def __init__(self):
self.carla_server = None
self.carla_client = None
self.carla_controller = None
self.bark_viewer = None
self.cosimulation_viewer = None
self.launch_args = ["external/carla/CarlaUE4.sh", "-quality-level=Low"]
# Bark parameter server
self.param_server = ParameterServer(
filename=BARK_PATH +
"examples/params/od8_const_vel_one_agent.json")
# World Definition
self.bark_world = World(self.param_server)
# Model Definitions
self.behavior_model = BehaviorIDMClassic(self.param_server)
self.execution_model = ExecutionModelInterpolate(self.param_server)
self.dynamic_model = SingleTrackModel(self.param_server)
# Map Definition
xodr_parser = XodrParser(BARK_PATH + "modules/runtime/tests/data/" +
BARK_MAP + ".xodr")
self.map_interface = MapInterface()
self.map_interface.SetOpenDriveMap(xodr_parser.map)
self.bark_world.SetMap(self.map_interface)
# Bark agent definition
self.agent_2d_shape = CarLimousine()
# use for converting carla actor id to bark agent id
self.carla_2_bark_id = dict()
# store the camera id attached to an agent
self.carla_agents_cam = dict()
def test_one_agent_at_goal_state_limits(self):
param_server = ParameterServer()
# Model Definition
behavior_model = BehaviorConstantVelocity(param_server)
execution_model = ExecutionModelInterpolate(param_server)
dynamic_model = SingleTrackModel(param_server)
# Agent Definition
agent_2d_shape = CarLimousine()
init_state = np.array(
[0, -191.789, -50.1725, 3.14 * 3.0 / 4.0, 150 / 3.6])
agent_params = param_server.AddChild("agent1")
goal_polygon = Polygon2d(
[0, 0, 0],
[Point2d(-1, -1),
Point2d(-1, 1),
Point2d(1, 1),
Point2d(1, -1)])
goal_polygon = goal_polygon.Translate(Point2d(-191.789, -50.1725))
agent = Agent(
init_state, behavior_model, dynamic_model, execution_model,
agent_2d_shape, agent_params,
GoalDefinitionStateLimits(
goal_polygon,
(3.14 * 3.0 / 4.0 - 0.08, 3.14 * 3.0 / 4.0 + 0.08)), None)
world = World(param_server)
world.AddAgent(agent)
evaluator = EvaluatorGoalReached(agent.id)
world.AddEvaluator("success", evaluator)
info = world.Evaluate()
self.assertEqual(info["success"], True)
def test_dr_deu_merging(self):
# threeway_intersection
xodr_parser = XodrParser(
"modules/runtime/tests/data/DR_DEU_Merging_MT_v01_shifted.xodr")
# World Definition
params = ParameterServer()
world = World(params)
map_interface = MapInterface()
map_interface.SetOpenDriveMap(xodr_parser.map)
world.SetMap(map_interface)
roads = [0, 1]
driving_direction = XodrDrivingDirection.forward
map_interface.GenerateRoadCorridor(roads, driving_direction)
road_corridor = map_interface.GetRoadCorridor(roads, driving_direction)
# Draw map
viewer = MPViewer(params=params, use_world_bounds=True)
viewer.drawWorld(world)
viewer.drawPolygon2d(road_corridor.lane_corridors[0].polygon,
color="blue",
alpha=0.5)
viewer.drawPolygon2d(road_corridor.lane_corridors[1].polygon,
color="blue",
alpha=0.5)
viewer.show(block=False)
self.assertTrue(road_corridor.lane_corridors[0].polygon.Valid())
self.assertTrue(road_corridor.lane_corridors[1].polygon.Valid())
self.assertTrue(road_corridor.polygon.Valid())
def test_road_corridor_forward(self):
xodr_parser = XodrParser(
"modules/runtime/tests/data/road_corridor_test.xodr")
# World Definition
params = ParameterServer()
world = World(params)
map_interface = MapInterface()
map_interface.SetOpenDriveMap(xodr_parser.map)
world.SetMap(map_interface)
open_drive_map = world.map.GetOpenDriveMap()
viewer = MPViewer(params=params, use_world_bounds=True)
# Draw map
viewer.drawWorld(world)
viewer.show(block=False)
# Generate RoadCorridor
roads = [0, 1, 2]
driving_direction = XodrDrivingDirection.forward
map_interface.GenerateRoadCorridor(roads, driving_direction)
road_corridor = map_interface.GetRoadCorridor(roads, driving_direction)
# Assert road corridor
# Assert: 3 roads
self.assertEqual(len(road_corridor.roads), 3)
# Assert: road1: 2 lanes, road2: 1 lane, road3: 1 lane
self.assertEqual(len(road_corridor.GetRoad(0).lanes), 3)
self.assertEqual(len(road_corridor.GetRoad(1).lanes), 2)
self.assertEqual(len(road_corridor.GetRoad(2).lanes), 3)
# Assert: next road
self.assertEqual(road_corridor.GetRoad(0).next_road.road_id, 1)
self.assertEqual(road_corridor.GetRoad(1).next_road.road_id, 2)
# Assert: lane links
self.assertEqual(
road_corridor.GetRoad(0).GetLane(3).next_lane.lane_id, 5)
self.assertEqual(
road_corridor.GetRoad(1).GetLane(5).next_lane.lane_id, 8)
# Assert: LaneCorridor
self.assertEqual(len(road_corridor.lane_corridors), 3)
colors = ["blue", "red", "green"]
count = 0
for lane_corridor in road_corridor.lane_corridors:
viewer.drawPolygon2d(lane_corridor.polygon,
color=colors[count],
alpha=0.5)
viewer.drawLine2d(lane_corridor.left_boundary, color="red")
viewer.drawLine2d(lane_corridor.right_boundary, color="blue")
viewer.drawLine2d(lane_corridor.center_line, color="black")
viewer.show(block=False)
plt.pause(2.)
