6 papers
Forecasting the Emergence and Evolution of Crash Hotspots: A Unified Deep Learning Framework for Proactive Traffic Safety
Jingwen Zhu, Keshu Wu, Pei Li +3
Road crashes remain among the gravest threats to public safety, and preventing them is a defining task of transportation systems worldwide. Much of that harm concentrates at hotspo…
V2I Work Zone Geometry Reconstruction with Pose-Conditioned UWB Range Denoising
Jiaxi Liu, Hangyu Li, Yang Cheng +7
Reliable work zone mapping is important for connected and autonomous vehicles (CAVs) to navigate safely and smoothly through work zone areas. Cone-mounted ultra-wideband (UWB) road…
An Agentic Workflow for Detecting Personally Identifiable Information in Crash Narratives
Junyi Ma, Pei Li, Rui Gan +3
Crash narratives in crash reports provide crucial contextual information for traffic safety analysis. Yet, their broader use is hindered by the presence of personally identifiable…
Truck Parking Usage Prediction with Decomposed Graph Neural Networks
Rei Tamaru, Yang Cheng, Steven Parker +3
Truck parking on freight corridors faces the major challenge of insufficient parking spaces. This is exacerbated by the Hour-of-Service (HOS) regulations, which often result in una…
V2X-LLM: Enhancing V2X Integration and Understanding in Connected Vehicle Corridors
Keshu Wu, Pei Li, Yang Zhou +8
The advancement of Connected and Automated Vehicles (CAVs) and Vehicle-to-Everything (V2X) offers significant potential for enhancing transportation safety, mobility, and sustainab…
A Digital Twin Framework for Physical-Virtual Integration in V2X-Enabled Connected Vehicle Corridors
Keshu Wu, Pei Li, Yang Cheng +4
Transportation Cyber-Physical Systems (T-CPS) enhance safety and mobility by integrating cyber and physical transportation systems. A key component of T-CPS is the Digital Twin (DT…