{"title":"道路网络从opdrive到Lanelets的自动转换","authors":"M. Althoff, S. Urban, Markus Koschi","doi":"10.1109/SOLI.2018.8476801","DOIUrl":null,"url":null,"abstract":"Detailed road maps are an important building block for autonomous driving. They accelerate creating a semantic environment model within the vehicle and serve as a backup solution when sensors are occluded or otherwise impaired. Due to the required detail of maps for autonomous driving and virtual test drives, creating such maps is quite labor-intensive. While some detailed maps for fairly large regions already exist, they are often in different formats and thus cannot be exchanged between companies and research institutions. To address this problem, we present the first publicly available converter from the OpenDRIVE format to lanelets—both representations are among the most popular map formats. We demonstrate the capabilities of the converter by using publicly available maps.","PeriodicalId":424115,"journal":{"name":"2018 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"30","resultStr":"{\"title\":\"Automatic Conversion of Road Networks from OpenDRIVE to Lanelets\",\"authors\":\"M. Althoff, S. Urban, Markus Koschi\",\"doi\":\"10.1109/SOLI.2018.8476801\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Detailed road maps are an important building block for autonomous driving. They accelerate creating a semantic environment model within the vehicle and serve as a backup solution when sensors are occluded or otherwise impaired. Due to the required detail of maps for autonomous driving and virtual test drives, creating such maps is quite labor-intensive. While some detailed maps for fairly large regions already exist, they are often in different formats and thus cannot be exchanged between companies and research institutions. To address this problem, we present the first publicly available converter from the OpenDRIVE format to lanelets—both representations are among the most popular map formats. We demonstrate the capabilities of the converter by using publicly available maps.\",\"PeriodicalId\":424115,\"journal\":{\"name\":\"2018 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"30\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SOLI.2018.8476801\",\"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 Service Operations and Logistics, and Informatics (SOLI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SOLI.2018.8476801","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic Conversion of Road Networks from OpenDRIVE to Lanelets
Detailed road maps are an important building block for autonomous driving. They accelerate creating a semantic environment model within the vehicle and serve as a backup solution when sensors are occluded or otherwise impaired. Due to the required detail of maps for autonomous driving and virtual test drives, creating such maps is quite labor-intensive. While some detailed maps for fairly large regions already exist, they are often in different formats and thus cannot be exchanged between companies and research institutions. To address this problem, we present the first publicly available converter from the OpenDRIVE format to lanelets—both representations are among the most popular map formats. We demonstrate the capabilities of the converter by using publicly available maps.