5 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…
Automated Vehicles Should be Connected with Natural Language
Xiangbo Gao, Keshu Wu, Hao Zhang +3
Multi-agent collaborative driving promises improvements in traffic safety and efficiency through collective perception and decision making. However, existing communication media --…
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…
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…