Comparison Of Different Approaches In Traffic Forecasting Models For The D-200 Highway In Turkey

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dc.contributor.authorDogan, Erdem
dc.contributor.authorKorkmaz, Ersin
dc.contributor.authorAkgungor, Ali Payidar
dc.date.accessioned2020-06-25T18:29:57Z
dc.date.available2020-06-25T18:29:57Z
dc.date.issued2018
dc.departmentKırıkkale Üniversitesi
dc.descriptionAKGUNGOR, ALI PAYIDAR/0000-0003-0669-5715
dc.description.abstractShort-term traffic estimations have a significant influence in terms of effectively controlling vehicle traffic. In this study, short-term traffic forecasting models have been developed based on different approaches. Seasonal autoregressive integrated moving average (SARIMA), artificial bee colony (ABC) and differential evolution (DE) algorithms are the techniques used in the optimization of models, which have been developed by using observation data for the D-200 highway in Turkey. 80% of the data were used for training, with the remaining data used for testing. The performances of the models were illustrated with mean absolute errors (MAEs), mean absolute percentage errors (MAPEs), the coefficient of determination (R2) and the root-mean-square errors (RMSEs). It is understood that all the models provided consistent and useful results when the developed models were compared with the statistical results. In the models created separately for two lanes, the R2 values of the models were calculated to be approximately 92% for the right lane, which is generally used by heavy vehicles, and 88% for the left lane, which is used by less traffic. Based on the MAE and RMSE values, the model developed by the ABC algorithm gave the lowest error and showed more effective performance than the other approaches. Thus, the ABC model showed that it is appropriate for use on other highways in Turkey.en_US
dc.description.sponsorshipKirikkale University's Scientific Research Project Funding (KKU BAP) [KKUBAP2016/019]en_US
dc.description.sponsorshipThe authors would like to thank Kirikkale University's Scientific Research Project Funding (KKU BAP) for their financial support [Project No. KKUBAP2016/019].en_US
dc.identifier.citationDogan, E., Korkmaz, E., Akgungor, A.P. Comparison of different approaches in traffic forecasting models for the D-200 highway in Turkey. Scientific Journal of Silesian University of Technology. Series Transport. 2018, 99, 25-42.en_US
dc.identifier.doi10.20858/sjsutst.2018.99.3
dc.identifier.endpage42en_US
dc.identifier.issn0209-3324
dc.identifier.issn2450-1549
dc.identifier.startpage25en_US
dc.identifier.urihttps://doi.org/10.20858/sjsutst.2018.99.3
dc.identifier.urihttps://hdl.handle.net/20.500.12587/7512
dc.identifier.volume99en_US
dc.identifier.wosWOS:000442596400003
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.language.isoen
dc.publisherFac Transport Silesian Univ Technologyen_US
dc.relation.ispartofScientific Journal Of Silesian University Of Technology-Series Transport
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjecttraffic forecastingen_US
dc.subjectSARIMAen_US
dc.subjectdifferential evolution algorithmen_US
dc.subjectartificial bee colony algorithmen_US
dc.titleComparison Of Different Approaches In Traffic Forecasting Models For The D-200 Highway In Turkeyen_US
dc.typeArticle

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