TU Delft SUMO Wrapper

A research-oriented wrapper for SUMO^[1] in python, developed for the DAIMoND lab at the Technische Universiteit Delft (TUD), the Netherlands. The full documentation & examples can be found at tud-sumo.github.io/docs/. Example code can be found at github.com/DAIMoNDLab/tud-sumo-examples.

Requirements

Python 3.10 or later is required. Dependencies are; tqdm, matplotlib, mpl-tools, shapely, requests, moviepy, sumolib, scipy and traci.

Using TUD-SUMO

TUD-SUMO is developed in the DAIMoND lab of TU Delft. For any questions or feedback, please contact Callum Evans at c.evans@tudelft.nl. Bug reports can be created in the GitHub repository: github.com/DAIMoNDLab/tud-sumo.

If you decide to use TUD-SUMO in your projects, please cite our SoftwareX publication using:

@misc{evans_tud_sumo_2026,
	title = {TUD-SUMO: A Research-oriented SUMO Wrapper for Traffic Simulation in Python},
	author = {Evans, Callum Done and Rinaldi, Marco and Taale, Henk and Hoogendoorn, Serge},
	journal = {SoftwareX},
	volume = {34},
	pages = {102745},
	year = {2026},
	issn = {2352-7110},
	doi = {https://doi.org/10.1016/j.softx.2026.102745},
	url = {https://www.sciencedirect.com/science/article/pii/S2352711026002372},
  	publisher={Elsevier},
	keywords = {Adaptive Traffic Control, Python, SUMO, Traffic Simulation}
}

Acknowledgements

TUD-SUMO is part of the research under the project "AI in Network Management," funded by Rijkswaterstaat, grant agreement nr. 31179439, under the label of ITS Edulab.

References

1. "Microscopic Traffic Simulation using SUMO"; Pablo Alvarez Lopez, Michael Behrisch, Laura Bieker-Walz, Jakob Erdmann, Yun-Pang Flötteröd, Robert Hilbrich, Leonhard Lücken, Johannes Rummel, Peter Wagner, and Evamarie Wießner. IEEE Intelligent Transportation Systems Conference (ITSC), 2018.