{"id":"https://openalex.org/W2900207796","doi":"https://doi.org/10.1109/tits.2018.2873137","title":"A Unified Spatio-Temporal Model for Short-Term Traffic Flow Prediction","display_name":"A Unified Spatio-Temporal Model for Short-Term Traffic Flow Prediction","publication_year":2018,"publication_date":"2018-11-06","ids":{"openalex":"https://openalex.org/W2900207796","doi":"https://doi.org/10.1109/tits.2018.2873137","mag":"2900207796"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2018.2873137","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2018.2873137","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/A5010309828","display_name":"Peibo Duan","orcid":"https://orcid.org/0000-0002-0686-8404"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Peibo Duan","raw_affiliation_strings":["School of Computing and Communication, The University of Technology Sydney, Ultimo, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"School of Computing and Communication, The University of Technology Sydney, Ultimo, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036000787","display_name":"Guoqiang Mao","orcid":"https://orcid.org/0000-0002-3598-4949"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Guoqiang Mao","raw_affiliation_strings":["School of Computing and Communication, The University of Technology Sydney, Ultimo, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"School of Computing and Communication, The University of Technology Sydney, Ultimo, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077465517","display_name":"Weifa Liang","orcid":"https://orcid.org/0000-0002-8207-6740"},"institutions":[{"id":"https://openalex.org/I118347636","display_name":"Australian National University","ror":"https://ror.org/019wvm592","country_code":"AU","type":"education","lineage":["https://openalex.org/I118347636"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Weifa Liang","raw_affiliation_strings":["Research School of Computer Science, Australian National University, Canberra, ACT, Australia"],"affiliations":[{"raw_affiliation_string":"Research School of Computer Science, Australian National University, Canberra, ACT, Australia","institution_ids":["https://openalex.org/I118347636"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070747390","display_name":"Degan Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I136765683","display_name":"Tianjin University of Technology","ror":"https://ror.org/00zbe0w13","country_code":"CN","type":"education","lineage":["https://openalex.org/I136765683"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Degan Zhang","raw_affiliation_strings":["School of Computer Science and Engineering, Tianjin University of Technology, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Tianjin University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I136765683"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5010309828"],"corresponding_institution_ids":["https://openalex.org/I114017466"],"apc_list":null,"apc_paid":null,"fwci":9.496,"has_fulltext":false,"cited_by_count":126,"citation_normalized_percentile":{"value":0.98457381,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"20","issue":"9","first_page":"3212","last_page":"3223"},"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9968000054359436,"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/T10524","display_name":"Traffic control and management","score":0.9958000183105469,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.6592556238174438},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6191396117210388},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.613231360912323},{"id":"https://openalex.org/keywords/traffic-generation-model","display_name":"Traffic generation model","score":0.48499342799186707},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.46949318051338196},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.4596928656101227},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4375925362110138},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4131300449371338},{"id":"https://openalex.org/keywords/variation","display_name":"Variation (astronomy)","score":0.4104158878326416},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.4103235602378845},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36855971813201904},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.35675495862960815},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3311803936958313},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.30173546075820923},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2949325442314148},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.19868913292884827},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1822865903377533},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1342993974685669}],"concepts":[{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.6592556238174438},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6191396117210388},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.613231360912323},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.48499342799186707},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.46949318051338196},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.4596928656101227},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4375925362110138},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4131300449371338},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.4104158878326416},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.4103235602378845},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36855971813201904},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.35675495862960815},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3311803936958313},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.30173546075820923},