{"id":"https://openalex.org/W4386609249","doi":"https://doi.org/10.1109/tits.2023.3304607","title":"Automated Vehicle Identification Based on Car-Following Data With Machine Learning","display_name":"Automated Vehicle Identification Based on Car-Following Data With Machine Learning","publication_year":2023,"publication_date":"2023-09-11","ids":{"openalex":"https://openalex.org/W4386609249","doi":"https://doi.org/10.1109/tits.2023.3304607"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2023.3304607","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2023.3304607","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/A5058154613","display_name":"Qianwen Li","orcid":"https://orcid.org/0000-0002-5901-8702"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Qianwen Li","raw_affiliation_strings":["School of Environmental, Civil, Agricultural and Mechanical Engineering, University of Georgia, Athens, GA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Environmental, Civil, Agricultural and Mechanical Engineering, University of Georgia, Athens, GA, USA","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100355083","display_name":"Xiaopeng Li","orcid":"https://orcid.org/0000-0002-5264-3775"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaopeng Li","raw_affiliation_strings":["Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, WI, USA"],"raw_orcid":"https://orcid.org/0000-0002-5264-3775","affiliations":[{"raw_affiliation_string":"Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052800794","display_name":"Handong Yao","orcid":"https://orcid.org/0000-0002-2778-084X"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Handong Yao","raw_affiliation_strings":["School of Environmental, Civil, Agricultural and Mechanical Engineering, University of Georgia, Athens, GA, USA"],"raw_orcid":"https://orcid.org/0000-0002-2778-084X","affiliations":[{"raw_affiliation_string":"School of Environmental, Civil, Agricultural and Mechanical Engineering, University of Georgia, Athens, GA, USA","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004135809","display_name":"Zhaohui Liang","orcid":"https://orcid.org/0000-0002-9361-5535"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhaohui Liang","raw_affiliation_strings":["Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, WI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048142877","display_name":"Weijun Xie","orcid":"https://orcid.org/0000-0001-5157-1194"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weijun Xie","raw_affiliation_strings":["H. Milton Stewart School of Industrial and Systems Engineering, Georgia Tech, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0000-0001-5157-1194","affiliations":[{"raw_affiliation_string":"H. Milton Stewart School of Industrial and Systems Engineering, Georgia Tech, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5058154613"],"corresponding_institution_ids":["https://openalex.org/I165733156"],"apc_list":null,"apc_paid":null,"fwci":2.8607,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.909084,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"24","issue":"12","first_page":"13893","last_page":"13902"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9998000264167786,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9995999932289124,"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/T10370","display_name":"Traffic and Road Safety","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/cruise-control","display_name":"Cruise control","score":0.8963422179222107},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6307350993156433},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.579483151435852},{"id":"https://openalex.org/keywords/advanced-driver-assistance-systems","display_name":"Advanced driver assistance systems","score":0.5234757661819458},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42053964734077454},{"id":"https://openalex.org/keywords/automation","display_name":"Automation","score":0.4149514138698578},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.388983815908432},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36498308181762695},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.3518826365470886},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.30021941661834717}],"concepts":[{"id":"https://openalex.org/C113168747","wikidata":"https://www.wikidata.org/wiki/Q507295","display_name":"Cruise control","level":3,"score":0.8963422179222107},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6307350993156433},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.579483151435852},{"id":"https://openalex.org/C87833898","wikidata":"https://www.wikidata.org/wiki/Q1060280","display_name":"Advanced driver assistance systems","level":2,"score":0.5234757661819458},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42053964734077454},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.4149514138698578},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.388983815908432},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36498308181762695},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.3518826365470886},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.30021941661834717},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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:10.1109/tits.2023.3304607","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2023.3304607","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4164076183","display_name":null,"funder_award_id":"CMMI 