def figure_eight_example(render=None):
"""Perform a simulation of vehicles on a figure eight.
Parameters
----------
render: bool, optional
specifies whether to use the gui during execution
Returns
-------
exp: flow.core.experiment.Experiment
A non-rl experiment demonstrating the performance of human-driven
vehicles on a figure eight.
"""
sim_params = AimsunParams(sim_step=0.5, render=False, emission_path='data')
if render is not None:
sim_params.render = render
vehicles = VehicleParams()
vehicles.add(veh_id="human",
acceleration_controller=(IDMController, {}),
num_vehicles=14)
env_params = EnvParams()
net_params = NetParams(additional_params=ADDITIONAL_NET_PARAMS.copy())
scenario = Figure8Scenario(name="figure8",
vehicles=vehicles,
net_params=net_params)
env = TestEnv(env_params, sim_params, scenario, simulator='aimsun')
return Experiment(env)
def figure_eight_example(render=None):
"""
Perform a simulation of vehicles on a figure eight.
Parameters
----------
render: bool, optional
specifies whether to use the gui during execution
Returns
-------
exp: flow.core.experiment.Experiment
A non-rl experiment demonstrating the performance of human-driven
vehicles on a figure eight.
"""
sim_params = SumoParams(render=True)
if render is not None:
sim_params.render = render
vehicles = VehicleParams()
vehicles.add(
veh_id="idm",
acceleration_controller=(IDMController, {}),
lane_change_controller=(StaticLaneChanger, {}),
routing_controller=(ContinuousRouter, {}),
car_following_params=SumoCarFollowingParams(
speed_mode="obey_safe_speed",
decel=1.5,
),
initial_speed=0,
num_vehicles=14)
env_params = EnvParams(additional_params=ADDITIONAL_ENV_PARAMS)
additional_net_params = ADDITIONAL_NET_PARAMS.copy()
net_params = NetParams(additional_params=additional_net_params)
scenario = Figure8Scenario(
name="figure8",
vehicles=vehicles,
net_params=net_params)
env = AccelEnv(env_params, sim_params, scenario)
return Experiment(env)
def figure_eight_example(render=None):
"""
Perform a simulation of vehicles on a figure eight.
Parameters
----------
render: bool, optional
specifies whether to use sumo's gui during execution
Returns
-------
exp: flow.core.SumoExperiment type
A non-rl experiment demonstrating the performance of human-driven
vehicles on a figure eight.
"""
sumo_params = SumoParams(render=True)
if render is not None:
sumo_params.render = render
vehicles = Vehicles()
vehicles.add(veh_id="idm",
acceleration_controller=(IDMController, {}),
lane_change_controller=(StaticLaneChanger, {}),
routing_controller=(ContinuousRouter, {}),
speed_mode="no_collide",
initial_speed=0,
num_vehicles=14)
env_params = EnvParams(additional_params=ADDITIONAL_ENV_PARAMS)
additional_net_params = ADDITIONAL_NET_PARAMS.copy()
net_params = NetParams(no_internal_links=False,
additional_params=additional_net_params)
scenario = Figure8Scenario(name="figure8",
vehicles=vehicles,
net_params=net_params)
env = AccelEnv(env_params, sumo_params, scenario)
return SumoExperiment(env, scenario)
# environment related parameters (see flow.core.params.EnvParams)
env=EnvParams(
horizon=HORIZON,
additional_params={
'target_velocity': 20,
'max_accel': 3,
'max_decel': 3,
'sort_vehicles': False
},
),
# network-related parameters (see flow.core.params.NetParams and the
# scenario's documentation or ADDITIONAL_NET_PARAMS component)
net=NetParams(
no_internal_links=False,
additional_params=ADDITIONAL_NET_PARAMS.copy(),
),
# vehicles to be placed in the network at the start of a rollout (see
# flow.core.vehicles.Vehicles)
veh=vehicles,
# parameters specifying the positioning of vehicles upon initialization/
# reset (see flow.core.params.InitialConfig)
initial=InitialConfig(),
)
def setup_exps():
alg_run = 'PPO'
),
# environment related parameters (see flow.core.params.EnvParams)
env=EnvParams(
horizon=HORIZON,
additional_params={
'target_velocity': 20,
'max_accel': 3,
'max_decel': 3,
'sort_vehicles': False
},
),
# network-related parameters (see flow.core.params.NetParams and the
# scenario's documentation or ADDITIONAL_NET_PARAMS component)
net=NetParams(additional_params=ADDITIONAL_NET_PARAMS.copy(), ),
# vehicles to be placed in the network at the start of a rollout (see
# flow.core.params.VehicleParams)
veh=vehicles,
# parameters specifying the positioning of vehicles upon initialization/
# reset (see flow.core.params.InitialConfig)
initial=InitialConfig(),
)
def setup_exps():
"""Return the relevant components of an RLlib experiment.
Returns
