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
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_centered"),
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=False)
sim_step_time = param_server["simulation"]["step_time",
"Step-time used in simulation",
0.05]
sim_real_time_factor = param_server["simulation"][
LaneCorridorConfig(
params=param_server,
source_pos=[3, -30],
sink_pos=[-30, 3],
behavior_model=BehaviorIntersectionRuleBased(param_server),
controlled_ids=True,
min_vel=5.,
max_vel=5.,
ds_min=5.,
ds_max=10.,
s_min=15.,
s_max=30.))
scenarios = \
ConfigWithEase(num_scenarios=3,
map_file_name=Data.xodr_data("threeway_intersection"),
random_seed=0,
params=param_server,
lane_corridor_configs=lane_corridors)
viewer = BufferedViewer()
env = Runtime(step_time=0.2,
viewer=viewer,
scenario_generator=scenarios,
render=True,
maintain_world_history=True)
# run BARKSCAPE
logger = logging.getLogger()
bark_server = BaseServer(runner=BARKRunner,
runnable_object=env,
from bark.runtime.scenario.scenario_generation.config_with_ease import \
LaneCorridorConfig, ConfigWithEase
from bark.runtime.runtime import Runtime
from bark.examples.paths import Data
from bark.core.models.behavior import *
try:
from bark.core.world.evaluation import EvaluatorRSS
except:
raise ImportError(
"This example requires building RSS, please run with \"bazel run //examples:highway_rss --define rss=true\""
)
# parameters
param_server = ParameterServer(
filename=Data.params_data("highway_merge_configurable"))
param_server["BehaviorLaneChangeRuleBased"]["MinVehicleRearDistance"] = 4.
param_server["BehaviorLaneChangeRuleBased"]["MinVehicleFrontDistance"] = 2.
param_server["BehaviorLaneChangeRuleBased"]["TimeKeepingGap"] = 0.
param_server["World"]["FracLateralOffset"] = 2.0
# param_server["Visualization"]["Evaluation"]["DrawRssDebugInfo"] = True
# param_server["Visualization"]["Evaluation"]["DrawRssSafetyResponses"] = True
param_server["Visualization"]["Evaluation"]["DrawEgoRSSSafetyResponses"] = True
# custom lane configuration that sets a different behavior model
# and sets the desired speed for the behavior
class HighwayLaneCorridorConfig(LaneCorridorConfig):
def __init__(self, params=None, **kwargs):
super().__init__(params=params, **kwargs)
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 = BufferedMPViewer(params=param_server)
sim_step_time = param_server["simulation"]["step_time",
"Step-time used in simulation", 0.2]
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="/Users/hart/2019/bark/video")
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
from bark.runtime.scenario.scenario_generation.interaction_dataset_scenario_generation import \
InteractionDatasetScenarioGeneration
from bark.runtime.commons.parameters import ParameterServer
from bark.runtime.viewer.matplotlib_viewer import MPViewer
from bark.runtime.viewer.video_renderer import VideoRenderer
from bark.examples.paths import Data
import os
import argparse
# set you json config that contains a map and matching tracks.
param_server = ParameterServer(
filename=Data.params_data("interaction_example"))
scenario_generation = InteractionDatasetScenarioGeneration(num_scenarios=1,
random_seed=0,
params=param_server)
viewer = MPViewer(params=param_server, use_world_bounds=True)
sim_step_time = param_server["simulation"]["step_time",
"Step-time used in simulation", 0.2]
sim_real_time_factor = param_server["simulation"][
"real_time_factor", "execution in real-time or faster", 1]
scenario = scenario_generation.create_scenarios(param_server, 1)[0]
world_state = scenario.GetWorldState()
sim_time_steps = param_server["simulation"]["simulation_time_steps",
# configure both lanes of the highway. the right lane has one controlled agent
left_lane = HighwayLaneCorridorConfig(params=param_server,
road_ids=[16],
lane_corridor_id=0)
right_lane = HighwayLaneCorridorConfig(params=param_server,
road_ids=[16],
lane_corridor_id=1,
controlled_ids=True)
# create 5 scenarios
scenarios = \
ConfigWithEase(
num_scenarios=5,
map_file_name=Data.xodr_data("city_highway_straight"),
random_seed=0,
params=param_server,
lane_corridor_configs=[left_lane, right_lane])
# viewer
viewer = MPViewer(params=param_server,
x_range=[-75, 75],
y_range=[-75, 75],
follow_agent_id=True)
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",
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
from bark.runtime.scenario.scenario_generation.interaction_dataset_scenario_generation import \
InteractionDatasetScenarioGeneration
from bark.runtime.commons.parameters import ParameterServer
from bark.runtime.viewer.matplotlib_viewer import MPViewer
from bark.runtime.viewer.video_renderer import VideoRenderer
from bark.examples.paths import Data
import os
import argparse
# set you json config that contains a map and matching tracks.
param_server = ParameterServer(filename=Data.params_data("interaction_example"))
scenario_generation = InteractionDatasetScenarioGeneration(num_scenarios=1,
random_seed=0,
params=param_server)
viewer = MPViewer(params=param_server, use_world_bounds=True)
sim_step_time = param_server["simulation"]["step_time",
"Step-time used in simulation",
0.2]
sim_real_time_factor = param_server["simulation"]["real_time_factor",
"execution in real-time or faster", 1]
scenario = scenario_generation.create_scenarios(param_server, 1)[0]
world_state = scenario.GetWorldState()
