A selection of state-of-the-art research materials on decision making and motion planning.

[ICDE'2023] When Spatio-Temporal Meet Wavelets: Disentangled Traffic Forecasting via Efficient Spectral Graph Attention Networks

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".

a Map-Matching-based Python Toolbox for Vehicle Trajectory Reconstruction

The vehicle orientation dataset is a large-scale dataset containing more than one million annotations for vehicle detection with simultaneous orientation classification using a standard object detection network.

[WWW'2023] "AutoST: Automated Spatio-Temporal Graph Contrastive Learning"

IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning

FedML for Autonomous Driving (AD), Intelligent Transportation Systems (ITS), Connected and Automated Vehicles (CAV)

FindVehicle: A NER dataset in transportation to extract keywords describing vehicles on the road

Intelligent Vehicle Perception Based on Inertial Sensing and Artificial Intelligence

[IEEE TIM] Let You See in Haze and Sandstorm: Two-in-One Low-visibility Enhancement Network

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

Traffic Control Test Bed

Exploring the Roles of Large Language Models in Reshaping Transportation Systems: A Survey, Framework, and Roadmap

Open data and performance hub for the City of Austin Transportation Department

Welcome to quote our published papers, and the codes have been uploaded.

"LLM4Urban: Urban Computing in the Era of Large Language Models"

An automatic vehicle speed measurement and speeding violation detection approach

A Novel Spatio-Temporal Generative Inference Network for Predicting the Long-Term Highway Traffic Speed

A curated list of Vehicle to X (V2X) resources (continually updated)