SUMO-RL¶
SUMO-RL provides a simple interface to instantiate Reinforcement Learning (RL) environments with SUMO for Traffic Signal Control.
Goals of this repository:
Provide a simple interface to work with Reinforcement Learning for Traffic Signal Control using SUMO
Support Multiagent RL
Compatibility with gymnasium.Env and popular RL libraries such as stable-baselines3 and RLlib
Easy customisation: state and reward definitions are easily modifiable
The main class is SumoEnvironment. If instantiated with parameter ‘single-agent=True’, it behaves like a regular Gymnasium Env. For multiagent environments, use env or parallel_env to instantiate a PettingZoo environment with AEC or Parallel API, respectively. TrafficSignal is responsible for retrieving information and actuating on traffic lights using TraCI API.
For more details, check the documentation online.