state, behavior, dynamic_model,
execution_model, vehicle_shape,
param_server.AddChild("agent{}".format(agent_id)),
goal_def, track_params["map_interface"])
# set agent id from track
bark_agent.SetAgentId(track_id)
return bark_agent
