def merge_example(sumo_binary=None):
sumo_params = SumoParams(sumo_binary="sumo-gui",
emission_path="./data/",
sim_step=0.2,
restart_instance=True)
if sumo_binary is not None:
sumo_params.sumo_binary = sumo_binary
vehicles = Vehicles()
vehicles.add(veh_id="human",
acceleration_controller=(IDMController, {
"noise": 0.2
}),
num_vehicles=5)
env_params = EnvParams(additional_params=ADDITIONAL_ENV_PARAMS,
sims_per_step=5,
warmup_steps=0)
inflow = InFlows()
inflow.add(veh_type="human",
edge="inflow_highway",
vehs_per_hour=(1 - RL_PENETRATION) * FLOW_RATE,
departLane="free",
departSpeed=10)
inflow.add(veh_type="human",
edge="inflow_merge",
vehs_per_hour=100,
departLane="free",
departSpeed=7.5)
additional_net_params = ADDITIONAL_NET_PARAMS.copy()
additional_net_params["merge_lanes"] = 1
additional_net_params["highway_lanes"] = 1
additional_net_params["pre_merge_length"] = 500
net_params = NetParams(in_flows=inflow,
no_internal_links=False,
additional_params=additional_net_params)
initial_config = InitialConfig(spacing="uniform",
perturbation=5.0,
lanes_distribution=float("inf"))
scenario = MergeScenario(name="merge-baseline",
generator_class=MergeGenerator,
vehicles=vehicles,
net_params=net_params,
initial_config=initial_config)
env = WaveAttenuationMergePOEnv(env_params, sumo_params, scenario)
return SumoExperiment(env, scenario)
def merge_baseline(num_runs, render=True):
"""Run script for all merge baselines.
Parameters
----------
num_runs : int
number of rollouts the performance of the environment is evaluated
over
render: bool, optional
specifies whether to use sumo's gui during execution
Returns
-------
SumoExperiment
class needed to run simulations
"""
# We consider a highway network with an upstream merging lane producing
# shockwaves
additional_net_params = ADDITIONAL_NET_PARAMS.copy()
additional_net_params["merge_lanes"] = 1
additional_net_params["highway_lanes"] = 1
additional_net_params["pre_merge_length"] = 500
# RL vehicles constitute 5% of the total number of vehicles
vehicles = Vehicles()
vehicles.add(veh_id="human",
acceleration_controller=(SumoCarFollowingController, {}),
speed_mode=9,
num_vehicles=5)
# Vehicles are introduced from both sides of merge, with RL vehicles
# entering from the highway portion as well
inflow = InFlows()
inflow.add(veh_type="human", edge="inflow_highway",
vehs_per_hour=FLOW_RATE,
departLane="free", departSpeed=10)
inflow.add(veh_type="human", edge="inflow_merge", vehs_per_hour=100,
departLane="free", departSpeed=7.5)
sumo_params = SumoParams(
restart_instance=True,
sim_step=0.5, # time step decreased to prevent occasional crashes
render=render,
)
env_params = EnvParams(
horizon=HORIZON,
sims_per_step=5, # value raised to ensure sec/step match experiment
warmup_steps=0,
evaluate=True, # Set to True to evaluate traffic metric performance
additional_params={
"max_accel": 1.5,
"max_decel": 1.5,
"target_velocity": 20,
"num_rl": NUM_RL,
},
)
initial_config = InitialConfig()
net_params = NetParams(
inflows=inflow,
no_internal_links=False,
additional_params=additional_net_params,
)
scenario = MergeScenario(name="merge",
generator_class=MergeGenerator,
vehicles=vehicles,
net_params=net_params,
initial_config=initial_config)
env = WaveAttenuationMergePOEnv(env_params, sumo_params, scenario)
exp = SumoExperiment(env, scenario)
results = exp.run(num_runs, HORIZON)
avg_speed = np.mean(results["mean_returns"])
return avg_speed
def merge_example(render=None):
"""
Perform a simulation of vehicles on a merge.
