{"id":"https://openalex.org/W3158773522","doi":"https://doi.org/10.1109/tits.2021.3074987","title":"Intelligent Traffic Accident Prediction Model for Internet of Vehicles With Deep Learning Approach","display_name":"Intelligent Traffic Accident Prediction Model for Internet of Vehicles With Deep Learning Approach","publication_year":2021,"publication_date":"2021-05-05","ids":{"openalex":"https://openalex.org/W3158773522","doi":"https://doi.org/10.1109/tits.2021.3074987","mag":"3158773522"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2021.3074987","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2021.3074987","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/A5112636432","display_name":"Da-Jie Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I4880106","display_name":"Feng Chia University","ror":"https://ror.org/05vhczg54","country_code":"TW","type":"education","lineage":["https://openalex.org/I4880106"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Da-Jie Lin","raw_affiliation_strings":["Department of Transportation and Logistics, Feng Chia University, Taichung, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Transportation and Logistics, Feng Chia University, Taichung, Taiwan","institution_ids":["https://openalex.org/I4880106"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038663636","display_name":"Mu\u2010Yen Chen","orcid":"https://orcid.org/0000-0002-3945-4363"},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Mu-Yen Chen","raw_affiliation_strings":["Department of Engineering Science, National Cheng Kung University, Tainan, Taiwan"],"raw_orcid":"https://orcid.org/0000-0002-3945-4363","affiliations":[{"raw_affiliation_string":"Department of Engineering Science, National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000576489","display_name":"Hsiu\u2010Sen Chiang","orcid":"https://orcid.org/0000-0003-0228-6826"},"institutions":[{"id":"https://openalex.org/I131948415","display_name":"National Taichung University of Science and Technology","ror":"https://ror.org/05bgcav40","country_code":"TW","type":"education","lineage":["https://openalex.org/I131948415"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hsiu-Sen Chiang","raw_affiliation_strings":["Department of Information Management, National Taichung University of Science and Technology, Taichung, Taiwan"],"raw_orcid":"https://orcid.org/0000-0003-0228-6826","affiliations":[{"raw_affiliation_string":"Department of Information Management, National Taichung University of Science and Technology, Taichung, Taiwan","institution_ids":["https://openalex.org/I131948415"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030441991","display_name":"Pradip Kumar Sharma","orcid":"https://orcid.org/0000-0001-6620-9083"},"institutions":[{"id":"https://openalex.org/I195460627","display_name":"University of Aberdeen","ror":"https://ror.org/016476m91","country_code":"GB","type":"education","lineage":["https://openalex.org/I195460627"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Pradip Kumar Sharma","raw_affiliation_strings":["Department of Computing Science, University of Aberdeen, Aberdeen, U.K"],"raw_orcid":"https://orcid.org/0000-0001-6620-9083","affiliations":[{"raw_affiliation_string":"Department of Computing Science, University of Aberdeen, Aberdeen, U.K","institution_ids":["https://openalex.org/I195460627"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.6825,"has_fulltext":false,"cited_by_count":87,"citation_normalized_percentile":{"value":0.9771186,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"23","issue":"3","first_page":"2340","last_page":"2349"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9983999729156494,"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":0.9983999729156494,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9836000204086304,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10761","display_name":"Vehicular Ad Hoc Networks (VANETs)","score":0.9818000197410583,"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/computer-science","display_name":"Computer science","score":0.5741742253303528},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.5540635585784912},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5377789735794067},{"id":"https://openalex.org/keywords/the-internet","display_name":"The Internet","score":0.5343747735023499},{"id":"https://openalex.org/keywords/traffic-accident","display_name":"Traffic accident","score":0.49659496545791626},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.47415250539779663},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41248393058776855},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.32575133442878723},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.3213657736778259},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.14748668670654297}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5741742253303528},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.5540635585784912},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5377789735794067},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.5343747735023499},{"id":"https://openalex.org/C2989506057","wikidata":"https://www.wikidata.org/wiki/Q9687","display_name":"Traffic