{"id":"https://openalex.org/W4220772424","doi":"https://doi.org/10.1109/tiv.2022.3160861","title":"Unsupervised Scalable Multimodal Driving Anomaly Detection","display_name":"Unsupervised Scalable Multimodal Driving Anomaly Detection","publication_year":2022,"publication_date":"2022-03-22","ids":{"openalex":"https://openalex.org/W4220772424","doi":"https://doi.org/10.1109/tiv.2022.3160861"},"language":"en","primary_location":{"id":"doi:10.1109/tiv.2022.3160861","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tiv.2022.3160861","pdf_url":"https://ieeexplore.ieee.org/ielx7/7274857/7448921/09739951.pdf","source":{"id":"https://openalex.org/S4210199657","display_name":"IEEE Transactions on Intelligent Vehicles","issn_l":"2379-8858","issn":["2379-8858","2379-8904"],"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 Vehicles","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://ieeexplore.ieee.org/ielx7/7274857/7448921/09739951.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103153285","display_name":"Yuning Qiu","orcid":"https://orcid.org/0000-0002-6377-229X"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuning Qiu","raw_affiliation_strings":["Department of Electrical Engineering, University of Texas at Dallas, Richardson, TX, USA","Electrical and Computer Engineering, The University of Texas at Dallas Erik Jonsson School of Engineering and Computer Science, 184698 Richardson, Texas, United States"],"raw_orcid":"https://orcid.org/0000-0002-6377-229X","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Texas at Dallas, Richardson, TX, USA","institution_ids":["https://openalex.org/I162577319"]},{"raw_affiliation_string":"Electrical and Computer Engineering, The University of Texas at Dallas Erik Jonsson School of Engineering and Computer Science, 184698 Richardson, Texas, United States","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084637778","display_name":"Teruhisa Misu","orcid":"https://orcid.org/0000-0002-6398-9245"},"institutions":[{"id":"https://openalex.org/I4210110847","display_name":"Human BioMolecular Research Institute","ror":"https://ror.org/018m20m74","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210110847"]},{"id":"https://openalex.org/I4210145184","display_name":"Honda (United States)","ror":"https://ror.org/04vdmc602","country_code":"US","type":"company","lineage":["https://openalex.org/I1283473643","https://openalex.org/I4210145184"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Teruhisa Misu","raw_affiliation_strings":["Honda Research Institute USA, Inc., San Jose, CA, USA","Human Interaction and Intelligence, Honda Research Institute, Mountain View, California, United States"],"raw_orcid":"https://orcid.org/0000-0002-6398-9245","affiliations":[{"raw_affiliation_string":"Honda Research Institute USA, Inc., San Jose, CA, USA","institution_ids":["https://openalex.org/I4210145184"]},{"raw_affiliation_string":"Human Interaction and Intelligence, Honda Research Institute, Mountain View, California, United States","institution_ids":["https://openalex.org/I4210110847"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040793194","display_name":"Carlos Busso","orcid":"https://orcid.org/0000-0002-4075-4072"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Carlos Busso","raw_affiliation_strings":["Department of Electrical Engineering, University of Texas at Dallas, Richardson, TX, USA","Electrical and Computer Engineering, The University of Texas at Dallas Erik Jonsson School of Engineering and Computer Science, 184698 Richardson, Texas, United States, 75080-3021"],"raw_orcid":"https://orcid.org/0000-0002-4075-4072","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Texas at Dallas, Richardson, TX, USA","institution_ids":["https://openalex.org/I162577319"]},{"raw_affiliation_string":"Electrical and Computer Engineering, The University of Texas at Dallas Erik Jonsson School of Engineering and Computer Science, 184698 Richardson, Texas, United States, 75080-3021","institution_ids":["https://openalex.org/I162577319"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.8851,"has_fulltext":true,"cited_by_count":33,"citation_normalized_percentile":{"value":0.9412706,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"8","issue":"4","first_page":"3154","last_page":"3165"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9995999932289124,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9995999932289124,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T10370","display_name":"Traffic and Road Safety","score":0.9958999752998352,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7759442329406738},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.7357974052429199},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7287490367889404},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7180075645446777},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5503803491592407},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5107443332672119},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4882996082305908},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4847504794597626},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.4623692035675049},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4398385286331177},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3747929334640503}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7759442329406738},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.7357974052429199},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7287490367889404},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7180075645446777},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5503803491592407},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5107443332672119},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4882996082305908},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4847504794597626},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.4623692035675049},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4398385286331177},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3747929334640503},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","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},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tiv.2022.3160861","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tiv.2022.3160861","pdf_url":"https://ieeexplore.ieee.org/ielx7/7274857/7448921/09739951.pdf","source":{"id":"https://openalex.org/S4210199657","display_name":"IEEE