count += 1
def _build_world_state(self):
param_server = ParameterServer(json=self._json_params)
world = World(param_server)
if self._map_interface is None:
world = self.setup_map(world, self._map_file_name)
else:
world.SetMap(self._map_interface)
for agent in self._agent_list:
agent.GenerateRoadCorridor(self._map_interface)
world.AddAgent(agent)
return world
def test_between_lanes(self):
xodr_parser = XodrParser(
"modules/runtime/tests/data/city_highway_straight.xodr")
np.set_printoptions(precision=8)
params = ParameterServer()
world = World(params)
map_interface = MapInterface()
map_interface.SetOpenDriveMap(xodr_parser.map)
world.SetMap(map_interface)
# Simple test
point_close = Point2d(5114.68262, 5086.44971)
lane_sw = map_interface.FindLane(point_close)
self.assertIsNotNone(
lane_sw,
"This point is still in the left lane! XodrLane boundary is 5114.683"
)
switched_lane = False
lng_coord = 5086.44971
i = 5114.5
lane_sw = map_interface.FindLane(Point2d(i, lng_coord))
assert lane_sw != None
prev = lane_sw.lane_id
prev_i = i
while (i < 5117.5):
lane_sw = map_interface.FindLane(Point2d(i, lng_coord))
self.assertIsNotNone(
lane_sw,
"Should always be on at least one lane! Currently at ({}, {})".
format(i, lng_coord))
if prev != lane_sw.lane_id:
# print(prev)
# print(prev_i)
# print(lane_sw.lane_id)
# print(i)
self.assertFalse(switched_lane,
"XodrLane switch should only happens once!")
switched_lane = True
prev_i = i
prev = lane_sw.lane_id
i = i + 0.01
self.assertTrue(switched_lane,
"Eventually should have switched lanes!")
def test_two_roads_one_lane(self):
xodr_map = MakeXodrMapOneRoadTwoLanes()
# World Definition
params = ParameterServer()
world = World(params)
map_interface = MapInterface()
map_interface.SetOpenDriveMap(xodr_map)
world.SetMap(map_interface)
open_drive_map = world.map.GetOpenDriveMap()
viewer = MPViewer(params=params, use_world_bounds=True)
# Draw map
viewer.drawWorld(world)
viewer.show(block=False)
# Generate RoadCorridor
roads = [100]
driving_direction = XodrDrivingDirection.forward
map_interface.GenerateRoadCorridor(roads, driving_direction)
road_corridor = map_interface.GetRoadCorridor(roads, driving_direction)
# Assert road corridor
# Assert: 1 road
self.assertEqual(len(road_corridor.roads), 1)
# Assert: road1: 2 lanes
self.assertEqual(len(road_corridor.GetRoad(roads[0]).lanes), 3)
colors = ["blue", "red", "green"]
count = 0
for lane_corridor in road_corridor.lane_corridors:
viewer.drawPolygon2d(lane_corridor.polygon,
color=colors[count],
alpha=0.5)
viewer.drawLine2d(lane_corridor.left_boundary, color="red")
viewer.drawLine2d(lane_corridor.right_boundary, color="blue")
viewer.drawLine2d(lane_corridor.center_line, color="black")
viewer.show(block=False)
plt.pause(2.)
count += 1
viewer.show(block=True)
def test_road_corridor_intersection(self):
xodr_parser = XodrParser(
"modules/runtime/tests/data/road_corridor_test.xodr")
# World Definition
params = ParameterServer()
world = World(params)
map_interface = MapInterface()
map_interface.SetOpenDriveMap(xodr_parser.map)
world.SetMap(map_interface)
open_drive_map = world.map.GetOpenDriveMap()
viewer = MPViewer(params=params, use_world_bounds=True)
# Draw map
viewer.drawWorld(world)
viewer.show(block=False)
# Generate RoadCorridor
roads = [0, 1, 2]
driving_direction = XodrDrivingDirection.forward
map_interface.GenerateRoadCorridor(roads, driving_direction)
road_corridor = map_interface.GetRoadCorridor(roads, driving_direction)
colors = ["blue", "red", "green", "yellow"]
count = 0
for road_id, road in road_corridor.roads.items():
for lane_id, lane in road.lanes.items():
print(road_id, lane_id, lane.driving_direction)
for lane_corridor in road_corridor.lane_corridors:
viewer.drawPolygon2d(lane_corridor.polygon,
color=colors[count],
alpha=0.5)
viewer.drawLine2d(lane_corridor.left_boundary, color="red")
viewer.drawLine2d(lane_corridor.right_boundary, color="blue")
viewer.drawLine2d(lane_corridor.center_line, color="black")
viewer.show(block=False)
plt.pause(0.5)
count += 1
viewer.show(block=True)
def test_Crossing8Course(self):
xodr_parser = XodrParser(
"modules/runtime/tests/data/Crossing8Course.xodr")
params = ParameterServer()
world = World(params)
map_interface = MapInterface()
map_interface.SetOpenDriveMap(xodr_parser.map)
world.SetMap(map_interface)
start_point = Point2d(0, -11)
lanes_near_start = map_interface.find_nearest_lanes(start_point, 1)
assert (len(lanes_near_start) == 1)
goal_point = Point2d(-191.789, -50.1725)
lanes_near_goal = map_interface.find_nearest_lanes(goal_point, 1)
assert (len(lanes_near_goal) == 1)
time.sleep(
2
) # if this is not here, the second unit test is not executed (maybe parsing takes too long?)
