1 citations · 1 across the 8 of their papers we have counts for
8 papers
Arterial Network Traffic State Prediction with Connected Vehicle Data: An Abnormality-Aware Spatiotemporal Network
Lei Han, Mohamed Abdel-Aty, Yang-Jun Joo
Emerging connected-vehicle (CV) data shows great potential in urban traffic monitoring and forecasting. However, prior CV-based studies on arterial traffic measures prediction are…
Real-time Secondary Crash Likelihood Prediction Excluding Post Primary Crash Features
Lei Han, Mohamed Abdel-Aty, Zubayer Islam +1
Secondary crash likelihood prediction is a critical component of an active traffic management system to mitigate congestion and adverse impacts caused by secondary crashes. However…
MMCAformer: Macro-Micro Cross-Attention Transformer for Traffic Speed Prediction with Microscopic Connected Vehicle Driving Behavior
Lei Han, Mohamed Abdel-Aty, Younggun Kim +2
Accurate speed prediction is crucial for proactive traffic management to enhance traffic efficiency and safety. Existing studies have primarily relied on aggregated, macroscopic tr…
An Integrated Causal Inference Framework for Traffic Safety Modeling with Semantic Street-View Visual Features
Lishan Sun, Yujia Cheng, Pengfei Cui +4
Macroscopic traffic safety modeling aims to identify critical risk factors for regional crashes, thereby informing targeted policy interventions for safety improvement. However, cu…
SAVeD: A First-Person Social Media Video Dataset for ADAS-equipped vehicle Near-Miss and Crash Event Analyses
Shaoyan Zhai, Mohamed Abdel-Aty, Chenzhu Wang +1
The advancement of safety-critical research in driving behavior in ADAS-equipped vehicles require real-world datasets that not only include diverse traffic scenarios but also captu…
Advanced Crash Causation Analysis for Freeway Safety: A Large Language Model Approach to Identifying Key Contributing Factors
Ahmed S. Abdelrahman, Mohamed Abdel-Aty, Samgyu Yang +1
Understanding the factors contributing to traffic crashes and developing strategies to mitigate their severity is essential. Traditional statistical methods and machine learning mo…