“汽车雷达——自动驾驶的关键技术:从探测和测距到环境理解”

J. Dickmann, J. Klappstein, Markus Hahn, N. Appenrodt, H. Bloecher, K. Werber, A. Sailer
{"title":"“汽车雷达——自动驾驶的关键技术:从探测和测距到环境理解”","authors":"J. Dickmann, J. Klappstein, Markus Hahn, N. Appenrodt, H. Bloecher, K. Werber, A. Sailer","doi":"10.1109/RADAR.2016.7485214","DOIUrl":null,"url":null,"abstract":"An overview on state of the art automotive radar usage is presented and the changing requirements from detection and ranging towards radar based environmental understanding for highly automated and autonomous driving deduced. The traditional segmentation in driving, manoeuvering and parking tasks vanishes at the driver less stage. Situation assessment and trajectory/manoeuver planning need to operate in a more thorough way. Hence, fast situational up-date, motion prediction of all kind of dynamic objects, object dimension, ego-motion estimation, (self)-localisation and more semantic/classification information, which allows to put static and dynamic world into correlation/context with each other is mandatory. All these are new areas for radar signal processing and needs revolutionary new solutions. The article outlines the benefits that make radar essential for autonomous driving and presents recent approaches in radar based environmental perception.","PeriodicalId":185932,"journal":{"name":"2016 IEEE Radar Conference (RadarConf)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"149","resultStr":"{\"title\":\"\\\"Automotive radar the key technology for autonomous driving: From detection and ranging to environmental understanding\\\"\",\"authors\":\"J. Dickmann, J. Klappstein, Markus Hahn, N. Appenrodt, H. Bloecher, K. Werber, A. Sailer\",\"doi\":\"10.1109/RADAR.2016.7485214\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An overview on state of the art automotive radar usage is presented and the changing requirements from detection and ranging towards radar based environmental understanding for highly automated and autonomous driving deduced. The traditional segmentation in driving, manoeuvering and parking tasks vanishes at the driver less stage. Situation assessment and trajectory/manoeuver planning need to operate in a more thorough way. Hence, fast situational up-date, motion prediction of all kind of dynamic objects, object dimension, ego-motion estimation, (self)-localisation and more semantic/classification information, which allows to put static and dynamic world into correlation/context with each other is mandatory. All these are new areas for radar signal processing and needs revolutionary new solutions. The article outlines the benefits that make radar essential for autonomous driving and presents recent approaches in radar based environmental perception.\",\"PeriodicalId\":185932,\"journal\":{\"name\":\"2016 IEEE Radar Conference (RadarConf)\",\"volume\":\"88 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-05-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"149\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE Radar Conference (RadarConf)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RADAR.2016.7485214\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Radar Conference (RadarConf)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RADAR.2016.7485214","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 149

摘要

概述了最先进的汽车雷达的使用状况,并推断了从探测和测距到基于雷达的高度自动化和自动驾驶环境理解的不断变化的需求。在无人驾驶阶段,传统的驾驶、机动和停车任务的分割消失了。态势评估和弹道/机动计划需要以更彻底的方式运作。因此,快速的态势更新、各种动态物体的运动预测、物体维度、自我运动估计、(自我)定位以及更多的语义/分类信息,这些都是必须的,它们允许将静态和动态世界置于相互关联/上下文中。所有这些都是雷达信号处理的新领域,需要革命性的新解决方案。本文概述了雷达对自动驾驶至关重要的好处,并介绍了基于雷达的环境感知的最新方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
"Automotive radar the key technology for autonomous driving: From detection and ranging to environmental understanding"
An overview on state of the art automotive radar usage is presented and the changing requirements from detection and ranging towards radar based environmental understanding for highly automated and autonomous driving deduced. The traditional segmentation in driving, manoeuvering and parking tasks vanishes at the driver less stage. Situation assessment and trajectory/manoeuver planning need to operate in a more thorough way. Hence, fast situational up-date, motion prediction of all kind of dynamic objects, object dimension, ego-motion estimation, (self)-localisation and more semantic/classification information, which allows to put static and dynamic world into correlation/context with each other is mandatory. All these are new areas for radar signal processing and needs revolutionary new solutions. The article outlines the benefits that make radar essential for autonomous driving and presents recent approaches in radar based environmental perception.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信