LucasAlegre/sumo-rl
Reinforcement Learning environments for Traffic Signal Control with SUMO. Compatible with Gymnasium, PettingZoo, and popular RL libraries.
This project helps traffic engineers and urban planners design and evaluate smart traffic signal systems. You input traffic network layouts and vehicle routing files, and it simulates how different signal control strategies impact traffic flow. The output shows key metrics like vehicle delay and queue length, allowing you to optimize traffic light timings for smoother urban mobility.
1,002 stars. Available on PyPI.
Use this if you need to test and compare different traffic signal control algorithms in a simulated urban environment to improve traffic flow and reduce congestion.
Not ideal if you are looking for a tool to directly control real-world traffic signals or require a simulation that doesn't use the SUMO platform.
Stars
1,002
Forks
256
Language
Python
License
MIT
Category
Last pushed
Mar 08, 2026
Commits (30d)
0
Dependencies
7
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