Journal of South China University of Technology(Natural Science) >
Division of Traffic Control Periods Based on Improved FCM Clustering
Received date: 2016-01-23
Revised date: 2016-06-12
Online published: 2016-11-01
Supported by
Supported by the National Key Technology Research and Development Program of the Ministry of Science and Technology of China(2014BAG03B03)
In this paper,the traditional fuzzy c-means clustering (FCM) algorithm is improved,and a method to divide the traffic signal control periods is proposed based on the improved FCM algorithm.In the method,first,a cardinal number of fuzzy clustering membership degree is introduced to automatically select the cluster number.Then,the hybrid simulated annealing genetic algorithm is employed to optimize the initial clustering center.Final- ly,the traffic control periods are divided according to the actual traffic flow data,and the performance of the schemes is evaluated by using the simulation software.The results show that,as compared with the traditional FCM algorithm,the proposed method can divide the traffic control periods more effectively and reflect the actual traffic characteristics more accurately,and it achieves a global optimal solution.In addition,in comparison with the origi- nal signal control scheme,although both the scheme based on the FCM algorithm and the proposed scheme can re- duce the average vehicle delay,the proposed scheme has a more obvious effect.
YU De-xin TIAN Xiu-juan YANG Zhao-sheng . Division of Traffic Control Periods Based on Improved FCM Clustering[J]. Journal of South China University of Technology(Natural Science), 2016 , 44(12) : 53 -60 . DOI: 10.3969/j.issn.1000-565X.2016.12.008
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