{"id":"https://openalex.org/W4390881003","doi":"https://doi.org/10.1080/15472450.2023.2301696","title":"Data-driven transfer learning framework for estimating on-ramp and off-ramp traffic flows","display_name":"Data-driven transfer learning framework for estimating on-ramp and off-ramp traffic flows","publication_year":2024,"publication_date":"2024-01-15","ids":{"openalex":"https://openalex.org/W4390881003","doi":"https://doi.org/10.1080/15472450.2023.2301696"},"language":"en","primary_location":{"id":"doi:10.1080/15472450.2023.2301696","is_oa":false,"landing_page_url":"https://doi.org/10.1080/15472450.2023.2301696","pdf_url":null,"source":{"id":"https://openalex.org/S172631016","display_name":"Journal of Intelligent Transportation Systems","issn_l":"1547-2442","issn":["1547-2442","1547-2450"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of 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/A5070597943","display_name":"Xiaobo Ma","orcid":"https://orcid.org/0000-0002-6158-4586"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xiaobo Ma","raw_affiliation_strings":["Department of Civil & Architectural Engineering & Mechanics, The University of Arizona","Department of Civil &amp; Architectural Engineering &amp; Mechanics, The University of Arizona, Tucson, AZ, USA"],"raw_orcid":"https://orcid.org/0000-0002-6158-4586","affiliations":[{"raw_affiliation_string":"Department of Civil & Architectural Engineering & Mechanics, The University of Arizona","institution_ids":["https://openalex.org/I138006243"]},{"raw_affiliation_string":"Department of Civil &amp; Architectural Engineering &amp; Mechanics, The University of Arizona, Tucson, AZ, USA","institution_ids":["https://openalex.org/I138006243"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087257014","display_name":"Abolfazl Karimpour","orcid":"https://orcid.org/0000-0002-8707-6408"},"institutions":[{"id":"https://openalex.org/I90965887","display_name":"SUNY Polytechnic Institute","ror":"https://ror.org/000fxgx19","country_code":"US","type":"education","lineage":["https://openalex.org/I90965887"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abolfazl Karimpour","raw_affiliation_strings":["College of Engineering, State University of New York Polytechnic Institute","College of Engineering, State University of New York Polytechnic Institute, Utica, NY, USA"],"raw_orcid":"https://orcid.org/0000-0002-8707-6408","affiliations":[{"raw_affiliation_string":"College of Engineering, State University of New York Polytechnic Institute","institution_ids":["https://openalex.org/I90965887"]},{"raw_affiliation_string":"College of Engineering, State University of New York Polytechnic Institute, Utica, NY, USA","institution_ids":["https://openalex.org/I90965887"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032118254","display_name":"Yao\u2010Jan Wu","orcid":"https://orcid.org/0000-0002-0456-7915"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yao-Jan Wu","raw_affiliation_strings":["Department of Civil & Architectural Engineering & Mechanics, The University of Arizona","Department of Civil &amp; Architectural Engineering &amp; Mechanics, The University of Arizona, Tucson, AZ, USA"],"raw_orcid":"https://orcid.org/0000-0002-0456-7915","affiliations":[{"raw_affiliation_string":"Department of Civil & Architectural Engineering & Mechanics, The University of Arizona","institution_ids":["https://openalex.org/I138006243"]},{"raw_affiliation_string":"Department of Civil &amp; Architectural Engineering &amp; Mechanics, The University of Arizona, Tucson, AZ, USA","institution_ids":["https://openalex.org/I138006243"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5070597943"],"corresponding_institution_ids":["https://openalex.org/I138006243"],"apc_list":null,"apc_paid":null,"fwci":4.9051,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.95459024,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"29","issue":"1","first_page":"67","last_page":"80"},"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":0.9995999932289124,"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":0.9977999925613403,"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/range","display_name":"Range (aeronautics)","score":0.6482852101325989},{"id":"https://openalex.org/keywords/weaving","display_name":"Weaving","score":0.6388202905654907},{"id":"https://openalex.org/keywords/transfer","display_name":"Transfer (computing)","score":0.5238668322563171},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5209497213363647},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.513359010219574},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.4789445996284485},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.4171420931816101},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.3244958221912384},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1645728349685669},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.09088411927223206}],"concepts":[{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.6482852101325989},{"id":"https://openalex.org/C54525549","wikidata":"https://www.wikidata.org/wiki/Q2553445","display_name":"Weaving","level":2,"score":0.6388202905654907},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.5238668322563171},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5209497213363647},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.513359010219574},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.4789445996284485},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.4171420931816101},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3244958221912384},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1645728349685669},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.09088411927223206},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/15472450.2023.2301696","is_oa":false,"landing_page_url":"https://doi.org/10.1080/15472450.2023.2301696","pdf_url":null,"source":{"id":"https://openalex.org/S172631016","display_name":"Journal