Something else that pybtls can do.#

In pybtls, different lanes can use different vehicle generation models.

There are four lanes of traffic:

  • Lane 1: Vehicles are generated from Grave model, and headways are in NHM condition.

  • Lane 2: Vehicles are generated from Nominal model, and headways are in Congested condition.

  • Lane 3: Vehicles are generated from Garage model, and headways are in Constant condition.

  • Lane 4: Vehicles are generated from Garage model, and headways are in Freeflow condition (Poisson arrival model).

This time we only generate the traffic without effect calculation.

Import the packages and initialize the traffic generator.

[15]:

import pybtls as pb
from pathlib import Path


traffic_gen = pb.TrafficGenerator(no_lane=4)

Set lane 1.

[16]:

# Define the flow composition
lfc_lane1 = pb.LaneFlowComposition(lane_index=1, lane_dir=1)
lfc_lane1.assign_lane_data(
    hourly_truck_flow=[100] * 24,
    hourly_car_flow=[0] * 24,
    hourly_speed_mean=[80 / 3.6 * 10] * 24,
    hourly_speed_std=[10.0] * 24,
    hourly_truck_composition=[
        [25.0, 25.0, 25.0, 25.0] for _ in range(24)
    ],  # only the Grave vehicle generator (gen by distribution) requires this info.
)

# Set the Grave vehicle generator and use the Auxerre truck features
vehicle_gen_Grave = pb.VehicleGenGrave(traffic_site="Auxerre")

# Set the headway generator
headway_gen_NHM = pb.HeadwayGenNHM()

# Config the first lane
traffic_gen.add_lane(
    vehicle_gen=vehicle_gen_Grave, headway_gen=headway_gen_NHM, lfc=lfc_lane1
)

Set lane 2.

[17]:

# Define the flow composition
lfc_lane2 = pb.LaneFlowComposition(lane_index=2, lane_dir=1)
lfc_lane2.assign_lane_data(hourly_truck_flow=[100] * 24, hourly_car_flow=[0] * 24)

# Set the Nominal vehicle generator with a custom vehicle
vehicle = pb.Vehicle(no_axles=3)
vehicle.set_axle_weights([100.0, 100.0, 100.0])  # in kN
vehicle.set_axle_spacings([3.0, 7.0, 0.0])  # in m
vehicle.set_axle_widths([2.0, 2.0, 2.0])  # in m

vehicle_gen_Nominal = pb.VehicleGenNominal(
    nominal_vehicle=vehicle, COV_list=[1.0, 1.0]
)

# Set the headway generator
headway_gen_Congested = pb.HeadwayGenCongested(
    congested_spacing=26.1, congested_speed=36.0, congested_gap_coef_var=0.05
)

# Config the second lane
traffic_gen.add_lane(
    vehicle_gen=vehicle_gen_Nominal, headway_gen=headway_gen_Congested, lfc=lfc_lane2
)

Set lane 3 and lane 4.

[18]:

# Set the flow composition
lfc_lane3 = pb.LaneFlowComposition(lane_index=3, lane_dir=2)
lfc_lane3.assign_lane_data(hourly_truck_flow=[100] * 24, hourly_car_flow=[0] * 24)

# Set the Garage vehicle generator
kernel = [[1.0, 0.08], [1.0, 0.05], [1.0, 0.02]]
vehicle_gen_Garage = pb.VehicleGenGarage(
    garage=Path(".") / "garage.txt", kernel=kernel, garage_format=4
)

# Set the headway generator
headway_gen_Constant = pb.HeadwayGenConstant(constant_speed=36.0, constant_gap=5.0)

# Config the third lane
traffic_gen.add_lane(
    vehicle_gen=vehicle_gen_Garage, headway_gen=headway_gen_Constant, lfc=lfc_lane3
)

# Set the flow composition
lfc_lane4 = pb.LaneFlowComposition(lane_index=4, lane_dir=2)
lfc_lane4.assign_lane_data(
    hourly_truck_flow=[100] * 24,
    hourly_car_flow=[0] * 24,
    hourly_speed_mean=[80 / 3.6 * 10] * 24,
    hourly_speed_std=[10.0] * 24,
)

# Use the same vehicle generator as the third lane.

# Set the headway generator
headway_gen_Freeflow = pb.HeadwayGenFreeflow()

# Config the fourth lane
traffic_gen.add_lane(
    vehicle_gen=vehicle_gen_Garage, headway_gen=headway_gen_Freeflow, lfc=lfc_lane4
)

Set the output to export the generated traffic.

