{"id":"https://openalex.org/W4377968443","doi":"https://doi.org/10.1109/icps58381.2023.10128100","title":"Scene-insensitive Driving Style Recognition using CAN Signals based on Factor Analysis","display_name":"Scene-insensitive Driving Style Recognition using CAN Signals based on Factor Analysis","publication_year":2023,"publication_date":"2023-05-08","ids":{"openalex":"https://openalex.org/W4377968443","doi":"https://doi.org/10.1109/icps58381.2023.10128100"},"language":"en","primary_location":{"id":"doi:10.1109/icps58381.2023.10128100","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icps58381.2023.10128100","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 6th International Conference on Industrial Cyber-Physical Systems (ICPS)","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/A5075853372","display_name":"Chaopeng Zhang","orcid":"https://orcid.org/0000-0002-5390-3161"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chaopeng Zhang","raw_affiliation_strings":["School of Mechanical Engineering Beijing Institute of Technology,Beijing,China","School of Mechanical Engineering Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering Beijing Institute of Technology,Beijing,China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"School of Mechanical Engineering Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055099598","display_name":"Wenshuo Wang","orcid":"https://orcid.org/0000-0002-1860-8351"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Wenshuo Wang","raw_affiliation_strings":["McGill University,Department of Civil Engineering,Montreal,Canada","Department of Civil Engineering, McGill University, Montreal, Canada"],"affiliations":[{"raw_affiliation_string":"McGill University,Department of Civil Engineering,Montreal,Canada","institution_ids":["https://openalex.org/I5023651"]},{"raw_affiliation_string":"Department of Civil Engineering, McGill University, Montreal, Canada","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100410104","display_name":"Jian Zhang","orcid":"https://orcid.org/0009-0001-7997-5438"},"institutions":[{"id":"https://openalex.org/I4210127843","display_name":"First Automotive Works (China)","ror":"https://ror.org/0353t4m91","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210127843"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Zhang","raw_affiliation_strings":["Intelligent Connected Vehicle Development Institute China FAW Group Co., Ltd.,Changchun,China","Intelligent Connected Vehicle Development Institute China FAW Group Co., Ltd., Changchun, China"],"affiliations":[{"raw_affiliation_string":"Intelligent Connected Vehicle Development Institute China FAW Group Co., Ltd.,Changchun,China","institution_ids":["https://openalex.org/I4210127843"]},{"raw_affiliation_string":"Intelligent Connected Vehicle Development Institute China FAW Group Co., Ltd., Changchun, China","institution_ids":["https://openalex.org/I4210127843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002374833","display_name":"Zhiyang Ju","orcid":"https://orcid.org/0000-0002-6186-6321"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyang Ju","raw_affiliation_strings":["School of Mechanical Engineering Beijing Institute of Technology,Beijing,China","School of Mechanical Engineering Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering Beijing Institute of Technology,Beijing,China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"School of Mechanical Engineering Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049170681","display_name":"Zhaokun Chen","orcid":"https://orcid.org/0009-0004-3412-2580"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaokun Chen","raw_affiliation_strings":["School of Mechanical Engineering Beijing Institute of Technology,Beijing,China","School of Mechanical Engineering Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering Beijing Institute of Technology,Beijing,China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"School of Mechanical Engineering Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102879296","display_name":"Junqiang Xi","orcid":"https://orcid.org/0000-0001-8607-4542"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junqiang Xi","raw_affiliation_strings":["School of Mechanical Engineering Beijing Institute of Technology,Beijing,China","School of Mechanical Engineering Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering Beijing Institute of Technology,Beijing,China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"School of Mechanical Engineering Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5075853372"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":0.345,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.55686339,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9997000098228455,"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":0.9997000098228455,"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/T12095","display_name":"Vehicle emissions and performance","score":0.9983000159263611,"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/T10805","display_name":"Vehicle Dynamics and Control Systems","score":0.987500011920929,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7582650780677795},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6785522699356079},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6262228488922119},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5962226390838623},{"id":"https://openalex.org/keywords/factor","display_name":"Factor (programming language)","score":0.5806854963302612},{"id":"https://openalex.org/keywords/style","display_name":"Style (visual arts)","score":0.5447746515274048},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4617142677307129},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4229058623313904},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.387115478515625},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36203521490097046}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7582650780677795},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6785522699356079},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6262228488922119},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5962226390838623},{"id":"https://openalex.org/C2781039887","wikidata":"https://www.wikidata.org/wiki/Q1391724","display_name":"Factor (programming language)","level":2,"score":0.5806854963302612},{"id":"https://openalex.org/C2776445246","wikidata":"https://www.wikidata.org/wiki/Q1792644","display_name":"Style (visual arts)","level":2,"score":0.5447746515274048},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4617142677307129},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4229058623313904},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.387115478515625},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36203521490097046},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icps58381.2023.10128100","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icps58381.2023.10128100","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 6th International Conference on Industrial Cyber-Physical Systems (ICPS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8345708856","display_name":null,"funder_award_id":"52272411","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W154700328","https://openalex.org/W1865136284","https://openalex.org/W2033000795","https://openalex.org/W2049891906","https://openalex.org/W2109195974","https://openalex.org/W2138539775","https://openalex.org/W2140405352","https://openalex.org/W2160172778","https://openalex.org/W2183877827","https://openalex.org/W2327678559","https://openalex.org/W2525337062","https://openalex.org/W2554310451","https://openalex.org/W2592152148","https://openalex.org/W2605241557","https://openalex.org/W2746721413","https://openalex.org/W2913367279","https://openalex.org/W2979420091","https://openalex.org/W3003690198","https://openalex.org/W3014009356","https://openalex.org/W3026302707","https://openalex.org/W3082508441","https://openalex.org/W3120519208","https://openalex.org/W3215870255","https://openalex.org/W4214604204","https://openalex.org/W4220804220","https://openalex.org/W4285180244","https://openalex.org/W4300621871","https://openalex.org/W6803893029","https://openalex.org/W6840206023"],"related_works":["https://openalex.org/W2356229341","https://openalex.org/W2349768204","https://openalex.org/W2804364458","https://openalex.org/W4298130764","https://openalex.org/W2132641928","https://openalex.org/W2090259340","https://openalex.org/W4310225030","https://openalex.org/W4313326281","https://openalex.org/W2083665254","https://openalex.org/W2393816671"],"abstract_inverted_index":{"Driving":[0],"style":[1,22,38,72,119,148],"recognition":[2,23,51,120],"plays":[3],"a":[4,67],"vital":[5],"role":[6],"in":[7,82,98,106,135],"devel-oping":[8],"human-centered":[9],"intelligent":[10],"vehicles":[11],"that":[12,159],"consider":[13],"drivers'":[14,99],"preferences.":[15],"However,":[16],"the":[17,34,42,45,48,62,96,107,142,146,160,171],"feature":[18],"selection":[19],"of":[20,36,47],"driving":[21,31,37,49,71,84,88,100,118,130,147,172],"is":[24,39,54,76,122,138],"diverse":[25,83],"and":[26,44,111,166],"inconsistent,":[27],"which":[28,53],"varies":[29],"with":[30,102,145,151],"scenarios.":[32],"Therefore,":[33],"application":[35],"limited":[40],"by":[41],"accuracy":[43],"rapidity":[46],"scene":[50],"algorithm,":[52],"difficult":[55],"for":[56,70],"low-cost":[57],"onboard":[58],"chips.":[59],"To":[60],"solve":[61],"problem,":[63],"this":[64],"paper":[65],"proposes":[66],"scene-insensitive":[68,167],"method":[69,144,162],"recognition.":[73],"Factor":[74],"analysis":[75],"employed":[77],"to":[78,140,169],"extract":[79],"common":[80,93],"factors":[81,94],"scenes":[85],"from":[86,132],"high-dimensional":[87],"data":[89,131],"segmentation.":[90],"The":[91],"unified":[92],"reflect":[95],"differences":[97],"behaviors":[101],"different":[103],"styles,":[104],"verified":[105],"publicly":[108],"available":[109],"dataset":[110],"100-driver":[112],"experimental":[113,156],"data.":[114],"Then,":[115],"an":[116,164],"efficient":[117,165],"algorithm":[121],"developed":[123],"based":[124],"on":[125],"K-means":[126],"Clustering.":[127],"Finally,":[128],"natural":[129],"100":[133],"drivers":[134],"Changchun,":[136],"China,":[137],"collected":[139],"evaluate":[141],"proposed":[143,161],"questionnaire.":[149],"Compared":[150],"six":[152],"supervised":[153],"learning":[154],"methods,":[155],"results":[157],"demonstrate":[158],"provides":[163],"way":[168],"recognize":[170],"style.":[173]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}