of Intelligent Transportation Systems","issn_l":"1547-2442","issn":["1547-2442","1547-2450"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.4099999964237213,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1571836963","https://openalex.org/W1979646154","https://openalex.org/W1994377164","https://openalex.org/W2016903344","https://openalex.org/W2020641160","https://openalex.org/W2033117307","https://openalex.org/W2040956860","https://openalex.org/W2042048367","https://openalex.org/W2045593919","https://openalex.org/W2063730714","https://openalex.org/W2078994812","https://openalex.org/W2079880609","https://openalex.org/W2099384301","https://openalex.org/W2122838776","https://openalex.org/W2140722533","https://openalex.org/W2158107760","https://openalex.org/W2163150789","https://openalex.org/W2177262641","https://openalex.org/W2515603563","https://openalex.org/W2529827714","https://openalex.org/W2593182953","https://openalex.org/W2773229229","https://openalex.org/W2884915450","https://openalex.org/W2900207796","https://openalex.org/W2950672904","https://openalex.org/W3009737788","https://openalex.org/W3036360162","https://openalex.org/W3091804291","https://openalex.org/W3095697787","https://openalex.org/W3158683705","https://openalex.org/W3176274399","https://openalex.org/W4200520974","https://openalex.org/W4210782077","https://openalex.org/W4224293834","https://openalex.org/W4226198606","https://openalex.org/W4226389324","https://openalex.org/W4234173777","https://openalex.org/W4291184086","https://openalex.org/W4302774182","https://openalex.org/W4306316982","https://openalex.org/W4367841378","https://openalex.org/W4382318985","https://openalex.org/W4384498760","https://openalex.org/W4384519332","https://openalex.org/W4385568099","https://openalex.org/W4385651678","https://openalex.org/W4385681974","https://openalex.org/W4390190589","https://openalex.org/W7062415574"],"related_works":["https://openalex.org/W2952092742","https://openalex.org/W2068981955","https://openalex.org/W67774003","https://openalex.org/W2368396969","https://openalex.org/W2740565117","https://openalex.org/W2365680989","https://openalex.org/W4231951841","https://openalex.org/W2188987414","https://openalex.org/W2907492746","https://openalex.org/W4285143946"],"abstract_inverted_index":{"To":[0,71],"develop":[1],"the":[2,12,16,85,113,116,121,128,131,154,157,180,205,210,225,234],"most":[3],"appropriate":[4],"control":[5,239],"strategy":[6],"and":[7,10,21,38,51,123,140,150,172,196],"monitor,":[8],"maintain,":[9],"evaluate":[11],"traffic":[13,31,61,147],"performance":[14],"of":[15,24,36,120,138,236],"freeway":[17,98],"weaving":[18],"areas,":[19],"state":[20],"local":[22],"Departments":[23],"Transportation":[25],"need":[26],"to":[27,30,48,57,167,175,191,199,232],"have":[28],"access":[29],"flows":[32,42,62,88,142,222],"at":[33],"each":[34],"pair":[35],"on-ramp":[37,139],"off-ramp.":[39],"However,":[40],"ramp":[41,87,221,238],"are":[43,69,246],"not":[44,247],"always":[45],"readily":[46],"available":[47],"transportation":[49,230],"agencies,":[50],"little":[52],"effort":[53],"has":[54],"been":[55],"made":[56],"estimate":[58,84],"these":[59],"missing":[60,86],"in":[63],"locations":[64,242],"where":[65,243],"no":[66],"physical":[67,244],"sensors":[68,245],"installed.":[70,248],"bridge":[72],"this":[73],"research":[74],"gap,":[75],"a":[76,104],"data-driven":[77],"framework":[78,102,133,212],"is":[79],"proposed":[80,101,132,211,226],"that":[81,115,209],"can":[82,134,228],"accurately":[83],"by":[89],"solely":[90],"using":[91],"data":[92,118],"collected":[93],"from":[94],"loop":[95],"detectors":[96],"on":[97,143,153,224],"mainlines.":[99],"The":[100,108,219],"employs":[103],"transfer":[105,109],"learning":[106,110,217],"model.":[107],"model":[111],"relaxes":[112],"assumption":[114],"underlying":[117],"distributions":[119],"source":[122],"target":[124],"domains":[125],"must":[126],"be":[127],"same.":[129],"Therefore,":[130],"guarantee":[135],"high-accuracy":[136],"estimation":[137,159,182],"off-ramp":[141],"freeways":[144],"with":[145],"different":[146],"patterns,":[148],"distributions,":[149],"characteristics.":[151],"Based":[152],"experimental":[155],"results,":[156],"flow":[158,181],"mean":[160,184],"absolute":[161],"errors":[162,186],"range":[163,187],"between":[164,188],"23.90":[165],"veh/h":[166,169,174,177,190,193,198,201],"40.85":[168],"for":[170,178,194,202,241],"on-ramps":[171],"31.58":[173],"45.31":[176],"off-ramps;":[179],"root":[183],"square":[185],"34.55":[189],"57.77":[192],"on-ramps,":[195],"41.75":[197],"58.80":[200],"off-ramps.":[203],"Further,":[204],"comparison":[206],"analysis":[207],"shows":[208],"outperforms":[213],"other":[214],"conventional":[215],"machine":[216],"models.":[218],"estimated":[220],"based":[223],"method":[227],"help":[229],"agencies":[231],"enhance":[233],"operations":[235],"their":[237],"strategies":[240]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":10}],"updated_date":"2026-05-15T08:27:34.491423","created_date":"2025-10-10T00:00:00"}
