{"id":"https://openalex.org/W7136870692","doi":"https://doi.org/10.1109/itsc60802.2025.11423579","title":"Network-Wide Traffic Volume Estimation from Speed Profiles Using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention","display_name":"Network-Wide Traffic Volume Estimation from Speed Profiles Using a Spatio-Temporal Graph Neural Network with Directed Spatial Attention","publication_year":2025,"publication_date":"2025-11-18","ids":{"openalex":"https://openalex.org/W7136870692","doi":"https://doi.org/10.1109/itsc60802.2025.11423579"},"language":null,"primary_location":{"id":"doi:10.1109/itsc60802.2025.11423579","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc60802.2025.11423579","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC)","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/A5129639719","display_name":"L\u00e9o Hein","orcid":null},"institutions":[{"id":"https://openalex.org/I265217849","display_name":"IFP \u00c9nergies nouvelles","ror":"https://ror.org/03gcbhc33","country_code":"FR","type":"facility","lineage":["https://openalex.org/I265217849"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"L\u00e9o Hein","raw_affiliation_strings":["IFP Energies nouvelles,Rueil-Malmaison,France,92852"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IFP Energies nouvelles,Rueil-Malmaison,France,92852","institution_ids":["https://openalex.org/I265217849"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058644490","display_name":"Giovanni De Nunzio","orcid":"https://orcid.org/0000-0003-1179-8735"},"institutions":[{"id":"https://openalex.org/I265217849","display_name":"IFP \u00c9nergies nouvelles","ror":"https://ror.org/03gcbhc33","country_code":"FR","type":"facility","lineage":["https://openalex.org/I265217849"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Giovanni De Nunzio","raw_affiliation_strings":["IFP Energies nouvelles,Rueil-Malmaison,France,92852"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IFP Energies nouvelles,Rueil-Malmaison,France,92852","institution_ids":["https://openalex.org/I265217849"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057226360","display_name":"Giovanni Chierchia","orcid":"https://orcid.org/0000-0001-5899-689X"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I4210152518","display_name":"Laboratoire d'Informatique Gaspard-Monge","ror":"https://ror.org/04t50yk91","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I142631665","https://openalex.org/I4210145102","https://openalex.org/I4210152518","https://openalex.org/I4210154111","https://openalex.org/I4210159245"]},{"id":"https://openalex.org/I4210154111","display_name":"Universit\u00e9 Gustave Eiffel","ror":"https://ror.org/03x42jk29","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210154111"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Giovanni Chierchia","raw_affiliation_strings":["Univ Gustave Eiffel,CNRS, LIGM,Marne-la-Vall&#x00E9;e,France,77454"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ Gustave Eiffel,CNRS, LIGM,Marne-la-Vall&#x00E9;e,France,77454","institution_ids":["https://openalex.org/I4210152518","https://openalex.org/I1294671590","https://openalex.org/I4210154111"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043991938","display_name":"Aur\u00e9lie Pirayre","orcid":"https://orcid.org/0000-0003-0112-3689"},"institutions":[{"id":"https://openalex.org/I265217849","display_name":"IFP \u00c9nergies nouvelles","ror":"https://ror.org/03gcbhc33","country_code":"FR","type":"facility","lineage":["https://openalex.org/I265217849"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Aur\u00e9lie Pirayre","raw_affiliation_strings":["IFP Energies nouvelles,Rueil-Malmaison,France,92852"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IFP Energies nouvelles,Rueil-Malmaison,France,92852","institution_ids":["https://openalex.org/I265217849"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052368829","display_name":"Laurent Najman","orcid":"https://orcid.org/0000-0002-6190-0235"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I4210152518","display_name":"Laboratoire d'Informatique Gaspard-Monge","ror":"https://ror.org/04t50yk91","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I142631665","https://openalex.org/I4210145102","https://openalex.org/I4210152518","https://openalex.org/I4210154111","https://openalex.org/I4210159245"]},{"id":"https://openalex.org/I4210154111","display_name":"Universit\u00e9 Gustave Eiffel","ror":"https://ror.org/03x42jk29","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210154111"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Laurent Najman","raw_affiliation_strings":["Univ Gustave Eiffel,CNRS, LIGM,Marne-la-Vall&#x00E9;e,France,77454"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ Gustave