{"id":"https://openalex.org/W2789865447","doi":"https://doi.org/10.3390/make1010003","title":"Category Maps Describe Driving Episodes Recorded with Event Data Recorders","display_name":"Category Maps Describe Driving Episodes Recorded with Event Data Recorders","publication_year":2018,"publication_date":"2018-03-12","ids":{"openalex":"https://openalex.org/W2789865447","doi":"https://doi.org/10.3390/make1010003","mag":"2789865447"},"language":"en","primary_location":{"id":"doi:10.3390/make1010003","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make1010003","pdf_url":"https://www.mdpi.com/2504-4990/1/1/3/pdf?version=1545210514","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2504-4990/1/1/3/pdf?version=1545210514","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015549649","display_name":"Hirokazu Madokoro","orcid":"https://orcid.org/0000-0001-5485-2928"},"institutions":[{"id":"https://openalex.org/I5467274","display_name":"Akita Prefectural University","ror":"https://ror.org/05b1kx621","country_code":"JP","type":"education","lineage":["https://openalex.org/I5467274"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Hirokazu Madokoro","raw_affiliation_strings":["Faculty of Systems Science and Technology, Akita Prefectural University, Yurihonjo City, Akita 015-0055, Japan"],"raw_orcid":"https://orcid.org/0000-0001-5485-2928","affiliations":[{"raw_affiliation_string":"Faculty of Systems Science and Technology, Akita Prefectural University, Yurihonjo City, Akita 015-0055, Japan","institution_ids":["https://openalex.org/I5467274"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004284371","display_name":"Kazuhito Sato","orcid":"https://orcid.org/0009-0006-3045-5112"},"institutions":[{"id":"https://openalex.org/I5467274","display_name":"Akita Prefectural University","ror":"https://ror.org/05b1kx621","country_code":"JP","type":"education","lineage":["https://openalex.org/I5467274"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuhito Sato","raw_affiliation_strings":["Faculty of Systems Science and Technology, Akita Prefectural University, Yurihonjo City, Akita 015-0055, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Systems Science and Technology, Akita Prefectural University, Yurihonjo City, Akita 015-0055, Japan","institution_ids":["https://openalex.org/I5467274"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074137157","display_name":"Nobuhiro Shimoi","orcid":"https://orcid.org/0000-0002-1024-0361"},"institutions":[{"id":"https://openalex.org/I5467274","display_name":"Akita Prefectural University","ror":"https://ror.org/05b1kx621","country_code":"JP","type":"education","lineage":["https://openalex.org/I5467274"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Nobuhiro Shimoi","raw_affiliation_strings":["Faculty of Systems Science and Technology, Akita Prefectural University, Yurihonjo City, Akita 015-0055, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Systems Science and Technology, Akita Prefectural University, Yurihonjo City, Akita 015-0055, Japan","institution_ids":["https://openalex.org/I5467274"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5015549649"],"corresponding_institution_ids":["https://openalex.org/I5467274"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01499973,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":"1","first_page":"43","last_page":"63"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9789999723434448,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9789999723434448,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10581","display_name":"Neural dynamics and brain function","score":0.9767000079154968,"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"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9660000205039978,"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/distraction","display_name":"Distraction","score":0.7741546630859375},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6923783421516418},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.6314393877983093},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5257290601730347},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5061449408531189},{"id":"https://openalex.org/keywords/cognitive-map","display_name":"Cognitive map","score":0.4312431216239929},{"id":"https://openalex.org/keywords/cognition","display_name":"Cognition","score":0.3590906262397766},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3402196764945984},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.1249043345451355},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.09750378131866455}],"concepts":[{"id":"https://openalex.org/C2776378700","wikidata":"https://www.wikidata.org/wiki/Q3030775","display_name":"Distraction","level":2,"score":0.7741546630859375},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6923783421516418},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.6314393877983093},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5257290601730347},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5061449408531189},{"id":"https://openalex.org/C170494330","wikidata":"https://www.wikidata.org/wiki/Q1778434","display_name":"Cognitive