13 citations · 32 across the 21 of their papers we have counts for
10 papers · 1 filter
AirV2X: Unified Air-Ground Vehicle-to-Everything Collaboration
Xiangbo Gao, Yuheng Wu, Fengze Yang +7
While multi-vehicular collaborative driving demonstrates clear advantages over single-vehicle autonomy, traditional infrastructure-based V2X systems remain constrained by substanti…
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…
Generative AI for Autonomous Driving: Frontiers and Opportunities
Yuping Wang, Shuo Xing, Cui Can +46
Generative Artificial Intelligence (GenAI) constitutes a transformative technological wave that reconfigures industries through its unparalleled capabilities for content creation,…
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…
V2X-LLM: Enhancing V2X Integration and Understanding in Connected Vehicle Corridors
Keshu Wu, Pei Li, Yang Zhou +8
The advancement of Connected and Automated Vehicles (CAVs) and Vehicle-to-Everything (V2X) offers significant potential for enhancing transportation safety, mobility, and sustainab…
Human Mobility Reimagined: Digital Twin Intelligence for Adaptive Campus Course Timetabling
Keshu Wu, Xinyue Ye, Suphanut Jamonnak +1
Daily operations in large campuses depend on how efficiently people \emph{move} through space and time. In this sense, course timetables are more than administrative schedules: the…
Integrating Spatiotemporal Vision Transformer into Digital Twins for High-Resolution Heat Stress Forecasting in Campus Environments
Wenjing Gong, Xinyue Ye, Keshu Wu +4
Extreme heat events, exacerbated by climate change, pose significant challenges to urban resilience and planning. This study introduces a climate-responsive digital twin framework…