9 papers
Learning from geometry-aware near misses to real-time COR: A corridor-wide grouped random parameters GEV framework
Mohammad Anis, Yang Zhou, Dominique Lord
Real-time corridor-wide crash-occurrence risk (COR) prediction is challenging because existing near-miss extreme value theory (EVT) models often oversimplify collision geometry, ne…
Pedestrian crash causation analysis near bus stops: Insights from random parameters Negative Binomial-Lindley model
Mohammad Anis, Srinivas R. Geedipally, Dominique Lord
Pedestrian safety remains a pressing concern near bus stops along urban transit, where frequent pedestrian-vehicle interactions occur. While prior research has primarily focused on…
Hypergraph-based Motion Generation with Multi-modal Interaction Relational Reasoning
Keshu Wu, Yang Zhou, Haotian Shi +3
The intricate nature of real-world driving environments, characterized by dynamic and diverse interactions among multiple vehicles and their possible future states, presents consid…
U.S. Port Disruptions under Tropical Cyclones: Resilience Analysis by Harnessing Multiple-Source Dataset
Chenchen Kuai, Zihao Li, Yunlong Zhang +3
This study introduces the CyPort Dataset, recording disruptions to 145 U.S. principal ports and freight network from 90 tropical cyclones (2015-2023). It addresses limitations of e…
Simulating the Unseen: Crash Prediction Must Learn from What Did Not Happen
Zihao Li, Xinyuan Cao, Xiangbo Gao +12
Traffic safety science has long been hindered by a fundamental data paradox: the crashes we most wish to prevent are precisely those events we rarely observe. Existing crash-freque…
AI2-Active Safety: AI-enabled Interaction-aware Active Safety Analysis with Vehicle Dynamics
Keshu Wu, Zihao Li, Sixu Li +3
This paper introduces an AI-enabled, interaction-aware active safety analysis framework that accounts for groupwise vehicle interactions. Specifically, the framework employs a bicy…