Michael Weber, Tobias Weiss, Franck Gechter, Reiner Kriesten
{"title":"Approach for improved development of advanced driver assistance systems for future smart mobility concepts","authors":"Michael Weber, Tobias Weiss, Franck Gechter, Reiner Kriesten","doi":"10.1007/s43684-023-00047-5","DOIUrl":null,"url":null,"abstract":"<div><p>To use the benefits of Advanced Driver Assistance Systems (ADAS)-Tests in simulation and reality a new approach for using Augmented Reality (AR) in an automotive vehicle for testing ADAS is presented in this paper. Our procedure provides a link between simulation and reality and should enable a faster development process for future increasingly complex ADAS tests and future mobility solutions. Test fields for ADAS offer a small number of orientation points. Furthermore, these must be detected and processed at high vehicle speeds. That requires high computational power both for developing our method and its subsequent use in testing. Using image segmentation (IS), artificial intelligence (AI) for object recognition, and visual simultaneous localization and mapping (vSLAM), we aim to create a three-dimensional model with accurate information about the test site. It is expected that using AI and IS will significantly improve performance as computational speed and accuracy for AR applications in automobiles.</p></div>","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"3 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43684-023-00047-5.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"自主智能系统(英文)","FirstCategoryId":"1093","ListUrlMain":"https://link.springer.com/article/10.1007/s43684-023-00047-5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
To use the benefits of Advanced Driver Assistance Systems (ADAS)-Tests in simulation and reality a new approach for using Augmented Reality (AR) in an automotive vehicle for testing ADAS is presented in this paper. Our procedure provides a link between simulation and reality and should enable a faster development process for future increasingly complex ADAS tests and future mobility solutions. Test fields for ADAS offer a small number of orientation points. Furthermore, these must be detected and processed at high vehicle speeds. That requires high computational power both for developing our method and its subsequent use in testing. Using image segmentation (IS), artificial intelligence (AI) for object recognition, and visual simultaneous localization and mapping (vSLAM), we aim to create a three-dimensional model with accurate information about the test site. It is expected that using AI and IS will significantly improve performance as computational speed and accuracy for AR applications in automobiles.