{"id":"https://openalex.org/W4290944300","doi":"https://doi.org/10.1145/3534678.3539236","title":"Modeling Network-level Traffic Flow Transitions on Sparse Data","display_name":"Modeling Network-level Traffic Flow Transitions on Sparse Data","publication_year":2022,"publication_date":"2022-08-12","ids":{"openalex":"https://openalex.org/W4290944300","doi":"https://doi.org/10.1145/3534678.3539236"},"language":"en","primary_location":{"id":"doi:10.1145/3534678.3539236","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3534678.3539236","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3534678.3539236","source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","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":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3534678.3539236","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087971424","display_name":"Xiaoliang Lei","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaoliang Lei","raw_affiliation_strings":["Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009279567","display_name":"Hao Mei","orcid":"https://orcid.org/0000-0002-5740-0844"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hao Mei","raw_affiliation_strings":["New Jersey Institute of Technology, Newark, NJ, USA"],"affiliations":[{"raw_affiliation_string":"New Jersey Institute of Technology, Newark, NJ, USA","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003001715","display_name":"Bin Shi","orcid":"https://orcid.org/0000-0001-8272-9361"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Shi","raw_affiliation_strings":["Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100777770","display_name":"Hua Wei","orcid":"https://orcid.org/0000-0002-3735-1635"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hua Wei","raw_affiliation_strings":["New Jersey Institute of Technology, Newark, NJ, USA"],"affiliations":[{"raw_affiliation_string":"New Jersey Institute of Technology, Newark, NJ, USA","institution_ids":["https://openalex.org/I118118575"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5087971424"],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":6.3756,"has_fulltext":true,"cited_by_count":20,"citation_normalized_percentile":{"value":0.98170732,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"835","last_page":"845"},"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":0.9993000030517578,"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":0.9984999895095825,"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/traffic-generation-model","display_name":"Traffic generation model","score":0.7541469931602478},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6505188941955566},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.6150223612785339},{"id":"https://openalex.org/keywords/traffic-congestion-reconstruction-with-kerners-three-phase-theory","display_name":"Traffic congestion reconstruction with Kerner's three-phase theory","score":0.5898312330245972},{"id":"https://openalex.org/keywords/flow-network","display_name":"Flow network","score":0.5708937644958496},{"id":"https://openalex.org/keywords/three-phase-traffic-theory","display_name":"Three-phase traffic theory","score":0.5156251788139343},{"id":"https://openalex.org/keywords/network-traffic-simulation","display_name":"Network traffic simulation","score":0.49915552139282227},{"id":"https://openalex.org/keywords/floating-car-data","display_name":"Floating car data","score":0.48518258333206177},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.46618860960006714},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4658184051513672},{"id":"https://openalex.org/keywords/traffic-conflict","display_name":"Traffic conflict","score":0.44015035033226013},{"id":"https://openalex.org/keywords/network-traffic-control","display_name":"Network traffic control","score":0.4208317995071411},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.3897005319595337},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3738400936126709},{"id":"https://openalex.org/keywords/traffic-congestion","display_name":"Traffic congestion","score":0.23622670769691467},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.23162493109703064},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17478686571121216},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.15707600116729736},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.14513558149337769},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08927321434020996}],"concepts":[{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.7541469931602478},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6505188941955566},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.6150223612785339},{"id":"https://openalex.org/C25492975","wikidata":"https://www.wikidata.org/wiki/Q960570","display_name":"Traffic congestion reconstruction with Kerner's three-phase theory","level":3,"score":0.5898312330245972},{"id":"https://openalex.org/C114809511","wikidata":"https://www.wikidata.org/wiki/Q1412924","display_name":"Flow network","level":2,"score":0.5708937644958496},{"id":"https://openalex.org/C21810127","wikidata":"https://www.wikidata.org/wiki/Q583342","display_name":"Three-phase traffic theory","level":4,"score":0.5156251788139343},{"id":"https://openalex.org/C94168897","wikidata":"https://www.wikidata.org/wiki/Q574324","display_name":"Network traffic simulation","level":4,"score":0.49915552139282227},{"id":"https://openalex.org/C64093975","wikidata":"https://www.wikidata.org/wiki/Q356677","display_name":"Floating car data","level":3,"score":0.48518258333206177},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.46618860960006714},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4658184051513672},{"id":"https://openalex.org/C178944661","wikidata":"https://www.wikidata.org/wiki/Q7832489","display_name":"Traffic conflict","level":4,"score":0.44015035033226013},{"id":"https://openalex.org/C201100257","wikidata":"https://www.wikidata.org/wiki/Q393287","display_name":"Network traffic