{"id":"https://openalex.org/W4312262053","doi":"https://doi.org/10.1109/tits.2022.3220089","title":"Spatial-Temporal Position-Aware Graph Convolution Networks for Traffic Flow Forecasting","display_name":"Spatial-Temporal Position-Aware Graph Convolution Networks for Traffic Flow Forecasting","publication_year":2022,"publication_date":"2022-11-10","ids":{"openalex":"https://openalex.org/W4312262053","doi":"https://doi.org/10.1109/tits.2022.3220089"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2022.3220089","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3220089","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/A5049828136","display_name":"Yiji Zhao","orcid":"https://orcid.org/0000-0001-8248-9441"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiji Zhao","raw_affiliation_strings":["Beijing Key Laboratory of Traffic Data Analysis and Mining, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8248-9441","affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Traffic Data Analysis and Mining, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102790320","display_name":"Youfang Lin","orcid":"https://orcid.org/0000-0002-1611-4323"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youfang Lin","raw_affiliation_strings":["Beijing Key Laboratory of Traffic Data Analysis and Mining, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-1611-4323","affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Traffic Data Analysis and Mining, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018234604","display_name":"Haomin Wen","orcid":"https://orcid.org/0000-0001-6130-126X"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haomin Wen","raw_affiliation_strings":["Beijing Key Laboratory of Traffic Data Analysis and Mining, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6130-126X","affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Traffic Data Analysis and Mining, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037218624","display_name":"Tonglong Wei","orcid":"https://orcid.org/0000-0002-7387-1363"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tonglong Wei","raw_affiliation_strings":["Beijing Key Laboratory of Traffic Data Analysis and Mining, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7387-1363","affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Traffic Data Analysis and Mining, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074391764","display_name":"Xiyuan Jin","orcid":"https://orcid.org/0000-0001-8201-2299"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiyuan Jin","raw_affiliation_strings":["Beijing Key Laboratory of Traffic Data Analysis and Mining, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8201-2299","affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Traffic Data Analysis and Mining, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065949777","display_name":"Huaiyu Wan","orcid":"https://orcid.org/0000-0002-0501-9363"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huaiyu Wan","raw_affiliation_strings":["Beijing Key Laboratory of Traffic Data Analysis and Mining, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0501-9363","affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Traffic Data Analysis and Mining, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":6.1585,"has_fulltext":false,"cited_by_count":64,"citation_normalized_percentile":{"value":0.97498279,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"24","issue":"8","first_page":"8650","last_page":"8666"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9897000193595886,"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"}},{"id":"https://openalex.org/T10370","display_name":"Traffic and Road Safety","score":0.9781000018119812,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/position","display_name":"Position (finance)","score":0.5299373865127563},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.48800769448280334},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4845949411392212},{"id":"https://openalex.org/keywords/flow-network","display_name":"Flow network","score":0.43105319142341614},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3735809922218323},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2301674485206604},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1985623836517334},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.12853291630744934}],"concepts":[{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.5299373865127563},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.48800769448280334},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4845949411392212},{"id":"https://openalex.org/C114809511","wikidata":"https://www.wikidata.org/wiki/Q1412924","display_name":"Flow network","level":2,"score":0.43105319142341614},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3735809922218323},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2301674485206604},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1985623836517334},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.12853291630744934},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2022.3220089","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3220089","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":[{"display_name":"Sustainable cities and