{"id":"https://openalex.org/W2891796867","doi":"https://doi.org/10.1109/tvt.2018.2868965","title":"A Hybrid Method Combining Markov Prediction and Fuzzy Classification for Driving Condition Recognition","display_name":"A Hybrid Method Combining Markov Prediction and Fuzzy Classification for Driving Condition Recognition","publication_year":2018,"publication_date":"2018-09-06","ids":{"openalex":"https://openalex.org/W2891796867","doi":"https://doi.org/10.1109/tvt.2018.2868965","mag":"2891796867"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2018.2868965","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2018.2868965","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","raw_type":"journal-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/A5100643524","display_name":"Haiming Xie","orcid":"https://orcid.org/0000-0002-6968-6026"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haiming Xie","raw_affiliation_strings":["State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-6968-6026","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067598839","display_name":"Guangyu Tian","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangyu Tian","raw_affiliation_strings":["State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5438-8862","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052389399","display_name":"Guangqian Du","orcid":"https://orcid.org/0000-0002-1487-314X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangqian Du","raw_affiliation_strings":["State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-1487-314X","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042005267","display_name":"Yong Huang","orcid":"https://orcid.org/0000-0001-6327-3602"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Huang","raw_affiliation_strings":["State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101462699","display_name":"Hongxu Chen","orcid":"https://orcid.org/0000-0002-3473-5780"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongxu Chen","raw_affiliation_strings":["State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081182489","display_name":"Xi Zheng","orcid":"https://orcid.org/0000-0002-2572-2355"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Xi Zheng","raw_affiliation_strings":["Macquarie University, Sydney, NSW, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Macquarie University, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040978564","display_name":"Tom H. Luan","orcid":"https://orcid.org/0000-0002-5215-7443"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tom H. Luan","raw_affiliation_strings":["Xidian University, Xi\u2019an, China","Xidian University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0002-5215-7443","affiliations":[{"raw_affiliation_string":"Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100643524"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":2.8503,"has_fulltext":false,"cited_by_count":41,"citation_normalized_percentile":{"value":0.9081942,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"67","issue":"11","first_page":"10411","last_page":"10424"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12095","display_name":"Vehicle emissions and performance","score":0.9995999932289124,"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/T12095","display_name":"Vehicle emissions and performance","score":0.9995999932289124,"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/T10117","display_name":"Advanced Combustion Engine Technologies","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1507","display_name":"Fluid Flow and Transfer Processes"},"field":{"id":"https://openalex.org/fields/15","display_name":"Chemical Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10808","display_name":"Electric and Hybrid Vehicle Technologies","score":0.9944999814033508,"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/hidden-markov-model","display_name":"Hidden Markov model","score":0.693299412727356},{"id":"https://openalex.org/keywords/statistic","display_name":"Statistic","score":0.6004663705825806},{"id":"https://openalex.org/keywords/sliding-window-protocol","display_name":"Sliding window protocol","score":0.5881879925727844},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5775398015975952},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5470631122589111},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4890163838863373},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46146634221076965},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4357870817184448},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4284835159778595},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4275820553302765},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39946818351745605},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3858145475387573},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.37729305028915405},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.32623982429504395},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1808614730834961},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08370089530944824}],"concepts":[{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.693299412727356},{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.6004663705825806},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.5881879