accident","level":2,"score":0.49659496545791626},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.47415250539779663},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41248393058776855},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.32575133442878723},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3213657736778259},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.14748668670654297}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2021.3074987","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2021.3074987","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":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.800000011920929}],"awards":[{"id":"https://openalex.org/G5032382037","display_name":null,"funder_award_id":"MOST109-2410-H-025-014-MY2","funder_id":"https://openalex.org/F4320321540","funder_display_name":"Ministry of Science and Technology of the People's Republic of China"},{"id":"https://openalex.org/G5246957495","display_name":null,"funder_award_id":"MOST109-2410-H-006-116-MY2","funder_id":"https://openalex.org/F4320321540","funder_display_name":"Ministry of Science and Technology of the People's Republic of China"}],"funders":[{"id":"https://openalex.org/F4320321540","display_name":"Ministry of Science and Technology of the People's Republic of China","ror":"https://ror.org/027s68j25"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W208128215","https://openalex.org/W1129591933","https://openalex.org/W1995875735","https://openalex.org/W2203247364","https://openalex.org/W2258901949","https://openalex.org/W2272008301","https://openalex.org/W2312235314","https://openalex.org/W2461459916","https://openalex.org/W2462369196","https://openalex.org/W2582903105","https://openalex.org/W2731770569","https://openalex.org/W2788552370","https://openalex.org/W2794425285","https://openalex.org/W2863526491","https://openalex.org/W2947106284","https://openalex.org/W2963874768","https://openalex.org/W2978345223","https://openalex.org/W2980330771","https://openalex.org/W3034786770","https://openalex.org/W3035530851","https://openalex.org/W3080962733","https://openalex.org/W3090396535","https://openalex.org/W3092339997","https://openalex.org/W3109470735","https://openalex.org/W3118519864"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2065457896","https://openalex.org/W3173234801","https://openalex.org/W2611989081","https://openalex.org/W2167984027","https://openalex.org/W3021302227","https://openalex.org/W10630519","https://openalex.org/W1919377569","https://openalex.org/W3144288563","https://openalex.org/W3123907821"],"abstract_inverted_index":{"In":[0],"this":[1,82],"study,":[2],"a":[3,155,204],"high":[4,51],"accident":[5,14,35,52,66,79,130],"risk":[6,36,53,80,96,131,179],"prediction":[7,37,132],"model":[8,38,135,172],"is":[9],"developed":[10],"to":[11,47,59,64,71,127,174,190],"analyze":[12],"traffic":[13,26,56,99,151,192],"data,":[15],"and":[16,30,32,90,120,149,210],"identify":[17,72,138],"priority":[18],"intersections":[19,76,170],"for":[20,55,98,158,160,171,206],"improvement.":[21,162],"A":[22],"database":[23],"of":[24,146,178],"the":[25,49,94,139,144,164,176,184,195],"accidents":[27,193],"was":[28,45],"organized":[29],"analyzed,":[31],"an":[33,129],"intersection":[34,161,208],"based":[39],"on":[40],"different":[41],"mechanical":[42],"learning":[43],"methods":[44],"created":[46],"estimate":[48,175],"possible":[50],"locations":[54],"management":[57,152],"departments":[58,153],"use":[60],"in":[61,183,194],"planning":[62],"countermeasures":[63],"reduce":[65],"risk.":[67],"Using":[68,163],"Bayes\u2019":[69],"theorem":[70],"environmental":[73,166,211],"variables":[74],"at":[75],"that":[77,85,142,180],"affect":[78,143],"levels,":[81],"study":[83],"found":[84],"road":[86],"width,":[87],"speed":[88],"limit":[89],"roadside":[91],"markings":[92],"are":[93],"significant":[95],"factors":[97,141],"accidents.":[100],"Meanwhile,":[101],"Na\u00efve":[102],"Bayes,":[103],"Decision":[104],"tree":[105],"C4.5,":[106],"Bayesian":[107],"Network,":[108],"Multilayer":[109],"perceptron":[110],"(MLP),":[111],"Deep":[112,116],"Neural":[113,122],"Networks":[114],"(DNN),":[115],"Belief":[117],"Network":[118,123],"(DBN)":[119],"Convolutional":[121],"(CNN)":[124],"were":[125],"used":[126,189,202],"develop":[128],"model.":[133],"This":[134],"can":[136,187,200],"also":[137,199],"key":[140],"occurrence":[145],"high-risk":[147,169],"intersections,":[148],"provide":[150],"with":[154],"better":[156],"basis":[157],"decision-making":[159],"same":[165],"characteristics":[167],"as":[168,203],"inputs":[173],"degree":[177],"may":[181],"occur":[182],"future,":[185],"which":[186],"be":[188,201],"prevent":[191],"future.":[196],"Moreover,":[197],"it":[198],"reference":[205],"future":[207],"design":[209],"improvements.":[212]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":26},{"year":2024,"cited_by_count":23},{"year":2023,"cited_by_count":23},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}