communities","score":0.75,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G1916410575","display_name":null,"funder_award_id":"2019JBM023","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":85,"referenced_works":["https://openalex.org/W116902681","https://openalex.org/W1485009520","https://openalex.org/W1522301498","https://openalex.org/W1662382123","https://openalex.org/W1924770834","https://openalex.org/W1982978808","https://openalex.org/W1996528178","https://openalex.org/W2004353783","https://openalex.org/W2036785686","https://openalex.org/W2048821851","https://openalex.org/W2064675550","https://openalex.org/W2085592822","https://openalex.org/W2108196201","https://openalex.org/W2137226992","https://openalex.org/W2150010190","https://openalex.org/W2186615578","https://openalex.org/W2194775991","https://openalex.org/W2465015709","https://openalex.org/W2528639018","https://openalex.org/W2558460151","https://openalex.org/W2567070169","https://openalex.org/W2572939427","https://openalex.org/W2756203131","https://openalex.org/W2789186812","https://openalex.org/W2797380400","https://openalex.org/W2802508687","https://openalex.org/W2808535700","https://openalex.org/W2901504064","https://openalex.org/W2903871660","https://openalex.org/W2945622688","https://openalex.org/W2962790412","https://openalex.org/W2963076818","https://openalex.org/W2963240573","https://openalex.org/W2963358464","https://openalex.org/W2963757395","https://openalex.org/W2964015378","https://openalex.org/W2964051675","https://openalex.org/W2964321699","https://openalex.org/W2965341826","https://openalex.org/W2965469401","https://openalex.org/W2967680350","https://openalex.org/W2996451395","https://openalex.org/W2996847713","https://openalex.org/W2997848713","https://openalex.org/W3012562343","https://openalex.org/W3018980093","https://openalex.org/W3021345226","https://openalex.org/W3035225512","https://openalex.org/W3038981236","https://openalex.org/W3045642713","https://openalex.org/W3080253043","https://openalex.org/W3088611441","https://openalex.org/W3102208850","https://openalex.org/W3103720336","https://openalex.org/W3109146615","https://openalex.org/W3120491054","https://openalex.org/W3123191313","https://openalex.org/W3152893301","https://openalex.org/W3169020476","https://openalex.org/W3176279440","https://openalex.org/W4230512065","https://openalex.org/W4285295189","https://openalex.org/W4294558607","https://openalex.org/W4297733535","https://openalex.org/W4313039183","https://openalex.org/W6600828923","https://openalex.org/W6604828220","https://openalex.org/W6631190155","https://openalex.org/W6637178625","https://openalex.org/W6640212811","https://openalex.org/W6659849045","https://openalex.org/W6680532697","https://openalex.org/W6686509673","https://openalex.org/W6719270105","https://openalex.org/W6720006811","https://openalex.org/W6726873649","https://openalex.org/W6731370813","https://openalex.org/W6738964360","https://openalex.org/W6745537798","https://openalex.org/W6746015598","https://openalex.org/W6748856961","https://openalex.org/W6776673096","https://openalex.org/W6780221082","https://openalex.org/W6785625837","https://openalex.org/W6796184174"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Recent":[0],"works":[1],"demonstrate":[2,254],"that":[3,45,58],"capturing":[4],"correlations":[5,27],"between":[6,28],"road":[7],"network":[8],"nodes":[9],"is":[10,33,170,189],"crucial":[11],"to":[12,35,96,117,172,191,236],"improving":[13],"traffic":[14,43,49,162],"flow":[15,163],"forecasting":[16],"accuracy.":[17],"In":[18],"general,":[19],"there":[20,86],"are":[21,87,210],"spatial,":[22],"temporal,":[23],"and":[24,37,54,105,114,176,219,265],"joint":[25,99],"spatial-temporal":[26,73,100,120,184,201,208,227],"two":[29],"nodes,":[30],"whose":[31],"strength":[32],"related":[34],"spatial":[36,104,175],"temporal":[38,70,106,177],"position":[39,107,246],"factors.":[40],"For":[41],"example,":[42],"congestion":[44],"occurs":[46],"at":[47,59],"a":[48,52,60,79,134,166,183,213,226],"hub":[50],"has":[51],"wider":[53],"stronger":[55],"impact":[56],"than":[57],"branch":[61],"road.":[62],"Moreover,":[63],"the":[64,111,128,174,180,194,198,206,233,238,243,255],"above":[65,129],"impacts":[66],"can":[67],"vary":[68],"with":[69,91,127],"position.":[71],"Although":[72],"graph":[74,214,234],"convolution":[75,215],"networks":[76],"have":[77],"become":[78],"popular":[80],"paradigm":[81],"for":[82,161,217],"modeling":[83,110],"those":[84],"correlations,":[85],"still":[88],"three":[89,199],"problems":[90],"existing":[92],"models:":[93],"(i)":[94],"failing":[95,116],"effectively":[97],"model":[98,259],"correlations;":[101,113],"(ii)":[102],"ignoring":[103],"factors":[108],"when":[109],"aforementioned":[112],"(iii)":[115],"capture":[118,237],"distinct":[119],"patterns":[121],"of":[122,179,197,245,257,262],"each":[123],"node.":[124],"To":[125],"cope":[126],"issues,":[130],"this":[131],"paper":[132],"proposes":[133],"novel":[135],"<underline":[136,140,144,148,152,156],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[137,141,145,149,153,157],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">S</u>":[138],"patial-":[139],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">T</u>":[142],"emporal":[143],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">P</u>":[146],"osition-aware":[147],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">G</u>":[150],"raph":[151],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">C</u>":[154],"onvolution":[155],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">N</u>":[158],"etwork":[159],"(STPGCN)":[160],"forecasting.":[164],"Specifically,":[165],"trainable":[167],"embedding":[168],"module":[169,188],"constructed":[171],"represent":[173],"positions":[178],"nodes.":[181],"Subsequently,":[182],"position-aware":[185,228],"relation":[186],"inference":[187],"proposed":[190],"adaptively":[192],"infer":[193],"correlation":[195],"weights":[196],"important":[200],"relations.":[202],"Based":[203],"on":[204,250],"this,":[205],"generated":[207],"relations":[209],"integrated":[211],"into":[212],"layer":[216],"aggregating":[218],"updating":[220],"node":[221],"features.":[222],"Finally,":[223],"we":[224],"design":[225],"gated":[229],"activation":[230],"unit":[231],"in":[232,260],"convolution,":[235],"node-specific":[239],"pattern":[240],"features":[241],"under":[242],"guidance":[244],"embedding.":[247],"Extensive":[248],"experiments":[249],"six":[251],"real-world":[252],"datasets":[253],"superiority":[256],"our":[258],"terms":[261],"prediction":[263],"performance":[264],"computational":[266],"efficiency.":[267]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":24},{"year":2024,"cited_by_count":24},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}