def test_world(self):
# create agent
params = ParameterServer()
behavior = BehaviorConstantVelocity(params)
execution = ExecutionModelInterpolate(params)
dynamic = SingleTrackModel(params)
shape = Polygon2d([1.25, 1, 0], [
Point2d(0, 0),
Point2d(0, 2),
Point2d(4, 2),
Point2d(4, 0),
Point2d(0, 0)
])
init_state = np.array([0, 0, 0, 0, 5])
agent = Agent(init_state, behavior, dynamic, execution, shape,
params.AddChild("agent"))
road_map = OpenDriveMap()
newXodrRoad = XodrRoad()
newXodrRoad.id = 1
newXodrRoad.name = "Autobahn A9"
newPlanView = PlanView()
newPlanView.AddLine(Point2d(0, 0), 1.57079632679, 10)
newXodrRoad.plan_view = newPlanView
line = newXodrRoad.plan_view.GetReferenceLine().ToArray()
p = Point2d(line[-1][0], line[-1][1])
newXodrRoad.plan_view.AddSpiral(p, 1.57079632679, 50.0, 0.0, 0.3, 0.4)
line = newXodrRoad.plan_view.GetReferenceLine()
lane_section = XodrLaneSection(0)
lane = XodrLane()
lane.line = line
lane_section.AddLane(lane)
newXodrRoad.AddLaneSection(lane_section)
road_map.AddRoad(newXodrRoad)
r = Roadgraph()
map_interface = MapInterface()
map_interface.SetOpenDriveMap(road_map)
map_interface.SetRoadgraph(r)
world = World(params)
world.AddAgent(agent)
def test_find_lane(self):
xodr_parser = XodrParser("modules/runtime/tests/data/urban_road.xodr")
params = ParameterServer()
world = World(params)
map_interface = MapInterface()
map_interface.SetOpenDriveMap(xodr_parser.map)
world.SetMap(map_interface)
lane_sw = map_interface.FindLane(Point2d(46, 180))
assert lane_sw.lane_type == XodrLaneType.sidewalk
lane_rl = map_interface.FindLane(Point2d(52, 130))
assert lane_rl.lane_type == XodrLaneType.driving
lane_no_lane = map_interface.FindLane(Point2d(120, 140))
assert lane_no_lane == None
xodr_parser = XodrParser(
"modules/runtime/tests/data/city_highway_straight.xodr")
np.set_printoptions(precision=8)
params = ParameterServer()
world = World(params)
map_interface = MapInterface()
map_interface.SetOpenDriveMap(xodr_parser.map)
world.SetMap(map_interface)
point = Point2d(5114, 5072)
viewer = MPViewer(params=params, use_world_bounds=True)
viewer.drawWorld(world)
viewer.drawPoint2d(point, 'red', 1.0)
viewer.show(block=True)
time.sleep(0.1)
lane_sw = map_interface.FindLane(point)
self.assertIsNotNone(lane_sw, "This point is clearly on a lane!")
