3 papers
cs.RO2025
On-Demand Scenario Generation for Testing Automated Driving Systems
Songyang Yan, Xiaodong Zhang, Kunkun Hao +7
The safety and reliability of Automated Driving Systems (ADS) are paramount, necessitating rigorous testing methodologies to uncover potential failures before deployment. Tradition…
cs.AI2025
DriveGen: Towards Infinite Diverse Traffic Scenarios with Large Models
Shenyu Zhang, Jiaguo Tian, Zhengbang Zhu +3
Microscopic traffic simulation has become an important tool for autonomous driving training and testing. Although recent data-driven approaches advance realistic behavior generatio…
cs.RO2024
Adversarial Safety-Critical Scenario Generation using Naturalistic Human Driving Priors
Kunkun Hao, Yonggang Luo, Wen Cui +5
Evaluating the decision-making system is indispensable in developing autonomous vehicles, while realistic and challenging safety-critical test scenarios play a crucial role. Obtain…