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Merged
merged 4 commits into from
Aug 25, 2018
Merged

Yapf #38

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504c3c8
yapf fixes
eugenevinitsky Aug 24, 2018
f8a9bcd
more yapf;
eugenevinitsky Aug 24, 2018
18ec521
more yapf
eugenevinitsky Aug 24, 2018
fba1ade
minor fixes
eugenevinitsky Aug 24, 2018
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84 changes: 36 additions & 48 deletions examples/rllab/cooperative_merge.py
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Original file line number Diff line number Diff line change
Expand Up @@ -30,41 +30,39 @@ def run_task(*_):
# so place the merging vehicles after the vehicles in the ring
vehicles = Vehicles()
# Inner ring vehicles
vehicles.add(veh_id="human",
acceleration_controller=(IDMController, {"noise": 0.2}),
lane_change_controller=(SumoLaneChangeController, {}),
routing_controller=(ContinuousRouter, {}),
num_vehicles=6,
sumo_car_following_params=SumoCarFollowingParams(
minGap=0.0,
tau=0.5
),
sumo_lc_params=SumoLaneChangeParams())
vehicles.add(
veh_id="human",
acceleration_controller=(IDMController, {
"noise": 0.2
}),
lane_change_controller=(SumoLaneChangeController, {}),
routing_controller=(ContinuousRouter, {}),
num_vehicles=6,
sumo_car_following_params=SumoCarFollowingParams(minGap=0.0, tau=0.5),
sumo_lc_params=SumoLaneChangeParams())

# A single learning agent in the inner ring
vehicles.add(veh_id="rl",
acceleration_controller=(RLController, {}),
lane_change_controller=(SumoLaneChangeController, {}),
routing_controller=(ContinuousRouter, {}),
speed_mode="no_collide",
num_vehicles=1,
sumo_car_following_params=SumoCarFollowingParams(
minGap=0.01,
tau=0.5
),
sumo_lc_params=SumoLaneChangeParams())
vehicles.add(
veh_id="rl",
acceleration_controller=(RLController, {}),
lane_change_controller=(SumoLaneChangeController, {}),
routing_controller=(ContinuousRouter, {}),
speed_mode="no_collide",
num_vehicles=1,
sumo_car_following_params=SumoCarFollowingParams(minGap=0.01, tau=0.5),
sumo_lc_params=SumoLaneChangeParams())

# Outer ring vehicles
vehicles.add(veh_id="merge-human",
acceleration_controller=(IDMController, {"noise": 0.2}),
lane_change_controller=(SumoLaneChangeController, {}),
routing_controller=(ContinuousRouter, {}),
num_vehicles=10,
sumo_car_following_params=SumoCarFollowingParams(
minGap=0.0,
tau=0.5
),
sumo_lc_params=SumoLaneChangeParams())
vehicles.add(
veh_id="merge-human",
acceleration_controller=(IDMController, {
"noise": 0.2
}),
lane_change_controller=(SumoLaneChangeController, {}),
routing_controller=(ContinuousRouter, {}),
num_vehicles=10,
sumo_car_following_params=SumoCarFollowingParams(minGap=0.0, tau=0.5),
sumo_lc_params=SumoLaneChangeParams())

env_params = EnvParams(
horizon=HORIZON,
Expand All @@ -75,45 +73,35 @@ def run_task(*_):
"n_preceding": 2,
"n_following": 2,
"n_merging_in": 2,
}
)
})

additional_net_params = ADDITIONAL_NET_PARAMS.copy()
additional_net_params["ring_radius"] = 50
additional_net_params["inner_lanes"] = 1
additional_net_params["outer_lanes"] = 1
additional_net_params["lane_length"] = 75
net_params = NetParams(
no_internal_links=False,
additional_params=additional_net_params
)
no_internal_links=False, additional_params=additional_net_params)

initial_config = InitialConfig(
x0=50,
spacing="uniform",
additional_params={"merge_bunching": 0}
)
x0=50, spacing="uniform", additional_params={"merge_bunching": 0})

scenario = TwoLoopsOneMergingScenario(
name=exp_tag,
generator_class=TwoLoopOneMergingGenerator,
vehicles=vehicles,
net_params=net_params,
initial_config=initial_config
)
initial_config=initial_config)

