Accurate trajectory prediction is a cornerstone for ensuring the safety and operational reliability of autonomous driving systems. However, conventional data-driven models often exhibit significant performance degradation in complex, highly interactive traffic scenarios. Insufficient modeling of directed vehicle intera...
Ji-Pu Li, Qi-Jun Huang, Hui-Wen Yin et al.· Accident Analysis and Preven...· 0 citations
OBJECTIVE
Safety validation of autonomous driving systems (ADS) is constrained by the rarity of safety-critical interactions in naturalistic driving and the difficulty of generating realistic multi-agent trajectories from reconstructed crash data. This study focuses on a common urban safety-critical scenario in which t...
Jiang Bian, Qian-Yuan Yu, Xi-Chang Liu et al.· Traffic Injury Prevention· 0 citations
Safe operation of Autonomous Vehicles (AVs) in complex traffic scenarios remains a challenge, particularly in interactions with Powered Two-Wheelers (PTWs), whose riders represent a common and vulnerable group of road users. This study proposes DRIVE (Diffusion-Reachability-based Interaction and Validation for Efficien...
Hei-Lai Huang, Zimo Yang, Jiang Bian et al.· Accident Analysis and Preven...· 0 citations
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