# Traffic Modeling with SUMO: a Tutorial

arXiv: https://arxiv.org/abs/2304.05982 · HTML: https://mlsanity.com/paper/2304.05982/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Mar 2023.

## Built on by (most cited first, 3 of 3)

- [Congestion Reduction in EV Charger Placement Using Traffic Equilibrium Models](https://mlsanity.com/paper/2512.12081/) (2025)
- [Efficient Prompt Learning for Traffic Forecasting](https://mlsanity.com/paper/2605.08273/) (2026)
- [ReasonLight: A Multimodal Foundation Model-Enhanced Reinforcement Learning Framework for Zero-Shot Traffic Signal Control](https://mlsanity.com/paper/2605.29425/) (2026)

## Abstract (arXiv)

This paper presents a step-by-step guide to generating and simulating a traffic scenario using the open-source simulation tool SUMO. It introduces the common pipeline used to generate a synthetic traffic model for SUMO, how to import existing traffic data into a model to achieve accuracy in traffic simulation (that is, producing a traffic model which dynamics is similar to the real one). It also describes how SUMO outputs information from simulation that can be used for data analysis purposes.