The Method of Dynamic Identification of the Maximum Speed Limit of Expressway Based on Electronic Toll Collection Data

To overcome the drawbacks of the maximum speed limit information of expressways (i.e., long update cycle and great complexity of information recognition), in this work, an Electronic Toll Collection (ETC) gantry data-based method for dynamically identifying the maximum speed limit information of exp...

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Autores principales:	Fumin Zou, Feng Guo, Junshan Tian, Sijie Luo, Xiang Yu, Qing Gu, Lyuchao Liao
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Computer software QA76.75-76.765
Acceso en línea:	https://doaj.org/article/cf68558168254d2b818b4fea09a29f00
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spelling	oai:doaj.org-article:cf68558168254d2b818b4fea09a29f002021-11-29T00:56:41ZThe Method of Dynamic Identification of the Maximum Speed Limit of Expressway Based on Electronic Toll Collection Data1875-919X10.1155/2021/4702669https://doaj.org/article/cf68558168254d2b818b4fea09a29f002021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/4702669https://doaj.org/toc/1875-919XTo overcome the drawbacks of the maximum speed limit information of expressways (i.e., long update cycle and great complexity of information recognition), in this work, an Electronic Toll Collection (ETC) gantry data-based method for dynamically identifying the maximum speed limit information of expressways is proposed. Firstly, the characteristics of the ETC gantry data are analyzed, and then data are cleaned and reconstructed, after which an algorithm is proposed for constructing a vehicle travel speed data set. Secondly, the speed feature vector model of the road section is established by taking the relationship among the speed distribution feature, time domain feature, and the maximum speed limit of the road section into consideration. Then, a data supplement algorithm is constructed to solve the problem of the imbalance of data samples. Finally, the combined GC-XGBoost classification algorithm is used to train and learn the potential speed limit features, and it is verified through the Fujian Provincial Expressway ETC data and the speed limit information provided by the Fujian Traffic Police. The result shows that the accuracy of the method in the recognition of the maximum limited speed information of the expressway is 97.5%. Compared with the traditional limited speed information recognition and extraction methods, the proposed approach can identify the maximum limited speed information of each section of the expressway more efficiently. It can also accurately identify the dynamic change of the maximum limited speed information, which is able to provide data support for intelligent expressway management systems and map providers.Fumin ZouFeng GuoJunshan TianSijie LuoXiang YuQing GuLyuchao LiaoHindawi LimitedarticleComputer softwareQA76.75-76.765ENScientific Programming, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Computer software QA76.75-76.765
spellingShingle	Computer software QA76.75-76.765 Fumin Zou Feng Guo Junshan Tian Sijie Luo Xiang Yu Qing Gu Lyuchao Liao The Method of Dynamic Identification of the Maximum Speed Limit of Expressway Based on Electronic Toll Collection Data
description	To overcome the drawbacks of the maximum speed limit information of expressways (i.e., long update cycle and great complexity of information recognition), in this work, an Electronic Toll Collection (ETC) gantry data-based method for dynamically identifying the maximum speed limit information of expressways is proposed. Firstly, the characteristics of the ETC gantry data are analyzed, and then data are cleaned and reconstructed, after which an algorithm is proposed for constructing a vehicle travel speed data set. Secondly, the speed feature vector model of the road section is established by taking the relationship among the speed distribution feature, time domain feature, and the maximum speed limit of the road section into consideration. Then, a data supplement algorithm is constructed to solve the problem of the imbalance of data samples. Finally, the combined GC-XGBoost classification algorithm is used to train and learn the potential speed limit features, and it is verified through the Fujian Provincial Expressway ETC data and the speed limit information provided by the Fujian Traffic Police. The result shows that the accuracy of the method in the recognition of the maximum limited speed information of the expressway is 97.5%. Compared with the traditional limited speed information recognition and extraction methods, the proposed approach can identify the maximum limited speed information of each section of the expressway more efficiently. It can also accurately identify the dynamic change of the maximum limited speed information, which is able to provide data support for intelligent expressway management systems and map providers.
format	article
author	Fumin Zou Feng Guo Junshan Tian Sijie Luo Xiang Yu Qing Gu Lyuchao Liao
author_facet	Fumin Zou Feng Guo Junshan Tian Sijie Luo Xiang Yu Qing Gu Lyuchao Liao
author_sort	Fumin Zou
title	The Method of Dynamic Identification of the Maximum Speed Limit of Expressway Based on Electronic Toll Collection Data
title_short	The Method of Dynamic Identification of the Maximum Speed Limit of Expressway Based on Electronic Toll Collection Data
title_full	The Method of Dynamic Identification of the Maximum Speed Limit of Expressway Based on Electronic Toll Collection Data
title_fullStr	The Method of Dynamic Identification of the Maximum Speed Limit of Expressway Based on Electronic Toll Collection Data
title_full_unstemmed	The Method of Dynamic Identification of the Maximum Speed Limit of Expressway Based on Electronic Toll Collection Data
title_sort	method of dynamic identification of the maximum speed limit of expressway based on electronic toll collection data
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/cf68558168254d2b818b4fea09a29f00
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The Method of Dynamic Identification of the Maximum Speed Limit of Expressway Based on Electronic Toll Collection Data

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