{"id":"https://openalex.org/W1550337734","doi":"https://doi.org/10.1109/ivs.2015.7225811","title":"Automatic lane change extraction based on temporal patterns of symbolized driving behavioral data","display_name":"Automatic lane change extraction based on temporal patterns of symbolized driving behavioral data","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W1550337734","doi":"https://doi.org/10.1109/ivs.2015.7225811","mag":"1550337734"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2015.7225811","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2015.7225811","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-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/A5000776443","display_name":"Masataka Mori","orcid":"https://orcid.org/0000-0002-1473-8669"},"institutions":[{"id":"https://openalex.org/I4210132650","display_name":"Denso (Japan)","ror":"https://ror.org/04hkpfa76","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210132650"]},{"id":"https://openalex.org/I67530263","display_name":"Denso (United States)","ror":"https://ror.org/02w314k38","country_code":"US","type":"company","lineage":["https://openalex.org/I4210132650","https://openalex.org/I67530263"]}],"countries":["JP","US"],"is_corresponding":true,"raw_author_name":"Masataka Mori","raw_affiliation_strings":["Kabushiki Kaisha Denso, Kariya, Aichi, JP","Corporate R&D Div. 3, DENSO CORPORATION, Aichi, Japan"],"affiliations":[{"raw_affiliation_string":"Kabushiki Kaisha Denso, Kariya, Aichi, JP","institution_ids":["https://openalex.org/I4210132650"]},{"raw_affiliation_string":"Corporate R&D Div. 3, DENSO CORPORATION, Aichi, Japan","institution_ids":["https://openalex.org/I67530263"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077857378","display_name":"Kazuhito Takenaka","orcid":"https://orcid.org/0009-0001-0821-2724"},"institutions":[{"id":"https://openalex.org/I67530263","display_name":"Denso (United States)","ror":"https://ror.org/02w314k38","country_code":"US","type":"company","lineage":["https://openalex.org/I4210132650","https://openalex.org/I67530263"]},{"id":"https://openalex.org/I4210132650","display_name":"Denso (Japan)","ror":"https://ror.org/04hkpfa76","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210132650"]}],"countries":["JP","US"],"is_corresponding":false,"raw_author_name":"Kazuhito Takenaka","raw_affiliation_strings":["Kabushiki Kaisha Denso, Kariya, Aichi, JP","Corporate R&D Div. 3, DENSO CORPORATION, Aichi, Japan"],"affiliations":[{"raw_affiliation_string":"Kabushiki Kaisha Denso, Kariya, Aichi, JP","institution_ids":["https://openalex.org/I4210132650"]},{"raw_affiliation_string":"Corporate R&D Div. 3, DENSO CORPORATION, Aichi, Japan","institution_ids":["https://openalex.org/I67530263"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067199220","display_name":"Takashi Bando","orcid":"https://orcid.org/0000-0001-8662-0742"},"institutions":[{"id":"https://openalex.org/I67530263","display_name":"Denso (United States)","ror":"https://ror.org/02w314k38","country_code":"US","type":"company","lineage":["https://openalex.org/I4210132650","https://openalex.org/I67530263"]},{"id":"https://openalex.org/I4210132650","display_name":"Denso (Japan)","ror":"https://ror.org/04hkpfa76","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210132650"]}],"countries":["JP","US"],"is_corresponding":false,"raw_author_name":"Takashi Bando","raw_affiliation_strings":["Kabushiki Kaisha Denso, Kariya, Aichi, JP","Corporate R&D Div. 3, DENSO CORPORATION, Aichi, Japan"],"affiliations":[{"raw_affiliation_string":"Kabushiki Kaisha Denso, Kariya, Aichi, JP","institution_ids":["https://openalex.org/I4210132650"]},{"raw_affiliation_string":"Corporate R&D Div. 3, DENSO CORPORATION, Aichi, Japan","institution_ids":["https://openalex.org/I67530263"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023160093","display_name":"Tadahiro Taniguchi","orcid":"https://orcid.org/0000-0002-5682-2076"},"institutions":[{"id":"https://openalex.org/I135768898","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03","country_code":"JP","type":"education","lineage":["https://openalex.org/I135768898","https://openalex.org/I4390039241"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tadahiro Taniguchi","raw_affiliation_strings":["Ritsumeikan Daigaku, Kyoto, Kyoto, JP","College of Information, Science and Engineering, Ritsumeikan University, Shiga, Japan"],"affiliations":[{"raw_affiliation_string":"Ritsumeikan Daigaku, Kyoto, Kyoto, JP","institution_ids":["https://openalex.org/I135768898"]},{"raw_affiliation_string":"College of Information, Science and Engineering, Ritsumeikan University, Shiga, Japan","institution_ids":["https://openalex.org/I135768898"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108524583","display_name":"Chiyomi Miyajima","orcid":null},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Chiyomi Miyajima","raw_affiliation_strings":["Nagoya Daigaku, Nagoya, Aichi, JP","Graduate School of Information Science, Nagoya University, Aichi, Japan"],"affiliations":[{"raw_affiliation_string":"Nagoya Daigaku, Nagoya, Aichi, JP","institution_ids":["https://openalex.org/I60134161"]},{"raw_affiliation_string":"Graduate School of Information Science, Nagoya University, Aichi, Japan","institution_ids":["https://openalex.org/I60134161"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042118446","display_name":"Kazuya Takeda","orcid":"https://orcid.org/0000-0002-0330-1787"},"institutions":[{"id":"https://openalex.org/I60134161","display_name":"Nagoya University","ror":"https://ror.org/04chrp450","country_code":"JP","type":"education","lineage":["https://openalex.org/I60134161"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuya Takeda","raw_affiliation_strings":["Nagoya Daigaku, Nagoya, Aichi, JP","Institute of Innovation for