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A Novel Method about the Representation and Discrimination of Traffic State

The representation and discrimination of various traffic states play an essential role in solving traffic accidents and congestion as the foundation of traffic state prediction. However, the existing representation of the traffic state usually only considers the road congestion layer and divides the...

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Detalles Bibliográficos
Autores principales: Jiang, Junfeng, Chen, Qiushi, Xue, Jie, Wang, Haobo, Chen, Zhijun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7570472/
https://www.ncbi.nlm.nih.gov/pubmed/32899826
http://dx.doi.org/10.3390/s20185039
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author Jiang, Junfeng
Chen, Qiushi
Xue, Jie
Wang, Haobo
Chen, Zhijun
author_facet Jiang, Junfeng
Chen, Qiushi
Xue, Jie
Wang, Haobo
Chen, Zhijun
author_sort Jiang, Junfeng
collection PubMed
description The representation and discrimination of various traffic states play an essential role in solving traffic accidents and congestion as the foundation of traffic state prediction. However, the existing representation of the traffic state usually only considers the road congestion layer and divides the traffic state into congested and unblocked. Representation only at the congestion layer is difficult to reflect the road traffic state comprehensively. Therefore, we select three indicators from the layers of road congestion, road safety, and road stability, respectively, then utilizing K-means to cluster the traffic state. The clustering results can be regarded as a new type for the representation of a traffic state. As a result, the traffic states are divided into four classes, which comprehensively reflects the level of road congestion, safety, and stability. Using the four traffic states obtained from the clustering results as class labels, we applied a multi-layer perceptron (MLP) to classify the different traffic states, and the receiver operating characteristic (ROC) curve is assessed to verify the superiority of the classification results. Finally, a visual display of the real-time traffic state in a city’s central area was given.
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spelling pubmed-75704722020-10-28 A Novel Method about the Representation and Discrimination of Traffic State Jiang, Junfeng Chen, Qiushi Xue, Jie Wang, Haobo Chen, Zhijun Sensors (Basel) Article The representation and discrimination of various traffic states play an essential role in solving traffic accidents and congestion as the foundation of traffic state prediction. However, the existing representation of the traffic state usually only considers the road congestion layer and divides the traffic state into congested and unblocked. Representation only at the congestion layer is difficult to reflect the road traffic state comprehensively. Therefore, we select three indicators from the layers of road congestion, road safety, and road stability, respectively, then utilizing K-means to cluster the traffic state. The clustering results can be regarded as a new type for the representation of a traffic state. As a result, the traffic states are divided into four classes, which comprehensively reflects the level of road congestion, safety, and stability. Using the four traffic states obtained from the clustering results as class labels, we applied a multi-layer perceptron (MLP) to classify the different traffic states, and the receiver operating characteristic (ROC) curve is assessed to verify the superiority of the classification results. Finally, a visual display of the real-time traffic state in a city’s central area was given. MDPI 2020-09-04 /pmc/articles/PMC7570472/ /pubmed/32899826 http://dx.doi.org/10.3390/s20185039 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Jiang, Junfeng
Chen, Qiushi
Xue, Jie
Wang, Haobo
Chen, Zhijun
A Novel Method about the Representation and Discrimination of Traffic State
title A Novel Method about the Representation and Discrimination of Traffic State
title_full A Novel Method about the Representation and Discrimination of Traffic State
title_fullStr A Novel Method about the Representation and Discrimination of Traffic State
title_full_unstemmed A Novel Method about the Representation and Discrimination of Traffic State
title_short A Novel Method about the Representation and Discrimination of Traffic State
title_sort novel method about the representation and discrimination of traffic state
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7570472/
https://www.ncbi.nlm.nih.gov/pubmed/32899826
http://dx.doi.org/10.3390/s20185039
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