A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario

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

Decision Intelligence platform for Traffic Crossing Signal Control

Multi & Single Agent Reinforcement Learning for Traffic Signal Control Problem

Paper & Code & Dataset Collection of Spatial-Temporal Data Mining.

This repository contains the code for the paper "LLM-Assisted Light: Leveraging Large Language Model Capabilities for Human-Mimetic Traffic Signal Control in Complex Urban Environments".

SUMO Pytorch Deep Reinforcement Learning Traffic Signal Control

This repository contains the code for the paper "UniTSA: A Universal Reinforcement Learning Framework for V2X Traffic Signal Control".

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

Integrate AutoRL into DQN to implement a single traffic signal control system.

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

Code for "Traffic Signal Cycle Control with Centralized Critic and Decentralized Actors under Varying Intervention Frequencies"

Adaptive traffic signal control using deep reinforcement learning built using SUMO

Designing and Modelling of an Intelligent Traffic Signal Controller using FSM in Verilog HDL

This project is a part of my Master's thesis and aims to improve traffic flow and reduce delays with the power of AI.

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

This model applies SARSA reinforcement learning for efficient urban traffic and pedestrian management, incorporating simulation, algorithmic implementation, and evaluation to enhance safety and reduce congestion.

Scalable Reinforcement Learning Framework for Traffic Signal Control under Communication Delays

Traffic Signal Controll by Tracking, counting and speed estimation of vehicles on surveillance cameras using YOLO v9 and Reinforcement Learning