Unexpected passenger flow propagation in urban rail transit network based on SIR model

2013 ◽  
pp. 281-284
Keyword(s):  
Sir Model ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Transit Network ◽  
Passenger Flow ◽  
Urban Rail ◽  
Flow Propagation ◽  
Urban Rail Transit Network

scholarly journals Vulnerability Analysis of Urban Rail Transit Network within Multi-Modal Public Transport Networks

2019 ◽  
Vol 11 (7) ◽  
pp. 2109 ◽  
Author(s):  
Qing-Chang Lu ◽  
Shan Lin
Keyword(s):  
Public Transport ◽  
Flow Characteristics ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Network Vulnerability ◽  
Transit Network ◽  
Rail Network ◽  
Passenger Flow ◽  
Urban Rail ◽  
Urban Rail Transit Network

In terms of urban rail transit network vulnerability, most studies have focused on the network topology characteristics and travel cost changes after network incidents and analyzed rail transit network independently. The neglects of passenger flow distributions on the network and alternative public transport modes under rail network disruptions would either underestimate or overestimate the vulnerability of rail transit network, and thus lead to inaccurate results and decisions. This study presents an accessibility-based measurement for urban rail transit network vulnerability analysis and explicitly accounts for rail passenger flow characteristics, travel cost changes, and alternative transit modes. It is shown that the proposed approach is capable of measuring the consequences on rail network, and the advantages of the accessibility method are demonstrated and compared. The methodology is applied to the urban rail transit network of Shenzhen, China within a multi-modal public transport network. Results reveal that the consequences of disruptions on network accessibility are obviously different for stations with different passenger flow characteristics, and some undisrupted stations are found to be vulnerable under surrounding station failures. The proposed methodology offers reliable measurements on rail transit network vulnerability and implications for decision-making under rail network disruptions.

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