摘要
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.
作者
王淳浩
闭家铭
阮利
魏彤羽
任宇翔
黄镇
刘云韬
纪岳天思
SAW Yinxuan
肖利民
WANG Chunhao;BI Jiaming;RUAN Li;WEI Tongyu;REN Yuxiang;HUANG Zhen;LIU Yuntao;JI Yuetiansi;SAW Yinxuan;XIAO Limin(Beijing Municipal Public Security Bureau Intelligent Connected Vehicle Traffic Accident Investigation and Reconstruction Standard Laboratory,Beijing Police College,Beijing 102202,China;Key Laboratory of Evidence Science(China University of Political Science and Law),Ministry of Education,Beijing 100191,China;School of Computer Science and Engineering,Beihang University,Beijing 102202,China;State Key Laboratory of Complex&Critical Software Environment,Beihang University,Beijing 100191,China)
出处
《信息与控制》
CSCD
北大核心
2024年第1期17-32,46,共17页
Information and Control
基金
北京警察学院校局合作重点项目(2022KXJ12)
公安部警用装备研发计划重点项目(2023ZB12)
证据科学教育部重点实验室(中国政法大学)开放基金(2022KFKT09)
国家自然科学基金项目(62272026)
关键词
自动驾驶汽车
安全关键场景
场景生成
深度生成模型
autonomous vehicle
safety-critical scenario
scenario generation
deep generative model
作者简介
通信作者:阮利(1978-),女,博士,副教授。研究领域为自动驾驶,时空大数据分析,ruanli@buaa.edu.cn;王淳浩(1978-),男,博士,教授。研究领域为道路交通事故处理,证据科学;闭家铭(1999-),男,硕士生。研究领域为自动驾驶场景生成。