1932452","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5284879186","display_name":null,"funder_award_id":"2246417","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5372905645","display_name":null,"funder_award_id":"CMMI 1558887","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"},{"id":"https://openalex.org/F4320310847","display_name":"University of South Florida","ror":"https://ror.org/032db5x82"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W388422750","https://openalex.org/W1546510067","https://openalex.org/W1965455100","https://openalex.org/W1975891294","https://openalex.org/W2028138594","https://openalex.org/W2106866030","https://openalex.org/W2487770199","https://openalex.org/W2524088233","https://openalex.org/W2606206351","https://openalex.org/W2755893646","https://openalex.org/W2773675741","https://openalex.org/W2789422831","https://openalex.org/W2790935900","https://openalex.org/W2795976486","https://openalex.org/W2800946744","https://openalex.org/W2946476763","https://openalex.org/W2982184585","https://openalex.org/W3007128802","https://openalex.org/W3007886928","https://openalex.org/W3011888019","https://openalex.org/W3033800859","https://openalex.org/W3037320068","https://openalex.org/W3041133507","https://openalex.org/W3087361755","https://openalex.org/W3092290311","https://openalex.org/W3108984337","https://openalex.org/W3133767846","https://openalex.org/W3157274478","https://openalex.org/W6613221337","https://openalex.org/W6632862882","https://openalex.org/W6676114642","https://openalex.org/W6837117956","https://openalex.org/W6941322317"],"related_works":["https://openalex.org/W4253720181","https://openalex.org/W644513019","https://openalex.org/W2586244547","https://openalex.org/W2517167844","https://openalex.org/W2246414322","https://openalex.org/W1122978781","https://openalex.org/W173875111","https://openalex.org/W651900853","https://openalex.org/W2140688431","https://openalex.org/W167640062"],"abstract_inverted_index":{"Vehicles":[0],"with":[1,19,181],"adaptive":[2,47],"cruise":[3,48],"control,":[4],"i.e.,":[5],"SAE":[6],"Levels":[7],"1":[8],"and":[9,22,38,42,76,88,143,167,210,226],"2":[10],"automated":[11],"vehicles":[12,50,53],"(AVs),":[13],"have":[14,189],"been":[15,190],"operating":[16],"on":[17,98],"roads":[18],"a":[20,57,66,129],"significant":[21],"rapidly":[23],"growing":[24],"penetration":[25],"rate.":[26],"Identifying":[27],"these":[28],"AVs":[29,142,166,198],"is":[30,71,82,110,152,236],"critical":[31],"to":[32,73,127,192,196,208,214],"understanding":[33],"near-future":[34],"mixed":[35,126,200,212],"traffic":[36,201,213,220],"characteristics":[37],"managing":[39],"highway":[40],"mobility":[41,227],"safety.":[43],"This":[44,203],"study":[45,177],"identifies":[46,163],"control-equipped":[49],"from":[51,122],"human-driven":[52],"(HVs)":[54],"by":[55,175],"constructing":[56],"set":[58],"of":[59,107,149,165,169,221,224],"learning-based":[60,150],"models":[61,94,151,173],"using":[62],"car-following":[63,105,117,194],"trajectories":[64],"in":[65,102,199],"short":[67],"time":[68],"window.":[69],"It":[70],"extendible":[72],"Level":[74],"3":[75],"+":[77],"AV":[78,109,120,230],"identification":[79,131,147,172],"when":[80,233],"data":[81],"available.":[83],"To":[84],"compare":[85],"model":[86],"performance":[87],"draw":[89],"physical":[90],"insights,":[91],"two":[92],"physics-based":[93,136],"are":[95,125],"proposed":[96],"based":[97],"the":[99,104,157,182,222,234],"premise":[100],"that,":[101],"general,":[103],"behavior":[106],"an":[108,114],"less":[111],"volatile":[112],"than":[113,140],"HV.":[115],"Four":[116],"datasets,":[118],"including":[119],"makes":[121],"different":[123],"manufacturers,":[124],"build":[128],"comprehensive":[130],"model.":[132],"Results":[133],"show":[134],"that":[135],"approaches":[137],"identify":[138],"more":[139],"80%":[141],"70%":[144],"HVs.":[145,170],"The":[146],"accuracy":[148],"even":[153],"higher.":[154],"For":[155],"example,":[156],"cluster-aware":[158],"long":[159],"short-term":[160],"memory":[161],"network":[162],"98.79%":[164],"95.45%":[168],"Learning-based":[171],"developed":[174],"this":[176],"can":[178],"be":[179],"integrated":[180],"existing":[183],"infrastructure":[184],"(e.g.,":[185,217,228],"surveillance":[186],"cameras),":[187],"which":[188],"used":[191],"extract":[193],"trajectories,":[195],"detect":[197],"streams.":[202],"opens":[204],"unparalleled":[205],"data-driven":[206],"opportunities":[207],"analyze":[209],"control":[211],"enhance":[215],"safety":[216],"notifying":[218],"surrounding":[219],"presence":[223],"AVs)":[225],"opening":[229],"dedicated":[231],"lanes":[232],"percentage":[235],"great":[237],"enough).":[238]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":9}],"updated_date":"2026-04-29T09:16:38.111599","created_date":"2025-10-10T00:00:00"}