Popular GitHub Repositories for Sumo

Reinforcement Learning environments for Traffic Signal Control with SUMO. Compatible with Gymnasium, PettingZoo, and popular RL libraries.

A framework where a deep Q-Learning Reinforcement Learning agent tries to choose the correct traffic light phase at an intersection to maximize traffic efficiency.

A benchmark towards generalizable reinforcement learning for autonomous driving.

applying multi-agent reinforcement learning for highway-merging autonomous vehicles

SUMO Pytorch Deep Reinforcement Learning Traffic Signal Control

stable-baselines3 reinforcement learning on SUMO traffic light system

Investigating Q-Learning and DQN variants for Traffic Signal Control problem

RouteRL is a multi-agent reinforcement learning framework for modeling and simulating the collective route choices of humans and autonomous vehicles.

DRIVE: A Digital Network Oracle for Cooperative Intelligent Transportation Systems

XRouting: An explainable vehicle rerouting system based on reinforcement learning with transformer structure

Study on the application of reinforcement learning to the management of a traffic light intersection.

Optimize traffic flow at intersections with a Deep Q-Learning agent. Utilizes reinforcement learning to control traffic signals efficiently.

Scramble Crossing with Deep Reinforcement Learning

SumoWare integrates SUMO and Autoware to enable realistic autonomous vehicle (AV) behavior evaluation in diverse traffic scenarios.

Framework of Distributed Learning in Vehicular Networks

In this repository, all codes necessary to implement an optimised traffic simulation are presented. This includes a one single intersection layout, and two intserection with one agent and multiagent.