Papers

LAST-V2X: Language-Driven Adaptive Scenario Synthesis and Testing for Communication-Induced Failures in V2X Safety Applications

Wu et al. 2026. arXiv preprint.

Large Language Model-Assisted Preparation of Transportation Management Plans: A Case Study with WisDOT WisTMP System

Sheng et al. 2026. arXiv preprint.

SEAL: Vision-language model-based Safe End-to-End Cooperative Autonomous Driving with Adaptive Long-Tail Modeling

You et al. 2026. Accid. Anal. Prev.

Real-time lane-level abnormal traffic detection on freeways using sparse telematics data

Liang et al. 2026. Accid. Anal. Prev.

Forecasting the Emergence and Evolution of Crash Hotspots: A Unified Deep Learning Framework for Proactive Traffic Safety

Zhu et al. 2026. arXiv preprint.

Geometry-Aware Infrastructure-Anchored Denoiser for UWB Sensing and Work-Zone Reconstruction

Tang et al. 2026. arXiv preprint.

CrashSight: A Phase-Aware, Infrastructure-Centric Video Benchmark for Traffic Crash Scene Understanding and Reasoning

Gan et al. 2026. CVPR Workshops.

Behavior-Grounded Lane Representation Learning for Multi-Task Traffic Digital Twins

Tamaru et al. 2026. arXiv preprint.

An Agentic Workflow for Detecting Personally Identifiable Information in Crash Narratives

Ma et al. 2026. arXiv preprint.

Real-time identification of cooperative perception necessity in road traffic scenarios

Ma et al. 2026. Transp. Res. C.

V2X-QA: A Comprehensive Reasoning Dataset and Benchmark for Multimodal Large Language Models in Autonomous Driving Across Ego, Infrastructure, and Cooperative Views

You et al. 2026. arXiv preprint.

Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection

Tamaru et al. 2025. arXiv preprint.

Goal-based neural physics vehicle trajectory prediction model

Gan et al. 2025. Transp. Res. C.

AI-Enabled Digital Twin Framework for Safe and Sustainable Intelligent Transportation

Long et al. 2025. Sustainability.

Sky-Drive: A distributed multiagent simulation platform for human–AI collaborative and socially aware future transportation

Huang et al. 2025. J. Intell. Connect. Veh.

Planning Safety Trajectories with Dual-Phase, Physics-Informed, and Transportation Knowledge-Driven Large Language Models

Gan et al. 2025. arXiv preprint.

V2X-LLM: Enhancing V2X Integration and Understanding in Connected Vehicle Corridors

Wu et al. 2025. arXiv preprint.

A Digital Twin Framework for Physical-Virtual Integration in V2X-Enabled Connected Vehicle Corridors

Wu et al. 2025. IEEE Trans. Intell. Transp. Syst.

A distributed deep reinforcement learning-based longitudinal control strategy for connected automated vehicles combining attention mechanism

Liu et al. 2025. Transp. Lett.

Enhancing Pedestrian Trajectory Prediction with Crowd Trip Information

Tamaru et al. 2024. arXiv preprint.

Demystifying deep reinforcement learning-based autonomous vehicle decision-making

Wan et al. 2024. arXiv preprint.

Real-World Data Inspired Interactive Connected Traffic Scenario Generation

You et al. 2024. arXiv preprint.

Personalized lane departure warning based on non-stationary crossformer and kernel density estimation

Yin et al. 2024. Alexandria Eng. J.

Analyzing relationships between latent topics in autonomous vehicle crash narratives and crash severity using natural language processing techniques and explainable XGBoost

Li et al. 2024. Accid. Anal. Prev.

How Does C-V2X Perform in Urban Environments? Results From Real-World Experiments on Urban Arterials

Li et al. 2023. IEEE Trans. Intell. Veh.

Why did the AI make that decision? Towards an explainable artificial intelligence (XAI) for autonomous driving systems

Dong et al. 2023. Transp. Res. C.

A Probabilistic Framework for Estimating the Risk of Pedestrian-Vehicle Conflicts at Intersections

Li et al. 2023. IEEE Trans. Intell. Transp. Syst.

Real-Time Big Data Analytics and Proactive Traffic Safety Management Visualization System

Abdel-Aty et al. 2023. J. Transp. Eng. A.

A Hybrid Machine Learning Model for Predicting Real-time Secondary Crash Likelihood

Li and Abdel-Aty 2022. Accid. Anal. Prev.

Real-Time Crash Likelihood Prediction Using Temporal Attention–Based Deep Learning and Trajectory Fusion

Li and Abdel-Aty 2022. J. Transp. Eng. A.

Improving Spatiotemporal Transferability of Real-Time Crash Likelihood Prediction Models Using Transfer-Learning Approaches

Li et al. 2022. Transp. Res. Rec.

Driving Maneuvers Detection using Semi-Supervised Long Short-Term Memory and Smartphone Sensors

Li et al. 2021. Transp. Res. Rec.

Using bus critical driving events as surrogate safety measures for pedestrian and bicycle crashes based on GPS trajectory data

Li et al. 2020. Accid. Anal. Prev.

A Deep Learning Approach to Detect Real-Time Vehicle Maneuvers Based on Smartphone Sensors

Li et al. 2020. IEEE Trans. Intell. Transp. Syst.

Prediction of pedestrian-vehicle conflicts at signalized intersections based on long short-term memory neural network

Zhang et al. 2020. Accid. Anal. Prev.

The application of novel connected vehicles emulated data on real-time crash potential prediction for arterials

Li et al. 2020. Accid. Anal. Prev.

Prediction of Pedestrian Crossing Intentions at Intersections Based on Long Short-Term Memory Recurrent Neural Network

Zhang et al. 2020. Transp. Res. Rec.

Real-time crash risk prediction on arterials based on LSTM-CNN

Li et al. 2020. Accid. Anal. Prev.