{"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}
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.
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.