SoVAR: Building Generalizable Scenarios from Accident Reports for Autonomous Driving Testing

Autor: Guo, An, Zhou, Yuan, Tian, Haoxiang, Fang, Chunrong, Sun, Yunjian, Sun, Weisong, Gao, Xinyu, Luu, Anh Tuan, Liu, Yang, Chen, Zhenyu

Publikováno v: 39th IEEE/ACM International Conference on Automated Software Engineering (ASE '24), October 27-November 1, 2024, Sacramento, CA, USA

Autonomous driving systems (ADSs) have undergone remarkable development and are increasingly employed in safety-critical applications. However, recently reported data on fatal accidents involving ADSs suggests that the desired level of safety has not

Externí odkaz: http://arxiv.org/abs/2409.08081