[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-118187-en":3,"doc-seo-118187-105":30,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},118187,8796095461564,"Liam","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Machine Learning-Aided Cooperative Localization under Dense Urban Environment - Abstract","Future wireless networks connect automobiles to support cooperative vehicular driving tasks, where machine learning can enhance robustness in localization and control. Localization becomes intractable as infrastructure scale grows when relying on centralized positioning. The approach presented uses a decentralized vehicular localization principle strengthened by machine learning for dense urban scenarios with frequent unreliable measurements. Vehicle collaboration improves positioning, and a virtual testbed validates feasibility for real-map networks.","arXiv :2404 .04096v 1 [ cs .IT] 5 Apr 2024  \nMachine Learning-Aided Cooperative Localization under Dense Urban Environment  \nHoon Lee, Hong Ki Kim, Seung Hyun Oh, and Sang Hyun Lee  \nAbstract  \nFuture wireless network technology provides automobiles with the connectivity feature to consolidate the concept of vehicular networks that collaborate on conducting cooperative driving tasks. The full potential of connected vehicles, which promises road safety and quality driving experience, can be leveraged if machine learning models guarantee the robustness in performing core functions including localization and controls. Location awareness, in particular, lends itself to the deployment of location-specific services and the improvement of the operation performance. The localization entails direct communication to the network infrastructure, and the resulting centralized positioning solutions readily become intractable as the network scales up. As an alternative to the centralized solutions, this article addresses decentralized principle of vehicular localization reinforced by machine learning techniques in dense urban environments with frequent inaccessibility to reliable measurement. As such, the collaboration of multiple vehicles enhances the positioning performance of machine learning approaches. A virtual testbed is developed to validate this machine learning model for real-map vehicular networks. Numerical results demonstrate universal feasibility of cooperative localization, in particular, for dense urban area configurations.  \nI. INTRODUCTION  \nRapid advances in automobile industry and information technology transform cars from traditional means of transportation to information-oriented commuting machines on the go [1] . Outfitting automobiles with wireless capabilities yields proactive and cooperative connection solutions that enable on-board network access, energy-cost reduction, and location-dependent  \nH. Lee is with the Department of Electrical Engineering and the Artificial Intelligence Graduate School, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919, Korea.  \nH. K. Kim, S. H. Oh, and S. H. Lee are with the School of Electrical Engineering, Korea University, Seoul 02841, Korea (e-mail: [sanghyunlee@korea.ac.kr](sanghyunlee@korea.ac.kr)).  \nservices [2] . Efficient coupling of such features also provides foundations for the realization of autonomous driving with promise of improving road safety and transporting mobility-impaired populations. Vehicles leverage vehicle-to-everything (V2X) communication to share information in real-time, and their basic operations can be distributed among neighboring vehicles [3] . Public interest in such services is booming, and their market potential is projected to reach nearly $800 billion by 2050 [4] .  \nLocation awareness, realized by identifying physical ego-positions of vehicles, enables to launch service of location-based applications and places fundamental requirements for global navigation [5] . The integration of mobile objects improves connectivity and coverage of the network to provide essential information since additional measurements can be collected. For ultra-reliable positioning, intensive research has been studied on localization via built-in V2X infrastructure [6], [7] . The nature of localization solutions depends on what types of measurements are acquired and how measurements are processed whether by central computing units orin decentralized fashion using in-vehicle computing.  \nGlobal navigation satellite systems (GNSSs) have been widely adopted for vehicular localization. However, GNSS measurements are often inaccessible in harsh environments, in particular, urban areas of densely located signal-blocking obstacles. Although dead reckoning in time intervals with absolute GNSS readings envisions to calculate current positions of vehicles, its uncertainty on blockage limits the localization accuracy. Thus, efficient and low-cost localization d","cbCaiePiujz6V0aN","https://ap.wps.com/l/cbCaiePiujz6V0aN","pdf",5205040,1,18,"English","en",105,"# Abstract\n# I. Introduction","[{\"question\":\"Why does centralized vehicular localization become intractable at scale?\",\"answer\":\"Centralized positioning requires direct communication to network infrastructure, and the approach becomes difficult to manage as the network scales up.\"},{\"question\":\"What problem does the paper address in dense urban environments?\",\"answer\":\"It addresses decentralized localization when reliable measurements are frequently inaccessible due to challenging urban conditions and measurement limitations.\"},{\"question\":\"How does machine learning improve cooperative localization in the proposed framework?\",\"answer\":\"The framework uses an ML-based decentralized collaborative localization mechanism where multiple vehicles share local information and improve positioning performance.\"}]","Machine Learning-Aided Cooperative Localization under Dense Urban Environment - Abstract | PDF",1785682085,45,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":28},"machine-learning-aided-cooperative-localization-under-dense-urban-environment-abstract","",{"@graph":36,"@context":86},[37,54,69],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/machine-learning-aided-cooperative-localization-under-dense-urban-environment-abstract/118187/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05","2026-08-02",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"Why does centralized vehicular localization become intractable at scale?","Question",{"text":76,"@type":77},"Centralized positioning requires direct communication to network infrastructure, and the approach becomes difficult to manage as the network scales up.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"What problem does the paper address in dense urban environments?",{"text":81,"@type":77},"It addresses decentralized localization when reliable measurements are frequently inaccessible due to challenging urban conditions and measurement limitations.",{"name":83,"@type":74,"acceptedAnswer":84},"How does machine learning improve cooperative localization in the proposed framework?",{"text":85,"@type":77},"The framework uses an ML-based decentralized collaborative localization mechanism where multiple vehicles share local information and improve positioning performance.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":46,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":46,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":46,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":46,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":46,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":46,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]