{"title":"通过分析物理测试驱动器收集仿真场景","authors":"P. Minnerup, Tobias Kessler, A. Knoll","doi":"10.1109/ITSC.2015.467","DOIUrl":null,"url":null,"abstract":"Ensuring safe operation of autonomous vehicles requires testing them including critical combinations of obstacle configurations plus sensor and actuator inaccuracies. A method for testing inaccuracy combinations has already been published by the authors. This paper enhances the capabilities of the method by automatically collecting scenarios from physical vehicle drives that are relevant for further analysis. For such situations, a state trace including all variables of the whole planning and control system is stored together with environment information. The stored data is the input for further analysis. An implementation of this approach is demonstrated using a simulation and a full size vehicle.","PeriodicalId":124818,"journal":{"name":"2015 IEEE 18th International Conference on Intelligent Transportation Systems","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Collecting Simulation Scenarios by Analyzing Physical Test Drives\",\"authors\":\"P. Minnerup, Tobias Kessler, A. Knoll\",\"doi\":\"10.1109/ITSC.2015.467\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ensuring safe operation of autonomous vehicles requires testing them including critical combinations of obstacle configurations plus sensor and actuator inaccuracies. A method for testing inaccuracy combinations has already been published by the authors. This paper enhances the capabilities of the method by automatically collecting scenarios from physical vehicle drives that are relevant for further analysis. For such situations, a state trace including all variables of the whole planning and control system is stored together with environment information. The stored data is the input for further analysis. An implementation of this approach is demonstrated using a simulation and a full size vehicle.\",\"PeriodicalId\":124818,\"journal\":{\"name\":\"2015 IEEE 18th International Conference on Intelligent Transportation Systems\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE 18th International Conference on Intelligent Transportation Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITSC.2015.467\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 18th International Conference on Intelligent Transportation Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITSC.2015.467","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Collecting Simulation Scenarios by Analyzing Physical Test Drives
Ensuring safe operation of autonomous vehicles requires testing them including critical combinations of obstacle configurations plus sensor and actuator inaccuracies. A method for testing inaccuracy combinations has already been published by the authors. This paper enhances the capabilities of the method by automatically collecting scenarios from physical vehicle drives that are relevant for further analysis. For such situations, a state trace including all variables of the whole planning and control system is stored together with environment information. The stored data is the input for further analysis. An implementation of this approach is demonstrated using a simulation and a full size vehicle.