Future Society, Nagoya University, Aichi, Japan"],"affiliations":[{"raw_affiliation_string":"Nagoya Daigaku, Nagoya, Aichi, JP","institution_ids":["https://openalex.org/I60134161"]},{"raw_affiliation_string":"Institute of Innovation for Future Society, Nagoya University, Aichi, Japan","institution_ids":["https://openalex.org/I60134161"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5000776443"],"corresponding_institution_ids":["https://openalex.org/I4210132650","https://openalex.org/I67530263"],"apc_list":null,"apc_paid":null,"fwci":3.1591,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.92123368,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"976","last_page":"981"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10799","display_name":"Data Visualization and Analytics","score":0.9901999831199646,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9839000105857849,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7702010869979858},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6280679702758789},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5693326592445374},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.5560862421989441},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.47489967942237854},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.4528515934944153},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3615758717060089},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34418508410453796},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3318251669406891},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0812387466430664}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7702010869979858},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6280679702758789},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5693326592445374},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.5560862421989441},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.47489967942237854},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.4528515934944153},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3615758717060089},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34418508410453796},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3318251669406891},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0812387466430664},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivs.2015.7225811","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2015.7225811","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W77912868","https://openalex.org/W1583553994","https://openalex.org/W1988790447","https://openalex.org/W1995122024","https://openalex.org/W2022643633","https://openalex.org/W2027911950","https://openalex.org/W2030418992","https://openalex.org/W2052080463","https://openalex.org/W2066634121","https://openalex.org/W2097545165","https://openalex.org/W2109797278","https://openalex.org/W2133362858","https://openalex.org/W2138997468","https://openalex.org/W2170003873","https://openalex.org/W2972891548","https://openalex.org/W4248437541","https://openalex.org/W6603126656","https://openalex.org/W6634668525","https://openalex.org/W6676594124","https://openalex.org/W6767874007"],"related_works":["https://openalex.org/W2568858292","https://openalex.org/W1515964938","https://openalex.org/W2389381914","https://openalex.org/W2376528221","https://openalex.org/W196800607","https://openalex.org/W2359428812","https://openalex.org/W3181296946","https://openalex.org/W2015705630","https://openalex.org/W2355368334","https://openalex.org/W2073313993"],"abstract_inverted_index":{"This":[0,191],"paper":[1],"proposes":[2],"a":[3,23,85,170],"method":[4,67],"of":[5,25,43,48,51,81,101,116,127,133,153,186,195,203],"automatically":[6],"extracting":[7,187],"lane":[8,139,161,188],"change":[9,140,162,189],"situations":[10,121,141,163],"from":[11,53,125],"large-scale":[12,20],"driving":[13,16,72,102,117,120,204],"corpora.":[14],"Naturalistic":[15],"data":[17,55,76],"stored":[18],"in":[19,184],"corpora":[21],"has":[22],"potential":[24,41],"contributing":[26],"for":[27,160,200],"developing":[28],"novel":[29],"advanced":[30],"driver-assistance":[31],"systems":[32],"based":[33,142],"on":[34,113,143],"estimated":[35],"information":[36,52],"about":[37],"driver's":[38],"intent":[39],"and/or":[40],"risk":[42],"accidents.":[44],"However,":[45],"direct":[46],"estimation":[47],"such":[49],"kind":[50],"stream":[54,75],"is":[56,77],"difficult.":[57],"To":[58],"address":[59],"the":[60,91,106,128,134,144],"issue,":[61],"we":[62,137],"apply":[63],"an":[64],"unsupervised":[65],"symbolization":[66,87,135],"and":[68,89,147,156],"topic":[69,145,154,178,198],"representation":[70],"to":[71,79],"data.":[73],"Driving":[74],"converted":[78],"sequences":[80,126],"discrete":[82],"symbols":[83,92,110,196],"by":[84,95,166],"non-parametric":[86],"method,":[88],"then":[90],"are":[93,111,122,164],"characterized":[94],"topics":[96],"which":[97],"represent":[98],"typical":[99],"distribution":[100],"behavior":[103],"observed":[104],"during":[105],"symbols.":[107,129],"Because":[108],"these":[109],"separated":[112],"changing":[114],"points":[115],"behavior,":[118],"similar":[119],"effectively":[123],"retrieved":[124],"For":[130],"evaluating":[131],"effectiveness":[132,194],"approach,":[136],"extract":[138],"proportions":[146,155,179,199],"their":[148,157,181],"temporal":[149,158,182],"patterns.":[150],"Distinctive":[151],"elements":[152],"patterns":[159,183],"extracted":[165],"AdaBoost":[167],"classifier.":[168],"As":[169],"result,":[171],"proposed":[172],"approach":[173],"outperforms":[174],"baselines":[175],"with":[176,197],"neither":[177],"nor":[180],"terms":[185],"situations.":[190,205],"result":[192],"shows":[193],"representing":[201],"characteristics":[202]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}