{"id":"https://openalex.org/W7139130475","doi":"https://doi.org/10.1109/tits.2026.3670120","title":"Analysis of Situational Acceptance and Objective Indicators During Automated Driving: A Driving Simulator Study","display_name":"Analysis of Situational Acceptance and Objective Indicators During Automated Driving: A Driving Simulator Study","publication_year":2026,"publication_date":"2026-03-19","ids":{"openalex":"https://openalex.org/W7139130475","doi":"https://doi.org/10.1109/tits.2026.3670120"},"language":null,"primary_location":{"id":"doi:10.1109/tits.2026.3670120","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2026.3670120","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/A5111015073","display_name":"Chenchang Li","orcid":null},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Chenchang Li","raw_affiliation_strings":["Institute of Industrial Science, The University of Tokyo, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0009-0003-9738-9971","affiliations":[{"raw_affiliation_string":"Institute of Industrial Science, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130203610","display_name":"Bo Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I207014233","display_name":"Kyushu Institute of Technology","ror":"https://ror.org/02278tr80","country_code":"JP","type":"education","lineage":["https://openalex.org/I207014233"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Bo Yang","raw_affiliation_strings":["School of Computer Science and Systems Engineering, Kyushu Institute of Technology, Fukuoka, Japan"],"raw_orcid":"https://orcid.org/0000-0001-8976-5971","affiliations":[{"raw_affiliation_string":"School of Computer Science and Systems Engineering, Kyushu Institute of Technology, Fukuoka, Japan","institution_ids":["https://openalex.org/I207014233"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022584343","display_name":"Muhua Guan","orcid":"https://orcid.org/0000-0002-7478-6152"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Muhua Guan","raw_affiliation_strings":["Institute of Industrial Science, The University of Tokyo, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0002-7478-6152","affiliations":[{"raw_affiliation_string":"Institute of Industrial Science, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087162559","display_name":"Zheng Wang","orcid":"https://orcid.org/0000-0002-7589-7954"},"institutions":[{"id":"https://openalex.org/I57093077","display_name":"Swinburne University of Technology","ror":"https://ror.org/031rekg67","country_code":"AU","type":"education","lineage":["https://openalex.org/I57093077"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Zheng Wang","raw_affiliation_strings":["Department of Computing Technologies, Swinburne University of Technology, Melbourne, Australia"],"raw_orcid":"https://orcid.org/0000-0002-7589-7954","affiliations":[{"raw_affiliation_string":"Department of Computing Technologies, Swinburne University of Technology, Melbourne, Australia","institution_ids":["https://openalex.org/I57093077"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023192293","display_name":"Kimihiko Nakano","orcid":"https://orcid.org/0000-0003-3532-960X"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kimihiko Nakano","raw_affiliation_strings":["Institute of Industrial Science, The University of Tokyo, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0003-3532-960X","affiliations":[{"raw_affiliation_string":"Institute of Industrial Science, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.29582214,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"27","issue":"6","first_page":"6474","last_page":"6490"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10525","display_name":"Human-Automation Interaction and Safety","score":0.9848999977111816,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social 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/T10525","display_name":"Human-Automation Interaction and Safety","score":0.9848999977111816,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social 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/T10370","display_name":"Traffic and Road Safety","score":0.0027000000700354576,"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"}},{"id":"https://openalex.org/T12315","display_name":"Older Adults Driving Studies","score":0.0012000000569969416,"subfield":{"id":"https://openalex.org/subfields/3612","display_name":"Physical Therapy, Sports Therapy and Rehabilitation"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/situational-ethics","display_name":"Situational ethics","score":0.5892000198364258},{"id":"https://openalex.org/keywords/driving-simulator","display_name":"Driving simulator","score":0.5347999930381775},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5098999738693237},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.49459999799728394},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4864000082015991},{"id":"https://openalex.org/keywords/situation-analysis","display_name":"Situation analysis","score":0.4819999933242798},{"id":"https://openalex.org/keywords/gaze","display_name":"Gaze","score":0.4311999976634979},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4284000098705292},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4156000018119812}],"concepts":[{"id":"https://openalex.org/C9114305","wikidata":"https://www.wikidata.org/wiki/Q1428317","display_name":"Situational ethics","level":2,"score":0.5892000198364258},{"id":"https://openalex.org/C2780689630","wikidata":"https://www.wikidata.org/wiki/Q2081815","display_name":"Driving