3 citations · 3 across the 9 of their papers we have counts for
11 papers
Integrated Automated Car Following and Lane-changing control based on a Parametrized Deep Q-network with Hybrid Action Space
Hao Zhang, Zihao Li, Yang Zhou
Lane-change, a triggering of traffic disturbances to the upstream vehicles, is detrimental to traffic safety and efficiency. Coupled with car-following behavior, the joint maneuver…
Knowledge-Grounded Agentic Large Language Models for Multi-Hazard Understanding from Reconnaissance Reports
Chenchen Kuai, Zihao Li, Braden Rosen +6
Post-disaster reconnaissance reports contain critical evidence for understanding multi-hazard interactions, yet their unstructured narratives make systematic knowledge transfer dif…
Modeling Headway in Heterogeneous and Mixed Traffic Flow: A Statistical Distribution Based on a General Exponential Function
Natchaphon Leungbootnak, Zihao Li, Zihang Wei +2
The ability of existing headway distributions to accurately reflect the diverse behaviors and characteristics in heterogeneous traffic (different types of vehicles) and mixed traff…
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…
CyPortQA: Benchmarking Multimodal Large Language Models for Cyclone Preparedness in Port Operation
Chenchen Kuai, Chenhao Wu, Yang Zhou +5
As tropical cyclones intensify and track forecasts become increasingly uncertain, U.S. ports face heightened supply-chain risk under extreme weather conditions. Port operators need…
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…
Signal Timing Optimization for Mixed Connected Automated Traffic Based on A Markov Delay Approximation
Ximin Yue, Yunlong Zhang, Zihao Li +1
Connected Automated Vehicles (CAVs) offer unparalleled opportunities to revolutionize existing transportation systems. In the near future, CAVs and human-driven vehicles (HDVs) are…
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…
Virtual Roads, Smarter Safety: A Digital Twin Framework for Mixed Autonomous Traffic Safety Analysis
Hao Zhang, Ximin Yue, Kexin Tian +5
This paper presents a digital-twin platform for active safety analysis in mixed traffic environments. The platform is built using a multi-modal data-enabled traffic environment con…
Why Anticipatory Sensing Matters in Commercial ACC Systems under Cut-In Scenarios: A Perspective from Stochastic Safety Analysis
Hao Zhang, Sixu Li, Zihao Li +3
This study presents an analytical solution for the vehicle state evolution of Adaptive Cruise Control (ACC) systems under cut-in scenarios, incorporating sensing delays and anticip…
Overview of Sensing Attacks on Autonomous Vehicle Technologies and Impact on Traffic Flow
Zihao Li, Sixu Li, Hao Zhang +3
While perception systems in Connected and Autonomous Vehicles (CAVs), which encompass both communication technologies and advanced sensors, promise to significantly reduce human dr…