2 papers
cs.LG2024
Accurately Predicting Probabilities of Safety-Critical Rare Events for Intelligent Systems
Ruoxuan Bai, Jingxuan Yang, Weiduo Gong +3
Intelligent systems are increasingly integral to our daily lives, yet rare safety-critical events present significant latent threats to their practical deployment. Addressing this…
eess.SY2024
Adaptive Testing Environment Generation for Connected and Automated Vehicles with Dense Reinforcement Learning
Jingxuan Yang, Ruoxuan Bai, Haoyuan Ji +3
The assessment of safety performance plays a pivotal role in the development and deployment of connected and automated vehicles (CAVs). A common approach involves designing testing…