Complex network based comparative analysis of Delhi Metro network and its extension

2019 ◽  
Vol 526 ◽  
pp. 120991 ◽  
Author(s):  
Kushal Kanwar ◽  
Harish Kumar ◽  
Sakshi Kaushal
Keyword(s):  
Comparative Analysis ◽  
Complex Network ◽  
Metro Network

Analysis of metro network performance from a complex network perspective

2018 ◽  
Vol 492 ◽  
pp. 553-563 ◽  
Author(s):  
Xingtang Wu ◽  
Hairong Dong ◽  
Chi Kong Tse ◽  
Ivan W.H. Ho ◽  
Francis C.M. Lau
Keyword(s):  
Complex Network ◽  
Network Performance ◽  
Metro Network

scholarly journals The influence of passenger flow on the topology characteristics of urban rail transit networks

2017 ◽  
Vol 31 (12) ◽  
pp. 1750181 ◽  
Author(s):  
Yingyue Hu ◽  
Feng Chen ◽  
Peiwen Chen ◽  
Yurong Tan
Keyword(s):  
Complex Network ◽  
Urban Rail Transit ◽  
Clustering Coefficient ◽  
Edge Weight ◽  
Passenger Flow ◽  
The Matrix ◽  
Passenger Volume ◽  
Metro Networks ◽  
Precautionary Measures ◽  
Metro Network

Current researches on the network characteristics of metro networks are generally carried out on topology networks without passenger flows running on it, thus more complex features of the networks with ridership loaded on it cannot be captured. In this study, we incorporated the load of metro networks, passenger volume, into the exploration of network features. Thus, the network can be examined in the context of operation, which is the ultimate purpose of the existence of a metro network. To this end, section load was selected as an edge weight to demonstrate the influence of ridership on the network, and a weighted calculation method for complex network indicators and robustness were proposed to capture the unique behaviors of a metro network with passengers flowing in it. The proposed method was applied on Beijing Subway. Firstly, the passenger volume in terms of daily origin and destination matrix was extracted from exhausted transit smart card data. Using the established approach and the matrix as weighting, common indicators of complex network including clustering coefficient, betweenness and degree were calculated, and network robustness were evaluated under potential attacks. The results were further compared to that of unweighted networks, and it suggests indicators of the network with consideration of passenger volumes differ from that without ridership to some extent, and networks tend to be more vulnerable than that without load on it. The significance sequence for the stations can be changed. By introducing passenger flow weighting, actual operation status of the network can be reflected more accurately. It is beneficial to determine the crucial stations and make precautionary measures for the entire network’s operation security.

scholarly journals Space‒Time Evolution Analysis of the Nanjing Metro Network Based on a Complex Network

2019 ◽  
Vol 11 (2) ◽  
pp. 523 ◽  
Author(s):  
Wei Yu ◽  
Jun Chen ◽  
Xingchen Yan
Keyword(s):  
Time Evolution ◽  
Complex Network ◽  
Space Time ◽  
Clustering Coefficient ◽  
Terminal Point ◽  
Node Degree ◽  
Traffic Pattern ◽  
Starting Point ◽  
Space Time Evolution ◽  
Metro Network

Many cities in China have opened a subway, which has become an important part of urban public transport. How the metro line forms the metro network, and then changes the urban traffic pattern, is a problem worthy of attention. From 2005 to 2018, 10 metro lines were opened in Nanjing, which provides important reference data for the study of the spatial and temporal evolution of the Metro network. In this study, using the complex network method, according to the opening sequence of 10 metro lines in Nanjing, space L and space P models are established, respectively. In view of the evolution of metro network parameters, four parameters—network density, network centrality, network clustering coefficient, and network average distance—are proposed for evaluation. In view of the spatial structure change of the metro network, this study combines the concept of node degree in a complex network, analyzes the starting point, terminal point, and intersection point of metro line, and puts forward the concepts of star structure and ring structure. The analysis of the space‒time evolution of Nanjing metro network shows that with the gradual opening of metro lines, the metro network presents a more complex structure; the line connection tends to important nodes, and gradually outlines the city’s commercial space pattern.

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