18 citations · 23 across the 13 of their papers we have counts for
5 papers · 1 filter
TeraSim-World: Worldwide Safety-Critical Data Synthesis for End-to-End Autonomous Driving
Jiawei Wang, Haowei Sun, Xintao Yan +3
Safe and scalable deployment of end-to-end (E2E) autonomous driving requires extensive and diverse data, particularly safety-critical events. Existing data are mostly generated fro…
Improving Traffic Signal Data Quality for the Waymo Open Motion Dataset
Xintao Yan, Erdao Liang, Jiawei Wang +2
Datasets pertaining to autonomous vehicles (AVs) hold significant promise for a range of research fields, including artificial intelligence (AI), autonomous driving, and transporta…
Behavioral Safety Assessment towards Large-scale Deployment of Autonomous Vehicles
Henry X. Liu, Xintao Yan, Haowei Sun +7
Autonomous vehicles (AVs) have significantly advanced in real-world deployment in recent years, yet safety continues to be a critical barrier to widespread adoption. Traditional fu…
RADE: Learning Risk-Adjustable Driving Environment via Multi-Agent Conditional Diffusion
Jiawei Wang, Xintao Yan, Yao Mu +3
Generating safety-critical scenarios in high-fidelity simulations offers a promising and cost-effective approach for efficient testing of autonomous vehicles. Existing methods typi…
TeraSim: Uncovering Unknown Unsafe Events for Autonomous Vehicles through Generative Simulation
Haowei Sun, Xintao Yan, Zhijie Qiao +14
Traffic simulation is essential for autonomous vehicle (AV) development, enabling comprehensive safety evaluation across diverse driving conditions. However, traditional rule-based…