required_speed=2,
),
Via(
"edge-west-EW",
lane_offset=70,
lane_index=1,
required_speed=2,
),
),
),
]
scenario = Scenario(
traffic={
"basic":
Traffic(flows=[
Flow(
route=RandomRoute(),
rate=3600,
actors={TrafficActor(name="car"): 1.0},
)
])
},
ego_missions=ego_missions,
)
gen_scenario(
scenario=scenario,
output_dir=Path(__file__).parent,
)
car_type_patient_ratio = 0.5
car_name_patient = "patient_car"
car_type_impatient = impatient_car
car_type_impatient_ratio = 0.5
car_name_impatient = "impatient_car"
traffic = Traffic(
flows = [
Flow(
route=RandomRoute(),
begin=0,
end=1
* 60
* 60, # make sure end time is larger than the time of one episode
rate=30,
actors={car_type_patient: car_type_patient_ratio, car_type_impatient: car_type_impatient_ratio},
)
for i in range(sv_num)
]
)
print(f"generate flow with {sv_num} social {car_name_patient, car_name_impatient} vehicles in {scenario_path} ")
gen_traffic(
scenario_path,
traffic,
name=f"{sv_num * 2}_{car_name_patient}_{car_type_patient_ratio}_{car_name_impatient}_{car_type_impatient_ratio}",
output_dir=scenario_path,
ego_missions = [
Mission(
route=Route(begin=("edge-south-SN", 1, 10),
end=("edge-west-EW", 1, 8)), # begin 45.6
),
]
left_traffic_actor = TrafficActor(
name="car",
speed=Distribution(sigma=0.2, mean=1),
lane_changing_model=LaneChangingModel(impatience=0),
# junction_model=JunctionModel(
# drive_after_yellow_time=1.0, impatience=0)
)
scenario = Scenario(
traffic={
"basic":
Traffic(flows=[
Flow(
route=RandomRoute(),
rate=1,
actors={left_traffic_actor: 1.0},
) for i in range(social_vehicle_num)
])
},
ego_missions=ego_missions,
)
gen_scenario(scenario=scenario, output_dir=Path(__file__).parent)
("west-WE", "east-WE"),
("east-EW", "west-EW"),
],
"all": [
("west-WE", "east-WE"),
("east-EW", "west-EW"),
("west-WE", "south-NS"),
("east-EW", "south-NS"),
],
}.items():
traffic = Traffic(flows=[
Flow(
route=Route(begin=(f"edge-{r[0]}", 0, 20),
end=(f"edge-{r[1]}", 0, -20)),
rate=total_rate,
# Share the total rate amongst all flows
actors={
impatient_car: (1.0 / len(routes)) * 0.5,
patient_car: (1.0 / len(routes)) * 0.5,
},
) for r in routes
])
gen_traffic(scenario, traffic, name=name)
gen_traffic(
scenario,
Traffic(flows=[
Flow(
route=RandomRoute(),
rate=3600,
actors={TrafficActor(name="car"): 1.0},
)
horizontal_routes = [("west-WE", "east-WE"), ("east-EW", "west-EW")]
turn_left_routes = [("east-EW", "south-NS")]
turn_right_routes = [("west-WE", "south-NS")]
for name, routes in {
"horizontal": horizontal_routes,
"turns": turn_left_routes + turn_right_routes,
}.items():
traffic = Traffic(flows=[
Flow(
route=Route(begin=(f"edge-{r[0]}", 0, "random"),
end=(f"edge-{r[1]}", 0, "max")),
rate=random.randint(50, 100),
actors={
cooperative_car: 0.35,
car: 0.20,
aggressive_car: 0.45
},
) for r in routes
])
for seed in [0, 5]:
gen_traffic(
scenario,
traffic,
name=f"{name}-{seed}",
seed=seed,
)
# Social Agents
UTurn,
)
ego_missions = [
Mission(
route=Route(begin=("edge-west-WE", 1, 30),
end=("edge-west-EW", 0, 100)),
task=UTurn(initial_speed=20),
),
]
scenario = Scenario(
traffic={
"basic":
Traffic(flows=[
Flow(
route=Route(begin=("edge-west-EW", 0, 20),
end=("edge-west-EW", 1, "max")),
rate=400,
actors={TrafficActor(name="car"): 1.0},
)
])
},
ego_missions=ego_missions,
)
gen_scenario(
scenario=scenario,
output_dir=Path(__file__).parent,
)
def generate_social_vehicles(
route_distribution,
start_end_on_different_lanes_probability,
num_vehicles,
route_direction,
route_lanes,
route_has_turn,
stopwatcher_info,
begin_time_init=None,
deadlock_optimization=True,
):
flows = []
behaviors = []
log_info = {
"num_vehicles": 0,
"route_distribution": None,
"start_end_on_different_lanes_probability": 0.0,
}
stopwatcher_added = False
# populate random routes based on their probability
start_lane, end_lane = route_direction
if stopwatcher_info and route_direction == stopwatcher_info["direction"]:
if stopwatcher_info["behavior"] not in behaviors:
behaviors.append(f'stopwatcher_{stopwatcher_info["behavior"]}')
num_vehicles = max(0, num_vehicles - 1) # used 1 for stopwatcher
stopwatcher_added = True
behaviors.extend(
random.choices(
list(route_distribution.keys()),
