{"id":"https://openalex.org/W2772329499","doi":"https://doi.org/10.1061/(asce)cp.1943-5487.0000730","title":"Cycle-Length Prediction in Actuated Traffic-Signal Control Using ARIMA Model","display_name":"Cycle-Length Prediction in Actuated Traffic-Signal Control Using ARIMA Model","publication_year":2017,"publication_date":"2017-12-09","ids":{"openalex":"https://openalex.org/W2772329499","doi":"https://doi.org/10.1061/(asce)cp.1943-5487.0000730","mag":"2772329499"},"language":"en","primary_location":{"id":"doi:10.1061/(asce)cp.1943-5487.0000730","is_oa":false,"landing_page_url":"https://doi.org/10.1061/(asce)cp.1943-5487.0000730","pdf_url":null,"source":{"id":"https://openalex.org/S176637136","display_name":"Journal of Computing in Civil Engineering","issn_l":"0887-3801","issn":["0887-3801","1943-5487"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315747","host_organization_name":"American Society of Civil Engineers","host_organization_lineage":["https://openalex.org/P4310315747"],"host_organization_lineage_names":["American Society of Civil Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computing in Civil Engineering","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/A5023534068","display_name":"Bahman Moghimi","orcid":"https://orcid.org/0000-0003-4129-1388"},"institutions":[{"id":"https://openalex.org/I125687163","display_name":"City College of New York","ror":"https://ror.org/00wmhkr98","country_code":"US","type":"education","lineage":["https://openalex.org/I125687163"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bahman Moghimi","raw_affiliation_strings":["Ph.D. Candidate, Dept. of Civil Engineering, City College of New York, New York, NY 10031","Ph.D. Candidate, Dept. of Civil Engineering, City College of New York, New York, NY 10031. E-mail:"],"affiliations":[{"raw_affiliation_string":"Ph.D. Candidate, Dept. of Civil Engineering, City College of New York, New York, NY 10031","institution_ids":["https://openalex.org/I125687163"]},{"raw_affiliation_string":"Ph.D. Candidate, Dept. of Civil Engineering, City College of New York, New York, NY 10031. E-mail:","institution_ids":["https://openalex.org/I125687163"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007282531","display_name":"Abolfazl Safikhani","orcid":"https://orcid.org/0000-0001-8678-1247"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abolfazl Safikhani","raw_affiliation_strings":["Assistant Professor, Dept. of Statistics, Columbia Univ., New York, NY 10027","Assistant Professor, Dept. of Statistics, Columbia Univ., New York, NY 10027. E-mail:"],"affiliations":[{"raw_affiliation_string":"Assistant Professor, Dept. of Statistics, Columbia Univ., New York, NY 10027","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Assistant Professor, Dept. of Statistics, Columbia Univ., New York, NY 10027. E-mail:","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088536140","display_name":"Camille Kamga","orcid":"https://orcid.org/0000-0002-9223-700X"},"institutions":[{"id":"https://openalex.org/I125687163","display_name":"City College of New York","ror":"https://ror.org/00wmhkr98","country_code":"US","type":"education","lineage":["https://openalex.org/I125687163"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Camille Kamga","raw_affiliation_strings":["Assistant Professor, Dept. of Civil Engineering, City College of New York, New York, NY 10031","Assistant Professor, Dept. of Civil Engineering, City College of New York, New York, NY 10031. E-mail:"],"affiliations":[{"raw_affiliation_string":"Assistant Professor, Dept. of Civil Engineering, City College of New York, New York, NY 10031","institution_ids":[]},{"raw_affiliation_string":"Assistant Professor, Dept. of Civil Engineering, City College of New York, New York, NY 10031. E-mail:","institution_ids":["https://openalex.org/I125687163"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043011100","display_name":"Wei Hao","orcid":"https://orcid.org/0000-0002-9301-8765"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wei Hao","raw_affiliation_strings":["Professor, Dept. of Transportation Engineering, Changsha Univ. of Science and Technology, Changsha 410205, China (corresponding author)"],"affiliations":[{"raw_affiliation_string":"Professor, Dept. of Transportation Engineering, Changsha Univ. of Science and Technology, Changsha 410205, China (corresponding author)","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5043011100"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.2473,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.9366781,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"32","issue":"2","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T10524","display_name":"Traffic control and management","score":0.9965000152587891,"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"}},{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.9883000254631042,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.829884946346283},{"id":"https://openalex.org/keywords/autocorrelation","display_name":"Autocorrelation","score":0.6910874843597412},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.5827050805091858},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.551964282989502},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.5138697624206543},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.46232110261917114},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4526890516281128},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4518536627292633},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.3937045931816101},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.36748218536376953},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.3379783630371094},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.3233356773853302},{"id":"https://openalex.org/keywords/control","display_name":"Control (management)","score":0.2937619090080261},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2599641680717468},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.13479948043823242}],"concepts":[{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.829884946346283},{"id":"https://openalex.org/C5297727","wikidata":"https://www.wikidata.org/wiki/Q786970","display_name":"Autocorrelation","level":2,"score":0.6910874843597412},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.5827050805091858},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.551964282989502},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.5138697624206543},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.46232110261917114},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4526890516281128},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4518536627292633},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.3937045931816101},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.36748218536376953},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.3379783630371094},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3233356773853302},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.2937619090080261},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2599641680717468},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.13479948043823242},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1061/(asce)cp.1943-5487.0000730","is_oa":false,"landing_page_url":"https://doi.org/10.1061/(asce)cp.1943-5487.0000730","pdf_url":null,"source":{"id":"https://openalex.org/S176637136","display_name":"Journal of Computing in Civil Engineering","issn_l":"0887-3801","issn":["0887-3801","1943-5487"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315747","host_organization_name":"American Society of Civil Engineers","host_organization_lineage":["https://openalex.org/P4310315747"],"host_organization_lineage_names":["American Society of Civil Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computing in Civil Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.8299999833106995,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W575008786","https://openalex.org/W1973943669","https://openalex.org/W1975285212","https://openalex.org/W1976557506","https://openalex.org/W1982978808","https://openalex.org/W1998798635","https://openalex.org/W2003873404","https://openalex.org/W2034320970","https://openalex.org/W2051612742","https://openalex.org/W2078125201","https://openalex.org/W2103785804","https://openalex.org/W2126831543","https://openalex.org/W2140323676","https://openalex.org/W2150488999","https://openalex.org/W2159878099","https://openalex.org/W2160507653","https://openalex.org/W2347110957","https://openalex.org/W2404102969","https://openalex.org/W2510300699","https://openalex.org/W3022458846"],"related_works":["https://openalex.org/W1982721348","https://openalex.org/W1493644805","https://openalex.org/W2371489490","https://openalex.org/W2130417215","https://openalex.org/W2047880019","https://openalex.org/W3175321409","https://openalex.org/W4312561791","https://openalex.org/W2389894046","https://openalex.org/W2215717369","https://openalex.org/W2974356760"],"abstract_inverted_index":{"In":[0,74],"urban":[1],"transportation":[2,30],"systems,":[3],"the":[4,8,22,47,77,87,91,100,112,118,126,185,191,218,227],"traffic":[5,13,17],"signal":[6,42,64],"is":[7,52,168],"main":[9],"component":[10,210],"in":[11,67],"controlling":[12],"congestion.":[14],"Using":[15],"actuated":[16,41,68,121],"control":[18,43,69],"as":[19,184,247],"one":[20],"of":[21,49,63,90,125,133,147,196],"traffic-controlling":[23],"systems":[24],"can":[25],"cause":[26],"fewer":[27],"delays":[28],"for":[29,158,199],"users,":[31],"specifically":[32],"when":[33],"it":[34,55,238],"comes":[35],"to":[36,59,80,189,217,249],"an":[37],"isolated":[38],"intersection.":[39],"Although":[40],"has":[44,214],"many":[45,72],"benefits,":[46],"prediction":[48,194,225,244,253],"cycle":[50,65,92,103,128,176,197,223],"length":[51,66,93,104,129,198,224],"cumbersome":[53],"because":[54],"varies":[56],"from":[57,117],"time":[58,106,148],"time.":[60],"The":[61,123,163],"value":[62,89],"depends":[70],"on":[71,139],"parameters.":[73],"this":[75,179],"research,":[76],"authors":[78],"attempted":[79],"understand":[81],"whether":[82],"any":[83],"dependence":[84,101,172,180],"existed":[85],"between":[86,173],"current":[88],"and":[94,161,178,193,237],"its":[95],"previous":[96],"values.":[97],"To":[98],"capture":[99],"among":[102],"data,":[105,113],"series":[107,149],"analysis":[108],"was":[109,135,156],"applied":[110],"over":[111],"which":[114],"were":[115],"obtained":[116],"simulated":[119],"fully":[120],"signal.":[122],"behavior":[124],"signal\u2019s":[127],"under":[130,233],"different":[131,234],"levels":[132],"demand":[134,186],"analyzed,":[136],"and,":[137],"based":[138],"sample":[140],"autocorrelation":[141],"functions":[142],"(ACFs),":[143],"a":[144,169,207,240],"well-known":[145],"family":[146],"called":[150],"autoregressive":[151],"integrated":[152],"moving":[153],"average":[154],"(ARIMA)":[155],"chosen":[157],"model":[159,229],"fitting":[160],"prediction.":[162],"results":[164],"revealed":[165],"that":[166],"there":[167],"statistically":[170],"significant":[171],"two":[174,204],"consecutive":[175],"lengths,":[177],"becomes":[181],"more":[182,202,250],"pronounced":[183],"increases.":[187],"Further,":[188],"improve":[190],"fit":[192],"accuracy":[195],"signals":[200],"with":[201],"than":[203],"critical":[205],"phases,":[206],"linear":[208],"regression":[209],"using":[211,226],"skipping":[212],"indicators":[213],"been":[215],"added":[216],"ARIMA":[219],"model.":[220],"Finally,":[221],"simulation-based":[222],"proposed":[228],"performs":[230],"reasonably":[231],"well":[232],"simulation":[235],"scenarios,":[236],"achieves":[239],"smaller":[241],"mean":[242],"squared":[243],"error":[245],"(MSPE)":[246],"compared":[248],"traditional":[251],"averaging":[252],"models.":[254]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
