{"id":"https://openalex.org/W2183365366","doi":"https://doi.org/10.1080/23249935.2015.1102173","title":"Application of finite mixture models for analysing freeway incident clearance time","display_name":"Application of finite mixture models for analysing freeway incident clearance time","publication_year":2015,"publication_date":"2015-10-01","ids":{"openalex":"https://openalex.org/W2183365366","doi":"https://doi.org/10.1080/23249935.2015.1102173","mag":"2183365366"},"language":"en","primary_location":{"id":"doi:10.1080/23249935.2015.1102173","doi":"https://doi.org/10.1080/23249935.2015.1102173","is_oa":false,"landing_page_url":"https://doi.org/10.1080/23249935.2015.1102173","pdf_url":null,"source":{"id":"https://openalex.org/S4210177949","display_name":"Transportmetrica A Transport Science","issn_l":"2324-9935","issn":["2324-9935","2324-9943"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-b","cwts-core","dongbi-d","jufo-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Transportmetrica A: Transport Science","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"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/A5071113267","display_name":"Yajie Zou","orcid":"https://orcid.org/0000-0002-3505-168X","observed_orcids":["https://orcid.org/0000-0002-3505-168X"]},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yajie Zou","raw_affiliation_strings":["Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai 201804, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai 201804, People's Republic of China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078288318","display_name":"Kristian C. Henrickson","orcid":"https://orcid.org/0000-0002-3042-0626","observed_orcids":["https://orcid.org/0000-0002-3042-0626"]},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kristian Henrickson","raw_affiliation_strings":["Department of Civil and Environmental Engineering, University of Washington, More Hall 133B, Box 352700, Seattle, WA 98195-2700, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Civil and Environmental Engineering, University of Washington, More Hall 133B, Box 352700, Seattle, WA 98195-2700, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089797666","display_name":"Dominique Lord","orcid":"https://orcid.org/0000-0002-7434-6886","observed_orcids":["https://orcid.org/0000-0002-7434-6886"]},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dominique Lord","raw_affiliation_strings":["Zachry Department of Civil Engineering, Texas A&M University, TAMU 3136, College Station, TX 77843-3136, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zachry Department of Civil Engineering, Texas A&M University, TAMU 3136, College Station, TX 77843-3136, USA","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012268687","display_name":"Yinhai Wang","orcid":"https://orcid.org/0000-0002-4180-5628","observed_orcids":["https://orcid.org/0000-0002-4180-5628"]},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yinhai Wang","raw_affiliation_strings":["Department of Civil and Environmental Engineering, University of Washington, More Hall 133B, Box 352700, Seattle, WA 98195-2700, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Civil and Environmental Engineering, University of Washington, More Hall 133B, Box 352700, Seattle, WA 98195-2700, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100440735","display_name":"Kun Xu","orcid":"https://orcid.org/0000-0001-6267-2548","observed_orcids":["https://orcid.org/0000-0001-6267-2548"]},"institutions":[{"id":"https://openalex.org/I145608581","display_name":"University of Miami","ror":"https://ror.org/02dgjyy92","country_code":"US","type":"education","lineage":["https://openalex.org/I145608581"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kun Xu","raw_affiliation_strings":["Department of Management Science, School of Business Administration, University of Miami, Coral Gables, FL 33146-6544, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Management Science, School of Business Administration, University of Miami, Coral Gables, FL 