Transactions on Intelligent Vehicles","issn_l":"2379-8858","issn":["2379-8858","2379-8904"],"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 Vehicles","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/tiv.2022.3160861","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tiv.2022.3160861","pdf_url":"https://ieeexplore.ieee.org/ielx7/7274857/7448921/09739951.pdf","source":{"id":"https://openalex.org/S4210199657","display_name":"IEEE Transactions on Intelligent Vehicles","issn_l":"2379-8858","issn":["2379-8858","2379-8904"],"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 Vehicles","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.5799999833106995},{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.44999998807907104}],"awards":[],"funders":[{"id":"https://openalex.org/F4320318799","display_name":"Honda Research Institute, USA","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4220772424.pdf","grobid_xml":"https://content.openalex.org/works/W4220772424.grobid-xml"},"referenced_works_count":62,"referenced_works":["https://openalex.org/W1677182931","https://openalex.org/W1987654648","https://openalex.org/W2012486076","https://openalex.org/W2034411841","https://openalex.org/W2064675550","https://openalex.org/W2067830548","https://openalex.org/W2089453973","https://openalex.org/W2096733369","https://openalex.org/W2098458112","https://openalex.org/W2129367100","https://openalex.org/W2135801466","https://openalex.org/W2138356292","https://openalex.org/W2139203131","https://openalex.org/W2151666054","https://openalex.org/W2177953264","https://openalex.org/W2286439238","https://openalex.org/W2539417147","https://openalex.org/W2545688254","https://openalex.org/W2552502643","https://openalex.org/W2561448204","https://openalex.org/W2565083562","https://openalex.org/W2566920298","https://openalex.org/W2584992898","https://openalex.org/W2587098040","https://openalex.org/W2590652386","https://openalex.org/W2618786344","https://openalex.org/W2622068151","https://openalex.org/W2787947370","https://openalex.org/W2903795257","https://openalex.org/W2911200746","https://openalex.org/W2911277083","https://openalex.org/W2945522692","https://openalex.org/W2949924544","https://openalex.org/W2963045681","https://openalex.org/W2963195425","https://openalex.org/W2965433388","https://openalex.org/W2980985189","https://openalex.org/W2991401881","https://openalex.org/W3003987610","https://openalex.org/W3008397561","https://openalex.org/W3015309989","https://openalex.org/W3015821389","https://openalex.org/W3026525412","https://openalex.org/W3047056580","https://openalex.org/W3091535876","https://openalex.org/W3100219394","https://openalex.org/W3113416056","https://openalex.org/W3115767379","https://openalex.org/W3120702710","https://openalex.org/W3136173905","https://openalex.org/W4212889157","https://openalex.org/W4221146588","https://openalex.org/W4294583247","https://openalex.org/W4320013936","https://openalex.org/W4385245566","https://openalex.org/W6653680688","https://openalex.org/W6731136988","https://openalex.org/W6739901393","https://openalex.org/W6748495906","https://openalex.org/W6776239335","https://openalex.org/W6783184368","https://openalex.org/W6809488104"],"related_works":["https://openalex.org/W2185469136","https://openalex.org/W2011264131","https://openalex.org/W2380075625","https://openalex.org/W4306353150","https://openalex.org/W2026860389","https://openalex.org/W8219677","https://openalex.org/W3216879894","https://openalex.org/W2890132085","https://openalex.org/W4285233543","https://openalex.org/W4230838436"],"abstract_inverted_index":{"Driving":[0],"anomaly":[1,192],"detection":[2,61],"aims":[3],"to":[4,28,34,46,109,126,130,135,144,174,178],"identify":[5,25,53],"objects,":[6],"events":[7],"or":[8],"actions":[9],"that":[10,50],"can":[11,23,51],"increase":[12],"the":[13,60,89,93,118,151,158,162,170,190],"risk":[14],"of":[15,62,99,150],"accidents,":[16],"reducing":[17],"road":[18],"safety.":[19],"While":[20],"supervised":[21],"approaches":[22,49],"effectively":[24],"aspects":[26],"related":[27],"driving":[29,40,55,63,73,183,191],"anomalies,":[30],"it":[31,43,106],"is":[32,44,102,107,167],"unfeasible":[33],"tabulate":[35],"and":[36,71,92,133,181],"address":[37],"all":[38],"potential":[39],"anomalies.":[41],"Instead,":[42],"appealing":[45],"design":[47],"unsupervised":[48,78],"automatically":[52],"unexpected":[54,72],"scenarios.":[56],"This":[57],"study":[58],"formulates":[59],"anomalies":[64],"as":[65],"a":[66,141],"binary-discrimination":[67],"task":[68],"between":[69],"expected":[70],"behaviors.":[74],"We":[75,113,185],"propose":[76],"an":[77],"contrastive":[79],"method":[80],"using":[81],"conditional":[82,142],"generative":[83],"adversarial":[84],"networks":[85],"(GANs)":[86],"implemented":[87],"with":[88,169],"attention":[90,155],"model":[91,156],"triplet":[94,171],"loss":[95,172],"function.":[96],"A":[97],"feature":[98],"our":[100],"framework":[101,166],"its":[103],"scalability,":[104],"where":[105],"easy":[108],"add":[110],"new":[111],"modalities.":[112,153,163],"consider":[114],"five":[115,152],"different":[116],"modalities:":[117],"vehicle's":[119],"CAN-Bus":[120],"signals,":[121,124],"driver's":[122],"physiological":[123],"distance":[125,129,134],"nearby":[127,131,136],"pedestrians,":[128],"vehicles":[132],"bicycles.":[137],"Our":[138],"approach":[139],"trains":[140],"GAN":[143],"extract":[145],"latent":[146,159],"features":[147],"from":[148,161],"each":[149],"An":[154],"combines":[157],"representations":[160,177],"The":[164],"entire":[165],"trained":[168],"function":[173],"generate":[175],"effective":[176],"discriminate":[179],"normal":[180],"abnormal":[182],"segments.":[184],"conduct":[186],"experimental":[187],"evaluations":[188],"on":[189],"dataset":[193],"(DAD),":[194],"achieving":[195],"improved":[196],"performance":[197],"over":[198],"alternative":[199],"approaches.":[200]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":12}],"updated_date":"2026-06-14T07:44:22.658603","created_date":"2025-10-10T00:00:00"}