925727844},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5775398015975952},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5470631122589111},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4890163838863373},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46146634221076965},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4357870817184448},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4284835159778595},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4275820553302765},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39946818351745605},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3858145475387573},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.37729305028915405},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.32623982429504395},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1808614730834961},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08370089530944824},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/tvt.2018.2868965","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2018.2868965","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7900000214576721,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G2537484338","display_name":null,"funder_award_id":"51775291","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":46,"referenced_works":["https://openalex.org/W170450756","https://openalex.org/W648223566","https://openalex.org/W650973245","https://openalex.org/W823033267","https://openalex.org/W1495870701","https://openalex.org/W1964023669","https://openalex.org/W1966163588","https://openalex.org/W1973004495","https://openalex.org/W1979323834","https://openalex.org/W1997846602","https://openalex.org/W2006651451","https://openalex.org/W2006699595","https://openalex.org/W2011804882","https://openalex.org/W2016115589","https://openalex.org/W2029799049","https://openalex.org/W2037645249","https://openalex.org/W2041278275","https://openalex.org/W2049004936","https://openalex.org/W2052605637","https://openalex.org/W2067162619","https://openalex.org/W2076640662","https://openalex.org/W2092950745","https://openalex.org/W2103773831","https://openalex.org/W2115583576","https://openalex.org/W2116544564","https://openalex.org/W2118382485","https://openalex.org/W2120261443","https://openalex.org/W2135137731","https://openalex.org/W2150241254","https://openalex.org/W2161758672","https://openalex.org/W2165530841","https://openalex.org/W2190859449","https://openalex.org/W2267263964","https://openalex.org/W2298171660","https://openalex.org/W2345604657","https://openalex.org/W2426227936","https://openalex.org/W2574617497","https://openalex.org/W2602126201","https://openalex.org/W2612464746","https://openalex.org/W2615310526","https://openalex.org/W2620642716","https://openalex.org/W2742838792","https://openalex.org/W2795543364","https://openalex.org/W3010319276","https://openalex.org/W6606910676","https://openalex.org/W6683501427"],"related_works":["https://openalex.org/W2053269318","https://openalex.org/W2364370872","https://openalex.org/W2097963413","https://openalex.org/W2294335174","https://openalex.org/W2025614924","https://openalex.org/W3145575561","https://openalex.org/W2001275470","https://openalex.org/W3014558862","https://openalex.org/W3005992387","https://openalex.org/W4360924407"],"abstract_inverted_index":{"Driving":[0],"condition":[1],"adaptive":[2],"control":[3],"is":[4,27,65,80,118,136],"an":[5,72],"effective":[6],"vehicle":[7],"fuel-saving":[8],"technique,":[9],"and":[10,104,127],"the":[11,17,54,68,100,122,128,140,174],"key":[12],"challenge":[13],"lies":[14],"in":[15,153],"improving":[16],"recognition":[18,111,116],"accuracy":[19,152,172],"of":[20,71],"current":[21,42,155],"driving":[22,32,43,156,163],"condition.":[23,44,157],"The":[24],"state-of-the-art":[25,175],"approach":[26,135],"based":[28],"on":[29,161],"recognizing":[30],"historical":[31],"data":[33,164],"with":[34],"a":[35,96,114,133],"fixed":[36],"length":[37],"sliding":[38],"window":[39],"to":[40,51,83,109,138,143,149],"detect":[41],"However,":[45],"few":[46],"research":[47],"has":[48,170],"been":[49],"conducted":[50],"directly":[52],"recognize":[53],"occurring":[55,73,101],"micro-trip":[56,102],"(a":[57],"speed":[58,77],"time":[59,78,142],"series":[60,79],"between":[61,145],"two":[62,105,147],"starts).":[63],"That":[64],"because":[66],"at":[67],"beginning":[69],"stage":[70],"micro-trip,":[74],"its":[75],"known":[76],"too":[81],"short":[82],"be":[84],"correctly":[85],"recognized.":[86],"In":[87],"this":[88,92],"paper,":[89],"we":[90],"addressed":[91],"issue":[93],"by":[94],"proposing":[95],"hybrid":[97,115],"method":[98],"for":[99],"recognition,":[103],"efforts":[106],"are":[107],"made":[108],"improve":[110],"accuracy.":[112],"First,":[113],"procedure":[117],"proposed,":[119],"which":[120],"combines":[121],"Markov":[123],"chain":[124],"prediction":[125],"model":[126],"fuzzy":[129],"classification":[130],"model.":[131],"Second,":[132],"statistic":[134],"proposed":[137,168],"estimate":[139],"best":[141],"switch":[144],"above-mentioned":[146],"models":[148],"achieve":[150],"higher":[151],"detecting":[154],"Our":[158],"evaluation":[159],"results":[160],"real-world":[162],"show":[165],"that":[166],"our":[167],"solution":[169],"better":[171],"than":[173],"approach.":[176]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