def test_lane_change(self):
# World Definition
params = ParameterServer()
world = World(params)
# Model Definitions
behavior_model = BehaviorMobil(params)
execution_model = ExecutionModelInterpolate(params)
dynamic_model = SingleTrackModel(params)
behavior_model2 = BehaviorIDMLaneTracking(params)
execution_model2 = ExecutionModelInterpolate(params)
dynamic_model2 = SingleTrackModel(params)
# Map Definition
map_interface = MapInterface()
xodr_map = MakeXodrMapOneRoadTwoLanes()
map_interface.SetOpenDriveMap(xodr_map)
world.SetMap(map_interface)
#agent_2d_shape = CarLimousine()
agent_2d_shape = CarRectangle()
init_state = np.array([0, 3, -1.75, 0, 5])
agent_params = params.AddChild("agent1")
goal_polygon = Polygon2d(
[1, 1, 0],
[Point2d(0, 0),
Point2d(0, 2),
Point2d(2, 2),
Point2d(2, 0)])
goal_polygon = goal_polygon.Translate(Point2d(50, -2))
agent = Agent(init_state, behavior_model, dynamic_model,
execution_model, agent_2d_shape, agent_params,
GoalDefinitionPolygon(goal_polygon), map_interface)
world.AddAgent(agent)
init_state2 = np.array([0, 15, -1.75, 0, 2])
agent2 = Agent(init_state2, behavior_model2, dynamic_model2,
execution_model2, agent_2d_shape, agent_params,
GoalDefinitionPolygon(goal_polygon), map_interface)
world.AddAgent(agent2)
# viewer
viewer = MPViewer(params=params, use_world_bounds=True)
# World Simulation
sim_step_time = params["simulation"]["step_time",
"Step-time in simulation", 0.05]
sim_real_time_factor = params["simulation"][
"real_time_factor", "execution in real-time or faster", 100]
# Draw map
for _ in range(0, 10):
viewer.clear()
world.Step(sim_step_time)
viewer.drawWorld(world)
viewer.show(block=False)
time.sleep(sim_step_time / sim_real_time_factor)
def test_two_roads_one_lane(self):
params = ParameterServer()
world = World(params)
xodr_map = MakeXodrMapOneRoadTwoLanes()
map_interface = MapInterface()
map_interface.SetOpenDriveMap(xodr_map)
world.SetMap(map_interface)
start_point = Point2d(0, -11)
lanes_near_start = map_interface.find_nearest_lanes(start_point, 1)
assert(len(lanes_near_start) == 1)
goal_point = Point2d(-191.789, -50.1725)
lanes_near_goal = map_interface.find_nearest_lanes(goal_point, 1)
assert(len(lanes_near_goal) == 1)
viewer = MPViewer(params=params, use_world_bounds=True)
viewer.drawWorld(world)
time.sleep(2) # if this is not here, the second unit test is not executed (maybe parsing takes too long?)
def test_one_agent_at_goal_sequential(self):
param_server = ParameterServer()
# Model Definition
dynamic_model = SingleTrackModel(param_server)
behavior_model = BehaviorMPContinuousActions(param_server)
idx = behavior_model.AddMotionPrimitive(np.array([1, 0]))
behavior_model.ActionToBehavior(idx)
execution_model = ExecutionModelInterpolate(param_server)
# Agent Definition
agent_2d_shape = CarLimousine()
init_state = np.array([0, 0, 0, 0, 0])
agent_params = param_server.AddChild("agent1")
goal_frame = Polygon2d([0, 0, 0],
[Point2d(-1,-1),
Point2d(-1,1),
Point2d(1,1),
Point2d(1,-1)])
goal_polygon1 = goal_frame.Translate(Point2d(10, 0))
goal_polygon2 = goal_frame.Translate(Point2d(20, 0))
goal_polygon3 = goal_frame.Translate(Point2d(30, 0))
goal_def1 = GoalDefinitionStateLimits(goal_polygon1, [-0.08, 0.08])
goal_def2 = GoalDefinitionStateLimits(goal_polygon2, [-0.08, 0.08])
goal_def3 = GoalDefinitionStateLimits(goal_polygon3, [-0.08, 0.08])
goal_definition = GoalDefinitionSequential([goal_def1,
goal_def2,
goal_def3])
self.assertEqual(len(goal_definition.sequential_goals),3)
agent = Agent(init_state,
behavior_model,
dynamic_model,
execution_model,
agent_2d_shape,
agent_params,
goal_definition,
None)
world = World(param_server)
world.AddAgent(agent)
evaluator = EvaluatorGoalReached(agent.id)
world.AddEvaluator("success", evaluator)
# just drive with the single motion primitive should be successful
for _ in range(0,1000):
world.Step(0.2)
info = world.Evaluate()
if info["success"]:
break
self.assertEqual(info["success"], True)
self.assertAlmostEqual(agent.state[int(StateDefinition.X_POSITION)], 30, delta=0.5)
def test_uct_single_agent(self):
try:
from bark.models.behavior import BehaviorUCTSingleAgentMacroActions
except:
print("Rerun with --define planner_uct=true")
return
# World Definition
scenario_param_file = "macro_actions_test.json" # must be within examples params folder
params = ParameterServer(filename=os.path.join(
"modules/world/tests/params/", scenario_param_file))
world = World(params)
# Model Definitions
behavior_model = BehaviorUCTSingleAgentMacroActions(params)
execution_model = ExecutionModelInterpolate(params)
dynamic_model = SingleTrackModel(params)
