M. Zofka, Marc Essinger, Tobias Fleck, R. Kohlhaas, Johann Marius Zöllner
{"title":"梦游者框架:通过混合现实激光雷达刺激验证和验证自动驾驶汽车","authors":"M. Zofka, Marc Essinger, Tobias Fleck, R. Kohlhaas, Johann Marius Zöllner","doi":"10.1109/SIMPAR.2018.8376285","DOIUrl":null,"url":null,"abstract":"Verification and validation of autonomous mobile systems, such as autonomous vehicles, is indispensable, since conflicts and serious incidents are rarely acceptable when human beings are involved. Although integrative simulation frameworks are commonly applied to test these systems, such simulations are usually too idealistic, while real world tests are both, expensive and not reproducible. To overcome this problem, we present the framework Sleepwalker for verifying and validating autonomous vehicles: Similar to a human sleepwalker, our framework stimulates the automated driving function at a sensor close level with virtual laserscans mixed with sensor data from the real environment. Thus, the autonomous driving function explicitely builds up a mixed reality environment model as a basis for the subsequent components and therefore enables an overall performance assessment. The instantiation of the framework is adaptable so it to can be balanced between the required result's plausibility and scenario criticality. We demonstrate the distinguished benefits of our framework by different instantiations stimulating an autonomous vehicle and conclude with further research questions.","PeriodicalId":156498,"journal":{"name":"2018 IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"The sleepwalker framework: Verification and validation of autonomous vehicles by mixed reality LiDAR stimulation\",\"authors\":\"M. Zofka, Marc Essinger, Tobias Fleck, R. Kohlhaas, Johann Marius Zöllner\",\"doi\":\"10.1109/SIMPAR.2018.8376285\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Verification and validation of autonomous mobile systems, such as autonomous vehicles, is indispensable, since conflicts and serious incidents are rarely acceptable when human beings are involved. Although integrative simulation frameworks are commonly applied to test these systems, such simulations are usually too idealistic, while real world tests are both, expensive and not reproducible. To overcome this problem, we present the framework Sleepwalker for verifying and validating autonomous vehicles: Similar to a human sleepwalker, our framework stimulates the automated driving function at a sensor close level with virtual laserscans mixed with sensor data from the real environment. Thus, the autonomous driving function explicitely builds up a mixed reality environment model as a basis for the subsequent components and therefore enables an overall performance assessment. The instantiation of the framework is adaptable so it to can be balanced between the required result's plausibility and scenario criticality. We demonstrate the distinguished benefits of our framework by different instantiations stimulating an autonomous vehicle and conclude with further research questions.\",\"PeriodicalId\":156498,\"journal\":{\"name\":\"2018 IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIMPAR.2018.8376285\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIMPAR.2018.8376285","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The sleepwalker framework: Verification and validation of autonomous vehicles by mixed reality LiDAR stimulation
Verification and validation of autonomous mobile systems, such as autonomous vehicles, is indispensable, since conflicts and serious incidents are rarely acceptable when human beings are involved. Although integrative simulation frameworks are commonly applied to test these systems, such simulations are usually too idealistic, while real world tests are both, expensive and not reproducible. To overcome this problem, we present the framework Sleepwalker for verifying and validating autonomous vehicles: Similar to a human sleepwalker, our framework stimulates the automated driving function at a sensor close level with virtual laserscans mixed with sensor data from the real environment. Thus, the autonomous driving function explicitely builds up a mixed reality environment model as a basis for the subsequent components and therefore enables an overall performance assessment. The instantiation of the framework is adaptable so it to can be balanced between the required result's plausibility and scenario criticality. We demonstrate the distinguished benefits of our framework by different instantiations stimulating an autonomous vehicle and conclude with further research questions.