weights=list(route_distribution.values()),
k=num_vehicles,
))
random.shuffle(behaviors) # because stopwatcher is always at the beginning
if begin_time_init is None:
begin_time_init_func = basic_begin_time_init_func
begin_time_init_params = {"probability": 0.0}
else:
begin_time_init_func = begin_time_init["func"]
begin_time_init_params = begin_time_init["params"]
begin_time_init_params = ({} if begin_time_init_params is None else
begin_time_init_params)
begin_times = begin_time_init_func(route_lanes[start_lane], len(behaviors),
**begin_time_init_params)
begin_time_idx = [0 for _ in range(route_lanes[start_lane])]
for behavior_idx in behaviors:
if behavior_idx not in log_info:
log_info[behavior_idx] = {
"count": 0,
"start_end_different_lanes": 0
}
if deadlock_optimization and route_has_turn:
# if route has a turn, start on the left-most lane
start_lane_id = route_lanes[start_lane] - 1
lane_changing_options = [
lane_id for lane_id in range(route_lanes[end_lane])
]
if (len(lane_changing_options) > 0 or random.uniform(0, 1) <
start_end_on_different_lanes_probability):
end_lane_id = random.choice(lane_changing_options)
else:
end_lane_id = start_lane_id
else:
start_lane_id = random.randint(0, route_lanes[start_lane] - 1)
end_lane_id = random.randint(0, route_lanes[end_lane] - 1)
# set begin/end time
begin_time = begin_times[start_lane_id][begin_time_idx[start_lane_id]]
begin_time_idx[start_lane_id] += 1
end_time = begin_time + 3600 # 1 hour
if "stopwatcher" in behavior_idx:
start_lane_id = route_lanes[stopwatcher_info["direction"][0]] - 1
end_lane_id = route_lanes[stopwatcher_info["direction"][1]] - 1
flows.append(
generate_stopwatcher(
stopwatcher_behavior=stopwatcher_info["behavior"],
stopwatcher_route=stopwatcher_info["direction"],
begin_time=begin_time,
start_lane_id=start_lane_id,
end_lane_id=end_lane_id,
))
else:
behavior = get_social_vehicle_behavior(behavior_idx)
flows.append(
Flow(
begin=begin_time,
end=end_time,
route=Route(
begin=(f"edge-{start_lane}", start_lane_id, "base"),
end=(f"edge-{end_lane}", end_lane_id, "max"),
),
rate=1,
actors={behavior: 1.0},
))
log_info[behavior_idx]["count"] += 1
log_info["route_distribution"] = route_distribution
log_info["num_vehicles"] = (num_vehicles +
1 if stopwatcher_added else num_vehicles)
log_info[
"start_end_on_different_lanes_probability"] = start_end_on_different_lanes_probability
log_info[behavior_idx]["start_end_different_lanes"] += (
1 if start_lane_id != end_lane_id else 0)
return flows, log_info
patient_car = TrafficActor(
name="car",
speed=Distribution(sigma=0.2, mean=0.5),
lane_changing_model=LaneChangingModel(impatience=0, cooperative=0.5),
junction_model=JunctionModel(drive_after_yellow_time=1.0, impatience=0.5),
)
car_type = patient_car
car_name = "patient_car"
traffic = Traffic(flows=[
Flow(
route=RandomRoute(),
begin=0,
end=1 * 60 *
60, # make sure end time is larger than the time of one episode
rate=30,
actors={car_type: 1},
) for i in range(sv_num)
])
print(
f"generate flow with {sv_num} social {car_name} vehicles in {scenario_path} "
)
gen_traffic(
scenario_path,
traffic,
name=f"{sv_num}_{car_name}",
output_dir=scenario_path,
seed=seed,
seed(seed_)
scenario_path = os.path.join(os.path.dirname(os.path.realpath(__file__)),
"../dataset_public/3lane")
traffic_actor = TrafficActor(
name="car",
speed=Distribution(sigma=0.2, mean=0.8),
)
# add 10 social vehicles with random routes.
traffic = Traffic(flows=[
# generate flows last for 10 hours
Flow(
route=RandomRoute(),
begin=0,
end=10 * 60 * 60,
rate=25,
actors={traffic_actor: 1},
) for i in range(10)
])
gen_traffic(
scenario_path,
traffic,
name="all",
output_dir=scenario_path,
seed=seed_,
overwrite=True,
)
]
for name, routes in {
"vertical":
vertical_routes,
"horizontal":
horizontal_routes,
"unprotected_left":
turn_left_routes,
"turns":
turn_left_routes + turn_right_routes,
"all":
vertical_routes + horizontal_routes + turn_left_routes +
turn_right_routes,
}.items():
traffic = Traffic(flows=[
Flow(
route=Route(
begin=(f"edge-{r[0]}", 0, "random"),
end=(f"edge-{r[1]}", 0, "random"),
),
rate=1,
actors={
impatient_car: 0.5,
patient_car: 0.5
},
) for r in routes
])
gen_traffic(scenario, traffic, name=name)