map","level":3,"score":0.4312431216239929},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.3590906262397766},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3402196764945984},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.1249043345451355},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.09750378131866455},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/make1010003","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make1010003","pdf_url":"https://www.mdpi.com/2504-4990/1/1/3/pdf?version=1545210514","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},{"id":"pmh:oai:mdpi.com:/2504-4990/1/1/3/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/make1010003","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning and Knowledge Extraction; Volume 1; Issue 1; Pages: 43-63","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/make1010003","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make1010003","pdf_url":"https://www.mdpi.com/2504-4990/1/1/3/pdf?version=1545210514","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.5799999833106995,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2789865447.pdf","grobid_xml":"https://content.openalex.org/works/W2789865447.grobid-xml"},"referenced_works_count":49,"referenced_works":["https://openalex.org/W616614584","https://openalex.org/W1518186130","https://openalex.org/W1566135517","https://openalex.org/W1588340522","https://openalex.org/W1966156549","https://openalex.org/W1980832965","https://openalex.org/W1986830331","https://openalex.org/W1988790447","https://openalex.org/W2006488519","https://openalex.org/W2037956097","https://openalex.org/W2042243302","https://openalex.org/W2048710758","https://openalex.org/W2052604480","https://openalex.org/W2053120614","https://openalex.org/W2093353037","https://openalex.org/W2104128137","https://openalex.org/W2110802877","https://openalex.org/W2113594567","https://openalex.org/W2114587936","https://openalex.org/W2114653151","https://openalex.org/W2120220258","https://openalex.org/W2124386111","https://openalex.org/W2127218421","https://openalex.org/W2128272608","https://openalex.org/W2138584058","https://openalex.org/W2142796031","https://openalex.org/W2144225695","https://openalex.org/W2146103513","https://openalex.org/W2149095485","https://openalex.org/W2150134853","https://openalex.org/W2152477898","https://openalex.org/W2164598857","https://openalex.org/W2217896605","https://openalex.org/W2290402387","https://openalex.org/W2508277576","https://openalex.org/W2581448385","https://openalex.org/W2615116922","https://openalex.org/W2724851297","https://openalex.org/W2734656543","https://openalex.org/W2913429812","https://openalex.org/W4213332169","https://openalex.org/W4232670376","https://openalex.org/W4297944103","https://openalex.org/W6636494156","https://openalex.org/W6677350515","https://openalex.org/W6681177894","https://openalex.org/W6684392942","https://openalex.org/W6740313844","https://openalex.org/W7000443800"],"related_works":["https://openalex.org/W1984342691","https://openalex.org/W2470048815","https://openalex.org/W2324884046","https://openalex.org/W641612223","https://openalex.org/W2906771794","https://openalex.org/W2028203774","https://openalex.org/W4205873045","https://openalex.org/W2174716869","https://openalex.org/W146094510","https://openalex.org/W4323276068"],"abstract_inverted_index":{"This":[0,19],"study":[1],"was":[2],"conducted":[3],"to":[4,31,133,143,151,189],"create":[5,134],"driving":[6,28,88,93,118,135,166,186,190],"episodes":[7,167],"using":[8,67,79,116,164,172],"machine-learning-based":[9],"algorithms":[10],"that":[11,91],"address":[12],"long-term":[13],"memory":[14,25],"(LTM)":[15],"and":[16,52,70,82,95,124,196],"topological":[17,65],"mapping.":[18],"paper":[20],"presents":[21],"a":[22,62,113,117,193],"novel":[23],"episodic":[24,110],"model":[26,35],"for":[27],"safety":[29],"according":[30,142,188],"traffic":[32],"scenes.":[33],"The":[34,98],"incorporates":[36],"three":[37],"important":[38],"features:":[39],"adaptive":[40],"resonance":[41],"theory":[42],"(ART),":[43],"which":[44,57,75],"learns":[45],"time-series":[46],"features":[47,81,147,187],"incrementally":[48],"while":[49],"maintaining":[50],"stability":[51],"plasticity;":[53],"self-organizing":[54],"maps":[55,78,86,103],"(SOMs),":[56],"represent":[58,87],"input":[59,80],"data":[60,175],"as":[61,109,129],"map":[63],"with":[64,168,178],"relations":[66],"self-mapping":[68],"characteristics;":[69],"counter":[71,83],"propagation":[72],"networks":[73],"(CPNs),":[74],"label":[76],"category":[77,182],"signals.":[84],"Category":[85],"episode":[89],"information":[90,132],"includes":[92],"contexts":[94],"facial":[96,146],"expressions.":[97],"bursting":[99],"states":[100],"of":[101,127,155,163],"respective":[102],"produce":[104],"LTM":[105],"created":[106],"on":[107,145,192],"ART":[108],"memory.":[111],"For":[112],"preliminary":[114],"experiment":[115],"simulator":[119],"(DS),":[120],"we":[121,138,184],"measure":[122,139],"gazes":[123],"face":[125],"orientations":[126],"drivers":[128],"their":[130],"internal":[131],"episodes.":[136],"Moreover,":[137],"cognitive":[140],"distraction":[141],"effects":[144],"shown":[148],"in":[149],"reaction":[150],"simulated":[152],"near-misses.":[153],"Evaluation":[154],"the":[156,161],"experimentally":[157],"obtained":[158,171],"results":[159],"show":[160],"possibility":[162],"recorded":[165],"image":[169],"datasets":[170],"an":[173,197],"event":[174],"recorder":[176],"(EDR)":[177],"two":[179],"cameras.":[180],"Using":[181],"maps,":[183],"visualize":[185],"scenes":[191],"public":[194],"road":[195],"expressway.":[198]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}