behavior_model2 = BehaviorConstantVelocity(params)
execution_model2 = ExecutionModelInterpolate(params)
dynamic_model2 = SingleTrackModel(params)
# Map Definition
map_interface = MapInterface()
xodr_map = MakeXodrMapOneRoadTwoLanes()
map_interface.SetOpenDriveMap(xodr_map)
world.SetMap(map_interface)
# agent_2d_shape = CarLimousine()
agent_2d_shape = CarRectangle()
init_state = np.array([0, 3, -5.25, 0, 20])
agent_params = params.AddChild("agent1")
# goal_polygon = Polygon2d(
# [1, 1, 0], [Point2d(0, 0), Point2d(0, 2), Point2d(2, 2), Point2d(2, 0)])
# goal_definition = GoalDefinitionPolygon(goal_polygon)
# goal_polygon = goal_polygon.Translate(Point2d(90, -2))
center_line = Line2d()
center_line.AddPoint(Point2d(0.0, -1.75))
center_line.AddPoint(Point2d(100.0, -1.75))
max_lateral_dist = (0.4, 0.5)
max_orientation_diff = (0.08, 0.1)
velocity_range = (5.0, 20.0)
goal_definition = GoalDefinitionStateLimitsFrenet(
center_line, max_lateral_dist, max_orientation_diff,
velocity_range)
agent = Agent(init_state, behavior_model, dynamic_model,
execution_model, agent_2d_shape, agent_params,
goal_definition, map_interface)
world.AddAgent(agent)
init_state2 = np.array([0, 25, -5.25, 0, 0])
agent2 = Agent(init_state2, behavior_model2, dynamic_model2,
execution_model2, agent_2d_shape, agent_params,
goal_definition, map_interface)
world.AddAgent(agent2)
# viewer
viewer = MPViewer(params=params, use_world_bounds=True)
# World Simulation
sim_step_time = params["simulation"]["step_time",
"Step-time in simulation", 0.2]
sim_real_time_factor = params["simulation"][
"real_time_factor", "execution in real-time or faster", 1]
# Draw map
video_renderer = VideoRenderer(renderer=viewer,
world_step_time=sim_step_time)
for _ in range(0, 5):
world.Step(sim_step_time)
viewer.clear()
video_renderer.drawWorld(world)
video_renderer.drawGoalDefinition(goal_definition)
time.sleep(sim_step_time / sim_real_time_factor)
video_renderer.export_video(filename="./test_video_intermediate",
remove_image_dir=True)
import numpy as np
# Name and Output Directory
# CHANGE THIS #
map_name = "4way_intersection"
output_dir = "/home/esterle/map_analysis" + map_name
# Map Definition
xodr_parser = XodrParser("modules/runtime/tests/data/" + map_name + ".xodr")
if not os.path.exists(output_dir):
os.makedirs(output_dir)
# World Definition
params = ParameterServer()
world = World(params)
map_interface = MapInterface()
map_interface.set_open_drive_map(xodr_parser.map)
world.set_map(map_interface)
open_drive_map = world.map.get_open_drive_map()
viewer = MPViewer(params=params, use_world_bounds=True)
viewer.drawWorld(world)
viewer.saveFig(output_dir + "/" + "world_plain.png")
color_triplet_gray = (0.7, 0.7, 0.7)
# Open Drive Elements (Roads, Lane Sections, Lanes)
for idx_r, road in open_drive_map.get_roads().items():
def test_one_agent_at_goal_state_limits_frenet(self):
param_server = ParameterServer()
# Model Definition
behavior_model = BehaviorConstantVelocity(param_server)
execution_model = ExecutionModelInterpolate(param_server)
dynamic_model = SingleTrackModel(param_server)
# Agent Definition
agent_2d_shape = CarLimousine()
agent_params = param_server.AddChild("agent1")
center_line = Line2d()
center_line.AddPoint(Point2d(5.0, 5.0))
center_line.AddPoint(Point2d(10.0, 10.0))
center_line.AddPoint(Point2d(20.0, 10.0))
max_lateral_dist = (0.4, 1)
max_orientation_diff = (0.08, 0.1)
velocity_range = (20.0, 25.0)
goal_definition = GoalDefinitionStateLimitsFrenet(
center_line, max_lateral_dist, max_orientation_diff,
velocity_range)
# not at goal x,y, others yes
agent1 = Agent(np.array([0, 6, 8, 3.14 / 4.0, velocity_range[0]]),
behavior_model, dynamic_model, execution_model,
agent_2d_shape, agent_params, goal_definition, None)
# at goal x,y and others
agent2 = Agent(np.array([0, 5.0, 5.5, 3.14 / 4.0, velocity_range[1]]),
behavior_model, dynamic_model, execution_model,
agent_2d_shape, agent_params, goal_definition, None)
# not at goal x,y,v yes but not orientation
agent3 = Agent(
np.array(
[0, 5, 5.5, 3.14 / 4.0 + max_orientation_diff[1] + 0.001,
20]), behavior_model, dynamic_model, execution_model,
agent_2d_shape, agent_params, goal_definition, None)
# not at goal x,y, orientation but not v
agent4 = Agent(
np.array([
0, 5, 4.5, 3.14 / 4 - max_orientation_diff[0],
velocity_range[0] - 0.01
]), behavior_model, dynamic_model, execution_model, agent_2d_shape,
agent_params, goal_definition, None)
# at goal x,y, at lateral limit
agent5 = Agent(
np.array([
0, 15, 10 - max_lateral_dist[0] + 0.05, 0, velocity_range[1]
]), behavior_model, dynamic_model, execution_model, agent_2d_shape,
agent_params, goal_definition, None)