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 merge.
"""
sim_params = SumoParams(
render=True,
emission_path=osp.abspath(osp.join(osp.dirname(__file__), 'data')),
sim_step=0.2,
restart_instance=False)
if render is not None:
sim_params.render = render
vehicles = VehicleParams()
vehicles.add(
veh_id="human",
acceleration_controller=(IDMController, {
"noise": 0.2
}),
car_following_params=SumoCarFollowingParams(
speed_mode="obey_safe_speed",
),
num_vehicles=5)
env_params = EnvParams(
additional_params=ADDITIONAL_ENV_PARAMS,
sims_per_step=5,
warmup_steps=0)
inflow = InFlows()
inflow.add(
veh_type="human",
edge="inflow_highway",
vehs_per_hour=FLOW_RATE,
departLane="free",
departSpeed=10)
inflow.add(
veh_type="human",
edge="inflow_merge",
vehs_per_hour=100,
departLane="free",
departSpeed=7.5)
additional_net_params = ADDITIONAL_NET_PARAMS.copy()
additional_net_params["merge_lanes"] = 1
additional_net_params["highway_lanes"] = 1
additional_net_params["pre_merge_length"] = 500
net_params = NetParams(
inflows=inflow,
no_internal_links=False,
additional_params=additional_net_params)
initial_config = InitialConfig(spacing="uniform", perturbation=5.0)
scenario = MergeScenario(
name="merge-baseline",
vehicles=vehicles,
net_params=net_params,
initial_config=initial_config)
env = WaveAttenuationMergePOEnv(env_params, sim_params, scenario)
return Experiment(env)
def merge_example(render=None):
"""Perform a simulation of vehicles on a merge.
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 merge.
"""
sim_params = params.AimsunParams(render=True,
emission_path="./data/",
sim_step=0.2,
restart_instance=False)
if render is not None:
sim_params.render = render
vehicles = params.VehicleParams()
vehicles.add(veh_id="human",
acceleration_controller=(IDMController, {
"noise": 0.2
}),
num_vehicles=5)
env_params = params.EnvParams(additional_params=ADDITIONAL_ENV_PARAMS,
sims_per_step=5,
warmup_steps=0)
inflow = params.InFlows()
inflow.add(veh_type="human",
edge="inflow_highway",
vehs_per_hour=HIGHWAY_RATE,
departLane="free",
departSpeed=10)
inflow.add(veh_type="human",
edge="inflow_merge",
vehs_per_hour=MERGE_RATE,
departLane="free",
departSpeed=7.5)
additional_net_params = ADDITIONAL_NET_PARAMS.copy()
additional_net_params["merge_lanes"] = 1
additional_net_params["highway_lanes"] = 1
additional_net_params["pre_merge_length"] = 500
net_params = params.NetParams(inflows=inflow,
no_internal_links=False,
additional_params=additional_net_params)
initial_config = params.InitialConfig()
scenario = MergeScenario(name="merge-baseline",
vehicles=vehicles,
net_params=net_params,
initial_config=initial_config)
env = WaveAttenuationMergePOEnv(env_params,
sim_params,
scenario,
simulator='aimsun')
return Experiment(env)
additional_params={
"max_accel": 1.5,
"max_decel": 1.5,
"target_velocity": 20,
"num_rl": NUM_RL,
},
)
initial_config = InitialConfig()
net_params = NetParams(
in_flows=inflow,
no_internal_links=False,
additional_params=additional_net_params,
)
scenario = MergeScenario(name="merge",
generator_class=MergeGenerator,
vehicles=vehicles,
net_params=net_params,
initial_config=initial_config)
env = WaveAttenuationMergePOEnv(env_params, sumo_params, scenario)
exp = SumoExperiment(env, scenario)
num_runs = 5
results = exp.run(num_runs, HORIZON)
avg_speed = np.mean(results["mean_returns"])
print('The average speed across {} runs is {}'.format(num_runs, avg_speed))
