Dynamic Robustness Analysis for Subway Network With Spatiotemporal Characteristic of Passenger Flow

IEEE Access

Zhen Wang¹  Yi Fan²  Shihong Jiang²  Fan Zhang²  Chao Gao²  Zhanwei Du³  Xianghua Li⁴ 

[1] Center for Optical Imagery Analysis and Learning, Northwestern Polytechnical University, Xi&x2019;College of Computer and Information Science, Southwest University, Chongqing, China;Key Laboratory of Urban Land Resources Monitoring and Simulation, MNR, Shenzhen, China;an, China;

关键词: Subway network;    robustness;    dynamic passenger flow;    cascading failure;   

DOI  :  10.1109/ACCESS.2020.2978279

来源: DOAJ

【 摘 要 】

The robustness is a crucial and essential problem of a subway network (SN), which can help us improve the efficiency of a transportation system. Several existing researches have analyzed the SN robustness based on the rail structure or the static distribution of passenger flow. However, the spatiotemporal characteristic of passenger flow also plays an important role in the SN robustness, since it can trigger some unexpected cascading failures in SN. Therefore, how to characterize the effect of this cascading failure on the SN robustness still remains an important and open problem. In this paper, we address the above problem as follows: (1) we propose a temporal subway network (TSN) to consider the dynamics of passenger flow in SN; (2) we adopt the linear threshold (LT) model to simulate the cascading failure process of TSN and propose a new robustness metric R(t) to evaluate the effect of this cascading failure on SN robustness. Based on the Shanghai subway smart card data, we carry out extensive experiments to analyze the effects of the cascading failure on the Shanghai SN robustness. Experiments show that the Shanghai TSN robustness varies over time. More significantly, the large volume of passenger flow can increase the impact of failure modes (i.e., random and malicious failure modes) on the Shanghai TSN robustness.

【 授权许可】

Unknown