def __setup_map_interface__(self):
params = ParameterServer()
# we are creating a dummy scenario to get the map interface from it
scenario = Scenario(map_file_name=self._map_filename,
json_params=params.ConvertToDict())
world = scenario.GetWorldState()
map_interface = world.map
return map_interface
def create_map_interface(map_file_name, road_ids):
params = ParameterServer()
# we are creating a dummy scenario to get the map interface from it
scenario = Scenario(map_file_name=map_file_name,
json_params=params.ConvertToDict())
world = scenario.GetWorldState()
map_interface = world.map
map_interface.GenerateRoadCorridor(road_ids, XodrDrivingDirection.forward)
return map_interface
def create_single_scenario(self):
scenario = Scenario(map_file_name=self._map_file_name,
json_params=self._params.ConvertToDict())
world = scenario.GetWorldState()
collected_sources_sinks_agent_states_geometries = []
collected_sources_sinks_default_param_configs = []
# Loop through each source sink config and first only create state
# and geometry information
road_corridors = []
kwargs_agent_states_geometry = []
sink_source_default_params = []
for idx, sink_source_config in enumerate(self._sinks_sources):
road_corridor = self.get_road_corridor_from_source_sink(sink_source_config, world.map)
road_corridors.append(road_corridor)
#1) create agent states and geometries for this source
args = [road_corridor]
agent_states, agent_geometries, kwargs_dict, default_params_state_geometry = \
self.eval_configuration( sink_source_config, "ConfigAgentStatesGeometries",
args, {})
kwargs_agent_states_geometry.append(kwargs_dict)
# collect default parameters of this config
sink_source_default_params.append(sink_source_config)
sink_source_default_params[idx]["ConfigAgentStatesGeometries"] = default_params_state_geometry.ConvertToDict()
collected_sources_sinks_agent_states_geometries.append((agent_states, agent_geometries))
#2 remove overlapping agent states from different sources and sinks
collected_sources_sinks_agent_states_geometries = \
self.resolve_overlaps_in_sources_sinks_agents(collected_sources_sinks_agent_states_geometries)
agent_list = []
controlled_agent_ids_all = []
for idx, agent_states_geometries in enumerate(
collected_sources_sinks_agent_states_geometries):
sink_source_config = self._sinks_sources[idx]
agent_states = agent_states_geometries[0]
agent_geometries = agent_states_geometries[1]
road_corridor = road_corridors[idx]
if(len(agent_states)== 0):
continue
#3) create behavior, execution and dynamic models
args_list = [road_corridor, agent_states ]
kwargs_dict = {**kwargs_agent_states_geometry[idx]}
config_return, kwargs_dict_tmp, default_params_behavior = \
self.eval_configuration(
sink_source_config, "ConfigBehaviorModels",
args_list, kwargs_dict)
behavior_models = config_return
sink_source_default_params[idx]["ConfigBehaviorModels"] = default_params_behavior.ConvertToDict()
kwargs_dict = {**kwargs_dict, **kwargs_dict_tmp}
config_return, kwargs_dict_tmp, default_params_execution = \
self.eval_configuration(
sink_source_config, "ConfigExecutionModels",
args_list, kwargs_dict)
execution_models = config_return
sink_source_default_params[idx]["ConfigExecutionModels"] = default_params_execution.ConvertToDict()
kwargs_dict = {**kwargs_dict, **kwargs_dict_tmp}
config_return, kwargs_dict_tmp, default_params_dynamic = \
self.eval_configuration(
sink_source_config, "ConfigDynamicModels",
args_list, kwargs_dict)
dynamic_models = config_return
sink_source_default_params[idx]["ConfigDynamicModels"] = default_params_dynamic.ConvertToDict()
kwargs_dict = {**kwargs_dict, **kwargs_dict_tmp}
#4 create goal definitions and controlled agents
config_return, kwargs_dict_tmp, default_params_controlled_agents = \
self.eval_configuration(
sink_source_config, "ConfigControlledAgents",
args_list, kwargs_dict)
controlled_agent_ids = config_return
controlled_agent_ids_all.extend(controlled_agent_ids)
sink_source_default_params[idx]["ConfigControlledAgents"] = default_params_controlled_agents.ConvertToDict()
kwargs_dict = {**kwargs_dict, **kwargs_dict_tmp}
args_list = [*args_list, controlled_agent_ids]
config_return, kwargs_dict_tmp, default_params_goals = \
self.eval_configuration(
sink_source_config, "ConfigGoalDefinitions",
args_list, kwargs_dict)
goal_definitions = config_return
sink_source_default_params[idx]["ConfigGoalDefinitions"] = default_params_goals.ConvertToDict()
#5 Build all agents for this source config
kwargs_dict = {**kwargs_dict, **kwargs_dict_tmp}
agent_params = ParameterServer(json = sink_source_config["AgentParams"])
sink_source_agents, controlled_ids = self.create_source_config_agents(agent_states,
agent_geometries, behavior_models, execution_models,
dynamic_models, goal_definitions, controlled_agent_ids,
world, agent_params)
sink_source_default_params[idx]["AgentParams"] = agent_params.ConvertToDict()
self.update_road_corridors(sink_source_agents, road_corridor)
agent_list.extend(sink_source_agents)
collected_sources_sinks_default_param_configs.append(sink_source_config)
self._sink_source_default_params = sink_source_default_params
scenario._eval_agent_ids = controlled_ids
scenario._agent_list = agent_list
return scenario
