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A review of Traffic State Prediction (TSP) methods in Intelligent Transportation Systems (ITS)

In todays world, traffic congestion is a major problem in almost all metropolitans. This problem is even becoming more crucial due to increasing numbers of vehicles. Mobility of people, travel time duration, quality of life, transportation planning systems and traffic management are examples which b...

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Main Authors: Ahanin, Fatemeh, Mustapha, Norwati, Zolkepli, Maslina, Husin, Nor Azura
Format: Article
Published: Human Resource Management Academic Research Society 2023
Online Access:http://psasir.upm.edu.my/id/eprint/106683/
https://hrmars.com/index.php/IJARBSS/article/view/16683/A-Review-of-Traffic-State-Prediction-TSP-Methods-in-Intelligent-Transportation-Systems-ITS
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id my.upm.eprints.106683
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spelling my.upm.eprints.1066832024-09-26T07:14:29Z http://psasir.upm.edu.my/id/eprint/106683/ A review of Traffic State Prediction (TSP) methods in Intelligent Transportation Systems (ITS) Ahanin, Fatemeh Mustapha, Norwati Zolkepli, Maslina Husin, Nor Azura In todays world, traffic congestion is a major problem in almost all metropolitans. This problem is even becoming more crucial due to increasing numbers of vehicles. Mobility of people, travel time duration, quality of life, transportation planning systems and traffic management are examples which bear the effects of traffic congestion The modern smart technology such as Artificial Intelligence (AI) has reduced traffic congestion by improving traffic monitoring and management technologies. These technologies require sufficient and accurate traffic data such as flow, velocity, and traffic density. Several machine learning-based methods have been proposed to predict the traffic state. Providing accurate prediction is an important stage in the successful implementation of Intelligent Transportation Systems (ITS). In this paper, we summarize the latest approaches in enhancing traffic state prediction, and possible developments in future, which potentially can transform many aspects of traffic management. Human Resource Management Academic Research Society 2023-03-12 Article PeerReviewed Ahanin, Fatemeh and Mustapha, Norwati and Zolkepli, Maslina and Husin, Nor Azura (2023) A review of Traffic State Prediction (TSP) methods in Intelligent Transportation Systems (ITS). International Journal of Academic Research in Business and Social Sciences, 13 (3). 923 - 935. ISSN 2222-6990 https://hrmars.com/index.php/IJARBSS/article/view/16683/A-Review-of-Traffic-State-Prediction-TSP-Methods-in-Intelligent-Transportation-Systems-ITS 10.6007/ijarbss/v13-i3/16683
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description In todays world, traffic congestion is a major problem in almost all metropolitans. This problem is even becoming more crucial due to increasing numbers of vehicles. Mobility of people, travel time duration, quality of life, transportation planning systems and traffic management are examples which bear the effects of traffic congestion The modern smart technology such as Artificial Intelligence (AI) has reduced traffic congestion by improving traffic monitoring and management technologies. These technologies require sufficient and accurate traffic data such as flow, velocity, and traffic density. Several machine learning-based methods have been proposed to predict the traffic state. Providing accurate prediction is an important stage in the successful implementation of Intelligent Transportation Systems (ITS). In this paper, we summarize the latest approaches in enhancing traffic state prediction, and possible developments in future, which potentially can transform many aspects of traffic management.
format Article
author Ahanin, Fatemeh
Mustapha, Norwati
Zolkepli, Maslina
Husin, Nor Azura
spellingShingle Ahanin, Fatemeh
Mustapha, Norwati
Zolkepli, Maslina
Husin, Nor Azura
A review of Traffic State Prediction (TSP) methods in Intelligent Transportation Systems (ITS)
author_facet Ahanin, Fatemeh
Mustapha, Norwati
Zolkepli, Maslina
Husin, Nor Azura
author_sort Ahanin, Fatemeh
title A review of Traffic State Prediction (TSP) methods in Intelligent Transportation Systems (ITS)
title_short A review of Traffic State Prediction (TSP) methods in Intelligent Transportation Systems (ITS)
title_full A review of Traffic State Prediction (TSP) methods in Intelligent Transportation Systems (ITS)
title_fullStr A review of Traffic State Prediction (TSP) methods in Intelligent Transportation Systems (ITS)
title_full_unstemmed A review of Traffic State Prediction (TSP) methods in Intelligent Transportation Systems (ITS)
title_sort review of traffic state prediction (tsp) methods in intelligent transportation systems (its)
publisher Human Resource Management Academic Research Society
publishDate 2023
url http://psasir.upm.edu.my/id/eprint/106683/
https://hrmars.com/index.php/IJARBSS/article/view/16683/A-Review-of-Traffic-State-Prediction-TSP-Methods-in-Intelligent-Transportation-Systems-ITS
_version_ 1811685946943340544
score 13.211869

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