Traffic sub-area division method based on density peak clustering

被引：0
|
作者：
Wei L. [1 ]
Gao L. [1 ,2 ]
Li J.-H. [2 ]
Yang J. [1 ,2 ]
Tian Y.-L. [1 ]
机构：
[1] Beijing Key Laboratory of Urban Road Traffic Intelligent Control Technology, North China University of Technology, Beijing
[2] School of Information Science and Technology, North China University of Technology, Beijing
来源：
Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) | 2023年 / 53卷 / 01期
关键词：
density peak clustering; intersection correlation degree; sub-area division; transportation information engineering and control; vehicle trajectory;
D O I：
10.13229/j.cnki.jdxbgxb20210513
中图分类号：
学科分类号：
摘要：
To improve the efficiency of urban traffic signal control system，this paper proposes a sub-area division method based on vehicle trajectory data and density peak clustering. Firstly，the correlation index between adjacent intersections is calculated by combining the influence of distance between intersections，vehicle delays and platoon dispersion based on vehicle trajectory data. Secondly，the distance matrix is obtained according to the correlation indexes，which is used as the input of the density peak clustering algorithm. For the hyperparameter determination in density peak clustering，the concept of potential entropy in the data field theory is introduced to optimize. Simultaneously，the elbow rule is used to determine the number of clusters. Finally，the division of sub-areas is completed by using the improved clustering algorithm. The experiment on real-world vehicle trajectory data in Zhongguancun West District of Beijing shows that the proposed method could divide the road network into sub-area effectively and reasonably based on vehicle trajectory data only. © 2023 Editorial Board of Jilin University. All rights reserved.
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页码：124 / 131
页数：7
相关论文
共 10 条
  • [1] Walinchus R J., Real-time network decomposition and sub-network interfacing, Highway Research Record, 366, pp. 20-28, (1971)
  • [2] Yagoda H N, Principe E H, Vick C E, Et al., Subdivision of signal systems into control areas, Traffic Engineering, Inst Traffic Engr, 43, 12, pp. 42-47, (1973)
  • [3] Chang E C P., How to decide the interconnection of isolated traffic signals, Proceedings of the 17th Conference on Winter Simulation, pp. 445-453, (1985)
  • [4] Ma Ying-ying, Yang Xiao-guang, Zeng Ying, Urban traffic signal control network partitioning using spectral method, Systems Engineering―Theory & Practice, 30, 12, pp. 2290-2296, (2010)
  • [5] Lin X, Xu J., Road network partitioning method based on canopy-kmeans clustering algorithm, Archives of Transport, 54, 2, pp. 95-106, (2020)
  • [6] Wang Li, Chen Zhi, Liu Xiao-ming, Et al., Sub-control-area division optimization of traffic network based on community discovery, Journal of Transportation Systems Engineering and Information Technology, 12, 6, pp. 164-169, (2012)
  • [7] Rodriguez A, Laio A., Clustering by fast search and find of density peaks, Science, 344, 6191, pp. 1492-1496, (2014)
  • [8] Gan Wen-yan, Liu Chong, An improved clustering algorithm that searches and finds density peaks, CAAI Transactions on Intelligent Systems, 12, 2, pp. 229-235, (2017)
  • [9] Wang S, Gan W, Li D, Et al., Data field for hierarchical clustering, International Journal of Data Warehousing and Mining, 7, 4, pp. 43-63, (2011)
  • [10] Kodinariya T M, Makwana P R., Review on determining number of cluster in k-means clustering, International Journal of Advance Research in Computer Science and Management Studies, 1, 6, pp. 90-95, (2013)
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