simulator","level":2,"score":0.5347999930381775},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5315999984741211},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5098999738693237},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.5005000233650208},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.49459999799728394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49140000343322754},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4864000082015991},{"id":"https://openalex.org/C14911803","wikidata":"https://www.wikidata.org/wiki/Q7532148","display_name":"Situation analysis","level":2,"score":0.4819999933242798},{"id":"https://openalex.org/C2779916870","wikidata":"https://www.wikidata.org/wiki/Q14467155","display_name":"Gaze","level":2,"score":0.4311999976634979},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4284000098705292},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.41850000619888306},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4156000018119812},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41179999709129333},{"id":"https://openalex.org/C145804949","wikidata":"https://www.wikidata.org/wiki/Q478123","display_name":"Situation awareness","level":2,"score":0.397599995136261},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.38179999589920044},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.373199999332428},{"id":"https://openalex.org/C87833898","wikidata":"https://www.wikidata.org/wiki/Q1060280","display_name":"Advanced driver assistance systems","level":2,"score":0.359499990940094},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.34549999237060547},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.30869999527931213},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.30799999833106995},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.30790001153945923},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.29679998755455017},{"id":"https://openalex.org/C2776185967","wikidata":"https://www.wikidata.org/wiki/Q112945","display_name":"Technology acceptance model","level":3,"score":0.2879999876022339},{"id":"https://openalex.org/C52970973","wikidata":"https://www.wikidata.org/wiki/Q2497134","display_name":"Adaptive system","level":2,"score":0.28349998593330383},{"id":"https://openalex.org/C6683253","wikidata":"https://www.wikidata.org/wiki/Q7075535","display_name":"Obstacle avoidance","level":4,"score":0.27559998631477356},{"id":"https://openalex.org/C89505385","wikidata":"https://www.wikidata.org/wiki/Q47146","display_name":"User interface","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C67712803","wikidata":"https://www.wikidata.org/wiki/Q7901853","display_name":"User modeling","level":3,"score":0.2538999915122986}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2026.3670120","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2026.3670120","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/G3110421111","display_name":null,"funder_award_id":"01101","funder_id":"https://openalex.org/F4320335839","funder_display_name":"National Institute of Information and Communications Technology"}],"funders":[{"id":"https://openalex.org/F4320335839","display_name":"National Institute of Information and Communications Technology","ror":"https://ror.org/016bgq349"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"the":[1,24,36,47,53,126,142,145,151,173,184],"rapidly":[2],"evolving":[3],"field":[4],"of":[5,26,38,49,55,63,87,144,150],"Intelligent":[6],"Transportation":[7],"Systems,":[8],"users\u2019":[9],"low":[10],"acceptance":[11,40,51,64,180,190],"caused":[12],"by":[13,113,168],"psychological":[14,114],"barriers":[15],"has":[16],"emerged":[17],"as":[18],"a":[19,27,60,67,177],"significant":[20],"obstacle":[21],"to":[22,79,132,138,170,188],"realizing":[23],"vision":[25],"safe,":[28],"efficient,":[29],"and":[30,45,58,83,104,107,134,196],"smooth":[31],"mobility":[32],"experience.":[33],"Building":[34],"on":[35,66,125],"foundation":[37],"technology":[39],"research,":[41],"this":[42],"study":[43,185],"introduces":[44],"validates":[46],"concept":[48],"situational":[50],"within":[52],"context":[54],"automated":[56],"driving,":[57],"establishes":[59],"two-dimensional":[61,152],"model":[62,72,153],"based":[65],"driving":[68],"simulator":[69],"study.":[70],"This":[71],"comprises":[73],"two":[74],"dimensions:":[75],"positivity":[76],"(the":[77,85],"tendency":[78],"accept":[80],"or":[81,155],"reject)":[82],"firmness":[84],"strength":[86],"that":[88],"tendency).":[89],"Each":[90],"dimension":[91],"showed":[92],"correlations":[93],"with":[94,165],"objective":[95,179],"indicators,":[96],"including":[97],"decision-making":[98],"timing,":[99],"gaze":[100],"fixation,":[101],"pupil":[102],"diameter,":[103],"eyelid":[105],"opening,":[106],"these":[108],"relationships":[109],"were":[110],"further":[111,140],"explained":[112],"theories.":[115],"Furthermore,":[116],"multiple":[117],"machine":[118],"learning":[119],"models":[120],"demonstrated":[121],"strong":[122],"classification":[123,158],"performance":[124],"feature":[127],"set":[128],"(four-class":[129],"accuracy":[130,136,159],"up":[131,137,169],"0.6379":[133],"binary":[135],"0.8608),":[139],"confirming":[141],"utility":[143],"selected":[146],"features.":[147],"The":[148],"incorporation":[149],"maintained":[154],"even":[156],"enhanced":[157],"while":[160],"substantially":[161],"reducing":[162],"computational":[163],"cost,":[164],"FLOPs":[166],"decreased":[167],"96%,":[171],"laying":[172],"groundwork":[174],"for":[175,202],"developing":[176,203],"real-time,":[178,204],"estimation":[181],"method.":[182],"Additionally,":[183],"provides":[186],"implications":[187],"enhance":[189],"in":[191],"interface":[192],"transparency,":[193],"motivational":[194],"mechanisms,":[195],"adaptive":[197,205],"personalization,":[198],"offering":[199],"actionable":[200],"insights":[201],"in-vehicle":[206],"systems.":[207]},"counts_by_year":[],"updated_date":"2026-06-05T06:17:00.636019","created_date":"2026-03-20T00:00:00"}
