运输中的合作定位 5.0

IF 14 1区 工程技术 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE IEEE Transactions on Intelligent Vehicles Pub Date : 2024-03-18 DOI:10.1109/TIV.2024.3377163
Letian Gao;Xin Xia;Zhaoliang Zheng;Hao Xiang;Zonglin Meng;Xu Han;Zewei Zhou;Yi He;Yutong Wang;Zhaojian Li;Yubiao Zhang;Jiaqi Ma
{"title":"运输中的合作定位 5.0","authors":"Letian Gao;Xin Xia;Zhaoliang Zheng;Hao Xiang;Zonglin Meng;Xu Han;Zewei Zhou;Yi He;Yutong Wang;Zhaojian Li;Yubiao Zhang;Jiaqi Ma","doi":"10.1109/TIV.2024.3377163","DOIUrl":null,"url":null,"abstract":"In the era of future mobility within Transportation 5.0, autonomy and cooperation across all road users and smart infrastructure stand as the key features to enhance transportation safety, efficiency, and sustainability, supported by cooperative perception, decision-making and planning, and control. An accurate and robust localization system plays a vital role in enabling these modules for future mobility and is constrained by environmental uncertainties and sensing limitations. To achieve precise and resilient localization in this new era, this letter introduces emerging technologies including edge computing, hybrid data-driven and physical model approaches, foundation models as well as parallel intelligence, that are beneficial for next-generation localization systems. On top of these key technologies, by integrating real-world testing and digital twin technology, we further put forward a Decentralized Autonomous Service (DAS)-based cooperative localization framework for future mobility systems to enhance the resilience, robustness, and safety of transportation systems.","PeriodicalId":36532,"journal":{"name":"IEEE Transactions on Intelligent Vehicles","volume":"9 3","pages":"4259-4264"},"PeriodicalIF":14.0000,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cooperative Localization in Transportation 5.0\",\"authors\":\"Letian Gao;Xin Xia;Zhaoliang Zheng;Hao Xiang;Zonglin Meng;Xu Han;Zewei Zhou;Yi He;Yutong Wang;Zhaojian Li;Yubiao Zhang;Jiaqi Ma\",\"doi\":\"10.1109/TIV.2024.3377163\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the era of future mobility within Transportation 5.0, autonomy and cooperation across all road users and smart infrastructure stand as the key features to enhance transportation safety, efficiency, and sustainability, supported by cooperative perception, decision-making and planning, and control. An accurate and robust localization system plays a vital role in enabling these modules for future mobility and is constrained by environmental uncertainties and sensing limitations. To achieve precise and resilient localization in this new era, this letter introduces emerging technologies including edge computing, hybrid data-driven and physical model approaches, foundation models as well as parallel intelligence, that are beneficial for next-generation localization systems. On top of these key technologies, by integrating real-world testing and digital twin technology, we further put forward a Decentralized Autonomous Service (DAS)-based cooperative localization framework for future mobility systems to enhance the resilience, robustness, and safety of transportation systems.\",\"PeriodicalId\":36532,\"journal\":{\"name\":\"IEEE Transactions on Intelligent Vehicles\",\"volume\":\"9 3\",\"pages\":\"4259-4264\"},\"PeriodicalIF\":14.0000,\"publicationDate\":\"2024-03-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Intelligent Vehicles\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10472068/\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Intelligent Vehicles","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10472068/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

摘要

在未来交通 5.0 时代,在合作感知、决策、规划和控制的支持下,所有道路使用者和智能基础设施的自主与合作是提高交通安全、效率和可持续性的关键特征。准确而稳健的定位系统在实现未来移动性的这些模块中发挥着至关重要的作用,并受到环境不确定性和传感限制的制约。为了在这个新时代实现精确而有弹性的定位,这封信介绍了边缘计算、混合数据驱动和物理模型方法、基础模型以及并行智能等新兴技术,这些技术对下一代定位系统大有裨益。在这些关键技术的基础上,通过整合真实世界测试和数字孪生技术,我们进一步为未来的移动系统提出了基于分散式自主服务(DAS)的合作定位框架,以增强交通系统的弹性、稳健性和安全性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Cooperative Localization in Transportation 5.0
In the era of future mobility within Transportation 5.0, autonomy and cooperation across all road users and smart infrastructure stand as the key features to enhance transportation safety, efficiency, and sustainability, supported by cooperative perception, decision-making and planning, and control. An accurate and robust localization system plays a vital role in enabling these modules for future mobility and is constrained by environmental uncertainties and sensing limitations. To achieve precise and resilient localization in this new era, this letter introduces emerging technologies including edge computing, hybrid data-driven and physical model approaches, foundation models as well as parallel intelligence, that are beneficial for next-generation localization systems. On top of these key technologies, by integrating real-world testing and digital twin technology, we further put forward a Decentralized Autonomous Service (DAS)-based cooperative localization framework for future mobility systems to enhance the resilience, robustness, and safety of transportation systems.
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
IEEE Transactions on Intelligent Vehicles
IEEE Transactions on Intelligent Vehicles Mathematics-Control and Optimization
CiteScore
12.10
自引率
13.40%
发文量
177
期刊介绍: The IEEE Transactions on Intelligent Vehicles (T-IV) is a premier platform for publishing peer-reviewed articles that present innovative research concepts, application results, significant theoretical findings, and application case studies in the field of intelligent vehicles. With a particular emphasis on automated vehicles within roadway environments, T-IV aims to raise awareness of pressing research and application challenges. Our focus is on providing critical information to the intelligent vehicle community, serving as a dissemination vehicle for IEEE ITS Society members and others interested in learning about the state-of-the-art developments and progress in research and applications related to intelligent vehicles. Join us in advancing knowledge and innovation in this dynamic field.
期刊最新文献
Table of Contents Introducing IEEE Collabratec The Autonomous Right of Way: Smart Governance for Smart Mobility With Intelligent Vehicles TechRxiv: Share Your Preprint Research with the World! Blank
×
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