def test_motion_primitives_concat_state(self):
params = ParameterServer(
filename="modules/runtime/tests/data/highway_merging.json")
scenario_generation = UniformVehicleDistribution(num_scenarios=3,
random_seed=0,
params=params)
state_observer = StateConcatenation()
action_wrapper = MotionPrimitives()
evaluator = GoalReached()
viewer = PygameViewer(
params=params, use_world_bounds=True
) # x_range=[-40,40], y_range=[-40,40], follow_agent_id=True)
runtimerl = RuntimeRL(action_wrapper=action_wrapper,
nn_observer=state_observer,
evaluator=evaluator,
step_time=0.2,
viewer=viewer,
scenario_generator=scenario_generation)
for _ in range(0, 5): # run 5 scenarios in a row, repeating after 3
nn_state = runtimerl.reset()
for _ in range(0, 10): # run each scenario for 10 steps
next_nn_state, reward, done, info = runtimerl.step(
action_wrapper.action_space.sample())
runtimerl.render()
print("State: {} \n Reward: {} \n Done {}, Info: {} \n \
=================================================".
format(next_nn_state, reward, done, info))
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)
agent_2d_shape2 = CarLimousine()
init_state2 = np.array([0, -11, -8, 3.14 * 3.0 / 4.0, 5.2])
agent_params2 = param_server.addChild("agent2")
agent2 = Agent(init_state2, behavior_model2, dynamic_model2, execution_model2,
agent_2d_shape2, agent_params2,
GoalDefinitionPolygon(goal_polygon), map_interface)
world.add_agent(agent2)
# viewer
"""
viewer = Panda3dViewer(params=param_server,
x_range=[-200, 200],
y_range=[-200, 200],)
"""
viewer = PygameViewer(params=param_server,
x_range=[-200, 200],
y_range=[-200, 200])
# World Simulation
sim_step_time = param_server["simulation"]["step_time",
"Step-time used in simulation", 1]
sim_real_time_factor = param_server["simulation"][
"real_time_factor", "execution in real-time or faster", 1]
for _ in range(0, 30):
world.step(sim_step_time)
viewer.drawWorld(world)
viewer.show(block=False)
time.sleep(sim_step_time / sim_real_time_factor)
param_server.save(
agent = Agent(
init_state,
behavior_model,
dynamic_model,
execution_model,
agent_2d_shape,
agent_params,
GoalDefinition(goal_polygon), # goal_lane_id
map_interface)
world.add_agent(agent)
# viewer
viewer = PygameViewer(params=param_server,
x_range=[-50, 50],
y_range=[-50, 50],
follow_agent_id=agent.id,
screen_dims=[500, 500])
#viewer = MPViewer(params=param_server)
# World Simulation
sim_step_time = param_server["simulation"]["step_time",
"Step-time in simulation", 0.05]
sim_real_time_factor = param_server["simulation"][
"real_time_factor", "execution in real-time or faster", 100]
for _ in range(0, 100):
viewer.clear()
world.step(sim_step_time)
viewer.drawWorld(world)
import time
import os
scenario_dump_folder = "examples/scenarios/"
scenario_param_file = "highway_merging.json" # must be within scenario dump folder
param_server = ParameterServer(
filename=os.path.join("examples/params/", scenario_param_file))
scenario_generation = UniformVehicleDistribution(num_scenarios=3,
random_seed=0,
params=param_server)
scenario_generation.params.save(
os.path.join(scenario_dump_folder, scenario_param_file))
viewer = PygameViewer(params=param_server, use_world_bounds=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", "execution in real-time or faster", 1]
for _ in range(0, 2): # run 5 scenarios in a row, repeating after 3
scenario, idx = scenario_generation.get_next_scenario()
world_state = scenario.get_world_state()
print("Running scenario {} of {}".format(
idx, scenario_generation.num_scenarios))
for _ in range(0, 10): # run each scenario for 3 steps
world_state.step(sim_step_time)
viewer.drawWorld(world_state)
viewer.show(block=False)
from modules.runtime.scenario.scenario_generation.uniform_vehicle_distribution import UniformVehicleDistribution
from modules.runtime.commons.parameters import ParameterServer
from modules.runtime.viewer.matplotlib_viewer import MPViewer
from modules.runtime.viewer.pygame_viewer import PygameViewer
from modules.runtime.viewer.threaded_viewer import ThreadedViewer
import time
import os
scenario_param_file ="highway_merging.json" # must be within examples params folder
param_server = ParameterServer(filename= os.path.join("examples/params/",scenario_param_file))
scenario_generation = UniformVehicleDistribution(num_scenarios=3, random_seed=0, params=param_server)
viewer = PygameViewer(params=param_server, x_range=[-50,50], y_range=[-20,80], 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, idx = scenario_generation.get_next_scenario()
world_state = scenario.get_world_state()
print("Running scenario {} of {}".format(idx, scenario_generation.num_scenarios))
for _ in range(0, 100): # run each scenario for 3 steps
world_state.do_planning(sim_step_time)
viewer.drawWorld(world_state)
# Copyright (c) 2019 fortiss GmbH
#
# This software is released under the MIT License.
# https://opensource.org/licenses/MIT
from modules.runtime.scenario.scenario_generation.scenario_generation import ScenarioGeneration
from modules.runtime.viewer.pygame_viewer import PygameViewer
from modules.runtime.viewer.matplotlib_viewer import MPViewer
from modules.runtime.commons.parameters import ParameterServer
import time
param_server = ParameterServer()
viewer = PygameViewer(params=param_server,
x_range=[4950, 5250],
y_range=[5100, 5300])
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]
scenario_generation = ScenarioGeneration()
scenario_generation.load_scenario_list(
filename="examples/scenarios/highway_merging.bark_scenarios")
for _ in range(0, 5): # run 5 scenarios in a row, repeating after 3
scenario, idx = scenario_generation.get_next_scenario()
world_state = scenario.get_world_state()
print("Running scenario {} of {}".format(
idx, scenario_generation.num_scenarios))