Discovering the Precursors of Traffic Breakdowns Using Spatiotemporal Graph Attribution Networks.

AI-Powered Urban Transportation Digital Twin: Methods and Applications.

diffIRM: A Diffusion-Augmented Invariant Risk Minimization Framework for Spatiotemporal Prediction over Graphs.

Cross- and Context-Aware Attention Based Spatial-Temporal Graph Convolutional Networks for Human Mobility Prediction.

A Game-Theoretic Framework for Generic Second-Order Traffic Flow Models Using Mean Field Games and Adversarial Inverse Reinforcement Learning.

DriveGenVLM: Real-world Video Generation for Vision Language Model based Autonomous Driving.

Can LLMs Understand Social Norms in Autonomous Driving Games?

Physics-Informed Deep Learning for Traffic State Estimation: A Survey and the Outlook.

Robust Data Sampling in Machine Learning: A Game-Theoretic Framework for Training and Validation Data Selection.

Detecting mild cognitive impairment and dementia in older adults using naturalistic driving data and interaction-based classification from influence score.

A Physics-Informed Deep Learning Paradigm for Traffic State and Fundamental Diagram Estimation.

A Physics-Informed Deep Learning Paradigm for Traffic State Estimation and Fundamental Diagram Discovery.

Physics-Informed Deep Learning for Traffic State Estimation.

A Physics-Informed Deep Learning Paradigm for Car-Following Models.

When Do Drivers Concentrate? Attention-based Driver Behavior Modeling With Deep Reinforcement Learning.

Interpenetrating Cooperative Localization in Dynamic Connected Vehicle Networks.

Clustering of Naturalistic Driving Encounters Using Unsupervised Learning.

Extracting V2V Encountering Scenarios from Naturalistic Driving Database.