Abstract

Under the background of urbanization and the rapid development of urban rail transit (URT), serious attention has been focused on URT network reliability in recent years. In this work, in order to measure network reliability, three indicators are constructed based on passengers’ tolerable travel paths, passenger travel efficiency and passenger travel realization on a URT network. The passenger tolerability coefficient, which is the ratio of passengers’ tolerable travel time to the shortest possible travel time, is proposed and added to the indicators. It reflects passengers’ behavior with respect to choice of travel paths. The ratio of affected passenger volume (RAPV) is proposed to identify important stations. Finally, the connectivity reliability of Wuhan’s subway network is analyzed by simulating attacks on stations. The results show that the degree centrality, betweenness centrality and RAPV indicators of stations can effectively identify the important stations that have a significant impact on the connectivity reliability of the network. In particular, the RAPV indicator effectively identifies stations that have the greatest influence on passenger travel realization. The connectivity reliability of Wuhan’s subway network is sensitive to passenger tolerability coefficient, and reliability is greater during non-peak hours than during peak hours. In addition, the stations that are important to the connectivity reliability of the Wuhan subway have two features, i.e., they are located at the center of the city, and they are important for connecting subgraphs of the network.

Highlights

  • In recent years, China has experienced rapid urbanization

  • The results show that the degree centrality, betweenness centrality and ratio of affected passenger volume (RAPV) indicators of stations can effectively identify the important stations that have a significant impact on the connectivity reliability of the network

  • Where Rrate is the rate of passenger travel realization on a urban rail transit (URT) network after the network has suffered damage ðd; xÞ, Vðd;xÞ is the number of passengers who travel on the network within tolerable travel time when the network has suffered damage, and nðodd;xÞ is a 0–1 variable which is equal to 1 if there is at least one tolerable travel path from station o to station d, and 0 otherwise

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Summary

Introduction

China has experienced rapid urbanization. Urban rail transit (URT), with the advantages of large capacity, low energy consumption and environmental protection, has grown rapidly. Researchers have proposed various effectiveness measures for analyzing transportation reliability. All of the above-mentioned studies primarily analyzed the connectivity reliability of networks based on network topology, the effects of removing nodes and links, without considering passenger effects. Zhang et al [16] proposed a level-of-service (LOS)-based evaluation model to calculate the connectivity reliability of a regional transportation network considering passenger volume. Many researchers assume that two nodes are connected as long as at least one connection path exists between the two nodes This assumption is not entirely consistent with passenger behavior regarding choice of travel path. Indicators are proposed for measuring the connectivity reliability of a URT network and identifying important stations on the network by drawing on the above-mentioned literature. The ratio of affected passenger volume (RAPV) is proposed to measure the importance of stations on the URT network. The sensitivity of the passenger tolerability coefficient to the three indicators of connectivity reliability of the Wuhan subway is analyzed

Method
Network Definition
Evaluating the Connectivity Reliability of a URT Network
Number of Tolerable Travel Paths on a URT Network
Travel Efficiency of a URT Network
Rate of Passenger Travel Realization on a URT Network
Identifying Important Stations
Data Preparation
Important Stations
Connectivity Reliability of Wuhan’s subway network
Relative Number of Tolerable Travel Paths in Wuhan’s subway network
Relative Travel Efficiency of Wuhan’s subway network
Rate of Passenger Travel Realization on Wuhan’s subway network
Sensitivity Analysis of the Passenger Tolerability Coefficient
Important Stations for Connectivity Reliability of Wuhan’s subway network
Findings
Conclusions
Full Text
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