7 papers · 1 filter
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…
V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision-Language Models
Junwei You, Haotian Shi, Zhuoyu Jiang +6
Vehicle-to-everything (V2X) cooperation has emerged as a promising paradigm to overcome the perception limitations of classical autonomous driving by leveraging information from bo…
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…
Planning Safety Trajectories with Dual-Phase, Physics-Informed, and Transportation Knowledge-Driven Large Language Models
Rui Gan, Pei Li, Keke Long +4
Foundation models have demonstrated strong reasoning and generalization capabilities in driving-related tasks, including scene understanding, planning, and control. However, they s…
A Digital Twin Framework for Physical-Virtual Integration in V2X-Enabled Connected Vehicle Corridors
Keshu Wu, Pei Li, Yang Cheng +4
Transportation Cyber-Physical Systems (T-CPS) enhance safety and mobility by integrating cyber and physical transportation systems. A key component of T-CPS is the Digital Twin (DT…