env_name = "TwoLoopsMergePOEnv"
pass_params = (env_name, sumo_params, vehicles, env_params,
net_params, initial_config, scenario)
pass_params = (env_name, sumo_params, vehicles, env_params, net_params,
initial_config, scenario)

env = GymEnv(env_name, record_video=False, register_params=pass_params)
horizon = env.horizon
env = normalize(env)

policy = GaussianMLPPolicy(
env_spec=env.spec,
hidden_sizes=(100, 50, 25)
)
policy = GaussianMLPPolicy(env_spec=env.spec, hidden_sizes=(100, 50, 25))

baseline = LinearFeatureBaseline(env_spec=env.spec)

Expand Down
67 changes: 39 additions & 28 deletions examples/rllab/figure_eight.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,36 +18,50 @@


def run_task(*_):
sumo_params = SumoParams(sim_step=0.1,
sumo_binary="sumo-gui")
sumo_params = SumoParams(sim_step=0.1, sumo_binary="sumo-gui")

vehicles = Vehicles()
vehicles.add(veh_id="rl",
acceleration_controller=(RLController, {}),
routing_controller=(ContinuousRouter, {}),
speed_mode="no_collide",
num_vehicles=1)
vehicles.add(veh_id="idm",
acceleration_controller=(IDMController, {"noise": 0.2}),
routing_controller=(ContinuousRouter, {}),
speed_mode="no_collide",
num_vehicles=13)

additional_env_params = {"target_velocity": 20,
"max_accel": 3, "max_decel": 3}
env_params = EnvParams(horizon=HORIZON,
additional_params=additional_env_params)

additional_net_params = {"radius_ring": 30, "lanes": 1, "speed_limit": 30,
"resolution": 40}
net_params = NetParams(no_internal_links=False,
additional_params=additional_net_params)
vehicles.add(
veh_id="rl",
acceleration_controller=(RLController, {}),
routing_controller=(ContinuousRouter, {}),
speed_mode="no_collide",
num_vehicles=1)
vehicles.add(
veh_id="idm",
acceleration_controller=(IDMController, {
"noise": 0.2
}),
routing_controller=(ContinuousRouter, {}),
speed_mode="no_collide",
num_vehicles=13)

additional_env_params = {
"target_velocity": 20,
"max_accel": 3,
"max_decel": 3
}
env_params = EnvParams(
horizon=HORIZON, additional_params=additional_env_params)

additional_net_params = {
"radius_ring": 30,
"lanes": 1,
"speed_limit": 30,
"resolution": 40
}
net_params = NetParams(
no_internal_links=False, additional_params=additional_net_params)

initial_config = InitialConfig(spacing="uniform")

print("XXX name", exp_tag)
scenario = Figure8Scenario(exp_tag, Figure8Generator, vehicles, net_params,
initial_config=initial_config)
scenario = Figure8Scenario(
exp_tag,
Figure8Generator,
vehicles,
net_params,
initial_config=initial_config)

env_name = "AccelEnv"
pass_params = (env_name, sumo_params, vehicles, env_params, net_params,
Expand All @@ -57,10 +71,7 @@ def run_task(*_):
horizon = env.horizon
env = normalize(env)

policy = GaussianMLPPolicy(
env_spec=env.spec,
hidden_sizes=(16, 16)
)
policy = GaussianMLPPolicy(env_spec=env.spec, hidden_sizes=(16, 16))

baseline = LinearFeatureBaseline(env_spec=env.spec)

Expand Down
95 changes: 54 additions & 41 deletions examples/rllab/green_wave.py
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Original file line number Diff line number Diff line change
Expand Up @@ -33,29 +33,32 @@ def gen_edges(row_num, col_num):

def get_flow_params(v_enter, vehs_per_hour, col_num, row_num,
additional_net_params):
initial_config = InitialConfig(spacing="uniform",
lanes_distribution=float("inf"),
shuffle=True)
initial_config = InitialConfig(
spacing="uniform", lanes_distribution=float("inf"), shuffle=True)

inflow = InFlows()
outer_edges = gen_edges(col_num, row_num)
for i in range(len(outer_edges)):
inflow.add(veh_type="idm", edge=outer_edges[i],
vehs_per_hour=vehs_per_hour,
departLane="free", departSpeed=v_enter)