# not at goal x,y slightly out of lateral limit
agent6 = Agent(
np.array([
0, 15, 10 + max_lateral_dist[0] + 0.05,
3.14 / 4 + max_orientation_diff[0], velocity_range[0]
]), behavior_model, dynamic_model, execution_model, agent_2d_shape,
agent_params, goal_definition, None)
# not at goal x,y,v yes but not orientation
agent7 = Agent(
np.array(
[0, 5, 5.5, 3.14 / 4.0 - max_orientation_diff[0] - 0.001,
20]), behavior_model, dynamic_model, execution_model,
agent_2d_shape, agent_params, goal_definition, None)
world = World(param_server)
world.AddAgent(agent1)
world.AddAgent(agent2)
world.AddAgent(agent3)
world.AddAgent(agent4)
world.AddAgent(agent5)
world.AddAgent(agent6)
world.AddAgent(agent7)
evaluator1 = EvaluatorGoalReached(agent1.id)
evaluator2 = EvaluatorGoalReached(agent2.id)
evaluator3 = EvaluatorGoalReached(agent3.id)
evaluator4 = EvaluatorGoalReached(agent4.id)
evaluator5 = EvaluatorGoalReached(agent5.id)
evaluator6 = EvaluatorGoalReached(agent6.id)
evaluator7 = EvaluatorGoalReached(agent7.id)
world.AddEvaluator("success1", evaluator1)
world.AddEvaluator("success2", evaluator2)
world.AddEvaluator("success3", evaluator3)
world.AddEvaluator("success4", evaluator4)
world.AddEvaluator("success5", evaluator5)
world.AddEvaluator("success6", evaluator6)
world.AddEvaluator("success7", evaluator7)
info = world.Evaluate()
self.assertEqual(info["success1"], False)
self.assertEqual(info["success2"], True)
self.assertEqual(info["success3"], False)
self.assertEqual(info["success4"], False)
self.assertEqual(info["success5"], True)
self.assertEqual(info["success6"], False)
self.assertEqual(info["success7"], False)
class Cosimulation:
def __init__(self):
self.carla_server = None
self.carla_client = None
self.carla_controller = None
self.bark_viewer = None
self.cosimulation_viewer = None
self.launch_args = ["external/carla/CarlaUE4.sh", "-quality-level=Low"]
# Bark parameter server
self.param_server = ParameterServer(
filename=BARK_PATH +
"examples/params/od8_const_vel_one_agent.json")
# World Definition
self.bark_world = World(self.param_server)
# Model Definitions
self.behavior_model = BehaviorIDMClassic(self.param_server)
self.execution_model = ExecutionModelInterpolate(self.param_server)
self.dynamic_model = SingleTrackModel(self.param_server)
# Map Definition
xodr_parser = XodrParser(BARK_PATH + "modules/runtime/tests/data/" +
BARK_MAP + ".xodr")
self.map_interface = MapInterface()
self.map_interface.SetOpenDriveMap(xodr_parser.map)
self.bark_world.SetMap(self.map_interface)
# Bark agent definition
self.agent_2d_shape = CarLimousine()
# use for converting carla actor id to bark agent id
self.carla_2_bark_id = dict()
# store the camera id attached to an agent
self.carla_agents_cam = dict()
def initialize_viewer(self):
# Viewer of Bark simulation, the pygame surface will be extracted
self.bark_viewer = PygameViewer(params=self.param_server,
use_world_bounds=True,
screen_dims=BARK_SCREEN_DIMS)
# Viewer of cosimulation
# Set the number of cameras to show both simulation side by side
# windows from Bark simulation & camera image from Carla simulation
self.cosimulation_viewer = CosimulationViewer(BARK_SCREEN_DIMS,
num_cameras=NUM_CAMERAS)
def close(self):
pg.display.quit()
pg.quit()
# kill the child of the subprocess
# sometimes the socket is not killed, blocking the launch of carla
# server
os.system("fuser {}/tcp -k".format(CARLA_PORT))
exit()
def launch_carla_server(self):
self.carla_server = subprocess.Popen(
self.launch_args[0] if not CARLA_LOW_QUALITY else self.launch_args)
# Wait for launching carla
time.sleep(8)
def connect_carla_server(self):
"""
create a carla client and try connect to carla server
"""
self.carla_client = CarlaClient()
self.carla_client.connect(carla_map=CARLA_MAP,
port=CARLA_PORT,
timeout=10)
self.carla_client.set_synchronous_mode(SYNCHRONOUS_MODE, DELTA_SECOND)
self.carla_controller = Controller(self.carla_client)
def spawn_npc_agents(self, num_agents):
"""spawn npc agents in both Carla and Bark
Arguments:
num_agents {int} -- number of agents to be spawned
"""
for i in range(num_agents):
carla_agent_id = self.carla_client.spawn_random_vehicle(
num_retries=5)
if carla_agent_id is not None:
self.carla_client.set_autopilot(carla_agent_id, True)
# spawn agent object in BARK
agent_params = self.param_server.addChild("agent{}".format(i))
bark_agent = Agent(
np.empty(5),
self.behavior_model,
self.dynamic_model,
self.execution_model,
self.agent_2d_shape,
agent_params,
None, # goal_lane_id
self.map_interface)
self.bark_world.AddAgent(bark_agent)
self.carla_2_bark_id[carla_agent_id] = bark_agent.id
if len(self.carla_2_bark_id) != num_agents:
