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A New Approach to Determine Traffic Peak Periods to Utilize in Transportation Planning

dc.contributor.authorSaracoglu, Abdulsamet
dc.contributor.authorOzen, Halit
dc.contributor.authorApaydin, Mehmet Serkan
dc.contributor.authorMaltas, Abdullah
dc.date.accessioned2026-06-27T14:33:12Z
dc.date.issued2021
dc.description.abstractDetection of the traffic peak periods for a city has many advantages not only in terms of the traffic operation but also in urban transportation planning. In the planning, future travel demand is analyzed for peak and off-peak periods separately and transportation networks are designed based on these analyses. However, the traffic peak periods may shift in time because of changes in people's activities. Therefore, the detection and update of these periods periodically provide to improve urban transportation planning. The aim of this research is to present a new approach to determine traffic peak periods in order to utilize for use in transportation planning. In order to achieve this goal, the inductive loop detector data are obtained for a city and cleaned. Regular traffic flow patterns (without days that include unexpected incidents) of the whole city are produced, and peak periods are determined with these data. The Facebook Prophet software, which is a forecasting procedure, is presented as a new approach to determine traffic peak periods based on changepoint detection. In order to compare the results, experts' opinion, which is the conventional method, and the k-medoids clustering methods are applied. In conclusion, it is seen that the suggested new approach facilitates so much the accurate determination of traffic peak periods for urban transportation planning.en
dc.description.urihttps://doi.org/10.1007/s13369-021-05384-2
dc.identifier.doi10.1007/s13369-021-05384-2
dc.identifier.eissn2191-4281
dc.identifier.endpage10418
dc.identifier.issn2193-567X
dc.identifier.issue11
dc.identifier.startpage10409
dc.identifier.urihttps://hdl.handle.net/20.500.14981/61983
dc.identifier.volume46
dc.identifier.wos000614009100015
dc.language.isoeng
dc.publisherSPRINGER HEIDELBERG
dc.relation.ispartofARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
dc.subjectChangepoint detection
dc.subjectFacebook prophet
dc.subjectk-medoids clustering
dc.subjectTraffic peak period
dc.subjectTransportation planning
dc.subjectMODEL
dc.subjectScience & Technology - Other Topics
dc.titleA New Approach to Determine Traffic Peak Periods to Utilize in Transportation Planning
dc.typeArticle
dspace.entity.typePublication
local.import.sourceWOS

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