自动驾驶安全关键场景生成技术综述

Survey on Automatic Driving Safety-Critical Scenario Generation Technology

安全关键场景生成是自动驾驶的重要方向,在自动驾驶测试、汽车安全性评估和汽车安全标准构建等领域都有着很高的应用价值,是关系自动驾驶应用落地的关键。现有研究缺乏重点围绕安全关键场景生成技术的综述,因此本文对安全关键场景生成技术进行了系统性综述。首先,分析了安全关键场景生成技术的综述相关研究;其次,对安全关键场景生成模型进行了对比分析;再次,分类总结了基于聚类、贝叶斯网络和对抗网络的安全关键场景生成方法的进展;最后,对安全关键场景生成方法研究趋势进行了展望。

The generation of safety-critical scenarios is a pivotal focus in the domain of autonomous driving,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 implementation of autonomous driving applications.Existing research lacks a survey focusing on safety-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 methods based on clustering,Bayesian networks,and adversarial networks.Finally,we present a prospective outlook on research trends in safety-critical scenario generation methods.