LucasAlegre/sumo-rl

Health v2 · maintenance only

Adoption not part of the score

1071 stars · 265 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

SUMO-RL is a Python library that provides Gymnasium and PettingZoo-compatible reinforcement learning environments for traffic signal control using the SUMO traffic simulator. It supports single-agent and multiagent RL with customizable state and reward definitions, and integrates with libraries like stable-baselines3 and RLlib.

Use cases

• train RL agents to control traffic lights in SUMO simulations
• run multiagent reinforcement learning experiments on traffic networks
• benchmark traffic signal control algorithms with Gymnasium environments
• customize observation and reward functions for traffic signal agents
• use stable-baselines3 or RLlib to optimize traffic congestion
• simulate and evaluate adaptive traffic signal timing policies

When to choose

• you need RL environments for traffic signal control built on SUMO
• you want Gymnasium or PettingZoo API compatibility for traffic experiments
• you need multiagent RL support for intersection networks
• you want easily customizable state and reward definitions for traffic agents

When to avoid

• you need traffic simulation without reinforcement learning
• you require a different traffic simulator than SUMO
• you need real-world traffic signal control rather than simulation

Facets

library · maturity active

reinforcement-learning simulation machine-learning reinforcement-learning simulation machine-learning python windows cross-platform sumo traffic-signal-control gymnasium pettingzoo multiagent-rl traci traffic-simulation transportation linux macos

Member repositories

For agents

markdown · JSON · MCP: product_card(name="LucasAlegre/sumo-rl")