{"id":"https://openalex.org/W2897116538","doi":"https://doi.org/10.1109/ivs.2018.8500444","title":"Analysis on Biosignal Characteristics to Evaluate Road Rage of Younger Drivers: A Driving Simulator Study","display_name":"Analysis on Biosignal Characteristics to Evaluate Road Rage of Younger Drivers: A Driving Simulator Study","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2897116538","doi":"https://doi.org/10.1109/ivs.2018.8500444","mag":"2897116538"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2018.8500444","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2018.8500444","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5078723950","display_name":"Hongyu Hu","orcid":"https://orcid.org/0000-0001-8083-6403"},"institutions":[{"id":"https://openalex.org/I4392738231","display_name":"State Key Laboratory of Automotive Simulation and Control","ror":"https://ror.org/00b67z867","country_code":null,"type":"facility","lineage":["https://openalex.org/I194450716","https://openalex.org/I4392738231"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyu Hu","raw_affiliation_strings":["State Key Laboratory of Automotive Simulation and Conrol, Changchun, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Automotive Simulation and Conrol, Changchun, China","institution_ids":["https://openalex.org/I4392738231"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101593151","display_name":"Zheng Zhu","orcid":"https://orcid.org/0000-0003-2634-4015"},"institutions":[{"id":"https://openalex.org/I4392738231","display_name":"State Key Laboratory of Automotive Simulation and Control","ror":"https://ror.org/00b67z867","country_code":null,"type":"facility","lineage":["https://openalex.org/I194450716","https://openalex.org/I4392738231"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Zhu","raw_affiliation_strings":["State Key Laboratory of Automotive Simulation and Conrol, Changchun, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Automotive Simulation and Conrol, Changchun, China","institution_ids":["https://openalex.org/I4392738231"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022668758","display_name":"Zhenhai Gao","orcid":"https://orcid.org/0000-0002-4623-3956"},"institutions":[{"id":"https://openalex.org/I4392738231","display_name":"State Key Laboratory of Automotive Simulation and Control","ror":"https://ror.org/00b67z867","country_code":null,"type":"facility","lineage":["https://openalex.org/I194450716","https://openalex.org/I4392738231"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenhai Gao","raw_affiliation_strings":["State Key Laboratory of Automotive Simulation and Conrol, Changchun, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Automotive Simulation and Conrol, Changchun, China","institution_ids":["https://openalex.org/I4392738231"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101533518","display_name":"Rencheng Zheng","orcid":"https://orcid.org/0000-0003-0706-6523"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rencheng Zheng","raw_affiliation_strings":["Institute of Industrial Science, the University of Tokyo, School of Automot ive Engineering, Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Industrial Science, the University of Tokyo, School of Automot ive Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0203,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.875,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"156","last_page":"161"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.994700014591217,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9837999939918518,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/biosignal","display_name":"Biosignal","score":0.8384034633636475},{"id":"https://openalex.org/keywords/anger","display_name":"Anger","score":0.818909227848053},{"id":"https://openalex.org/keywords/standard-deviation","display_name":"Standard deviation","score":0.5374195575714111},{"id":"https://openalex.org/keywords/driving-simulator","display_name":"Driving simulator","score":0.5303564667701721},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5242669582366943},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.504116415977478},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.420733243227005},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.4117937684059143},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35346418619155884},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31923559308052063},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.29106271266937256},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.289874792098999},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.199520081281662},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18007326126098633},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.16720008850097656}],"concepts":[{"id":"https://openalex.org/C2779055241","wikidata":"https://www.wikidata.org/wiki/Q644240","display_name":"Biosignal","level":3,"score":0.8384034633636475},{"id":"https://openalex.org/C2779302386","wikidata":"https://www.wikidata.org/wiki/Q79871","display_name":"Anger","level":2,"score":0.818909227848053},{"id":"https://openalex.org/C22679943","wikidata":"https://www.wikidata.org/wiki/Q159375","display_name":"Standard