{"id":"https://openalex.org/W3215870255","doi":"https://doi.org/10.1109/tits.2021.3127491","title":"Exploring Behavioral Patterns of Lane Change Maneuvers for Human-Like Autonomous Driving","display_name":"Exploring Behavioral Patterns of Lane Change Maneuvers for Human-Like Autonomous Driving","publication_year":2021,"publication_date":"2021-11-22","ids":{"openalex":"https://openalex.org/W3215870255","doi":"https://doi.org/10.1109/tits.2021.3127491","mag":"3215870255"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2021.3127491","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2021.3127491","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","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/A5043540785","display_name":"Yaoyu Chen","orcid":"https://orcid.org/0000-0003-4587-0539"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yaoyu Chen","raw_affiliation_strings":["Institute of Human Factors and Ergonomics, Shenzhen University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Human Factors and Ergonomics, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030291480","display_name":"Guofa Li","orcid":"https://orcid.org/0000-0002-7889-4695"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guofa Li","raw_affiliation_strings":["Institute of Human Factors and Ergonomics, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-7889-4695","affiliations":[{"raw_affiliation_string":"Institute of Human Factors and Ergonomics, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107117626","display_name":"Shen Li","orcid":"https://orcid.org/0000-0002-7111-8861"},"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":"Shen Li","raw_affiliation_strings":["Department of Civil Engineering, Tsinghua University, Beijing, China","State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100393027","display_name":"Wenjun Wang","orcid":"https://orcid.org/0000-0002-3325-7481"},"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":"Wenjun Wang","raw_affiliation_strings":["State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100747108","display_name":"Shengbo Eben Li","orcid":"https://orcid.org/0000-0003-4923-3633"},"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":"Shengbo Eben Li","raw_affiliation_strings":["Department of Civil Engineering, Tsinghua University, Beijing, China","State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4923-3633","affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100640936","display_name":"Bo Cheng","orcid":"https://orcid.org/0000-0002-1753-2922"},"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":"Bo Cheng","raw_affiliation_strings":["State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5043540785"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":5.2484,"has_fulltext":false,"cited_by_count":60,"citation_normalized_percentile":{"value":0.9651708,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"23","issue":"9","first_page":"14322","last_page":"14335"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9976000189781189,"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":0.9976000189781189,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9962000250816345,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9912999868392944,"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/computer-science","display_name":"Computer science","score":0.6232532858848572},{"id":"https://openalex.org/keywords/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.6166427731513977},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6050684452056885},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5890527963638306},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5763119459152222},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.5051491856575012},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4643697142601013},{"id":"https://openalex.org/keywords/perplexity","display_name":"Perplexity","score":0.4310300350189209},{"id":"https://openalex.org/keywords/intension","display_name":"Intension","score":0.4296427369117737},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37214794754981995},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35159367322921753},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.16456744074821472}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6232532858848572},{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.6166427731513977},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6050684452056885},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5890527963638306},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5763119459152222},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.5051491856575012},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4643697142601013},{"id":"https://openalex.org/C100279451","wikidata":"https://www.wikidata.org/wiki/Q372193","display_name":"Perplexity","level":3,"score":0.4310300350189209},{"id":"https://openalex.org/C61341680","wikidata":"https://www.wikidata.org/wiki/Q1923256","display_name":"Intension","level":2,"score":0.4296427369117737},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37214794754981995},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35159367322921753},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.16456744074821472},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2021.3127491","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2021.3127491","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G305240560","display_name":null,"funder_award_id":"JCYJ20190808142613246","funder_id":"https://openalex.org/F4320329791","funder_display_name":"Shenzhen Fundamental Research Program"},{"id":"https://openalex.org/G4147806968","display_name":null,"funder_award_id":"20200803015912001","funder_id":"https://openalex.org/F4320329791","funder_display_name":"Shenzhen