net_params = NetParams(in_flows=inflow,
no_internal_links=False,
additional_params=additional_net_params)
inflow.add(
veh_type="idm",
edge=outer_edges[i],
vehs_per_hour=vehs_per_hour,
departLane="free",
departSpeed=v_enter)

net_params = NetParams(
in_flows=inflow,
no_internal_links=False,
additional_params=additional_net_params)

return initial_config, net_params


def get_non_flow_params(enter_speed, additional_net_params):
additional_init_params = {"enter_speed": enter_speed}
initial_config = InitialConfig(additional_params=additional_init_params)
net_params = NetParams(no_internal_links=False,
additional_params=additional_net_params)
net_params = NetParams(
no_internal_links=False, additional_params=additional_net_params)

return initial_config, net_params

Expand All @@ -74,43 +77,56 @@ def run_task(*_):
tot_cars = (num_cars_left + num_cars_right) * m \
+ (num_cars_bot + num_cars_top) * n

grid_array = {"short_length": short_length, "inner_length": inner_length,
"long_length": long_length, "row_num": n, "col_num": m,
"cars_left": num_cars_left, "cars_right": num_cars_right,
"cars_top": num_cars_top, "cars_bot": num_cars_bot}
grid_array = {
"short_length": short_length,
"inner_length": inner_length,
"long_length": long_length,
"row_num": n,
"col_num": m,
"cars_left": num_cars_left,
"cars_right": num_cars_right,
"cars_top": num_cars_top,
"cars_bot": num_cars_bot
}

sumo_params = SumoParams(sim_step=1,
sumo_binary="sumo-gui")
sumo_params = SumoParams(sim_step=1, sumo_binary="sumo-gui")

vehicles = Vehicles()
vehicles.add(veh_id="idm",
acceleration_controller=(SumoCarFollowingController, {}),
sumo_car_following_params=SumoCarFollowingParams(
min_gap=2.5,
tau=1.1,
max_speed=v_enter),
routing_controller=(GridRouter, {}),
num_vehicles=tot_cars,
speed_mode="all_checks")
vehicles.add(
veh_id="idm",
acceleration_controller=(SumoCarFollowingController, {}),
sumo_car_following_params=SumoCarFollowingParams(
min_gap=2.5, tau=1.1, max_speed=v_enter),
routing_controller=(GridRouter, {}),
num_vehicles=tot_cars,
speed_mode="all_checks")

tl_logic = TrafficLights(baseline=False)

additional_env_params = {"target_velocity": 50, "num_steps": 500,
"switch_time": 3.0}
additional_env_params = {
"target_velocity": 50,
"num_steps": 500,
"switch_time": 3.0
}
env_params = EnvParams(additional_params=additional_env_params)

additional_net_params = {"speed_limit": 35, "grid_array": grid_array,
"horizontal_lanes": 1, "vertical_lanes": 1}
additional_net_params = {
"speed_limit": 35,
"grid_array": grid_array,
"horizontal_lanes": 1,
"vertical_lanes": 1
}

initial_config, net_params = get_flow_params(10, 300, n, m,
additional_net_params)

scenario = SimpleGridScenario(name="grid-intersection",
generator_class=SimpleGridGenerator,
vehicles=vehicles,
net_params=net_params,
initial_config=initial_config,
traffic_lights=tl_logic)
scenario = SimpleGridScenario(
name="grid-intersection",
generator_class=SimpleGridGenerator,
vehicles=vehicles,
net_params=net_params,
initial_config=initial_config,
traffic_lights=tl_logic)

env_name = "PO_TrafficLightGridEnv"
pass_params = (env_name, sumo_params, vehicles, env_params, net_params,
Expand All @@ -120,10 +136,7 @@ def run_task(*_):
horizon = env.horizon
env = normalize(env)

policy = GaussianMLPPolicy(
env_spec=env.spec,
hidden_sizes=(32, 32)
)
policy = GaussianMLPPolicy(env_spec=env.spec, hidden_sizes=(32, 32))

baseline = LinearFeatureBaseline(env_spec=env.spec)

Expand Down
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