{"id":"https://openalex.org/W4402509039","doi":"https://doi.org/10.1109/thms.2024.3452411","title":"Building Contextualized Trust Profiles in Conditionally Automated Driving","display_name":"Building Contextualized Trust Profiles in Conditionally Automated Driving","publication_year":2024,"publication_date":"2024-09-13","ids":{"openalex":"https://openalex.org/W4402509039","doi":"https://doi.org/10.1109/thms.2024.3452411"},"language":"en","primary_location":{"id":"doi:10.1109/thms.2024.3452411","is_oa":false,"landing_page_url":"https://doi.org/10.1109/thms.2024.3452411","pdf_url":null,"source":{"id":"https://openalex.org/S2476799526","display_name":"IEEE Transactions on Human-Machine Systems","issn_l":"2168-2291","issn":["2168-2291","2168-2305"],"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 Human-Machine 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/A5032813310","display_name":"Lilit Avetisyan","orcid":"https://orcid.org/0000-0003-4206-6385"},"institutions":[{"id":"https://openalex.org/I4210130704","display_name":"University of Michigan\u2013Dearborn","ror":"https://ror.org/035wtm547","country_code":"US","type":"education","lineage":["https://openalex.org/I4210130704"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Lilit Avetisyan","raw_affiliation_strings":["Department of Industrial and Manufacturing Systems Engineering, The University of Michigan, Dearborn, MI, USA"],"affiliations":[{"raw_affiliation_string":"Department of Industrial and Manufacturing Systems Engineering, The University of Michigan, Dearborn, MI, USA","institution_ids":["https://openalex.org/I4210130704"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007618410","display_name":"Jackie Ayoub","orcid":"https://orcid.org/0000-0003-0274-492X"},"institutions":[{"id":"https://openalex.org/I4210130704","display_name":"University of Michigan\u2013Dearborn","ror":"https://ror.org/035wtm547","country_code":"US","type":"education","lineage":["https://openalex.org/I4210130704"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jackie Ayoub","raw_affiliation_strings":["Department of Industrial and Manufacturing Systems Engineering, The University of Michigan, Dearborn, MI, USA"],"affiliations":[{"raw_affiliation_string":"Department of Industrial and Manufacturing Systems Engineering, The University of Michigan, Dearborn, MI, USA","institution_ids":["https://openalex.org/I4210130704"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067895217","display_name":"X. Jessie Yang","orcid":"https://orcid.org/0000-0001-6071-0387"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"X. Jessie Yang","raw_affiliation_strings":["Industrial and Operations Engineering, and Robotics, University of Michigan, Ann Arbor, MI, USA"],"affiliations":[{"raw_affiliation_string":"Industrial and Operations Engineering, and Robotics, University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047702220","display_name":"Feng Zhou","orcid":"https://orcid.org/0000-0001-6123-073X"},"institutions":[{"id":"https://openalex.org/I4210130704","display_name":"University of Michigan\u2013Dearborn","ror":"https://ror.org/035wtm547","country_code":"US","type":"education","lineage":["https://openalex.org/I4210130704"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Feng Zhou","raw_affiliation_strings":["Department of Industrial and Manufacturing Systems Engineering, The University of Michigan, Dearborn, MI, USA"],"affiliations":[{"raw_affiliation_string":"Department of Industrial and Manufacturing Systems Engineering, The University of Michigan, Dearborn, MI, USA","institution_ids":["https://openalex.org/I4210130704"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5032813310"],"corresponding_institution_ids":["https://openalex.org/I4210130704"],"apc_list":null,"apc_paid":null,"fwci":0.695,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.7562937,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"54","issue":"6","first_page":"658","last_page":"667"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9847999811172485,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9847999811172485,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.960099995136261,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10927","display_name":"Access Control and Trust","score":0.9556000232696533,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"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/computer-science","display_name":"Computer science","score":0.44793546199798584},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.3376097083091736}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44793546199798584},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.3376097083091736}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/thms.2024.3452411","is_oa":false,"landing_page_url":"https://doi.org/10.1109/thms.2024.3452411","pdf_url":null,"source":{"id":"https://openalex.org/S2476799526","display_name":"IEEE