{"id":"https://openalex.org/W4402569092","doi":"https://doi.org/10.1109/tits.2024.3456890","title":"Edge Computing Enabled Large-Scale Traffic Flow Prediction With GPT in Intelligent Autonomous Transport System for 6G Network","display_name":"Edge Computing Enabled Large-Scale Traffic Flow Prediction With GPT in Intelligent Autonomous Transport System for 6G Network","publication_year":2024,"publication_date":"2024-09-17","ids":{"openalex":"https://openalex.org/W4402569092","doi":"https://doi.org/10.1109/tits.2024.3456890"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2024.3456890","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3456890","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Yi Rong","orcid":"https://orcid.org/0009-0002-5194-7707"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yi Rong","raw_affiliation_strings":["College of Computer Science and Software Engineering, Hohai University, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0002-5194-7707","affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Hohai University, Nanjing, China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113881053","display_name":"Yingchi Mao","orcid":"https://orcid.org/0000-0002-9884-8100"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingchi Mao","raw_affiliation_strings":["College of Computer Science and Software Engineering, Hohai University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-9884-8100","affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Hohai University, Nanjing, China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068811671","display_name":"Huajun Cui","orcid":"https://orcid.org/0000-0002-5579-195X"},"institutions":[{"id":"https://openalex.org/I4210120238","display_name":"PowerChina (China)","ror":"https://ror.org/01varr368","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210120238"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huajun Cui","raw_affiliation_strings":["Digital Intelligence Research Institute, PowerChina Beijing Engineering Corporation Ltd., Beijing, China","Digital Intelligence Research Institute, PowerChina Beijing Engineering Corporation Ltd, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Digital Intelligence Research Institute, PowerChina Beijing Engineering Corporation Ltd., Beijing, China","institution_ids":["https://openalex.org/I4210120238"]},{"raw_affiliation_string":"Digital Intelligence Research Institute, PowerChina Beijing Engineering Corporation Ltd, Beijing, China","institution_ids":["https://openalex.org/I4210120238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068227459","display_name":"Xiaoming He","orcid":"https://orcid.org/0000-0003-4196-3041"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoming He","raw_affiliation_strings":["College of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100760718","display_name":"Mingkai Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingkai Chen","raw_affiliation_strings":["Key Laboratory of Broadband Wireless Communication and Sensor Network Technology, Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-8826-2587","affiliations":[{"raw_affiliation_string":"Key Laboratory of Broadband Wireless Communication and Sensor Network Technology, Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I163340411"],"apc_list":null,"apc_paid":null,"fwci":7.8654,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.98231181,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"26","issue":"10","first_page":"17321","last_page":"17338"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9459999799728394,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9459999799728394,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5770834684371948},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.5315394401550293},{"id":"https://openalex.org/keywords/flow-network","display_name":"Flow network","score":0.5161041021347046},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4904286563396454},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.41876980662345886},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.387284517288208},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3266274929046631},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.24043118953704834},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21301820874214172},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.19800737500190735},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09983155131340027}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5770834684371948},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.5315394401550293},{"id":"https://openalex.org/C114809511","wikidata":"https://www.wikidata.org/wiki/Q1412924","display_name":"Flow network","level":2,"score":0.5161041021347046},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4904286563396454},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.41876980662345886},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.387284517288208},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3266274929046631},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.24043118953704834},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21301820874214172},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.19800737500190735},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09983155131340027},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2024.3456890","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3456890","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3052520570","display_name":null,"funder_award_id":"2022YFC3005401","funder_id":"https://openalex.org/F4320334010","funder_display_name":"Key