def bottleneck_example(flow_rate, horizon, sumo_binary=None):
if sumo_binary is None:
sumo_binary = "sumo"
sumo_params = SumoParams(sim_step=0.5,
sumo_binary=sumo_binary,
overtake_right=False,
restart_instance=True)
vehicles = Vehicles()
vehicles.add(veh_id="human",
speed_mode=25,
lane_change_controller=(SumoLaneChangeController, {}),
routing_controller=(ContinuousRouter, {}),
lane_change_mode=1621,
num_vehicles=1)
additional_env_params = {
"target_velocity": 40,
"max_accel": 1,
"max_decel": 1,
"lane_change_duration": 5,
"add_rl_if_exit": False,
"disable_tb": DISABLE_TB,
"disable_ramp_metering": DISABLE_RAMP_METER
}
env_params = EnvParams(horizon=horizon,
additional_params=additional_env_params)
inflow = InFlows()
inflow.add(veh_type="human",
edge="1",
vehsPerHour=flow_rate,
departLane="random",
departSpeed=10)
traffic_lights = TrafficLights()
if not DISABLE_TB:
traffic_lights.add(node_id="2")
if not DISABLE_RAMP_METER:
traffic_lights.add(node_id="3")
additional_net_params = {"scaling": SCALING}
net_params = NetParams(in_flows=inflow,
no_internal_links=False,
additional_params=additional_net_params)
initial_config = InitialConfig(spacing="random",
min_gap=5,
lanes_distribution=float("inf"),
edges_distribution=["2", "3", "4", "5"])
scenario = BBTollScenario(name="bay_bridge_toll",
generator_class=BBTollGenerator,
vehicles=vehicles,
net_params=net_params,
initial_config=initial_config,
traffic_lights=traffic_lights)
env = BottleneckEnv(env_params, sumo_params, scenario)
return SumoExperiment(env, scenario)
def bottleneck_example(flow_rate,
horizon,
restart_instance=False,
render=None):
"""
Perform a simulation of vehicles on a bottleneck.
Parameters
----------
flow_rate : float
total inflow rate of vehicles into the bottleneck
horizon : int
time horizon
restart_instance: bool, optional
whether to restart the instance upon reset
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 bottleneck.
"""
if render is None:
render = False
sim_params = SumoParams(sim_step=0.5,
render=render,
overtake_right=False,
restart_instance=restart_instance)
vehicles = VehicleParams()
vehicles.add(veh_id="human",
lane_change_controller=(SimLaneChangeController, {}),
routing_controller=(ContinuousRouter, {}),
car_following_params=SumoCarFollowingParams(speed_mode=25, ),
lane_change_params=SumoLaneChangeParams(
lane_change_mode=1621, ),
num_vehicles=1)
additional_env_params = {
"target_velocity": 40,
"max_accel": 1,
"max_decel": 1,
"lane_change_duration": 5,
"add_rl_if_exit": False,
"disable_tb": DISABLE_TB,
"disable_ramp_metering": DISABLE_RAMP_METER
}
env_params = EnvParams(horizon=horizon,
additional_params=additional_env_params)
inflow = InFlows()
inflow.add(veh_type="human",
edge="1",
vehsPerHour=flow_rate,
departLane="random",
departSpeed=10)
traffic_lights = TrafficLightParams()
if not DISABLE_TB:
traffic_lights.add(node_id="2")
if not DISABLE_RAMP_METER:
traffic_lights.add(node_id="3")
additional_net_params = {"scaling": SCALING, "speed_limit": 23}
net_params = NetParams(inflows=inflow,
no_internal_links=False,
additional_params=additional_net_params)
initial_config = InitialConfig(spacing="random",
min_gap=5,
lanes_distribution=float("inf"),
edges_distribution=["2", "3", "4", "5"])
scenario = BottleneckScenario(name="bay_bridge_toll",
vehicles=vehicles,
net_params=net_params,
initial_config=initial_config,
traffic_lights=traffic_lights)
env = BottleneckEnv(env_params, sim_params, scenario)
return BottleneckDensityExperiment(env)