Identification of critical stations in a Metro System: A substitute complex network analysis

Kopsidas, Athanasios; Κεπαπτσόγλου, Κωνσταντίνος

doi:10.1016/j.physa.2022.127123

Cited by 33 publications

(15 citation statements)

References 39 publications

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“…The graph of the metro network G is an unweighted, directed, L-space representation of the metro infrastructure, with stations as nodes, and connections between any two consecutive stations of the same line as edges. The graph of the substitute network G s , as de ned by Kopsidas & Kepaptsoglou (2022), is a weighted, directed P-space representation of the alternative options (usually bus routes) connecting any two metro stations outside the metro system. The nodes of the substitute network also correspond to stations, while the edges are alternative public transport travel options between them, weighted by their performance in terms of time.…”

Section: Overviewmentioning

confidence: 99%

Exploring the association between network centralities and passenger flows in metro systems

Kopsidas

Douvaras

Κεπαπτσόγλου

2023

Preprint

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Network science offers valuable tools for planning and managing public transportation systems, with measures such as network centralities proposed as complementary predictors of ridership. This paper explores the relationship between different cases of passenger flows at metro stations and network centralities of both metro and alternative public transport (substitute) networks; such an association can be useful for managing metro system operations when disruptions occur. For that purpose, linear regression and non-parametric machine learning models are developed and compared. The Athens metro system is used as testbed for developing the proposed methodology. The findings of this study can be used for deriving medium-term ridership estimates in cases of metro disruptions, as the proposed methodology can support contingency plans for both platform and rail track disruptions.

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Section: Overviewmentioning

confidence: 99%

Exploring the association between network centralities and passenger flows in metro systems

Kopsidas

Douvaras

Κεπαπτσόγλου

2023

Preprint

Self Cite

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“…Its low construction cost, low construction difficulty and high safety factor can greatly improve the utilization rate of road space while alleviating urban congestion. By the end of 2021, 36 tram lines have been opened in 20 cities in China, and trams have become an important support for urban rail transit [1] .…”

Section: Introductionmentioning

confidence: 99%

Explore the collision safety of tram and passenger vehicle under disparate right of way

Guo

Liu

Xiao

et al. 2023

Sixth International Conference on Traffic Engineering and Transportation System (ICTETS 2022)

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Unlike traditional railway vehicles, the particularity of tram right of way determines the multiple and diversity of its accident forms. Based on the analysis of accident data at home and abroad, this paper determines the three road right management modes with the highest accident rate. On this basis, three collision scenarios are designed between a threemodule 100% low-floor tram and various types of passenger vehicles. In this paper, we innovatively use PC-Crash crash simulation combined with SPSS quantitative analysis to study the accident characteristics of tram and passenger vehicle collisions under disparate right of way. The results show that the occupant's living space is smaller in 45° side impact under the semi-independent right of way. Under the mixed right of way, when the tram is used as a rear-end vehicle, the collision interface force is more intense. At the same collision speed, the displacement of the vehicle body and the invasion of the living space will be larger under the mixed right of way. Finally, based on the simulation results and causal analysis method, an accurate and highly flexible accident cause analysis framework is formed. From the aspects of single influence and comprehensive influence, the factors affecting the safety of tram operation under diverse road right management modes are analyzed, and tailored suggestions are given to improve the safety of the track system.

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“…Some scholars proposed that the topology of public transportation is a complex network [7] . At present, research on the vulnerability of metro networks has focused on structural and functional vulnerability of the networks [8] . The former assesses the network vulnerability by analyzing the topological characteristics of the physical network.…”

Section: Introductionmentioning

confidence: 99%

Vulnerability analysis of weighted metro networks considering station traffic: the case of Shenzhen

Long

Liu

Zheng

et al. 2023

Sixth International Conference on Traffic Engineering and Transportation System (ICTETS 2022)

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Due to the large number of passengers served by the metro, with its extensive served area, as well as the interconnection of different stations within the metro system, there is a high possibility that a large number of city residents' trips will be delayed or forced to be canceled and cause economic losses, once a safety accident occurs in the subway system. An easy-to-practice and highly flexible evaluation framework are proposed to explore the identification of vulnerable nodes in a weighted metro network, considering network connectivity and node traffic. The degree distribution of the passenger flow weighted network obeys the power law distribution. The relationship between node connectivity, node passenger flow, and key players in the network are also discussed. We simulated network node failures under four scenarios to assess the impact of node failures on network accessibility and the number of passengers served. The network is robust when the nodes fail randomly; the network is vulnerable to deliberate attacks based on topological node characteristics. The strategies that have the most significant impact on site traffic are node weight-based attack and node weighted-degree-based attack, with the weighted-degree-based attack being more disruptive to network connectivity and the best performing strategy in aggregate. Furthermore, we have identified the top 10 nodes in the Shenzhen Metro network that are more influential to passengers and disruptive to the network structure, which could provide a reference for metro emergency management.

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Identification of critical stations in a Metro System: A substitute complex network analysis

Cited by 33 publications

References 39 publications

Exploring the association between network centralities and passenger flows in metro systems

Exploring the association between network centralities and passenger flows in metro systems

Explore the collision safety of tram and passenger vehicle under disparate right of way

Vulnerability analysis of weighted metro networks considering station traffic: the case of Shenzhen

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