control","level":3,"score":0.4208317995071411},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.3897005319595337},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3738400936126709},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.23622670769691467},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.23162493109703064},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17478686571121216},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.15707600116729736},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.14513558149337769},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08927321434020996},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3534678.3539236","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3534678.3539236","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3534678.3539236","source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","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":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2208.06646","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2208.06646","pdf_url":"https://arxiv.org/pdf/2208.06646","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3534678.3539236","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3534678.3539236","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3534678.3539236","source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","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":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.8199999928474426}],"awards":[{"id":"https://openalex.org/G2172159137","display_name":null,"funder_award_id":"2153311","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2873976831","display_name":null,"funder_award_id":"62002282","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3969212899","display_name":null,"funder_award_id":"IRT_17R86","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6370265225","display_name":null,"funder_award_id":"No. 62002282","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6449033798","display_name":null,"funder_award_id":"NSFC No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322724","display_name":"Ministry of Education, India","ror":"https://ror.org/048xjjh50"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4290944300.pdf","grobid_xml":"https://content.openalex.org/works/W4290944300.grobid-xml"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W157189987","https://openalex.org/W1533198000","https://openalex.org/W1964312966","https://openalex.org/W2007894170","https://openalex.org/W2054141820","https://openalex.org/W2101383794","https://openalex.org/W2131398657","https://openalex.org/W2146332392","https://openalex.org/W2528639018","https://openalex.org/W2539781657","https://openalex.org/W2607883279","https://openalex.org/W2624190409","https://openalex.org/W2744444739","https://openalex.org/W2788134583","https://openalex.org/W2803403013","https://openalex.org/W2809148419","https://openalex.org/W2890655496","https://openalex.org/W2890686416","https://openalex.org/W2898770554","https://openalex.org/W2901504064","https://openalex.org/W2903871660","https://openalex.org/W2910952060","https://openalex.org/W2912818700","https://openalex.org/W2962764167","https://openalex.org/W2962790412","https://openalex.org/W2963358464","https://openalex.org/W2964749398","https://openalex.org/W2965341826","https://openalex.org/W2983997240","https://openalex.org/W2989847038","https://openalex.org/W2996847713","https://openalex.org/W3003365835","https://openalex.org/W3012562343","https://openalex.org/W3033039844","https://openalex.org/W3080253043","https://openalex.org/W3080548826","https://openalex.org/W3094009742","https://openalex.org/W3102436600","https://openalex.org/W3103720336","https://openalex.org/W3105017587","https://openalex.org/W3126367810","https://openalex.org/W3166589372","https://openalex.org/W3170140111","https://openalex.org/W3207461654","https://openalex.org/W4200278706","https://openalex.org/W4288562516","https://openalex.org/W6631691190"],"related_works":["https://openalex.org/W2587362999","https://openalex.org/W2060036720","https://openalex.org/W2029436115","https://openalex.org/W3141970871","https://openalex.org/W1550043390","https://openalex.org/W2156393949","https://openalex.org/W4390945665","https://openalex.org/W572895083","https://openalex.org/W2004329191","https://openalex.org/W1984847333"],"abstract_inverted_index":{"Modeling":[0],"how":[1],"network-level":[2,87,117],"traffic":[3,22,37,48,51,55,76,88,105,118,126,134,150],"flow":[4,23,89],"changes":[5],"in":[6,14,154,173],"the":[7,46,62,69,73,83,95,104,125,137,155],"urban":[8,19],"environment":[9],"is":[10,65,98,107],"useful":[11],"for":[12],"decision-making":[13,172],"transportation,":[15,146],"public":[16],"safety":[17],"and":[18,72,147,168],"planning.":[20],"The":[21],"system":[24,49,106,127],"can":[25,115,169],"be":[26],"viewed":[27],"as":[28,128],"a":[29,91,129],"dynamic":[30,130],"process":[31],"that":[32,114,162],"transits":[33],"between":[34],"states":[35,71,151],"(e.g.,":[36],"volumes":[38],"on":[39],"each":[40],"road":[41],"segment)":[42],"over":[43],"time.":[44],"In":[45,78],"real-world":[47,92],"with":[50,152],"operation":[52],"actions":[53,74],"like":[54],"signal":[56],"control":[57],"or":[58],"reversible":[59],"lane":[60],"changing,":[61],"system's":[63],"state":[64],"influenced":[66,132],"by":[67,133,141],"both":[68],"historical":[70],"of":[75,85,103],"operations.":[77],"this":[79],"paper,":[80],"we":[81,160],"consider":[82],"problem":[84],"modeling":[86],"under":[90],"setting,":[93],"where":[94],"available":[96],"data":[97],"sparse":[99,121],"(i.e.,":[100],"only":[101],"part":[102],"observed).":[108],"We":[109],"present":[110],"DTIGNN,":[111],"an":[112],"approach":[113],"predict":[116],"flows":[119],"from":[120,145],"data.":[122],"DTIGNN":[123],"models":[124,139],"graph":[131],"signals,":[135],"learns":[136],"transition":[138,143],"grounded":[140],"fundamental":[142],"equations":[144],"predicts":[148],"future":[149],"imputation":[153],"process.":[156],"Through":[157],"comprehensive":[158],"experiments,":[159],"demonstrate":[161],"our":[163],"method":[164],"outperforms":[165],"state-of-the-art":[166],"methods":[167],"better":[170],"support":[171],"transportation.":[174]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":3}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