logging.warning(
"Some agents cannot be spawned due to collision in the spawning location, {} agents are spawned"
.format(len(self.carla_2_bark_id)))
else:
logging.info("{} agents spawned sucessfully.".format(num_agents))
def initialize_camera_manager(self, surfaces):
"""create object for fetching image from carla
Arguments:
surfaces {list} -- list of pygame surfaces
"""
self.cam_manager = CameraManager(surfaces,
synchronous_mode=SYNCHRONOUS_MODE)
def simulation_loop(self, carla_ego_id):
bark_ego_id = self.carla_2_bark_id[carla_ego_id]
self.bark_viewer.clear()
self.cosimulation_viewer.tick()
agent_state_map = self.carla_client.get_vehicles_state(
self.carla_2_bark_id)
self.bark_world.fillWorldFromCarla(0, agent_state_map)
plan = self.bark_world.plan_agents(DELTA_SECOND,
[bark_ego_id])[bark_ego_id]
self.carla_controller.control(
self.carla_client.get_actor(carla_ego_id), plan[-2][1:3],
plan[-1][1:3], plan[-1][4], plan[-1][3])
if SYNCHRONOUS_MODE:
frame_id = self.carla_client.tick()
self.cam_manager.fetch_image(frame_id)
self.cosimulation_viewer.update_cameras(self.cam_manager.surfaces)
# get agents' state in carla, and fill the state into bark
carla_agent_states = self.carla_client.get_vehicles_state(
self.carla_2_bark_id)
self.bark_world.fillWorldFromCarla(DELTA_SECOND, carla_agent_states)
self.bark_viewer.drawWorld(self.bark_world,
show=False,
eval_agent_ids=[bark_ego_id])
self.cosimulation_viewer.update_bark(self.bark_viewer.screen_surface)
self.cosimulation_viewer.show()
import numpy as np
# Name and Output Directory
# CHANGE THIS #
map_name = "city_highway_straight"
output_dir = "/home/hart/Dokumente/2020/" + map_name
# Map Definition
xodr_parser = XodrParser("modules/runtime/tests/data/" + map_name + ".xodr")
if not os.path.exists(output_dir):
os.makedirs(output_dir)
# World Definition
params = ParameterServer()
world = World(params)
map_interface = MapInterface()
map_interface.SetOpenDriveMap(xodr_parser.map)
world.SetMap(map_interface)
open_drive_map = world.map.GetOpenDriveMap()
viewer = MPViewer(params=params,
use_world_bounds=True)
viewer.drawWorld(world)
viewer.saveFig(output_dir + "/" + "world_plain.png")
color_triplet_gray = (0.7,0.7,0.7)
# Open Drive Elements (XodrRoads, XodrLane Sections, XodrLanes)
def test_three_way_intersection(self):
# threeway_intersection
xodr_parser = XodrParser(
"modules/runtime/tests/data/threeway_intersection.xodr")
# World Definition
params = ParameterServer()
world = World(params)
map_interface = MapInterface()
map_interface.SetOpenDriveMap(xodr_parser.map)
world.SetMap(map_interface)
open_drive_map = world.map.GetOpenDriveMap()
viewer = MPViewer(params=params, use_world_bounds=True)
comb_all = []
start_point = [Point2d(-30, -2)]
end_point_list = [Point2d(30, -2), Point2d(-2, -30)]
comb = list(itertools.product(start_point, end_point_list))
comb_all = comb_all + comb
# starting on the right
start_point = [Point2d(30, 2)]
end_point_list = [Point2d(-30, 2)]
comb = list(itertools.product(start_point, end_point_list))
comb_all = comb_all + comb
# starting on the bottom
start_point = [Point2d(2, -30)]
end_point_list = [Point2d(30, -2), Point2d(-30, 2)]
comb = list(itertools.product(start_point, end_point_list))
comb_all = comb_all + comb
# check few corridors
def GenerateRoadCorridor(map_interface, comb):
(start_p, end_p) = comb
polygon = Polygon2d([0, 0, 0], [
Point2d(-1, -1),
Point2d(-1, 1),
Point2d(1, 1),
Point2d(1, -1)
])
start_polygon = polygon.Translate(start_p)
goal_polygon = polygon.Translate(end_p)
rc = map_interface.GenerateRoadCorridor(start_p, goal_polygon)
return rc
# assert road ids
rc = GenerateRoadCorridor(map_interface, comb_all[0])
self.assertEqual(rc.road_ids, [0, 11, 1])
self.assertEqual(len(rc.lane_corridors), 3)
rc = GenerateRoadCorridor(map_interface, comb_all[1])
self.assertEqual(rc.road_ids, [0, 5, 2])
self.assertEqual(len(rc.lane_corridors), 3)
rc = GenerateRoadCorridor(map_interface, comb_all[2])
self.assertEqual(rc.road_ids, [1, 10, 0])
self.assertEqual(len(rc.lane_corridors), 3)
rc = GenerateRoadCorridor(map_interface, comb_all[3])
self.assertEqual(rc.road_ids, [2, 6, 1])
self.assertEqual(len(rc.lane_corridors), 3)
rc = GenerateRoadCorridor(map_interface, comb_all[4])
self.assertEqual(rc.road_ids, [2, 4, 0])
self.assertEqual(len(rc.lane_corridors), 3)
from bark.models.dynamic import SingleTrackModel
from bark.world import World
from bark.world.goal_definition import GoalDefinitionPolygon
from bark.world.agent import Agent
from bark.world.map import MapInterface
from bark.geometry.standard_shapes import CarLimousine
from bark.geometry import Point2d, Polygon2d
