{"title":"A Survey of Autonomous Driving Scenarios and Scenario Databases","authors":"Hongping Ren, Hui Gao, He Chen, Guangzhen Liu","doi":"10.1109/DSA56465.2022.00107","DOIUrl":null,"url":null,"abstract":"With the development of autonomous driving technology, traditional road testing methods can no longer meet the needs of autonomous driving testing. These methods lack sufficiency, comprehensiveness and efficiency. Using the autonomous driving scenario databases for testing can greatly shorten the test time and cost, and can improve the safety and reliability of the test. By systematically sorting out a large number of related publications, this paper summarizes the research progress of autonomous driving scenarios and scenario databases. The article firstly compares and analyzes the different definitions of autonomous driving scenarios, clarifies the connotation of the scenarios, summarizes the types of elements of the scenarios, and introduces the scenario layered model; secondly, we outline the description standards of scenario. We mainly summarize the two scenario data formats, OpenDRIVE and OpenSCENARIO, which are commonly used in the world. Thirdly, the scenario data collection and research work carried out at home and abroad is reviewed from the perspective of scenario data sources, and different datasets are compared; In addition, the definition of the scenario database, the construction process of the scenario database and the typical scenario databases are summarized; Finally, the problems and future development trends of autonomous driving scenarios and scenario databases are discussed and prospected.","PeriodicalId":208148,"journal":{"name":"2022 9th International Conference on Dependable Systems and Their Applications (DSA)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 9th International Conference on Dependable Systems and Their Applications (DSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DSA56465.2022.00107","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
With the development of autonomous driving technology, traditional road testing methods can no longer meet the needs of autonomous driving testing. These methods lack sufficiency, comprehensiveness and efficiency. Using the autonomous driving scenario databases for testing can greatly shorten the test time and cost, and can improve the safety and reliability of the test. By systematically sorting out a large number of related publications, this paper summarizes the research progress of autonomous driving scenarios and scenario databases. The article firstly compares and analyzes the different definitions of autonomous driving scenarios, clarifies the connotation of the scenarios, summarizes the types of elements of the scenarios, and introduces the scenario layered model; secondly, we outline the description standards of scenario. We mainly summarize the two scenario data formats, OpenDRIVE and OpenSCENARIO, which are commonly used in the world. Thirdly, the scenario data collection and research work carried out at home and abroad is reviewed from the perspective of scenario data sources, and different datasets are compared; In addition, the definition of the scenario database, the construction process of the scenario database and the typical scenario databases are summarized; Finally, the problems and future development trends of autonomous driving scenarios and scenario databases are discussed and prospected.