Fundamental Research Program"},{"id":"https://openalex.org/G7742627185","display_name":null,"funder_award_id":"51805332","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"},{"id":"https://openalex.org/F4320329791","display_name":"Shenzhen Fundamental Research Program","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":76,"referenced_works":["https://openalex.org/W206388996","https://openalex.org/W1109171990","https://openalex.org/W1484769566","https://openalex.org/W1488006703","https://openalex.org/W1550337734","https://openalex.org/W1919962963","https://openalex.org/W1931305913","https://openalex.org/W1961245208","https://openalex.org/W1967042859","https://openalex.org/W1971414456","https://openalex.org/W1991485860","https://openalex.org/W1995122024","https://openalex.org/W1999005035","https://openalex.org/W2006303452","https://openalex.org/W2011760672","https://openalex.org/W2012849708","https://openalex.org/W2020047635","https://openalex.org/W2027911950","https://openalex.org/W2052080463","https://openalex.org/W2066006005","https://openalex.org/W2081980673","https://openalex.org/W2083955608","https://openalex.org/W2092755020","https://openalex.org/W2102434152","https://openalex.org/W2105015918","https://openalex.org/W2136211638","https://openalex.org/W2136851074","https://openalex.org/W2142561902","https://openalex.org/W2145989380","https://openalex.org/W2146404773","https://openalex.org/W2154943827","https://openalex.org/W2158266063","https://openalex.org/W2161050705","https://openalex.org/W2163145488","https://openalex.org/W2166070098","https://openalex.org/W2174602916","https://openalex.org/W2243711867","https://openalex.org/W2279536494","https://openalex.org/W2508541768","https://openalex.org/W2554310451","https://openalex.org/W2604187552","https://openalex.org/W2755725656","https://openalex.org/W2906565763","https://openalex.org/W2920048299","https://openalex.org/W2952385071","https://openalex.org/W2955481631","https://openalex.org/W2962925961","https://openalex.org/W2964264720","https://openalex.org/W2972891548","https://openalex.org/W2975381807","https://openalex.org/W2990170267","https://openalex.org/W3019397229","https://openalex.org/W3019688365","https://openalex.org/W3100672372","https://openalex.org/W3101584909","https://openalex.org/W3104490327","https://openalex.org/W3107030699","https://openalex.org/W3109323072","https://openalex.org/W3112856749","https://openalex.org/W3123479729","https://openalex.org/W3126174111","https://openalex.org/W3208016204","https://openalex.org/W3208246861","https://openalex.org/W3211345831","https://openalex.org/W4237791300","https://openalex.org/W4247388085","https://openalex.org/W6608407660","https://openalex.org/W6637727759","https://openalex.org/W6683296186","https://openalex.org/W6684844159","https://openalex.org/W6692005019","https://openalex.org/W6744452246","https://openalex.org/W6767874007","https://openalex.org/W6778962259","https://openalex.org/W6787266491","https://openalex.org/W6816560326"],"related_works":["https://openalex.org/W2376415519","https://openalex.org/W1601381279","https://openalex.org/W4206967254","https://openalex.org/W4293734197","https://openalex.org/W2761847515","https://openalex.org/W2131689821","https://openalex.org/W2501642273","https://openalex.org/W2250993361","https://openalex.org/W130869231","https://openalex.org/W2043781532"],"abstract_inverted_index":{"Due":[0],"to":[1,46,105,123,157,185],"the":[2,12,31,50,58,62,75,97,100,107,125,145,199],"growing":[3],"interest":[4],"in":[5,93],"automated":[6],"driving,":[7],"a":[8,180],"deep":[9,187],"understanding":[10,190],"on":[11,191],"characteristics":[13],"of":[14,53,60,111,129,201],"human":[15],"driving":[16,26,38,154],"behavior":[17],"is":[18,30],"critical":[19],"for":[20,35,57],"human-like":[21,202],"autonomous":[22,203],"vehicles.":[23,204],"Among":[24],"various":[25],"behaviors,":[27,195],"lane":[28,54,67,76,149,174,193],"change":[29,55,77,150,175,194],"most":[32],"important":[33],"one":[34],"vehicle":[36],"lateral":[37],"safety.":[39],"This":[40,69,177],"study":[41,178],"proposes":[42],"an":[43],"unsupervised":[44],"method":[45,70,166],"extract":[47],"and":[48,132,137,142,188],"discover":[49],"behavioral":[51,64,109,171],"patterns":[52,65,172],"maneuvers":[56],"purpose":[59],"exploring":[61],"composed":[63],"during":[66],"change.":[68],"involves":[71],"two":[72],"phases:":[73],"Firstly,":[74],"sequences":[78],"will":[79,102,197],"be":[80,103],"segmented":[81],"into":[82],"blocks":[83],"using":[84],"time-series":[85],"segmentation":[86,89,131],"algorithms.":[87],"Three":[88],"algorithms":[90,134],"were":[91,121,135,155],"utilized":[92],"this":[94,165],"study.":[95],"In":[96],"second":[98],"phase,":[99],"segments":[101],"clustered":[104],"find":[106],"corresponding":[108],"pattern":[110],"each":[112],"segment.":[113],"Two":[114],"extended":[115],"latent":[116],"Dirichlet":[117],"allocation":[118],"(LDA)":[119],"models":[120],"adopted":[122],"cluster":[124],"segments.":[126],"The":[127,161],"combination":[128],"different":[130],"clustering":[133],"evaluated":[136],"compared":[138],"by":[139],"employing":[140],"entropy":[141],"perplexity":[143],"as":[144],"evaluation":[146],"criteria.":[147],"Collected":[148],"data":[151,182],"from":[152,173],"naturalistic":[153],"applied":[156],"examine":[158],"its":[159],"effectiveness.":[160],"results":[162],"show":[163],"that":[164],"could":[167],"effectively":[168],"mine":[169],"descriptive":[170],"data.":[176],"provides":[179],"promising":[181],"mining":[183],"solution":[184],"facilitating":[186],"comprehensive":[189],"driver":[192],"which":[196],"promote":[198],"development":[200]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":20},{"year":2024,"cited_by_count":19},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":1}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}
