PyTSC: Traffic Signal Control Environment for Multi-Agent Reinforcement Learning

PyTSC is a Python library for training reinforcement learning (RL) models for traffic signal control (TSC). It lets you simulate traffic scenarios and train agents using different RL/MARL algorithms. You can either SUMO or CityFlow simulator. The library is modular so you can modify MDP formulations as per as your need.

Contributions from the community are welcome and appreciated!

Citation

If you use this repository for your research, please cite it using the following BibTeX entry:

@article{bokade2025pytsc,
  title={Pytsc: A unified platform for multi-agent reinforcement learning in traffic signal control},
  author={Bokade, Rohit and Jin, Xiaoning},
  journal={Sensors},
  volume={25},
  number={5},
  pages={1302},
  year={2025},
  publisher={MDPI}
}