dc.contributor.author | Kababulut, Fevzi Yasin | |
dc.contributor.author | Kuntalp, Damla | |
dc.contributor.author | Akay, Olcay | |
dc.contributor.author | Duzenli, Timur | |
dc.date.accessioned | 2019-09-01T13:04:24Z | |
dc.date.available | 2019-09-01T13:04:24Z | |
dc.date.issued | 2018 | |
dc.identifier.issn | 0353-5320 | |
dc.identifier.issn | 1848-4069 | |
dc.identifier.uri | https://dx.doi.org/10.7307/ptt.v30i5.2757 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12450/938 | |
dc.description | WOS: 000457181600008 | en_US |
dc.description.abstract | Intelligent traffic systems attempt to solve the problem of traffic congestion, which is one of the most important environmental and economic issues of urban life. In this study, we approach this problem via prediction of traffic status using past average traveler speed (ATS). Five different algorithms are proposed for predicting the traffic status. They are applied to real data provided by the Traffic Control Center of Istanbul Metropolitan Municipality. Algorithm 1 predicts future ATS on a highway section based on the past speed information obtained from the same road section. The other proposed algorithms, Algorithms 2 through 5, predict the traffic status as fluent, moderately congested, or congested, again using past traffic state information for the same road segment. Here, traffic states are assigned according to predetermined intervals of ATS values. In the proposed algorithms, ATS values belonging to past five consecutive 10-minute time intervals are used as input data. Performances of the proposed algorithms are evaluated in terms of root mean square error (RMSE), sample accuracy, balanced accuracy, and processing time. Although the proposed algorithms are relatively simple and require only past speed values, they provide fairly reliable results with noticeably low prediction errors. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | SVENCILISTE U ZAGREBU, FAKULTET PROMETNIH ZNANOSTI | en_US |
dc.relation.isversionof | 10.7307/ptt.v30i5.2757 | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | ATS prediction | en_US |
dc.subject | vehicle traffic | en_US |
dc.subject | prediction of traffic status | en_US |
dc.title | SIMPLE AND EFFICIENT PREDICTION OF NEAR FUTURE STATE OF TRAFFIC USING ONLY PAST SPEED INFORMATION | en_US |
dc.type | article | en_US |
dc.relation.journal | PROMET-TRAFFIC & TRANSPORTATION | en_US |
dc.authorid | kuntalp, damla -- 0000-0003-0617-7918; | en_US |
dc.identifier.volume | 30 | en_US |
dc.identifier.issue | 5 | en_US |
dc.identifier.startpage | 589 | en_US |
dc.identifier.endpage | 599 | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.contributor.department-temp | [Kababulut, Fevzi Yasin] Minist Transport & Infrastruct, Reg Directorate Cesmebasi Neighborhood 4, Alpaslan Ave 2, Ovaakca Osmangazi, Bursa, Turkey -- [Kuntalp, Damla -- Akay, Olcay] Dokuz Eylul Univ, Dept Elect & Elect Engn, Tinaztepe Campus, TR-35100 Izmir, Turkey -- [Duzenli, Timur] Amasya Univ, Technol Fac, Dept Elect & Elect Engn, A Block,Room A303, TR-05100 Amasya, Turkey | en_US |