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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Main Authors: Fevzi Yasin Kababulut, Damla Kuntalp, Olcay Akay, Timur Düzenli
Format: Article
Language:English
Published: University of Zagreb, Faculty of Transport and Traffic Sciences 2018-11-01
Series:Promet (Zagreb)
Subjects:
Online Access:https://traffic.fpz.hr/index.php/PROMTT/article/view/2757
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spelling 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
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