33146-6544, USA","institution_ids":["https://openalex.org/I145608581"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5012268687"],"corresponding_institution_ids":["https://openalex.org/I201448701"],"apc_list":null,"apc_paid":null,"fwci":10.1855,"has_fulltext":false,"cited_by_count":57,"citation_normalized_percentile":{"value":0.97665707,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":99},"biblio":{"volume":"12","issue":"2","first_page":"99","last_page":"115"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10370","display_name":"Traffic and Road Safety","score":0.3686999976634979,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T10370","display_name":"Traffic and Road Safety","score":0.3686999976634979,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.16850000619888306,"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"}},{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.16769999265670776,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/mixture-models","display_name":"mixture models","score":0.8360000252723694},{"id":"https://openalex.org/keywords/incident-clearance-time","display_name":"incident clearance time","score":0.8650000095367432},{"id":"https://openalex.org/keywords/freeway-incidents","display_name":"freeway incidents","score":0.8320000171661377},{"id":"https://openalex.org/keywords/incident-management","display_name":"incident management","score":0.5049999952316284},{"id":"https://openalex.org/keywords/accelerated-failure-time-model","display_name":"accelerated failure time model","score":0.7879999876022339},{"id":"https://openalex.org/keywords/proportional-hazard-model","display_name":"proportional hazard model","score":0.8190000057220459},{"id":"https://openalex.org/keywords/survival-analysis","display_name":"survival analysis","score":0.6980000138282776},{"id":"https://openalex.org/keywords/hazard-function","display_name":"hazard function","score":0.5609999895095825},{"id":"https://openalex.org/keywords/incident-duration-prediction","display_name":"incident duration prediction","score":0.7559999823570251}],"concepts":[{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.7692323327064514},{"id":"https://openalex.org/C33114746","wikidata":"https://www.wikidata.org/wiki/Q4672282","display_name":"Accelerated failure time model","level":3,"score":0.7517786026000977},{"id":"https://openalex.org/C49261128","wikidata":"https://www.wikidata.org/wiki/Q1132455","display_name":"Hazard","level":2,"score":0.6375404596328735},{"id":"https://openalex.org/C112758219","wikidata":"https://www.wikidata.org/wiki/Q16038819","display_name":"Duration (music)","level":2,"score":0.5249612331390381},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.485638290643692},{"id":"https://openalex.org/C50382708","wikidata":"https://www.wikidata.org/wiki/Q223218","display_name":"Proportional hazards model","level":2,"score":0.4782811105251312},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.46477988362312317},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4563106298446655},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.4262884855270386},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2540341019630432},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.08899039030075073},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/23249935.2015.1102173","doi":"https://doi.org/10.1080/23249935.2015.1102173","is_oa":false,"landing_page_url":"https://doi.org/10.1080/23249935.2015.1102173","pdf_url":null,"source":{"id":"https://openalex.org/S4210177949","display_name":"Transportmetrica A Transport Science","issn_l":"2324-9935","issn":["2324-9935","2324-9943"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-b","cwts-core","dongbi-d","jufo-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Transportmetrica A: Transport