PhD Dissertation Defense by SUN Yang | Law-Aware Autonomous Driving

ABOUT THE TALK

Autonomous driving systems (ADSs) necessitate comprehensive testing prior to deployment in Autonomous Vehicles (AVs). High-fidelity simulators are crucial for this testing, as they can replicate a wide range of scenarios, including those that are difficult or dangerous to recreate in real-world conditions. While previous approaches have demonstrated that test cases can be generated automatically, they often focus on weak oracles (e.g., reaching the destination without collisions) and fail to assess whether the journey was conducted safely and in compliance with some complex property specifications such as traffic laws. In this dissertation, we develop a series of approaches that enable us to evaluate whether an ADS conforms to complex property specifications such as traffic laws. Furthermore, we propose systematic approaches to enhance the ADS, ensuring law/regulation conformance.

ABOUT THE SPEAKER

Sun Yang is a fourth-year PhD candidate at Singapore Management University, where he is supervised by Professor SUN Jun. His main research interests lie in the areas of autonomous driving, particularly focusing on testing and improvement of existing autonomous driving systems. Prior to his doctoral studies, Yang earned his Bachelor of Engineering from Zhejiang University.   During his time at SMU, Yang has collaborated with outstanding researchers, including professors, postdoctoral fellows, senior students, and research engineers from across the globel. These collaborations have led to multiple papers being accepted at top-tier venues, such as ICSE, ASE, ISSTA, and TSE.