Research and Development Program of Ningxia"},{"id":"https://openalex.org/G8939506005","display_name":null,"funder_award_id":"202203AA080009","funder_id":"https://openalex.org/F4320336596","funder_display_name":"Key Research and Development Program of Sichuan Province"}],"funders":[{"id":"https://openalex.org/F4320334010","display_name":"Key Research and Development Program of Ningxia","ror":null},{"id":"https://openalex.org/F4320336596","display_name":"Key Research and Development Program of Sichuan Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1502922572","https://openalex.org/W1970265040","https://openalex.org/W2135099885","https://openalex.org/W2139606794","https://openalex.org/W2158107760","https://openalex.org/W2166292977","https://openalex.org/W2171707538","https://openalex.org/W2572939427","https://openalex.org/W2575125657","https://openalex.org/W2910892140","https://openalex.org/W2963039217","https://openalex.org/W2965341826","https://openalex.org/W2997848713","https://openalex.org/W3113577433","https://openalex.org/W3131157223","https://openalex.org/W3155328257","https://openalex.org/W4210350255","https://openalex.org/W4283794074","https://openalex.org/W4285286407","https://openalex.org/W4291910369","https://openalex.org/W4297095047","https://openalex.org/W4312937689","https://openalex.org/W4320170194","https://openalex.org/W4382318973","https://openalex.org/W4385245566","https://openalex.org/W4385267225","https://openalex.org/W4386918706","https://openalex.org/W4387624003","https://openalex.org/W4387789490","https://openalex.org/W4407838869"],"related_works":["https://openalex.org/W2521728836","https://openalex.org/W2052899165","https://openalex.org/W2008562718","https://openalex.org/W4324372666","https://openalex.org/W4225706866","https://openalex.org/W2994939960","https://openalex.org/W2914646191","https://openalex.org/W4386004629","https://openalex.org/W2942586735","https://openalex.org/W3042990279"],"abstract_inverted_index":{"The":[0,226],"Intelligent":[1],"Autonomous":[2],"Transport":[3],"System":[4],"in":[5,62,81,97,146,238],"6G":[6],"(6G-IATS)":[7],"refers":[8],"to":[9,24,70,84,92,103,199,235],"the":[10,85,94,118,128,163,173,201,205,231,236,239,243],"coordination":[11],"of":[12,114,204,245],"6G,":[13],"Artificial":[14],"Intelligence":[15],"(AI),":[16],"and":[17,47,73,107,137,190,242],"intelligent":[18,27],"transportation":[19,28,45],"systems,":[20],"which":[21,121],"is":[22,68,196,215,233],"expected":[23],"revolutionize":[25],"future":[26],"systems.":[29],"In":[30,157],"6G-IATS,":[31,82,147],"large-scale":[32,75,99,142,165],"traffic":[33,76,143,223],"flow":[34,77,144,224],"prediction,":[35,40],"affiliated":[36],"with":[37],"time":[38,63],"series":[39,64],"holds":[41],"significant":[42],"value":[43],"for":[44,141],"planning":[46],"urban":[48],"management.":[49],"As":[50],"an":[51,176,207],"emerging":[52],"AI":[53],"method,":[54],"Large":[55,151,182,192],"Language":[56,152,183,193],"Models":[57],"(LLMs)":[58],"have":[59],"emerged":[60],"prominently":[61],"forecasting.":[65],"Unfortunately,":[66],"it":[67],"challenging":[69],"achieve":[71],"accurate":[72],"efficient":[74],"prediction":[78,105,145,240],"by":[79],"LLMs":[80,90],"due":[83],"two":[86,129,221],"issues:":[87],"a)":[88],"these":[89],"fail":[91],"capture":[93,172],"spatio-temporal":[95,174],"correlations":[96],"a":[98,111,134],"road":[100,166],"network,":[101],"leading":[102],"limited":[104],"accuracy,":[106],"b)":[108],"they":[109],"process":[110],"substantial":[112],"amount":[113],"training":[115,124,202,209],"data":[116],"on":[117,154,212,220],"central":[119],"server,":[120],"imposes":[122],"low":[123],"efficiency.":[125],"Jointly":[126],"considering":[127],"concerns,":[130],"this":[131,158],"paper":[132],"proposes":[133],"novel":[135],"LLM":[136],"edge":[138,208,213],"computing-based":[139],"architecture":[140],"called":[148],"Spatio-Temporal":[149,180,187],"Generative":[150,181,191],"Model":[153,184,194],"Edge":[155],"(STGLLM-E).":[156],"architecture,":[159],"we":[160],"first":[161],"decompose":[162],"entire":[164],"network":[167],"into":[168],"several":[169],"subgraphs.":[170],"To":[171],"correlations,":[175],"LLM-based":[177],"method":[178],"named":[179],"(STGLLM)":[185],"including":[186],"Module":[188],"(STM)":[189],"(GLLM)":[195],"proposed.":[197],"Secondly,":[198],"improve":[200],"efficiency":[203,244],"STGLLM-E,":[206],"strategy":[210],"based":[211],"servers":[214],"devised.":[216],"Experiments":[217],"are":[218],"conducted":[219],"real-world":[222],"datasets.":[225],"experimental":[227],"results":[228],"illustrate":[229],"that":[230],"STGLLM-E":[232],"superior":[234],"baselines":[237],"accuracy":[241],"training.":[246]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":26},{"year":2024,"cited_by_count":4}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
