{"id":"https://openalex.org/W4312885537","doi":"https://doi.org/10.1109/pimrc54779.2022.9977794","title":"Spatiotemporal Graph Attention Networks for Urban Traffic Flow Prediction","display_name":"Spatiotemporal Graph Attention Networks for Urban Traffic Flow Prediction","publication_year":2022,"publication_date":"2022-09-12","ids":{"openalex":"https://openalex.org/W4312885537","doi":"https://doi.org/10.1109/pimrc54779.2022.9977794"},"language":"en","primary_location":{"id":"doi:10.1109/pimrc54779.2022.9977794","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pimrc54779.2022.9977794","pdf_url":null,"source":{"id":"https://openalex.org/S4363605306","display_name":"2022 IEEE 33rd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 33rd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5001147575","display_name":"Yuanpeng Zhao","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":"Yuanpeng Zhao","raw_affiliation_strings":["School of Internet of Things Nanjing University of Posts and Telecommunications,Nanjing,China","School of Internet of Things Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Internet of Things Nanjing University of Posts and Telecommunications,Nanjing,China","institution_ids":["https://openalex.org/I41198531"]},{"raw_affiliation_string":"School of Internet of Things Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010821185","display_name":"Yepeng Xu","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":"Yepeng Xu","raw_affiliation_strings":["School of Internet of Things Nanjing University of Posts and Telecommunications,Nanjing,China","School of Internet of Things Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Internet of Things Nanjing University of Posts and Telecommunications,Nanjing,China","institution_ids":["https://openalex.org/I41198531"]},{"raw_affiliation_string":"School of Internet of Things Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040651921","display_name":"Xitao He","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":"Xitao He","raw_affiliation_strings":["School of Internet of Things Nanjing University of Posts and Telecommunications,Nanjing,China","School of Internet of Things Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Internet of Things Nanjing University of Posts and Telecommunications,Nanjing,China","institution_ids":["https://openalex.org/I41198531"]},{"raw_affiliation_string":"School 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/A5076984228","display_name":"Dengyin Zhang","orcid":"https://orcid.org/0000-0001-6080-6151"},"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":"Dengyin Zhang","raw_affiliation_strings":["School of Internet of Things Nanjing University of Posts and Telecommunications,Nanjing,China","School of Internet of Things Nanjing University of Posts and Telecommunications, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Internet of Things Nanjing University of Posts and Telecommunications,Nanjing,China","institution_ids":["https://openalex.org/I41198531"]},{"raw_affiliation_string":"School of Internet of Things Nanjing University of Posts and Telecommunications, Nanjing, China","institution_ids":["https://openalex.org/I41198531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I41198531"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"340","last_page":"345"},"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":0.9954000115394592,"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":0.994700014591217,"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":0.725107729434967},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.6696391105651855},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5284155607223511},{"id":"https://openalex.org/keywords/traffic-generation-model","display_name":"Traffic generation model","score":0.5194225311279297},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.4835774302482605},{"id":"https://openalex.org/keywords/flow-network","display_name":"Flow network","score":0.4413383901119232},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43244418501853943},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4196470379829407},{"id":"https://openalex.org/keywords/traffic-speed","display_name":"Traffic speed","score":0.4180963337421417},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.41117599606513977},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3087228238582611},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.17781004309654236},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.15953117609024048},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.1404782235622406},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12733709812164307},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08094415068626404}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.725107729434967},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.6696391105651855},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5284155607223511},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.5194225311279297},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.4835774302482605},{"id":"https://openalex.org/C114809511","wikidata":"https://www.wikidata.org/wiki/Q1412924","display_name":"Flow network","level":2,"score":0.4413383901119232},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43244418501853943},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4196470379829407},{"id":"https://openalex.org/C2993660032","wikidata":"https://www.wikidata.org/wiki/Q746984","display_name":"Traffic speed","level":2,"score":0.4180963337421417},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.41117599606513977},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3087228238582611},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.17781004309654236},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.15953117609024048},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.1404782235622406},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12733709812164307},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08094415068626404},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/pimrc54779.2022.9977794","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pimrc54779.2022.9977794","pdf_url":null,"source":{"id":"https://openalex.org/S4363605306","display_name":"2022 IEEE 33rd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 33rd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.8399999737739563}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W626441390","https://openalex.org/W1971741995","https://openalex.org/W2041567331","https://openalex.org/W2083238230","https://openalex.org/W2090192376","https://openalex.org/W2145039203","https://openalex.org/W2157331557","https://openalex.org/W2165991108","https://openalex.org/W2528639018","https://openalex.org/W2573587735","https://openalex.org/W2613331518","https://openalex.org/W2903871660","https://openalex.org/W2921685418","https://openalex.org/W2963358464","https://openalex.org/W2964015378","https://openalex.org/W2965806703","https://openalex.org/W2997848713","https://openalex.org/W3092125438","https://openalex.org/W3103720336","https://openalex.org/W3108550173","https://openalex.org/W3204085121","https://openalex.org/W3204365986","https://openalex.org/W4297733535","https://openalex.org/W6726873649"],"related_works":["https://openalex.org/W2149721642","https://openalex.org/W2587362999","https://openalex.org/W432084041","https://openalex.org/W2394010358","https://openalex.org/W2361078351","https://openalex.org/W2986732134","https://openalex.org/W4239349137","https://openalex.org/W1463884142","https://openalex.org/W2963251637","https://openalex.org/W239469043"],"abstract_inverted_index":{"Short-term":[0],"traffic":[1,18,81,96,111,119,131],"flow":[2,24,97,120],"forecasting":[3],"is":[4,10,25,59,138,157],"a":[5,61,72,85,100],"challenging":[6,62],"subject,":[7],"and":[8,20,36,43,47,98,144],"it":[9],"of":[11,31,40,110,122,130,154],"great":[12],"significance":[13],"for":[14],"travel":[15],"route":[16],"planning,":[17],"regulation":[19],"other":[21,160],"directions.":[22],"Traffic":[23],"affected":[26],"by":[27],"the":[28,32,37,54,80,91,95,108,118,127,136,145,151,155],"topological":[29],"structure":[30],"urban":[33],"road":[34,82],"network":[35,83,88],"dynamic":[38],"changes":[39],"time":[41],"series,":[42],"has":[44],"both":[45],"temporal":[46],"spatial":[48,92],"characteristics.":[49],"However,":[50],"how":[51],"to":[52,66,105,125,159],"extract":[53],"correlation":[55],"between":[56],"spatiotemporal":[57],"features":[58,121],"still":[60],"task.":[63],"In":[64,114,133],"response":[65],"these":[67],"problems,":[68],"this":[69,134],"paper":[70],"proposes":[71],"new":[73],"deep":[74],"learning":[75],"model":[76,137,156],"(GAGRU),":[77],"which":[78],"models":[79],"through":[84],"graph":[86],"attention":[87],"(GAT),":[89],"extracts":[90],"dependencies":[93],"in":[94],"uses":[99],"gated":[101],"recurrent":[102],"unit":[103],"(GRU)":[104],"focus":[106],"on":[107],"Characteristics":[109],"over":[112],"time.":[113],"addition,":[115],"we":[116],"fuse":[117],"multiple":[123],"sequences":[124],"consider":[126],"periodic":[128],"characteristics":[129],"flow.":[132],"paper,":[135],"experimentally":[139],"validated":[140],"using":[141],"real-world":[142],"datasets,":[143],"final":[146],"experimental":[147],"results":[148],"show":[149],"that":[150],"prediction":[152],"accuracy":[153],"superior":[158],"baseline":[161],"methods.":[162]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}