Dynamic Robustness Analysis for Subway Network With Spatiotemporal Characteristic of Passenger Flow
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 spatiote...
Main Authors: | , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9024061/ |
id |
doaj-d0a86c5dada946bb88c8df473cf834cf |
---|---|
record_format |
Article |
spelling |
doaj-d0a86c5dada946bb88c8df473cf834cf2021-03-30T03:10:18ZengIEEEIEEE Access2169-35362020-01-018455444555510.1109/ACCESS.2020.29782799024061Dynamic Robustness Analysis for Subway Network With Spatiotemporal Characteristic of Passenger FlowYi Fan0Fan Zhang1Shihong Jiang2Chao Gao3https://orcid.org/0000-0002-5865-2285Zhanwei Du4https://orcid.org/0000-0002-2020-767XZhen Wang5Xianghua Li6https://orcid.org/0000-0003-0253-3882College of Computer and Information Science, Southwest University, Chongqing, ChinaCollege of Computer and Information Science, Southwest University, Chongqing, ChinaCollege of Computer and Information Science, Southwest University, Chongqing, ChinaCollege of Computer and Information Science, Southwest University, Chongqing, ChinaKey Laboratory of Urban Land Resources Monitoring and Simulation, MNR, Shenzhen, ChinaCenter for Optical Imagery Analysis and Learning, Northwestern Polytechnical University, Xi’an, ChinaCollege of Computer and Information Science, Southwest University, Chongqing, ChinaThe 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.https://ieeexplore.ieee.org/document/9024061/Subway networkrobustnessdynamic passenger flowcascading failure |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yi Fan Fan Zhang Shihong Jiang Chao Gao Zhanwei Du Zhen Wang Xianghua Li |
spellingShingle |
Yi Fan Fan Zhang Shihong Jiang Chao Gao Zhanwei Du Zhen Wang Xianghua Li Dynamic Robustness Analysis for Subway Network With Spatiotemporal Characteristic of Passenger Flow IEEE Access Subway network robustness dynamic passenger flow cascading failure |
author_facet |
Yi Fan Fan Zhang Shihong Jiang Chao Gao Zhanwei Du Zhen Wang Xianghua Li |
author_sort |
Yi Fan |
title |
Dynamic Robustness Analysis for Subway Network With Spatiotemporal Characteristic of Passenger Flow |
title_short |
Dynamic Robustness Analysis for Subway Network With Spatiotemporal Characteristic of Passenger Flow |
title_full |
Dynamic Robustness Analysis for Subway Network With Spatiotemporal Characteristic of Passenger Flow |
title_fullStr |
Dynamic Robustness Analysis for Subway Network With Spatiotemporal Characteristic of Passenger Flow |
title_full_unstemmed |
Dynamic Robustness Analysis for Subway Network With Spatiotemporal Characteristic of Passenger Flow |
title_sort |
dynamic robustness analysis for subway network with spatiotemporal characteristic of passenger flow |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2020-01-01 |
description |
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. |
topic |
Subway network robustness dynamic passenger flow cascading failure |
url |
https://ieeexplore.ieee.org/document/9024061/ |
work_keys_str_mv |
AT yifan dynamicrobustnessanalysisforsubwaynetworkwithspatiotemporalcharacteristicofpassengerflow AT fanzhang dynamicrobustnessanalysisforsubwaynetworkwithspatiotemporalcharacteristicofpassengerflow AT shihongjiang dynamicrobustnessanalysisforsubwaynetworkwithspatiotemporalcharacteristicofpassengerflow AT chaogao dynamicrobustnessanalysisforsubwaynetworkwithspatiotemporalcharacteristicofpassengerflow AT zhanweidu dynamicrobustnessanalysisforsubwaynetworkwithspatiotemporalcharacteristicofpassengerflow AT zhenwang dynamicrobustnessanalysisforsubwaynetworkwithspatiotemporalcharacteristicofpassengerflow AT xianghuali dynamicrobustnessanalysisforsubwaynetworkwithspatiotemporalcharacteristicofpassengerflow |
_version_ |
1724184026368966656 |