{"id":"https://openalex.org/W4414348278","doi":"https://doi.org/10.1109/tits.2025.3605014","title":"Multi-Source Urban Traffic Flow Forecasting With Drone and Loop Detector Data","display_name":"Multi-Source Urban Traffic Flow Forecasting With Drone and Loop Detector Data","publication_year":2025,"publication_date":"2025-09-19","ids":{"openalex":"https://openalex.org/W4414348278","doi":"https://doi.org/10.1109/tits.2025.3605014"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2025.3605014","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3605014","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":true,"oa_status":"green","oa_url":"https://infoscience.epfl.ch/handle/20.500.14299/245279","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Weijiang Xiong","orcid":"https://orcid.org/0009-0008-2157-2979"},"institutions":[{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH"],"is_corresponding":true,"raw_author_name":"Weijiang Xiong","raw_affiliation_strings":["Urban Transport Systems Laboratory (LUTS), &#x00C9;cole Polytechnique F&#x00E9;d&#x00E9;rale de Lausanne (EPFL), Lausanne, Switzerland"],"affiliations":[{"raw_affiliation_string":"Urban Transport Systems Laboratory (LUTS), &#x00C9;cole Polytechnique F&#x00E9;d&#x00E9;rale de Lausanne (EPFL), Lausanne, Switzerland","institution_ids":["https://openalex.org/I5124864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072807533","display_name":"R\u00f3bert F\u00f3nod","orcid":"https://orcid.org/0000-0002-9434-3156"},"institutions":[{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Robert Fonod","raw_affiliation_strings":["Urban Transport Systems Laboratory (LUTS), &#x00C9;cole Polytechnique F&#x00E9;d&#x00E9;rale de Lausanne (EPFL), Lausanne, Switzerland"],"affiliations":[{"raw_affiliation_string":"Urban Transport Systems Laboratory (LUTS), &#x00C9;cole Polytechnique F&#x00E9;d&#x00E9;rale de Lausanne (EPFL), Lausanne, Switzerland","institution_ids":["https://openalex.org/I5124864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068504559","display_name":"Alexandre Alahi","orcid":"https://orcid.org/0000-0002-5004-1498"},"institutions":[{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Alexandre Alahi","raw_affiliation_strings":["Visual Intelligence for Transportation Laboratory (VITA), &#xC9;cole Polytechnique F&#xE9;d&#xE9;rale de Lausanne (EPFL),, Lausanne, Switzerland"],"affiliations":[{"raw_affiliation_string":"Visual Intelligence for Transportation Laboratory (VITA), &#xC9;cole Polytechnique F&#xE9;d&#xE9;rale de Lausanne (EPFL),, Lausanne, Switzerland","institution_ids":["https://openalex.org/I5124864"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075389676","display_name":"Nikolas Geroliminis","orcid":"https://orcid.org/0000-0001-6940-3607"},"institutions":[{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Nikolas Geroliminis","raw_affiliation_strings":["Urban Transport Systems Laboratory (LUTS), &#x00C9;cole Polytechnique F&#x00E9;d&#x00E9;rale de Lausanne (EPFL), Lausanne, Switzerland"],"affiliations":[{"raw_affiliation_string":"Urban Transport Systems Laboratory (LUTS), &#x00C9;cole Polytechnique F&#x00E9;d&#x00E9;rale de Lausanne (EPFL), Lausanne, Switzerland","institution_ids":["https://openalex.org/I5124864"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I5124864"],"apc_list":null,"apc_paid":null,"fwci":3.8301,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.93363355,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"26","issue":"11","first_page":"18637","last_page":"18652"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9987000226974487,"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":0.9987000226974487,"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":0.9684000015258789,"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/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.9584000110626221,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/drone","display_name":"Drone","score":0.7764999866485596},{"id":"https://openalex.org/keywords/induction-loop","display_name":"Induction loop","score":0.6653000116348267},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.6122999787330627},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5350000262260437},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.5227000117301941},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4004000127315521},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.3849000036716461},{"id":"https://openalex.org/keywords/loop","display_name":"Loop (graph theory)","score":0.36730000376701355}],"concepts":[{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.7764999866485596},{"id":"https://openalex.org/C8406815","wikidata":"https://www.wikidata.org/wiki/Q2163913","display_name":"Induction