Simple and Efficient Prediction of Near Future State of Traffic Using Only Past Speed Information
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 algorit...
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University of Zagreb, Faculty of Transport and Traffic Sciences
2018-11-01
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doaj-9c15131831dc4f25aece49ab324d4e022020-11-25T01:48:42ZengUniversity of Zagreb, Faculty of Transport and Traffic SciencesPromet (Zagreb)0353-53201848-40692018-11-0130558959910.7307/ptt.v30i5.27572757Simple and Efficient Prediction of Near Future State of Traffic Using Only Past Speed InformationFevzi Yasin Kababulut0Damla Kuntalp1Olcay Akay2Timur Düzenli3Dokuz Eylül UniversityDokuz Eylül UniversityDokuz Eylül UniversityAmasya UniversityIntelligent 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.https://traffic.fpz.hr/index.php/PROMTT/article/view/2757ATS predictionvehicle trafficprediction of traffic status |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Fevzi Yasin Kababulut Damla Kuntalp Olcay Akay Timur Düzenli |
spellingShingle |
Fevzi Yasin Kababulut Damla Kuntalp Olcay Akay Timur Düzenli Simple and Efficient Prediction of Near Future State of Traffic Using Only Past Speed Information Promet (Zagreb) ATS prediction vehicle traffic prediction of traffic status |
author_facet |
Fevzi Yasin Kababulut Damla Kuntalp Olcay Akay Timur Düzenli |
author_sort |
Fevzi Yasin Kababulut |
title |
Simple and Efficient Prediction of Near Future State of Traffic Using Only Past Speed Information |
title_short |
Simple and Efficient Prediction of Near Future State of Traffic Using Only Past Speed Information |
title_full |
Simple and Efficient Prediction of Near Future State of Traffic Using Only Past Speed Information |
title_fullStr |
Simple and Efficient Prediction of Near Future State of Traffic Using Only Past Speed Information |
title_full_unstemmed |
Simple and Efficient Prediction of Near Future State of Traffic Using Only Past Speed Information |
title_sort |
simple and efficient prediction of near future state of traffic using only past speed information |
publisher |
University of Zagreb, Faculty of Transport and Traffic Sciences |
series |
Promet (Zagreb) |
issn |
0353-5320 1848-4069 |
publishDate |
2018-11-01 |
description |
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. |
topic |
ATS prediction vehicle traffic prediction of traffic status |
url |
https://traffic.fpz.hr/index.php/PROMTT/article/view/2757 |
work_keys_str_mv |
AT fevziyasinkababulut simpleandefficientpredictionofnearfuturestateoftrafficusingonlypastspeedinformation AT damlakuntalp simpleandefficientpredictionofnearfuturestateoftrafficusingonlypastspeedinformation AT olcayakay simpleandefficientpredictionofnearfuturestateoftrafficusingonlypastspeedinformation AT timurduzenli simpleandefficientpredictionofnearfuturestateoftrafficusingonlypastspeedinformation |
_version_ |
1725010568460369920 |