Validation of a Radar Sensor Model under non-ideal Conditions for Testing Automated Driving Systems

Diogo Wachtel, S. Schröder, Fabio Reway, W. Huber, M. Vossiek
{"title":"Validation of a Radar Sensor Model under non-ideal Conditions for Testing Automated Driving Systems","authors":"Diogo Wachtel, S. Schröder, Fabio Reway, W. Huber, M. Vossiek","doi":"10.1109/ivworkshops54471.2021.9669205","DOIUrl":null,"url":null,"abstract":"Testing of advanced driver-assistance systems (ADAS) is complex, time-consuming and expensive. Therefore, new methods for the validation of such applications are required. A common solution is the use of virtual validation via environment simulation tools, but their reliability must first be confirmed. For this purpose, a comparison of a real and a simulated radar sensor under adverse weather conditions is performed in this work.To quantify the deviation between reality and the virtual test environment, a complex scenario with multiple traffic objects is set up on the proving ground and in the simulation. The data is measured for clear weather, rain and fog and afterwards compared to validate the performance of the sensor model under those non-ideal conditions.The implemented method shows that both sensors neglect the same traffic objects. Compared to the real radar, the variation of the measured parameters according to changing weather conditions in the simulation tends to be correct, but the values are not completely realistic.Though, the validation method is implemented successfully, in further work the comparison of different sensors is recommended. Furthermore, an in-depth examination of the impact due to varying intensity of rain and fog has to be undertaken.","PeriodicalId":256905,"journal":{"name":"2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ivworkshops54471.2021.9669205","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Testing of advanced driver-assistance systems (ADAS) is complex, time-consuming and expensive. Therefore, new methods for the validation of such applications are required. A common solution is the use of virtual validation via environment simulation tools, but their reliability must first be confirmed. For this purpose, a comparison of a real and a simulated radar sensor under adverse weather conditions is performed in this work.To quantify the deviation between reality and the virtual test environment, a complex scenario with multiple traffic objects is set up on the proving ground and in the simulation. The data is measured for clear weather, rain and fog and afterwards compared to validate the performance of the sensor model under those non-ideal conditions.The implemented method shows that both sensors neglect the same traffic objects. Compared to the real radar, the variation of the measured parameters according to changing weather conditions in the simulation tends to be correct, but the values are not completely realistic.Though, the validation method is implemented successfully, in further work the comparison of different sensors is recommended. Furthermore, an in-depth examination of the impact due to varying intensity of rain and fog has to be undertaken.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
非理想条件下自动驾驶系统雷达传感器模型的验证
高级驾驶辅助系统(ADAS)的测试复杂、耗时且昂贵。因此,需要新的方法来验证这些应用程序。一种常见的解决方案是通过环境仿真工具使用虚拟验证,但它们的可靠性必须首先得到确认。为此,在这项工作中,对恶劣天气条件下的真实雷达传感器和模拟雷达传感器进行了比较。为了量化现实与虚拟测试环境之间的偏差,在试验场和仿真中设置了具有多个交通对象的复杂场景。这些数据是在晴天、雨天和大雾天气下测量的,然后进行比较,以验证传感器模型在这些非理想条件下的性能。实现的方法表明,两个传感器忽略相同的流量对象。与真实雷达相比,模拟中测量参数随天气条件变化的变化趋于正确,但数值并不完全真实。虽然验证方法已经成功实现,但建议在进一步的工作中对不同传感器进行比较。此外,还必须对不同强度的雨和雾造成的影响进行深入研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Trajectory Planning with Comfort and Safety in Dynamic Traffic Scenarios for Autonomous Driving Unsupervised Joint Multi-Task Learning of Vision Geometry Tasks An adaptive cooperative adaptive cruise control against varying vehicle loads* Fundamental Design Criteria for Logical Scenarios in Simulation-based Safety Validation of Automated Driving Using Sensor Model Knowledge Parameter-Based Testing and Debugging of Autonomous Driving Systems
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1