[19]:

output_config = pb.OutputConfig()
output_config.set_vehicle_file_output(
    write_vehicle_file=True,
    vehicle_file_format=4,
    vehicle_file_name="generated_traffic_file.txt",
)

Do the simulation and read the output.

[20]:

sim_task = pb.Simulation(Path(".") / "temp")
sim_task.add_sim(
    traffic=traffic_gen,
    no_day=30,  # 30 days traffic
    output_config=output_config,
    track_progress=True,  # optional, print the simulation days.
    tag="Case4",
)

# Run simulation
sim_task.run(no_core=1)

# Get the output
case4_output = sim_task.get_output()["Case4"]
print(case4_output.get_summary())

from IPython.display import display
display(case4_output.read_data("traffic")["generated_traffic_file"])

Starting simulation...
Day complete...

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['traffic']
Head Year Month Day Hour Min Sec NoAxles NoAxleGroups GVW Velocity Length Lane Dir Trns AxleWeights AxleSpacings AxleWidths
0 1001 1 1 0 0 0 3.689 3 0 371.25945 10.0 10.902 2 1 1.8 [110.61756000000001, 185.69349000000003, 74.93... [3.994, 6.908, 0.0] [1.98, 1.98, 1.98]
1 47799 1 1 0 0 0 5.000 2 2 15.48018 10.0 2.875 2 2 1.8 [7.9461, 7.534080000000001] [2.875, 0.0] [1.98, 1.98]
2 1001 1 1 0 0 0 7.367 3 0 330.67548 10.0 10.228 2 1 1.8 [76.47876000000001, 135.17199000000002, 119.02... [2.715, 7.513, 0.0] [1.98, 1.98, 1.98]
3 42741 1 1 0 0 0 10.000 2 2 15.06816 10.0 2.897 2 2 1.8 [8.328690000000002, 6.739470000000001] [2.897, 0.0] [1.98, 1.98]
4 1001 1 1 0 0 0 11.100 3 0 338.75892 10.0 12.807 2 1 1.8 [51.01200000000001, 110.97072000000001, 176.77... [2.71, 10.097, 0.0] [1.98, 1.98, 1.98]
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
1381671 42332 5 2 0 23 59 55.000 2 2 12.67452 10.0 2.744 2 2 1.8 [6.729660000000001, 5.93505] [2.744, 0.0] [1.98, 1.98]
1381672 1001 5 2 0 23 59 55.680 3 0 221.61771 10.0 11.796 2 1 1.8 [55.142010000000006, 64.25550000000001, 102.2202] [3.887, 7.91, 0.0] [1.98, 1.98, 1.98]
1381673 1001 5 2 0 23 59 59.413 3 0 333.21627 10.0 13.354 2 1 1.8 [175.33413000000002, 122.13450000000002, 35.74... [5.304, 8.05, 0.0] [1.98, 1.98, 1.98]
1381674 47792 6 2 0 0 0 0.000 3 2 122.55633 10.0 5.241 2 2 1.8 [56.407500000000006, 36.31662, 29.84202] [3.924, 1.317, 0.0] [1.98, 1.98, 1.98]
1381675 1001 6 2 0 0 0 3.363 3 0 400.07142 10.0 11.735 2 1 1.8 [158.70618000000002, 111.60837000000001, 129.7... [3.967, 7.768, 0.0] [1.98, 1.98, 1.98]

1381676 rows × 18 columns

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