A selection of state-of-the-art research materials on decision making and motion planning.
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Updated
Aug 26, 2020
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
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"
This is the python code corresponding to the article "Let You See in Haze and Sandstorm: Two-in-One Low-visibility Enhancement Network".
FindVehicle: A NER dataset in transportation to extract keywords describing vehicles on the road
Intelligent Vehicle Perception Based on Inertial Sensing and Artificial Intelligence
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".
Traffic Control Test Bed
Open data and performance hub for the City of Austin Transportation Department
FedML for Autonomous Driving (AD), Intelligent Transportation Systems (ITS), Connected and Automated Vehicles (CAV)
This repository contains the code for the paper "UniTSA: A Universal Reinforcement Learning Framework for V2X Traffic Signal Control".
An automatic vehicle speed measurement and speeding violation detection approach
Welcome to quote our published papers, and the codes have been uploaded.
A Novel Spatio-Temporal Generative Inference Network for Predicting the Long-Term Highway Traffic Speed
Python scripts for Austin Transportation's ETL tasks
This is the python code corresponding to the article "Deep learning-driven surveillance quality enhancement for maritime management promotion under low-visibility weathers ".
Controlling Traffic Lights Using Image Processing
IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning
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