{"id":"https://openalex.org/W2980985189","doi":"https://doi.org/10.1145/3340555.3353749","title":"Driving Anomaly Detection with Conditional Generative Adversarial Network using Physiological and CAN-Bus Data","display_name":"Driving Anomaly Detection with Conditional Generative Adversarial Network using Physiological and CAN-Bus Data","publication_year":2019,"publication_date":"2019-10-14","ids":{"openalex":"https://openalex.org/W2980985189","doi":"https://doi.org/10.1145/3340555.3353749","mag":"2980985189"},"language":"en","primary_location":{"id":"doi:10.1145/3340555.3353749","doi":"https://doi.org/10.1145/3340555.3353749","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340555.3353749","pdf_url":null,"source":{"id":"https://openalex.org/S4363608440","display_name":"INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Multimodal Interaction","raw_type":"proceedings-article"},"volume":null,"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/A5070961417","display_name":"Yuning Qiu","orcid":"https://orcid.org/0000-0003-0268-0890","observed_orcids":["https://orcid.org/0000-0003-0268-0890","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":["University of Texas at Dallas, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Texas at Dallas, USA","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","observed_orcids":["https://orcid.org/0000-0002-6398-9245"]},"institutions":[{"id":"https://openalex.org/I4405271240","display_name":"Honda Research Institute, USA","ror":"https://ror.org/02441en43","country_code":"US","type":"facility","lineage":["https://openalex.org/I4405271240"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Teruhisa Misu","raw_affiliation_strings":["Honda Research Institute USA, Inc., USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Honda Research Institute USA, Inc., USA","institution_ids":["https://openalex.org/I4405271240"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040793194","display_name":"Carlos Busso","orcid":"https://orcid.org/0000-0002-4075-4072","observed_orcids":["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":["The University of Texas at Dallas, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Texas at Dallas, USA","institution_ids":["https://openalex.org/I162577319"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.2322,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.94405498,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"164","last_page":"173"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.33500000834465027,"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"}},"topics":[{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.33500000834465027,"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/T10525","display_name":"Human-Automation Interaction and Safety","score":0.3140000104904175,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.18160000443458557,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/conditional-gan","display_name":"conditional generative adversarial networks","score":0.9100000262260437},{"id":"https://openalex.org/keywords/physiological-signals","display_name":"physiological signals","score":0.7450000047683716},{"id":"https://openalex.org/keywords/driver-monitoring","display_name":"driver monitoring","score":0.5370000004768372},{"id":"https://openalex.org/keywords/can-bus","display_name":"CAN bus","score":0.7300000190734863},{"id":"https://openalex.org/keywords/driver-assistance-systems","display_name":"driver assistance systems","score":0.9089999794960022},{"id":"https://openalex.org/keywords/unsupervised-anomaly-detection","display_name":"unsupervised anomaly detection","score":0.925000011920929},{"id":"https://openalex.org/keywords/driving-dataset","display_name":"driving data","score":0.6019999980926514},{"id":"https://openalex.org/keywords/driver-intervention","display_name":"driver intervention","score":0.4410000145435333}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7443951368331909},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.651938259601593},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.5620276927947998},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5384191870689392},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5176916122436523},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5171372294425964},{"id":"https://openalex.org/C203479927","wikidata":"https://www.wikidata.org/wiki/Q5165939","display_name":"Controller (irrigation)","level":2,"score":0.49424293637275696},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.4849734306335449},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.46510204672813416},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46333611011505127},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36289602518081665},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14237242937088013},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.09307655692100525},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3340555.3353749","doi":"https://doi.org/10.1145/3340555.3353749","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340555.3353749","pdf_url":null,"source":{"id":"https://openalex.org/S4363608440","display_name":"INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Conference on Multimodal Interaction","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"sustainable_development_goals_aurora":[{"display_name":"Reduced inequalities","score":0.7099999785423279,"id":"https://metadata.un.org/sdg/10"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1985423199","https://openalex.org/W1987654648","https://openalex.org/W1989075876","https://openalex.org/W2048964781","https://openalex.org/W2094577405","https://openalex.org/W2099471712","https://openalex.org/W2100798515","https://openalex.org/W2115579991","https://openalex.org/W2171801645","https://openalex.org/W2176240313","https://openalex.org/W2305684127","https://openalex.org/W2552465644","https://openalex.org/W2561448204","https://openalex.org/W2566837273","https://openalex.org/W2598831904","https://openalex.org/W2735189551","https://openalex.org/W2798338071","https://openalex.org/W2806723288","https://openalex.org/W2891273344","https://openalex.org/W2903795257","https://openalex.org/W2904298530","https://openalex.org/W2962968835","https://openalex.org/W2991401881","https://openalex.org/W3154476931","https://openalex.org/W4244484547"],"related_works":["https://openalex.org/W4221146588","https://openalex.org/W4220772424","https://openalex.org/W3115767379","https://openalex.org/W4411447246","https://openalex.org/W4312905178","https://openalex.org/W4391567551","https://openalex.org/W2954713061","https://openalex.org/W4407213767","https://openalex.org/W2809871074","https://openalex.org/W4388726329"],"abstract_inverted_index":{"New":[0],"developments":[1],"in":[2,23,158],"advanced":[3],"driver":[4],"assistance":[5],"systems":[6,25],"(ADAS)":[7],"can":[8,63],"help":[9],"drivers":[10],"deal":[11],"with":[12],"risky":[13],"driving":[14,59,87,174,184,217],"maneuvers,":[15],"preventing":[16],"potential":[17],"hazard":[18],"scenarios.":[19],"A":[20],"key":[21],"challenge":[22],"these":[24],"is":[26,43,49,93,167,189],"to":[27,30,52,66,94,191],"determine":[28,53],"when":[29],"intervene.":[31],"While":[32],"there":[33],"are":[34,146],"situations":[35],"where":[36,90,143],"the":[37,69,91,119,127,144,149,156,159,162,198,201,208],"needs":[38],"for":[39,172,183,215],"intervention":[40],"or":[41,74,76],"feedback":[42],"clear":[44],"(e.g.,":[45],"lane":[46],"departure),":[47],"it":[48],"often":[50],"difficult":[51],"scenarios":[54,62],"that":[55,98,113],"deviate":[56],"from":[57,78,118,126],"normal":[58],"conditions.":[60],"These":[61],"appear":[64],"due":[65],"errors":[67],"by":[68,148],"drivers,":[70],"presence":[71],"of":[72,155,200,211],"pedestrian":[73],"bicycles,":[75],"maneuvers":[77],"other":[79],"vehicles.":[80],"We":[81,176,196],"formulate":[82],"this":[83,103,212],"problem":[84],"as":[85,169],"a":[86,110,170,180],"anomaly":[88,185],"detection,":[89],"goal":[92],"automatically":[95],"identify":[96],"cases":[97],"require":[99],"intervention.":[100],"Towards":[101],"addressing":[102],"challenging":[104],"but":[105],"important":[106],"goal,":[107],"we":[108],"propose":[109],"multimodal":[111],"system":[112,135],"considers":[114],"(1)":[115],"physiological":[116],"signals":[117,150,166],"driver,":[120],"and":[121,164,178,203],"(2)":[122],"vehicle":[123],"information":[124],"obtained":[125],"controller":[128],"area":[129],"network":[130],"(CAN)":[131],"bus":[132],"sensor.":[133],"The":[134,153],"relies":[136],"on":[137],"conditional":[138],"generative":[139],"adversarial":[140],"networks":[141],"(GAN)":[142],"models":[145],"constrained":[147],"previously":[151],"observed.":[152],"difference":[154],"scores":[157],"discriminator":[160],"between":[161],"predicted":[163],"actual":[165],"used":[168,190],"metric":[171],"detecting":[173,216],"anomalies.":[175,218],"collected":[177],"annotated":[179],"novel":[181],"dataset":[182],"detection":[186],"tasks,":[187],"which":[188,206],"validate":[192],"our":[193],"proposed":[194],"models.":[195],"present":[197],"analysis":[199],"results,":[202],"perceptual":[204],"evaluations":[205],"demonstrate":[207],"discriminative":[209],"power":[210],"unsupervised":[213],"approach":[214]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2019-10-25T00:00:00"}
