{"id":"https://openalex.org/W4285286407","doi":"https://doi.org/10.1109/tits.2022.3185503","title":"Spatial-Temporal Attention Graph Convolution Network on Edge Cloud for Traffic Flow Prediction","display_name":"Spatial-Temporal Attention Graph Convolution Network on Edge Cloud for Traffic Flow Prediction","publication_year":2022,"publication_date":"2022-07-07","ids":{"openalex":"https://openalex.org/W4285286407","doi":"https://doi.org/10.1109/tits.2022.3185503"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2022.3185503","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3185503","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":"https://openalex.org/A5080515847","display_name":"Qifeng Lai","orcid":"https://orcid.org/0000-0003-4260-4681"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qifeng Lai","raw_affiliation_strings":["School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-4260-4681","affiliations":[{"raw_affiliation_string":"School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101902782","display_name":"Jinyu Tian","orcid":"https://orcid.org/0000-0002-2449-5277"},"institutions":[{"id":"https://openalex.org/I111950717","display_name":"Macau University of Science and Technology","ror":"https://ror.org/03jqs2n27","country_code":"MO","type":"education","lineage":["https://openalex.org/I111950717","https://openalex.org/I4391767947"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Jinyu Tian","raw_affiliation_strings":["School of Computer Science and Engineering, Macau University of Science and Technology, Taipa, Macau"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Macau University of Science and Technology, Taipa, Macau","institution_ids":["https://openalex.org/I111950717"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wei Wang","orcid":"https://orcid.org/0000-0002-5987-738X"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Wang","raw_affiliation_strings":["School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-5987-738X","affiliations":[{"raw_affiliation_string":"School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007941489","display_name":"Xiping Hu","orcid":"https://orcid.org/0000-0002-4952-699X"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiping Hu","raw_affiliation_strings":["School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.8889,"has_fulltext":false,"cited_by_count":34,"citation_normalized_percentile":{"value":0.91029318,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"24","issue":"4","first_page":"4565","last_page":"4576"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":1.0,"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":1.0,"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"}},{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.9911999702453613,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7506614923477173},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.7284467220306396},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.593454897403717},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.47017115354537964},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.4619162082672119},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.45604896545410156},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.44437214732170105},{"id":"https://openalex.org/keywords/traffic-congestion","display_name":"Traffic congestion","score":0.4275122582912445},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4165725111961365},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24047574400901794},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14992767572402954},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.12030497193336487}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7506614923477173},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.7284467220306396},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.593454897403717},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.47017115354537964},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.4619162082672119},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.45604896545410156},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44437214732170105},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.4275122582912445},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4165725111961365},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24047574400901794},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14992767572402954},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.12030497193336487},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2022.3185503","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3185503","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":[{"id":"https://metadata.un.org/sdg/11","score":0.7400000095367432,"display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G8526955030","display_name":null,"funder_award_id":"52102400","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W43001522","https://openalex.org/W637153065","https://openalex.org/W1662382123","https://