自动驾驶安全关键场景生成技术综述OA北大核心CSTPCD

The generation of safety-critical scenarios is a pivotal focus in the domain of autonomous driv-ing,holding significant application value in areas such as autonomous driving testing,automotive safety assessments,and the establishment of automotive safety standards.It is the key to the im-plementation of autonomous driving applications.Existing research lacks a survey focusing on safe-ty-critical scenario generation techniques.We provide a systematic review of safety-critical scenario generation techniques.We summarize the research progress in the field of safety-critical scenario generation techniques.Furthermore,we conduct a comparative analysis of models dedicated to safety-critical scenario generation.In addition,we explore safety-critical scenario generation meth-ods based on clustering,Bayesian networks,and adversarial networks.Finally,we present a pro-spective outlook on research trends in safety-critical scenario generation methods.