Transactions on Human-Machine Systems","issn_l":"2168-2291","issn":["2168-2291","2168-2305"],"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 Human-Machine Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8696153165","display_name":null,"funder_award_id":"2138274","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1979004942","https://openalex.org/W1981856831","https://openalex.org/W1987329516","https://openalex.org/W2069706646","https://openalex.org/W2079512457","https://openalex.org/W2118448219","https://openalex.org/W2130087774","https://openalex.org/W2142175015","https://openalex.org/W2143074722","https://openalex.org/W2169863498","https://openalex.org/W2319663855","https://openalex.org/W2466627989","https://openalex.org/W2515228516","https://openalex.org/W2522016997","https://openalex.org/W2920919283","https://openalex.org/W2922404818","https://openalex.org/W2963029566","https://openalex.org/W3003266444","https://openalex.org/W3048723388","https://openalex.org/W3048724669","https://openalex.org/W3089447464","https://openalex.org/W3096501110","https://openalex.org/W3118767882","https://openalex.org/W3121315930","https://openalex.org/W3124080842","https://openalex.org/W3177369277","https://openalex.org/W3184621130","https://openalex.org/W3189469417","https://openalex.org/W3199595333","https://openalex.org/W4206019193","https://openalex.org/W4231598180","https://openalex.org/W4231751901","https://openalex.org/W4243342770","https://openalex.org/W4285496425","https://openalex.org/W4285792044","https://openalex.org/W4288421664","https://openalex.org/W4296306243","https://openalex.org/W4312355362","https://openalex.org/W4385453451","https://openalex.org/W4399801096","https://openalex.org/W6682020077","https://openalex.org/W6748816842","https://openalex.org/W6751754416"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"Trust":[0],"is":[1,18],"crucial":[2],"for":[3,45,200],"ensuring":[4],"the":[5,22,116,134,144,151,201],"safety,":[6],"security,":[7],"and":[8,15,21,76,85,100,128,165,208,219],"widespread":[9],"adoption":[10],"of":[11,52,163,168,174,194,203],"automated":[12,223],"vehicles":[13],"(AVs),":[14],"if":[16],"trust":[17,37,65,158,180,186,206,214],"lacking,":[19],"drivers":[20,46],"general":[23],"public":[24],"may":[25],"hesitate":[26],"to":[27,34,41,89,111,149,211],"embrace":[28],"this":[29,195],"technology.":[30],"This":[31],"research":[32,196],"seeks":[33],"investigate":[35],"contextualized":[36,64,157,179],"profiles":[38,66,181],"in":[39,47,87,118,155,222],"order":[40],"create":[42],"personalized":[43,204],"experiences":[44],"AVs":[48],"with":[49],"varying":[50],"levels":[51],"reliability.":[53],"A":[54],"driving":[55],"simulator":[56],"experiment":[57,103],"involving":[58],"70":[59],"participants":[60,108],"revealed":[61],"three":[62,119],"distinct":[63],"(i.e.,":[67],"<italic":[68,72,77],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[69,73,78],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">confident":[70],"copilots</i>,":[71],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">myopic":[74],"pragmatists</i>,":[75],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">reluctant":[79],"automators</i>)":[80],"identified":[81],"through":[82],"K-means":[83],"clustering,":[84],"analyzed":[86],"relation":[88],"drivers'":[90,213],"dynamic":[91],"trust,":[92,94,97],"dispositional":[93],"initial":[95],"learned":[96],"personality":[98],"traits,":[99],"emotions.":[101],"The":[102,192],"encompassed":[104],"eight":[105],"scenarios":[106],"where":[107],"were":[109],"requested":[110],"take":[112],"over":[113],"control":[114,122],"from":[115,188],"AV":[117],"conditions:":[120],"a":[121,124,129,136,189],"condition,":[123,127],"false":[125],"alarm":[126],"miss":[130],"condition.":[131],"To":[132],"validate":[133],"models,":[135],"multinomial":[137],"logistic":[138],"regression":[139],"model":[140],"was":[141],"constructed":[142],"using":[143],"shapley":[145],"additive":[146],"explanations":[147],"explainer":[148],"determine":[150],"most":[152],"influential":[153],"features":[154],"predicting":[156],"profiles,":[159],"achieving":[160],"an":[161,166,172],"F1-score":[162],"0.90":[164],"accuracy":[167],"0.89.":[169],"In":[170],"addition,":[171],"examination":[173],"how":[175],"individual":[176],"factors":[177],"impact":[178],"provided":[182],"valuable":[183],"insights":[184],"into":[185],"dynamics":[187],"user-centric":[190],"perspective.":[191],"outcomes":[193],"hold":[197],"significant":[198],"implications":[199],"development":[202],"in-vehicle":[205],"monitoring":[207],"calibration":[209],"systems":[210],"modulate":[212],"levels,":[215],"thereby":[216],"enhancing":[217],"safety":[218],"user":[220],"experience":[221],"driving.":[224]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}