openalex.org/W1854214752","https://openalex.org/W1924770834","https://openalex.org/W1970265040","https://openalex.org/W2024558842","https://openalex.org/W2029657381","https://openalex.org/W2064675550","https://openalex.org/W2082454007","https://openalex.org/W2083238230","https://openalex.org/W2090715271","https://openalex.org/W2133564696","https://openalex.org/W2137541292","https://openalex.org/W2165991108","https://openalex.org/W2166292977","https://openalex.org/W2171707538","https://openalex.org/W2372844811","https://openalex.org/W2392395307","https://openalex.org/W2392708022","https://openalex.org/W2533328922","https://openalex.org/W2550245413","https://openalex.org/W2606202972","https://openalex.org/W2754025451","https://openalex.org/W2756203131","https://openalex.org/W2781091734","https://openalex.org/W2782977972","https://openalex.org/W2798466145","https://openalex.org/W2885727112","https://openalex.org/W2892190444","https://openalex.org/W2901504064","https://openalex.org/W2903871660","https://openalex.org/W2962813278","https://openalex.org/W2963039217","https://openalex.org/W2964015378","https://openalex.org/W2964199361","https://openalex.org/W2964321699","https://openalex.org/W2964335123","https://openalex.org/W2991205212","https://openalex.org/W2996847713","https://openalex.org/W3006854884","https://openalex.org/W3103720336","https://openalex.org/W3113577433","https://openalex.org/W3130499959","https://openalex.org/W3131157223","https://openalex.org/W3133663379","https://openalex.org/W3170708168","https://openalex.org/W3204586135","https://openalex.org/W4206006196","https://openalex.org/W6620673361","https://openalex.org/W6637178625","https://openalex.org/W6640212811","https://openalex.org/W6679434410","https://openalex.org/W6720006811","https://openalex.org/W6726873649"],"related_works":["https://openalex.org/W4324372666","https://openalex.org/W4225706866","https://openalex.org/W2914646191","https://openalex.org/W4322761281","https://openalex.org/W4238233472","https://openalex.org/W4313339048","https://openalex.org/W3111395152","https://openalex.org/W4313526662","https://openalex.org/W3023564924","https://openalex.org/W2942586735"],"abstract_inverted_index":{"Accurate":[0],"short-term":[1,38],"traffic":[2,39,58,69,142,206],"flow":[3,40],"prediction":[4,54],"plays":[5],"an":[6],"important":[7],"role":[8],"in":[9,14,221,239],"providing":[10],"road":[11],"condition":[12],"information":[13],"the":[15,19,27,53,56,67,82,103,112,116,140,159,179,193,228,246],"immediate":[16],"future.":[17],"With":[18],"information,":[20],"intelligent":[21],"vehicles":[22],"can":[23],"plan":[24],"and":[25,76,114,151,187,204,218,242],"adjust":[26],"route":[28],"to":[29,45,63,87,147,161,174,200,223],"prevent":[30],"congestion.":[31],"As":[32],"a":[33,73,77,96,126,162],"result,":[34],"many":[35],"models":[36],"for":[37,80,167],"forecasting":[41],"have":[42,72],"been":[43],"proposed":[44],"date.":[46],"However,":[47],"most":[48],"of":[49,55,99,118,158],"them":[50],"focus":[51],"on":[52,102,111,132,178],"entire":[57,68,141],"network,":[59],"which":[60,81],"could":[61,71,106],"lead":[62],"several":[64,145],"problems:":[65],"(1)":[66],"network":[70,143,160],"large":[74,97],"scale":[75,150],"complex":[78],"structure,":[79],"model":[83,135,235],"training":[84,100],"is":[85,171],"likely":[86],"be":[88],"time-consuming":[89],"as":[90,92],"well":[91,237],"inefficient;":[93],"(2)":[94],"processing":[95],"amount":[98],"data":[101,177],"central":[104,180],"cloud":[105],"cause":[107],"much":[108],"calculation":[109],"pressure":[110],"server":[113],"increase":[115],"risk":[117],"privacy":[119],"leakage.":[120],"In":[121],"this":[122],"paper,":[123],"we":[124,154,183,210,230],"propose":[125],"Spatial-Temporal":[127],"Attention":[128],"Graph":[129],"Convolution":[130],"Network":[131],"Edge":[133],"Cloud":[134],"(STAGCN-EC).":[136],"We":[137],"first":[138],"divide":[139],"into":[144],"parts":[146],"reduce":[148],"its":[149],"complexity.":[152],"Then,":[153],"allocate":[155],"each":[156],"part":[157],"certain":[163],"Roadside":[164],"Unit":[165],"(RSU)":[166],"training,":[168],"thus":[169],"there":[170],"no":[172],"need":[173],"process":[175],"all":[176],"server.":[181],"Besides,":[182],"utilize":[184],"spatial-temporal":[185,202],"attention":[186],"features":[188],"extracting":[189],"module":[190],"that":[191,233],"fits":[192],"low":[194],"computational":[195],"power":[196],"devices":[197],"like":[198],"RSUs,":[199],"capture":[201],"dependence":[203],"predict":[205],"flow.":[207],"At":[208],"last,":[209],"use":[211],"two":[212],"highway":[213],"datasets":[214],"from":[215],"District":[216,219],"7":[217],"4":[220],"California":[222],"validate":[224],"our":[225,234],"model.":[226],"Through":[227],"experiments,":[229],"find":[231],"out":[232],"performs":[236],"both":[238],"predicted":[240],"precision":[241],"efficiency":[243],"compared":[244],"with":[245],"five":[247],"baseline":[248],"methods.":[249]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":10}],"updated_date":"2026-07-16T13:24:37.021932","created_date":"2025-10-10T00:00:00"}