Science","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.761900007724762,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W58077054","https://openalex.org/W605692607","https://openalex.org/W1485147006","https://openalex.org/W1521175566","https://openalex.org/W1529414135","https://openalex.org/W1579271636","https://openalex.org/W1586481371","https://openalex.org/W1599919652","https://openalex.org/W1883111670","https://openalex.org/W1909447605","https://openalex.org/W1964259136","https://openalex.org/W1968068654","https://openalex.org/W1969372462","https://openalex.org/W1975185440","https://openalex.org/W1980888841","https://openalex.org/W1981177109","https://openalex.org/W1981530736","https://openalex.org/W1993339912","https://openalex.org/W1995433411","https://openalex.org/W1995840715","https://openalex.org/W2004939947","https://openalex.org/W2010039425","https://openalex.org/W2011365084","https://openalex.org/W2019439562","https://openalex.org/W2025816835","https://openalex.org/W2035481685","https://openalex.org/W2036197159","https://openalex.org/W2042652202","https://openalex.org/W2046309797","https://openalex.org/W2047355029","https://openalex.org/W2050138223","https://openalex.org/W2056425734","https://openalex.org/W2057055929","https://openalex.org/W2061893665","https://openalex.org/W2067819510","https://openalex.org/W2074184267","https://openalex.org/W2082845493","https://openalex.org/W2087660514","https://openalex.org/W2091497030","https://openalex.org/W2092568949","https://openalex.org/W2098642267","https://openalex.org/W2272723297","https://openalex.org/W2312269111","https://openalex.org/W2324805613","https://openalex.org/W2990646398"],"related_works":["https://openalex.org/W7095817963","https://openalex.org/W2046309797","https://openalex.org/W1994567542","https://openalex.org/W4392729533","https://openalex.org/W1909447605","https://openalex.org/W2592555241","https://openalex.org/W4307039773","https://openalex.org/W3186471970","https://openalex.org/W2091010572","https://openalex.org/W608638608"],"abstract_inverted_index":{"A":[0],"number":[1],"of":[2,17,63,88,113,168,193],"approaches":[3],"have":[4,39],"been":[5,40],"developed":[6],"for":[7,218,224,246],"analysing":[8,247],"incident":[9,75,107,120,169,201,221,226,249,254],"clearance":[10,22,76,108,121,170,202],"time":[11,36,77,122,203],"data":[12,53,78,123,251],"and":[13,33,55,83,135,143,149,165,172,243,252],"investigating":[14],"the":[15,64,68,74,86,114,139,144,155,162,180,191,210,229,236],"effects":[16,87,192],"different":[18,61,94,197,225],"explanatory":[19,89],"variables":[20,90,195],"on":[21,125,196,256],"time.":[23,109],"Among":[24],"these":[25],"methods,":[26],"hazard-based":[27],"duration":[28,250,255],"models":[29],"(i.e.":[30],"proportional":[31],"hazard":[32,65,166],"accelerated":[34],"failure":[35],"(AFT)":[37],"models)":[38],"extensively":[41],"used.":[42],"The":[43,151,183,205],"finite":[44,69,116],"mixture":[45,70,101,117,141,157,184,212,237],"model":[46,71,102,118,142,146,158,185,213],"is":[47,103,240],"an":[48],"alternative":[49],"approach":[50,239],"in":[51,59,128,200,231],"survival":[52,163],"analysis,":[54],"offers":[56],"greater":[57],"flexibility":[58],"describing":[60],"shapes":[62],"function.":[66],"Additionally,":[67],"assumes":[72],"that":[73,154,235],"set":[79],"contains":[80],"distinct":[81],"subpopulations,":[82],"it":[84],"allows":[85],"to":[91,105,179],"vary":[92],"between":[93],"subpopulations.":[95],"In":[96],"this":[97,232],"study,":[98],"a":[99,241],"g-component":[100],"applied":[104],"analyse":[106],"To":[110],"demonstrate":[111,234],"advantages":[112],"proposed":[115,140,156,211],"framework,":[119],"collected":[124],"freeway":[126],"sections":[127],"Seattle,":[129],"Washington":[130],"State":[131],"are":[132,147],"analysed.":[133],"Estimation":[134],"prediction":[136,177],"results":[137,152],"from":[138,209],"AFT":[145,181],"presented":[148],"compared.":[150],"suggest":[153],"can":[159,173,186,214],"better":[160],"describe":[161],"probability":[164,167],"time,":[171],"provide":[174,188],"more":[175],"accurate":[176],"compared":[178],"model.":[182],"also":[187],"inferences":[189],"about":[190],"explainable":[194],"subpopulations":[198],"present":[199],"data.":[204],"additional":[206],"information":[207],"obtained":[208],"be":[215],"potentially":[216],"useful":[217,242],"designing":[219],"targeted":[220],"management":[222],"strategies":[223],"types.":[227],"Overall,":[228],"findings":[230],"study":[233],"modelling":[238],"informative":[244],"method":[245],"heterogeneous":[248],"predicting":[253],"freeways.":[257]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":6},{"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":3},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":1}],"updated_date":"2026-10-14T16:39:01.820549","created_date":"2016-06-24T00:00:00"}