Eiffel,CNRS, LIGM,Marne-la-Vall&#x00E9;e,France,77454","institution_ids":["https://openalex.org/I4210152518","https://openalex.org/I1294671590","https://openalex.org/I4210154111"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"553","last_page":"560"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.8794999718666077,"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":0.8794999718666077,"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":0.02969999983906746,"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/T10138","display_name":"Network Traffic and Congestion Control","score":0.015200000256299973,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5306000113487244},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.45329999923706055},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37860000133514404},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.3529999852180481},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.3352000117301941},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.30959999561309814}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6531000137329102},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5307000279426575},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5306000113487244},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.45329999923706055},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37860000133514404},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.3529999852180481},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3441999852657318},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.3352000117301941},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33149999380111694},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.30959999561309814},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.30250000953674316},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27480000257492065},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2590999901294708},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2549000084400177},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.25380000472068787}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc60802.2025.11423579","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc60802.2025.11423579","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320883","display_name":"Agence Nationale de la Recherche","ror":"https://ror.org/00rbzpz17"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1940460828","https://openalex.org/W2756203131","https://openalex.org/W3096877845","https://openalex.org/W3109602317","https://openalex.org/W3127940350","https://openalex.org/W3193281533","https://openalex.org/W3203984526","https://openalex.org/W4224946912","https://openalex.org/W4231449374","https://openalex.org/W4360765140","https://openalex.org/W4363676665","https://openalex.org/W4388255668","https://openalex.org/W4388936714","https://openalex.org/W4401023337","https://openalex.org/W4412871000","https://openalex.org/W4415179034"],"related_works":[],"abstract_inverted_index":{"Existing":[0],"traffic":[1,9,54,120,162],"volume":[2,42,55,102,121,163,168],"estimation":[3,103,164],"methods":[4,32],"typically":[5],"address":[6,34],"either":[7],"forecasting":[8,22],"on":[10,41,167],"sensor-equipped":[11],"roads":[12,27],"or":[13],"spatially":[14],"imputing":[15],"missing":[16],"volumes":[17],"using":[18],"nearby":[19],"sensors.":[20],"While":[21],"models":[23],"generally":[24],"disregard":[25],"unmonitored":[26],"by":[28],"design,":[29],"spatial":[30],"imputation":[31],"explicitly":[33],"network-wide":[35,101,161],"estimation;":[36],"yet":[37],"this":[38,80],"approach":[39,106],"relies":[40],"data":[43,169],"at":[44,170],"inference":[45,171],"time,":[46],"limiting":[47],"its":[48],"applicability":[49],"in":[50,75,127],"sensor-scarce":[51],"cities.":[52],"Unlike":[53],"data,":[56],"probe":[57],"vehicle":[58],"speeds":[59],"and":[60,68,113,152],"static":[61,110],"road":[62,73,111,114,125],"attributes":[63],"are":[64],"more":[65],"broadly":[66],"accessible":[67],"support":[69],"full":[70],"coverage":[71],"of":[72,134,156],"segments":[74,126],"most":[76],"urban":[77],"networks.":[78],"In":[79],"work,":[81],"we":[82,137],"present":[83],"the":[84,100,128,132,144,154],"Hybrid":[85],"Directed-Attention":[86],"Spatio-Temporal":[87],"Graph":[88],"Neural":[89],"Network":[90],"(HDA-STGNN),":[91],"an":[92],"inductive":[93],"deep":[94],"learning":[95],"framework":[96],"designed":[97],"to":[98,117,147],"tackle":[99],"problem.":[104],"Our":[105],"leverages":[107],"speed":[108],"profiles,":[109],"attributes,":[112],"network":[115],"topology":[116],"predict":[118],"daily":[119],"profiles":[122],"across":[123],"all":[124],"network.":[129],"To":[130],"evaluate":[131],"effectiveness":[133],"our":[135],"approach,":[136],"perform":[138],"extensive":[139],"ablation":[140],"studies":[141],"that":[142],"demonstrate":[143],"model's":[145],"capacity":[146],"capture":[148],"complex":[149],"spatio-temporal":[150],"dependencies":[151],"highlight":[153],"value":[155],"topological":[157],"information":[158],"for":[159],"accurate":[160],"without":[165],"relying":[166],"time.":[172]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2026-03-17T00:00:00"}
