35 citations · 43 across the 4 of their papers we have counts for
4 papers
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…
Generative Modeling for Adversarial Lane-Change Scenarios
Chuancheng Zhang, Zhenhao Wang, Jiangcheng Wang +5
Decision-making in long-tail scenarios is pivotal to autonomous-driving development, and realistic and challenging simulations play a crucial role in testing safety-critical situat…
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…
Bridging Data-Driven and Knowledge-Driven Approaches for Safety-Critical Scenario Generation in Automated Vehicle Validation
Kunkun Hao, Lu Liu, Wen Cui +4
Automated driving vehicles~(ADV) promise to enhance driving efficiency and safety, yet they face intricate challenges in safety-critical scenarios. As a result, validating ADV with…