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2949325442314148},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.19868913292884827},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1822865903377533},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1342993974685669},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C44870925","wikidata":"https://www.wikidata.org/wiki/Q37547","display_name":"Astrophysics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","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":2,"locations":[{"id":"doi:10.1109/tits.2018.2873137","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2018.2873137","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"},{"id":"pmh:oai:openresearch-repository.anu.edu.au:1885/296960","is_oa":false,"landing_page_url":"http://hdl.handle.net/1885/296960","pdf_url":null,"source":{"id":"https://openalex.org/S4306402539","display_name":"ANU Open Research (Australian National University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I118347636","host_organization_name":"Australian National University","host_organization_lineage":["https://openalex.org/I118347636"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"Journal article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6899999976158142,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W594114979","https://openalex.org/W1555857857","https://openalex.org/W1559321207","https://openalex.org/W1587573180","https://openalex.org/W1610291649","https://openalex.org/W1839456025","https://openalex.org/W1875626450","https://openalex.org/W1952209694","https://openalex.org/W1974539152","https://openalex.org/W1977153226","https://openalex.org/W1984969638","https://openalex.org/W1991410369","https://openalex.org/W1991770012","https://openalex.org/W2024558842","https://openalex.org/W2036785686","https://openalex.org/W2057011654","https://openalex.org/W2057918527","https://openalex.org/W2073488975","https://openalex.org/W2086482048","https://openalex.org/W2093134417","https://openalex.org/W2133646105","https://openalex.org/W2145039203","https://openalex.org/W2150498351","https://openalex.org/W2160507653","https://openalex.org/W2163150789","https://openalex.org/W2169481445","https://openalex.org/W2171234954","https://openalex.org/W2181176856","https://openalex.org/W2217607432","https://openalex.org/W2274750026","https://openalex.org/W2293786206","https://openalex.org/W2331634986","https://openalex.org/W2340330583","https://openalex.org/W2343970958","https://openalex.org/W2564747559","https://openalex.org/W2565955504","https://openalex.org/W2593182953","https://openalex.org/W6644426853","https://openalex.org/W6659849045","https://openalex.org/W6686038180","https://openalex.org/W6731004731"],"related_works":["https://openalex.org/W2349019353","https://openalex.org/W2587362999","https://openalex.org/W432084041","https://openalex.org/W2986732134","https://openalex.org/W2394010358","https://openalex.org/W2361078351","https://openalex.org/W2052374615","https://openalex.org/W1463884142","https://openalex.org/W2163239346","https://openalex.org/W2963251637"],"abstract_inverted_index":{"This":[0],"paper":[1,16],"proposes":[2],"a":[3,23,104,116,132,212],"unified":[4,117],"spatio-temporal":[5,34,43,101,129],"model":[6,118],"for":[7,204],"short-term":[8],"road":[9,49,65,87,146],"traffic":[10,28,37,66,89,148,163],"prediction.":[11],"The":[12,42],"contributions":[13],"of":[14,71,100,109,128,134,161,207],"this":[15],"are":[17,138],"as":[18],"follows.":[19],"First,":[20],"we":[21],"develop":[22],"physically":[24,76],"intuitive":[25,77],"approach":[26,74,114,169],"to":[27,64,84,141,196],"prediction":[29],"that":[30,96,119,166,197],"captures":[31],"the":[32,48,72,98,110,112,121,126,154,167,175,185,208],"time-varying":[33,52,55],"correlation":[35,44,102,130],"between":[36],"at":[38],"different":[39,59,205],"measurement":[40],"points.":[41],"is":[45,192],"affected":[46],"by":[47,103,199],"network":[50,189],"topology,":[51],"speed,":[53],"and":[54,68,88,107,143,147,184,191,216],"trip":[56],"distribution.":[57],"Distinctly":[58],"from":[60],"previous":[61],"black-box":[62],"approaches":[63],"modeling":[67],"prediction,":[69],"parameters":[70,137],"proposed":[73,113,168],"have":[75],"meanings":[78],"which":[79],"make":[80],"them":[81],"readily":[82],"amendable":[83],"suit":[85],"changing":[86],"conditions.":[90],"Second,":[91],"unlike":[92],"some":[93],"existing":[94],"techniques":[95],"capture":[97],"variation":[99,127],"complete":[105],"re-design":[106],"calibration":[108],"model,":[111],"uses":[115],"incorporates":[120],"physical":[122],"factors":[123],"potentially":[124],"affecting":[125],"into":[131],"series":[133],"parameters.":[135],"These":[136],"relatively":[139],"easy":[140],"control":[142],"adjust":[144],"when":[145],"conditions":[149],"change,":[150],"thereby":[151],"greatly":[152],"reducing":[153],"computational":[155,215],"complexity.":[156,218],"Experiments":[157],"using":[158],"two":[159],"sets":[160],"real":[162],"traces":[164],"demonstrate":[165],"has":[170],"superior":[171],"accuracy":[172],"compared":[173],"with":[174,211],"widely":[176],"used":[177],"space-time":[178],"autoregressive":[179],"integrated":[180],"moving":[181],"average":[182],"(STARIMA)":[183],"back":[186],"propagation":[187],"neural":[188],"approaches,":[190],"only":[193],"marginally":[194],"inferior":[195],"obtained":[198],"constructing":[200],"multiple":[201],"STARIMA":[202],"models":[203],"times":[206],"day,":[209],"however,":[210],"much":[213],"reduced":[214],"implementation":[217]},"counts_by_year":[{"year":2025,"cited_by_count":18},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":22},{"year":2022,"cited_by_count":23},{"year":2021,"cited_by_count":22},{"year":2020,"cited_by_count":25},{"year":2019,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}