# Parameters Definitions
param_server = ParameterServer(
filename="examples/params/od8_const_vel_one_agent.json")
# set parameter that is accessible in Python as well as cpp
# param_server.setReal("wheel_base", 0.8)
# World Definition
world = World(param_server)
# Model Definitions
behavior_model = BehaviorConstantVelocity(param_server)
execution_model = ExecutionModelInterpolate(param_server)
dynamic_model = SingleTrackModel(param_server)
# Map Definition
xodr_parser = XodrParser("modules/runtime/tests/data/Crossing8Course.xodr")
map_interface = MapInterface()
map_interface.SetOpenDriveMap(xodr_parser.map)
world.SetMap(map_interface)
# Agent Definition
agent_2d_shape = CarLimousine()
init_state = np.array([0, -15, -13, 3.14 * 5.0 / 4.0, 10 / 3.6])
def test_evaluator_drivable_area(self):
# World Definition
params = ParameterServer()
world = World(params)
# Model Definitions
behavior_model = BehaviorConstantVelocity(params)
execution_model = ExecutionModelInterpolate(params)
dynamic_model = SingleTrackModel(params)
# Map Definition
map_interface = MapInterface()
xodr_map = MakeXodrMapOneRoadTwoLanes()
map_interface.SetOpenDriveMap(xodr_map)
world.SetMap(map_interface)
#open_drive_map = world.map.GetOpenDriveMap()
#agent_2d_shape = CarLimousine()
agent_2d_shape = Polygon2d(
[1.25, 1, 0],
[Point2d(-1, -1),
Point2d(-1, 1),
Point2d(3, 1),
Point2d(3, -1)])
init_state = np.array([0, 3, -1.75, 0, 5])
agent_params = params.AddChild("agent1")
goal_polygon = Polygon2d(
[1, 1, 0],
[Point2d(0, 0),
Point2d(0, 2),
Point2d(2, 2),
Point2d(2, 0)])
goal_polygon = goal_polygon.Translate(Point2d(50, -2))
agent = Agent(
init_state,
behavior_model,
dynamic_model,
execution_model,
agent_2d_shape,
agent_params,
GoalDefinitionPolygon(goal_polygon), # goal_lane_id
map_interface)
world.AddAgent(agent)
evaluator = EvaluatorDrivableArea()
world.AddEvaluator("drivable_area", evaluator)
info = world.Evaluate()
self.assertFalse(info["drivable_area"])
viewer = MPViewer(params=params, use_world_bounds=True)
# Draw map
viewer.drawGoalDefinition(goal_polygon,
color=(1, 0, 0),
alpha=0.5,
facecolor=(1, 0, 0))
viewer.drawWorld(world)
viewer.drawRoadCorridor(agent.road_corridor)
viewer.show(block=False)
def test_python_behavior_model(self):
# World Definition
scenario_param_file = "macro_actions_test.json" # must be within examples params folder
params = ParameterServer(filename=os.path.join(
"modules/world/tests/params/", scenario_param_file))
world = World(params)
# Define two behavior models one python one standard c++ model
behavior_model = PythonDistanceBehavior(params)
execution_model = ExecutionModelInterpolate(params)
dynamic_model = SingleTrackModel(params)
behavior_model2 = BehaviorConstantVelocity(params)
execution_model2 = ExecutionModelInterpolate(params)
dynamic_model2 = SingleTrackModel(params)
# Define the map interface and load a testing map
map_interface = MapInterface()
xodr_map = MakeXodrMapOneRoadTwoLanes()
map_interface.SetOpenDriveMap(xodr_map)
world.SetMap(map_interface)
# Define the agent shapes
agent_2d_shape = CarRectangle()
init_state = np.array([0, 3, -5.25, 0, 20])
# Define the goal definition for agents
center_line = Line2d()
center_line.AddPoint(Point2d(0.0, -1.75))
center_line.AddPoint(Point2d(100.0, -1.75))
max_lateral_dist = (0.4, 0.5)
max_orientation_diff = (0.08, 0.1)
velocity_range = (5.0, 20.0)
goal_definition = GoalDefinitionStateLimitsFrenet(
center_line, max_lateral_dist, max_orientation_diff,
velocity_range)
# define two agents with the different behavior models
agent_params = params.AddChild("agent1")
agent = Agent(init_state, behavior_model, dynamic_model,
execution_model, agent_2d_shape, agent_params,
goal_definition, map_interface)
world.AddAgent(agent)
init_state2 = np.array([0, 25, -5.25, 0, 15])
agent2 = Agent(init_state2, behavior_model2, dynamic_model2,
execution_model2, agent_2d_shape, agent_params,
goal_definition, map_interface)
world.AddAgent(agent2)
# viewer
viewer = MPViewer(params=params, use_world_bounds=True)
# World Simulation
sim_step_time = params["simulation"]["step_time",
"Step-time in simulation", 0.2]
sim_real_time_factor = params["simulation"][
"real_time_factor", "execution in real-time or faster", 1]
# Draw map
video_renderer = VideoRenderer(renderer=viewer,
world_step_time=sim_step_time)
for _ in range(0, 20):
world.Step(sim_step_time)
viewer.clear()
video_renderer.drawWorld(world)
video_renderer.drawGoalDefinition(goal_definition, "red", 0.5,
"red")
time.sleep(sim_step_time / sim_real_time_factor)
video_renderer.export_video(filename="./test_video_intermediate",
remove_image_dir=True)