{"id":"https://openalex.org/W3035184251","doi":"https://doi.org/10.1109/tits.2020.2997412","title":"Fine-Grained Traffic Flow Prediction of Various Vehicle Types via Fusion of Multisource Data and Deep Learning Approaches","display_name":"Fine-Grained Traffic Flow Prediction of Various Vehicle Types via Fusion of Multisource Data and Deep Learning Approaches","publication_year":2020,"publication_date":"2020-06-08","ids":{"openalex":"https://openalex.org/W3035184251","doi":"https://doi.org/10.1109/tits.2020.2997412","mag":"3035184251"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2020.2997412","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2020.2997412","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/A5100338728","display_name":"Ping Wang","orcid":"https://orcid.org/0000-0003-2963-9476"},"institutions":[{"id":"https://openalex.org/I25355098","display_name":"Chang'an University","ror":"https://ror.org/05mxya461","country_code":"CN","type":"education","lineage":["https://openalex.org/I25355098"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ping Wang","raw_affiliation_strings":["Institute for Transportation Systems Engineering Research and School of Electric and Control Engineering, Chang\u2019an University, Xi\u2019an, China","Institute for Transportation Systems Engineering Research and School of Electric and Control Engineering, Chang'an University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0003-2963-9476","affiliations":[{"raw_affiliation_string":"Institute for Transportation Systems Engineering Research and School of Electric and Control Engineering, Chang\u2019an University, Xi\u2019an, China","institution_ids":["https://openalex.org/I25355098"]},{"raw_affiliation_string":"Institute for Transportation Systems Engineering Research and School of Electric and Control Engineering, Chang'an University, Xi'an, China","institution_ids":["https://openalex.org/I25355098"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082806856","display_name":"Wenbang Hao","orcid":"https://orcid.org/0000-0002-3998-3564"},"institutions":[{"id":"https://openalex.org/I25355098","display_name":"Chang'an University","ror":"https://ror.org/05mxya461","country_code":"CN","type":"education","lineage":["https://openalex.org/I25355098"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenbang Hao","raw_affiliation_strings":["Institute for Transportation Systems Engineering Research and School of Electric and Control Engineering, Chang\u2019an University, Xi\u2019an, China","Institute for Transportation Systems Engineering Research and School of Electric and Control Engineering, Chang'an University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0002-3998-3564","affiliations":[{"raw_affiliation_string":"Institute for Transportation Systems Engineering Research and School of Electric and Control Engineering, Chang\u2019an University, Xi\u2019an, China","institution_ids":["https://openalex.org/I25355098"]},{"raw_affiliation_string":"Institute for Transportation Systems Engineering Research and School of Electric and Control Engineering, Chang'an University, Xi'an, China","institution_ids":["https://openalex.org/I25355098"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101761946","display_name":"Yinli Jin","orcid":"https://orcid.org/0000-0002-2803-8989"},"institutions":[{"id":"https://openalex.org/I25355098","display_name":"Chang'an University","ror":"https://ror.org/05mxya461","country_code":"CN","type":"education","lineage":["https://openalex.org/I25355098"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yinli Jin","raw_affiliation_strings":["Institute for Transportation Systems Engineering Research and School of Electric and Control Engineering, Chang\u2019an University, Xi\u2019an, China","Institute for Transportation Systems Engineering Research and School of Electric and Control Engineering, Chang'an University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0002-2803-8989","affiliations":[{"raw_affiliation_string":"Institute for Transportation Systems Engineering Research and School of Electric and Control Engineering, Chang\u2019an University, Xi\u2019an, China","institution_ids":["https://openalex.org/I25355098"]},{"raw_affiliation_string":"Institute for Transportation Systems Engineering Research and School of Electric and Control Engineering, Chang'an University, Xi'an, China","institution_ids":["https://openalex.org/I25355098"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I25355098"],"apc_list":null,"apc_paid":null,"fwci":4.4354,"has_fulltext":false,"cited_by_count":55,"citation_normalized_percentile":{"value":0.94619877,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"22","issue":"11","first_page":"6921","last_page":"6930"},"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":0.9977999925613403,"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":0.9904999732971191,"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-flow","display_name":"Traffic flow (computer networking)","score":0.5929387211799622},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5852131843566895},{"id":"https://openalex.org/keywords/floating-car-data","display_name":"Floating car data","score":0.5487495064735413},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.5291438698768616},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5181085467338562},{"id":"https://openalex.org/keywords/toll","display_name":"Toll","score":0.49168044328689575},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48686638474464417},{"id":"https://openalex.org/keywords/data-collection","display_name":"Data collection","score":0.4607919156551361},{"id":"https://openalex.org/keywords/traffic-congestion","display_name":"Traffic congestion","score":0.3841763436794281},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.3689870536327362},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.34953445196151733},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33105742931365967},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3010350465774536},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.27350369095802307},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.09472039341926575}],"concepts":[{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.5929387211799622},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5852131843566895},{"id":"https://openalex.org/C64093975","wikidata":"https://www.wikidata.org/wiki/Q356677","display_name":"Floating