scholarly journals Resilience Assessment and Optimization for Urban Rail Transit Networks: A Case Study of Beijing Subway Network

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 71221-71234 ◽  
Author(s):  
Ming Li ◽  
Hongwei Wang ◽  
Huashen Wang
2020 ◽  
Vol 12 (14) ◽  
pp. 5756
Author(s):  
Jianhua Zhang ◽  
Ziqi Wang ◽  
Shuliang Wang ◽  
Shengyang Luan ◽  
Wenchao Shao

Urban rail transit has received much attention in the last two decades, and a significant number of cities have established urban rail transit networks (URTNs). Although URTNs have brought enormous convenience to the daily life of citizens, system failures still frequently occur, therefore the vulnerability of URTNs must be a concern. In this paper, we propose a novel measurement called the node strength parameter to assess the importance of nodes and present a redundant recovery scheme to imitate the system recovery of URTNs subjected to failures. Employing three malicious attacks and taking the Nanjing subway network as the case study, we investigated the network vulnerability under scenarios of different simulated attacks. The results illustrate that passenger in-flow shows the negligible impact on the vulnerability of the node, while out-flow plays a considerable role in the largest strength node-based attack. Further, we find that vulnerability will decrease as passenger out-flow increases, and the vulnerability characteristics are the same with the increase in the construction cost of URTNs. Considering different attack scenarios, the results indicate that the highest betweenness node-based attack will cause the most damage to the system, and increasing the construction cost can improve the robustness of URTNs.


2013 ◽  
Vol 361-363 ◽  
pp. 1963-1966
Author(s):  
Wei Zhu

An integrated assignment model for urban rail transit (URT) networks was proposed and discussed in four typical scenarios with the consideration of passenger difference between native and non-native. An overall algorithm framework for the model was also developed, which introduced three critical route choice models and combined them appropriately to different scenarios. A case study was performed on a real-scale network of Shanghai during the Expo 2010. The results revealed that the proposed model can deliver more appropriate solution to the assignment problem compared to the existing practice in the real world.


2015 ◽  
Vol 7 (6) ◽  
pp. 6919-6936 ◽  
Author(s):  
Daniel Sun ◽  
Yuhan Zhao ◽  
Qing-Chang Lu

2020 ◽  
Vol 12 (10) ◽  
pp. 4166 ◽  
Author(s):  
Xuan Li ◽  
Toshiyuki Yamamoto ◽  
Tao Yan ◽  
Lili Lu ◽  
Xiaofei Ye

This paper proposes a novel model to optimize the first train timetables for urban rail transit networks, with the goal of maximizing passengers’ transfer waiting time satisfaction. To build up the relationship of transfer waiting time and passenger satisfaction, a reference-based piecewise function is formulated with the consideration of passengers’ expectations, tolerances and dissatisfaction on “just miss”. In order to determine the parameters of zero waiting satisfaction rating, the most comfortable waiting time, and the maximum tolerable waiting time in time satisfaction function, a stated preference survey is conducted in rail transit transfer stations in Shanghai. An artificial bee colony algorithm is developed to solve the timetabling model. Through a real-world case study on Shanghai’s urban rail transit network and comparison with the results of minimizing the total transfer time, we demonstrate that our approach performs better in decreasing extremely long wait and “just miss” events and increasing the number of passengers with a relatively comfortable waiting time in [31s, 5min). Finally, four practical suggestions are proposed for urban rail transit network operations.


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