This repository contains the python implementation accompanying the paper:

Probabilistic game-theoretic traffic routing
Emilio Benenati, Sergio Grammatico
IEEE Transactions on intelligent transportation systems, 2024
DOI: 10.1109/TITS.2024.3399112

Description

This code solves for the Nash equilibrium routing solution for a fleet of vehicles. The solution can either be computed offline, or offline via a receding-horizon controller.

Dependencies

See requirements.txt

Running the code

To execute the code:

• Create the test graph

python create_test_graph.py

• Compute offline routing solution

python main.py

• Store the resulting saved file in a folder and update this line accordingly
• Plot offline routing solution

python plot.py

• Compute receding-horizon routing solution

python main_multiperiod.py

• Store the resulting saved file in a folder and update this line accordingly
• Plot results of the receding horizon solution

python plot_multiperiod.py

In the simulation section of the referenced paper paper, the results are obtained by running the code multiple times with randomized parameters and initial condition (see paper for details). The generated data used in the paper is available with DOI: 10.4121/dbbfecf5-a6a3-4077-968e-11c3681f4a93