car data","level":3,"score":0.5487495064735413},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.5291438698768616},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5181085467338562},{"id":"https://openalex.org/C2778025104","wikidata":"https://www.wikidata.org/wiki/Q408004","display_name":"Toll","level":2,"score":0.49168044328689575},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48686638474464417},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.4607919156551361},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.3841763436794281},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.3689870536327362},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.34953445196151733},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33105742931365967},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3010350465774536},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.27350369095802307},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.09472039341926575},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2020.2997412","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2020.2997412","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":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5699999928474426}],"awards":[{"id":"https://openalex.org/G7598841840","display_name":null,"funder_award_id":"2020GY-020","funder_id":"https://openalex.org/F4320336350","funder_display_name":"Key Research and Development Projects of Shaanxi Province"},{"id":"https://openalex.org/G7905164814","display_name":null,"funder_award_id":"2019YFB1600703","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8150890666","display_name":null,"funder_award_id":"51505037","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8238719222","display_name":null,"funder_award_id":"300102320305","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null},{"id":"https://openalex.org/F4320336350","display_name":"Key Research and Development Projects of Shaanxi Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1488517345","https://openalex.org/W1509749701","https://openalex.org/W1902793265","https://openalex.org/W1943797426","https://openalex.org/W1977405947","https://openalex.org/W1989597542","https://openalex.org/W2004353783","https://openalex.org/W2036785686","https://openalex.org/W2104349879","https://openalex.org/W2111991989","https://openalex.org/W2136922672","https://openalex.org/W2143612262","https://openalex.org/W2165991108","https://openalex.org/W2190353863","https://openalex.org/W2418256651","https://openalex.org/W2460404912","https://openalex.org/W2528639018","https://openalex.org/W2572939427","https://openalex.org/W2593182953","https://openalex.org/W2614809091","https://openalex.org/W2724431948","https://openalex.org/W2743198946","https://openalex.org/W2782977972","https://openalex.org/W2788134583","https://openalex.org/W2792660917","https://openalex.org/W2806123914","https://openalex.org/W2884121921","https://openalex.org/W2891280833","https://openalex.org/W2904393163","https://openalex.org/W2906990041","https://openalex.org/W2945622688","https://openalex.org/W2963124587","https://openalex.org/W2963358464","https://openalex.org/W6728547873","https://openalex.org/W6746015598","https://openalex.org/W6748300305","https://openalex.org/W6748555476"],"related_works":["https://openalex.org/W3126076810","https://openalex.org/W576156795","https://openalex.org/W2053810344","https://openalex.org/W65202228","https://openalex.org/W3023977068","https://openalex.org/W2103013853","https://openalex.org/W2005409769","https://openalex.org/W4390341805","https://openalex.org/W2973192971","https://openalex.org/W4360619413"],"abstract_inverted_index":{"Both":[0],"road":[1,4,145,217],"users":[2],"and":[3,25,36,88,103,114,140,161,180,193,223],"administrators":[5],"are":[6,82,117,125,154],"keen":[7],"to":[8,30,57,64,73,128,169,184,202,226],"know":[9],"traffic":[10,20,108,130,200,209],"flow":[11,21,131],"of":[12,22,33,68,92,95,110,132,135],"fine-grained":[13,111],"vehicle":[14,27,42,96,195,213],"type.":[15],"Successful":[16],"prediction":[17,170,192],"on":[18,41,147],"the":[19,31,39,60,66,93,165,173,185,208,216],"heavy,":[23,112],"medium":[24,113],"small":[26,115],"could":[28,53],"contribute":[29],"improvement":[32],"travel":[34],"safety":[35],"efficiency.":[37],"However,":[38],"classification":[40],"type":[43],"is":[44],"always":[45],"not":[46],"accurate":[47],"enough":[48],"using":[49],"in":[50,137,164,178],"practice.":[51],"It":[52,197],"cost":[54],"a":[55,148,152],"lot":[56],"identify":[58],"from":[59],"additional":[61],"video":[62],"cameras":[63],"cover":[65],"full-length":[67],"large-scale":[69],"freeway":[70,204],"with":[71,90,156,182],"high-resolution":[72],"capture":[74],"vehicles":[75,116,136],"clearly.":[76],"In":[77],"this":[78],"paper,":[79],"empirical":[80],"data":[81,102,157,163],"cleaned,":[83],"normalized,":[84],"compensated,":[85],"filled,":[86],"decoded":[87],"filtered":[89],"help":[91],"fusion":[94],"detector":[97],"data,":[98],"remote":[99],"microwave":[100],"sensors":[101],"toll":[104],"collection":[105],"data.":[106],"The":[107],"flows":[109],"successfully":[118],"reconstructed.":[119],"Improved":[120],"deep":[121],"belief":[122],"network":[123],"(DBN)":[124],"then":[126],"proposed":[127,174],"forecast":[129],"different":[133],"types":[134],"30-,":[138],"60-":[139],"120-minutes":[141],"time":[142,191],"interval.":[143],"Random-selected":[144],"segments":[146],"ring":[149],"way":[150],"around":[151],"city":[153],"trained":[155],"accumulated":[158],"three":[159],"months":[160],"predict":[162],"next":[166],"month.":[167],"According":[168],"error":[171],"analysis,":[172],"method":[175],"performs":[176],"better":[177],"estimation":[179],"forecasting,":[181],"respect":[183],"existing":[186],"methods,":[187],"especially":[188],"for":[189,229],"longer":[190],"heavy":[194,212],"prediction.":[196],"would":[198],"benefit":[199],"control":[201],"prevent":[203],"congestion":[205],"escalation,":[206],"protect":[207],"infrastructure":[210],"via":[211],"control,":[214],"reduce":[215],"risk,":[218],"prompt":[219],"quick":[220],"emergency":[221],"response":[222],"eventually":[224],"contributes":[225],"more":[227],"applications":[228],"intelligent":[230],"transportation":[231],"system":[232],"(ITS).":[233]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":4}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2025-10-10T00:00:00"}