loop","level":3,"score":0.6653000116348267},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6499000191688538},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.6122999787330627},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5350000262260437},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.5227000117301941},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4544999897480011},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4004000127315521},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.3849000036716461},{"id":"https://openalex.org/C184670325","wikidata":"https://www.wikidata.org/wiki/Q512604","display_name":"Loop (graph theory)","level":2,"score":0.36730000376701355},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.36419999599456787},{"id":"https://openalex.org/C64093975","wikidata":"https://www.wikidata.org/wiki/Q356677","display_name":"Floating car data","level":3,"score":0.3531000018119812},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.32679998874664307},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.3260999917984009},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3249000012874603},{"id":"https://openalex.org/C114809511","wikidata":"https://www.wikidata.org/wiki/Q1412924","display_name":"Flow network","level":2,"score":0.3068000078201294},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.2987000048160553},{"id":"https://openalex.org/C186886427","wikidata":"https://www.wikidata.org/wiki/Q5441213","display_name":"Feedback loop","level":2,"score":0.2800999879837036},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.27459999918937683},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.2727000117301941},{"id":"https://openalex.org/C539828613","wikidata":"https://www.wikidata.org/wiki/Q178512","display_name":"Public transport","level":2,"score":0.26989999413490295},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26759999990463257}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tits.2025.3605014","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3605014","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:infoscience.epfl.ch:20.500.14299/245279","is_oa":true,"landing_page_url":"https://infoscience.epfl.ch/handle/20.500.14299/245279","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"}],"best_oa_location":{"id":"pmh:oai:infoscience.epfl.ch:20.500.14299/245279","is_oa":true,"landing_page_url":"https://infoscience.epfl.ch/handle/20.500.14299/245279","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G330376158","display_name":null,"funder_award_id":"51NF40_180545","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Traffic":[0],"forecasting":[1,165],"has":[2,66],"been":[3],"a":[4,28,82,107],"fundamental":[5],"task":[6],"in":[7,56],"transportation":[8],"research,":[9],"with":[10,120,147,166],"many":[11],"methods":[12,65],"and":[13,42,64,73,101,116,137,155],"datasets":[14,63],"mainly":[15],"based":[16],"on":[17,150],"highway":[18],"loop":[19,74,102],"detector":[20,75],"data.":[21,168],"In":[22],"recent":[23],"years,":[24],"drones":[25,47,100],"have":[26,48,157],"become":[27],"favorable":[29],"choice":[30],"for":[31,91,133,141],"urban":[32,92,163],"traffic":[33,57,93,164],"monitoring,":[34,58],"due":[35],"to":[36,111],"their":[37],"flexibility,":[38],"high":[39],"data":[40,76,151],"quality":[41],"larger":[43],"spatial":[44],"coverage.":[45],"Although":[46],"promising":[49],"possibilities":[50],"of":[51,61,71,162],"becoming":[52],"an":[53],"additional":[54],"asset":[55],"the":[59,68,139,159],"lack":[60],"public":[62],"made":[67],"joint":[69],"use":[70],"drone":[72],"fairly":[77],"under-explored.":[78],"Therefore,":[79],"we":[80,105],"create":[81],"novel":[83],"multi-source":[84,167],"dataset":[85],"SimBarca":[86],"from":[87,98],"simulated":[88],"vehicle":[89],"trajectories":[90],"forecasting,":[94],"featuring":[95],"speed":[96,135,144],"measurements":[97],"both":[99],"detectors.":[103],"Additionally,":[104],"provide":[106],"graph-based":[108],"model":[109],"HiMSNet":[110,129],"handle":[112],"multiple":[113],"input":[114],"modalities":[115],"evaluate":[117],"it":[118],"along":[119],"other":[121],"basic":[122],"benchmark":[123],"predictors.":[124],"Our":[125],"analysis":[126],"shows":[127],"that":[128],"achieves":[130],"good":[131],"performance":[132],"regional":[134],"prediction,":[136],"outperforms":[138],"baselines":[140],"road":[142],"segment-level":[143],"prediction.":[145],"Experiments":[146],"various":[148],"configurations":[149],"modality,":[152],"sensor":[153],"coverage":[154],"noises":[156],"demonstrated":[158],"great":[160],"potential":[161]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
