SR-Traffic

This repository contains the code used to produce the results of the paper SR-Traffic: Discovering Macroscopic Traffic Flow Models with Symbolic Regression

Installation

The dependencies are collected in environment.yaml and can be installed, after cloning the repository, using mamba:

$ mamba env create -f environment.yaml

Once the environment is installed and activated, install the library using

$ pip install -e .

Usage

To reproduce the results of the paper just run

$ python src/sr_traffic/fund_diagrams/fund_diagrams_results.py

Make sure to update the task name in fund_diagrams_results.py so it matches the specific task you want to reproduce.

To re-calibrate a given fundamental diagram, run

$ python src/sr_traffic/fund_diagrams/fund_diagrams_calibration.py

By modifying just a few lines in fund_diagrams_calibration.py, you can easily switch the fundamental diagram, select a different task, and adjust the optimizer type or its parameters.

Finally, to perform a run of SR-Traffic, run

$ python src/sr_traffic/learning/stgp_traffic.py

You can change the parameters of the algorithm modifying stgp_traffic.yaml.

Citing