NCut partitioning algorithm for urban road networks based on similarity of traffic flow time series

被引：0
|
作者：
Yin C.-K. [1 ]
Fang R. [1 ]
Li T. [2 ]
机构：
[1] School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing
[2] Luban (Beijing) E-Commerce Technology Co., Ltd., Beijing
来源：
Jiaotong Yunshu Gongcheng Xuebao/Journal of Traffic and Transportation Engineering | 2021年 / 21卷 / 05期
基金：
中国国家自然科学基金;
关键词：
Dynamic partitioning; Normalized cut; Road network partitioning; Time series similarity; Traffic engineering;
D O I：
10.19818/j.cnki.1671-1637.2021.05.020
中图分类号：
学科分类号：
摘要：
Under practical demand of partitioning for large-scale urban road traffic networks, a comprehensive index that measures the similarity of traffic flow time series was constructed based on the Pearson correlation coefficient and Euclidean distance which reflects the trend and describes the spatial relationships for time series. By incorporating the spatial-temporal similarity of the traffic flow time series, an improved static partitioning algorithm for road networks was designed using the normalized cut (NCut) algorithm under the spatial connectivity constraint for each subregion. To reflect the time-varying characteristics of road networks, reasonable cluster numbers during each time period was determined by selecting an appropriate evaluation criterion, and a dynamic partitioning algorithm of the road network based on NCut for the time series was proposed. By using the link traffic flow speed data collected within a region in the Northeast Second Ring of Beijing, the designed partitioning algorithms were applied to the road network covering 7.23 km2, and the partitioning performances during evening peak hours was compared. Analysis results indicate that the proposed partitioning algorithms can effectively distinguish the traffic conditions in different areas within the road network. Using the dynamic partitioning algorithm with a time interval of 30 min, the road network can be divided into several alterable subregions with time-varying cluster numbers and time-varying scopes. Compared to the static partitioning algorithm using fixed subregion numbers of 2, 3, 4, and 5, the evaluation criterion of the proposed dynamic partitioning algorithm increase by 63.77%, 50.06%, 6.43%, and 7.13%, respectively, and the partitioning performance for the road network improves. Therefore, the proposed dynamic partitioning algorithm can divide the heterogeneous road networks into a number of internally homogeneous subregions while the internal connectivity within each subregion is guaranteed, and can fully embody the spatial-temporal evolution characteristics of the traffic flow, and can benefit to formulating dynamical perimeter control scheme for multiple regions. © 2021, Editorial Department of Journal of Traffic and Transportation Engineering. All right reserved.
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页码：238 / 250
页数：12
相关论文
共 30 条
  • [1] LIU Qiang, WANG Qing, LIU Shu-an, An improved sub-networks partitioning method for urban traffic networks, 31st Chinese Control and Decision Conference, pp. 6405-6410, (2019)
  • [2] XUN Jing, LIU Tong, NING Bin, Et al., Using approximate dynamic programming to maximize regenerative energy utilization for metro, IEEE Transactions on Intelligent Transportation Systems, 21, 9, pp. 3650-3662, (2020)
  • [3] LIU Xiao-ming, HE Zhong-he, Development and tendency of intelligent transportation systems in China, Automation Panorama, 32, 1, pp. 58-60, (2015)
  • [4] WALINCHUS R J., Real-time network decomposition and subnetwork interfacing, Highway Research Record, 366, pp. 20-28, (1971)
  • [5] DAGANZO C F., Urban gridlock: macroscopic modeling and mitigation approaches, Transportation Research Part B: Methodological, 41, 1, pp. 49-62, (2007)
  • [6] GEROLIMINIS N, DAGANZO C F., Existence of urban-scale macroscopic fundamental diagrams: some experimental findings, Transportation Research Part B: Methodological, 42, 9, pp. 759-770, (2008)
  • [7] JI Y, GEROLIMINIS N., On the spatial partitioning of urban transportation networks, Transportation Research Part B: Methodological, 46, 10, pp. 1639-1656, (2012)
  • [8] SAEDI R, SAEEDMANESH M, ZOCKAIE A, Et al., Estimating network travel time reliability with network partitioning, Transportation Research Part C: Emerging Technologies, 112, pp. 46-61, (2020)
  • [9] MA Dong-fang, LI Wen-jing, SONG Xiang, Et al., Time-of-day breakpoints optimisation through recursive time series partitioning, IET Intelligent Transport Systems, 13, 4, pp. 683-692, (2019)
  • [10] LECLERCQ L, LADINO A, BECARIE C., Enforcing optimal routing through dynamic avoidance maps, Transportation Research Part B: Methodological, 149, pp. 118-137, (2021)
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