Monish Gogri, Maike Hartstern, W. Stork, T. Winsel
{"title":"确定传感器星座评估测试场景的方法","authors":"Monish Gogri, Maike Hartstern, W. Stork, T. Winsel","doi":"10.1109/CAVS51000.2020.9334603","DOIUrl":null,"url":null,"abstract":"This paper proposes a methodology for determining strategically bundled relevant test scenarios for the simulation- based evaluation of sensor constellations. This is achieved by gogri identification of important use cases for the autonomous driving operation, (b) the conversion of these use cases into Regions of Interests (ROIs) around the vehicle along with (c) a definition of a critical index (CI) for each of these regions and (d) a procedure to derive crucial scenarios and (e) categorise them into scenario families. The derived test scenarios help to optimise the field of view of the sensor constellation for the most important regions around the ego vehicle. The novelty lies in its independence from traditional methods of deriving test scenarios and its capability of providing targeted feedback to improve the sensor constellation at the identified pain points. The test scenario families can reduce the development time of highly automated vehicles by providing virtual testing of the sensor constellation performance in the vehicle concept phase.","PeriodicalId":409507,"journal":{"name":"2020 IEEE 3rd Connected and Automated Vehicles Symposium (CAVS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Methodology to Determine Test Scenarios for Sensor Constellation Evaluations\",\"authors\":\"Monish Gogri, Maike Hartstern, W. Stork, T. Winsel\",\"doi\":\"10.1109/CAVS51000.2020.9334603\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a methodology for determining strategically bundled relevant test scenarios for the simulation- based evaluation of sensor constellations. This is achieved by gogri identification of important use cases for the autonomous driving operation, (b) the conversion of these use cases into Regions of Interests (ROIs) around the vehicle along with (c) a definition of a critical index (CI) for each of these regions and (d) a procedure to derive crucial scenarios and (e) categorise them into scenario families. The derived test scenarios help to optimise the field of view of the sensor constellation for the most important regions around the ego vehicle. The novelty lies in its independence from traditional methods of deriving test scenarios and its capability of providing targeted feedback to improve the sensor constellation at the identified pain points. The test scenario families can reduce the development time of highly automated vehicles by providing virtual testing of the sensor constellation performance in the vehicle concept phase.\",\"PeriodicalId\":409507,\"journal\":{\"name\":\"2020 IEEE 3rd Connected and Automated Vehicles Symposium (CAVS)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 3rd Connected and Automated Vehicles Symposium (CAVS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CAVS51000.2020.9334603\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 3rd Connected and Automated Vehicles Symposium (CAVS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAVS51000.2020.9334603","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Methodology to Determine Test Scenarios for Sensor Constellation Evaluations
This paper proposes a methodology for determining strategically bundled relevant test scenarios for the simulation- based evaluation of sensor constellations. This is achieved by gogri identification of important use cases for the autonomous driving operation, (b) the conversion of these use cases into Regions of Interests (ROIs) around the vehicle along with (c) a definition of a critical index (CI) for each of these regions and (d) a procedure to derive crucial scenarios and (e) categorise them into scenario families. The derived test scenarios help to optimise the field of view of the sensor constellation for the most important regions around the ego vehicle. The novelty lies in its independence from traditional methods of deriving test scenarios and its capability of providing targeted feedback to improve the sensor constellation at the identified pain points. The test scenario families can reduce the development time of highly automated vehicles by providing virtual testing of the sensor constellation performance in the vehicle concept phase.