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

被引:9
|
作者
Zou, Fumin [1 ]
Guo, Feng [1 ]
Tian, Junshan [2 ]
Luo, Sijie [2 ]
Yu, Xiang [2 ]
Gu, Qing [3 ]
Liao, Lyuchao [4 ]
机构
[1] Fuzhou Univ, Coll Math & Comp Sci, Fuzhou 350108, Fujian, Peoples R China
[2] Fujian Univ Technol, Fujian Key Lab Automot Elect & Elect Dr, Fuzhou 350118, Fujian, Peoples R China
[3] Fujian Prov Expressway Informat Technol Co Ltd, Fuzhou 350011, Fujian, Peoples R China
[4] Fujian Univ Technol, Fujian Prov Big Data Res Inst Intelligent Transpo, Fuzhou 350118, Fujian, Peoples R China
关键词
RISK;
D O I
10.1155/2021/4702669
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
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.
引用
收藏
页数:15
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