def __init__(self,
blueprint=None,
ml_behavior=None,
observer=None,
evaluator=None,
step_time=None,
viewer=None,
scenario_generator=None,
render=False):
if blueprint is not None:
self._scenario_generator = blueprint._scenario_generation
self._viewer = blueprint._viewer
self._ml_behavior = blueprint._ml_behavior
self._step_time = blueprint._dt
self._evaluator = blueprint._evaluator
self._observer = blueprint._observer
Runtime.__init__(self,
step_time=step_time or self._step_time,
viewer=viewer or self._viewer,
scenario_generator=scenario_generator
or self._scenario_generator,
render=render)
self._ml_behavior = ml_behavior or self._ml_behavior
self._observer = observer or self._observer
self._evaluator = evaluator or self._evaluator
def GenerateRuntime():
# parameters
param_server = ParameterServer()
# configure both lanes of the highway. the right lane has one controlled agent
left_lane = CustomLaneCorridorConfig(params=param_server,
lane_corridor_id=0,
road_ids=[0, 1],
behavior_model=BehaviorMobilRuleBased(param_server),
s_min=5.,
s_max=50.)
right_lane = CustomLaneCorridorConfig(params=param_server,
lane_corridor_id=1,
road_ids=[0, 1],
controlled_ids=True,
behavior_model=BehaviorMobilRuleBased(param_server),
s_min=5.,
s_max=20.)
scenarios = \
ConfigWithEase(num_scenarios=3,
map_file_name=Data.xodr_data("DR_DEU_Merging_MT_v01_shifted"),
random_seed=0,
params=param_server,
lane_corridor_configs=[left_lane, right_lane])
# viewer
viewer = MPViewer(params=param_server,
x_range=[-35, 35],
y_range=[-35, 35],
follow_agent_id=True)
env = Runtime(step_time=0.2,
viewer=viewer,
scenario_generator=scenarios,
render=True,
maintain_world_history=True)
return env
# y_range=[-35, 35],
follow_agent_id=False)
sim_step_time = param_server["simulation"]["step_time",
"Step-time used in simulation",
0.05]
sim_real_time_factor = param_server["simulation"][
"real_time_factor", "execution in real-time or faster", 1.]
viewer = VideoRenderer(renderer=viewer,
world_step_time=sim_step_time,
fig_path="/tmp/video")
env = Runtime(step_time=0.2,
viewer=viewer,
scenario_generator=scenarios,
render=True,
maintain_world_history=True)
# Defining vehicles dynamics for RSS
# Input format:
# [longitudinal max acceleration, longitudinal max braking, longitudinal min acceleration,
# longitudinal min brake correct, lateral max acceleration, lateral min braking,
# lateral flucatuation_margin, agent response time]
#
# Detailed explanation please see:
# https://intel.github.io/ad-rss-lib/ad_rss/Appendix-ParameterDiscussion/#parameter-discussion
# Example of using RSS to evaluate the safety situation of the evaluating agent.
# The evaluating agent is defined with agent_id when initializing EvaluatorRSS.
sim_step_time = param_server["simulation"]["step_time",
"Step-time used in simulation",
0.05]
sim_real_time_factor = param_server["simulation"][
"real_time_factor",
"execution in real-time or faster",
0.5]
# viewer = VideoRenderer(renderer=viewer,
# world_step_time=sim_step_time,
# fig_path="/home/hart/Dokumente/2020/bark/video")
# gym like interface
env = Runtime(step_time=0.2,
viewer=viewer,
scenario_generator=scenarios,
render=True)
# run 3 scenarios
for episode in range(0, 1):
env.reset()
# step each scenario 20 times
for step in range(0, 70):
env.step()
time.sleep(sim_step_time/sim_real_time_factor)
# viewer.export_video(filename="/home/hart/Dokumente/2020/bark/video/video", remove_image_dir=False)
right_lane = CustomLaneCorridorConfig(
params=param_server,
lane_corridor_id=1,
road_ids=[0, 1],
controlled_ids=True,
behavior_model=BehaviorMobilRuleBased(param_server),
s_min=5.,
s_max=20.)
scenarios = \
ConfigWithEase(num_scenarios=3,
map_file_name="examples/data/DR_DEU_Merging_MT_v01_shifted.xodr",
random_seed=0,
params=param_server,
lane_corridor_configs=[left_lane, right_lane])
viewer = BufferedViewer()
env = Runtime(step_time=0.2,
viewer=viewer,
scenario_generator=scenarios,
render=True,
maintain_world_history=True)
# run BARKSCAPE
logger = logging.getLogger()
custom_stream = CustomStream(logger=logger)
bark_server = BaseServer(runner=BARKRunner,
runnable_object=env,
logger=logger,
stream=custom_stream)
bark_server.Start()