deviation","level":2,"score":0.5374195575714111},{"id":"https://openalex.org/C2780689630","wikidata":"https://www.wikidata.org/wiki/Q2081815","display_name":"Driving simulator","level":2,"score":0.5303564667701721},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5242669582366943},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.504116415977478},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.420733243227005},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.4117937684059143},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35346418619155884},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31923559308052063},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.29106271266937256},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.289874792098999},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.199520081281662},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18007326126098633},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.16720008850097656},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivs.2018.8500444","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2018.8500444","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.46000000834465027,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W124010068","https://openalex.org/W1969445141","https://openalex.org/W1980553000","https://openalex.org/W1993407462","https://openalex.org/W2024955945","https://openalex.org/W2054093967","https://openalex.org/W2056239517","https://openalex.org/W2056433498","https://openalex.org/W2056980486","https://openalex.org/W2069168312","https://openalex.org/W2070643646","https://openalex.org/W2112420691","https://openalex.org/W2124767042","https://openalex.org/W2137941897","https://openalex.org/W2168676097","https://openalex.org/W2171801645","https://openalex.org/W2393094368","https://openalex.org/W2508509980","https://openalex.org/W2525771685","https://openalex.org/W2594591742","https://openalex.org/W2611557233","https://openalex.org/W6605141904","https://openalex.org/W6667917372"],"related_works":["https://openalex.org/W4214581441","https://openalex.org/W2053762217","https://openalex.org/W2494432015","https://openalex.org/W2114479223","https://openalex.org/W2134572333","https://openalex.org/W2531028440","https://openalex.org/W2150501849","https://openalex.org/W1968240874","https://openalex.org/W2080835026","https://openalex.org/W2779694590"],"abstract_inverted_index":{"This":[0],"paper":[1],"focused":[2],"on":[3,52],"biosignal":[4,75],"characteristics":[5],"to":[6,37,63],"analyze":[7],"road":[8],"rage":[9],"of":[10,20,42,71,82,103,162,170],"young":[11],"drivers":[12],"in":[13],"a":[14,58,93,112,130,158,201],"driving":[15,208,213],"simulator":[16],"experiment.":[17],"A":[18],"total":[19],"12":[21],"subjects":[22],"were":[23,183],"enrolled":[24],"during":[25],"the":[26,39,46,53,72,89,104,119,135,140,145,163,187],"experimental":[27],"study.":[28],"At":[29],"first,":[30],"an":[31],"unfair":[32],"incident":[33],"video":[34],"is":[35,49,61,157],"utilized":[36],"induce":[38],"anger":[40,47,55],"emotion":[41,209],"drivers,":[43],"and":[44,67,84,96,100,123,149,175,194,204,211],"then":[45],"state":[48,165],"recorded":[50],"based":[51],"Likert":[54],"scale;":[56],"meanwhile,":[57],"physiological":[59],"recorder":[60],"used":[62],"acquire":[64],"electroencephalogram":[65],"(EEG)":[66],"electrocardiogram":[68],"(ECG)":[69],"signals":[70],"subjects.":[73],"In":[74,117],"processing":[76],"stage,":[77],"four":[78,105,150],"typical":[79,106,167],"rhythm":[80,107,168],"bands":[81,108,169],"\u03b1,\u03b2,\u03b4,":[83,171],"\u03b8":[85],"are":[86,109,127,142],"extracted":[87],"from":[88,134],"original":[90,136],"EEG":[91],"using":[92],"digital":[94],"filter":[95],"wavelet":[97],"packet":[98],"decomposition,":[99],"power":[101],"spectrums":[102],"obtained":[110],"with":[111],"fast":[113],"Fourier":[114],"transform":[115],"analysis.":[116],"addition,":[118],"average":[120,172],"heart":[121,173],"rate":[122,174],"R-R":[124,176],"standard":[125,177],"deviation":[126],"calculated":[128,147],"through":[129],"temporal":[131],"domain":[132],"analysis":[133],"ECG":[137],"signals.":[138],"Furthermore,":[139],"relationships":[141],"analyzed":[143],"between":[144],"sex":[146],"indicators":[148],"angry":[151,164],"levels.":[152],"It":[153],"indicates":[154],"that":[155,180],"there":[156],"mainly":[159],"statistical":[160],"effect":[161],"for":[166,186,207],"deviation,":[178],"indicating":[179],"these":[181],"features":[182],"significantly":[184],"different":[185],"normal":[188],"state,":[189],"light":[190],"anger,":[191,193],"moderate":[192],"heavy":[195],"anger.":[196],"The":[197],"research":[198],"results":[199],"provide":[200],"theoretical":[202],"basis":[203],"data":[205],"support":[206],"detection":[210],"aggressive":[212],"behavior":[214],"analyzing.":[215]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
