collaborators

5 papers

eess.SY2025

Efficient Safety Verification of Autonomous Vehicles with Neural Network Operator

Lingxiang Fan, Linxuan He, Haoyuan Ji +1

When autonomous vehicles encounter untrained scenarios, ensuring safety hinges on effective safety verification to prevent accidents stemming from unexpected model decisions. Reach…

cs.RO2025

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…

cs.RO2025

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…

cs.CV2025

Challenger: Affordable Adversarial Driving Video Generation

Zhiyuan Xu, Bohan Li, Huan-ang Gao +7

Generating photorealistic driving videos has seen significant progress recently, but current methods largely focus on ordinary, non-adversarial scenarios. Meanwhile, efforts to gen…

cs.RO2025

Knowledge-data fusion dominated vehicle platoon dynamics modeling and analysis: A physics-encoded deep learning approach

Hao Lyu, Yanyong Guo, Pan Liu +3

Recently, artificial intelligence (AI)-enabled nonlinear vehicle platoon dynamics modeling plays a crucial role in predicting and optimizing the interactions between vehicles. Exis…