Application of centrality metrics for finding critical nodes and assessing their impact on the transport network
https://doi.org/10.52170/1815-9265_2025_75_42
Abstract
This study introduces a methodology for identifying critical nodes within the metropolitan transport network by employing a composite metric that integrates multiple measures of graph centrality. The primary objective is to determine the most significant elements of urban transport infrastructure and to evaluate their impact on the overall resilience of the system under disruptive conditions. The road network graph was constructed using the OSMnx library and OpenStreetMap data, filtered to include only automobile roads, which ensured an accurate representation of the city’s street network.
The analysis is based on several classical centrality indicators, including betweenness centrality, degree centrality, closeness centrality, harmonic centrality, and load centrality. All measures were normalized to a common scale to enable comparability. A composite centrality metric was then proposed, defined as the mean of the normalized values, which provides an integrated assessment of both the topological and functional properties of network nodes.
To validate the proposed approach, simulation experiments were conducted, incorporating scenarios of edge weight increase to emulate traffic congestion as well as the complete removal of selected nodes. The findings demonstrate that betweenness centrality remains the most influential factor in identifying critical nodes; however, the composite metric yields a more balanced and robust evaluation. Moreover, the removal of critical nodes was shown to significantly increase the average shortest path length, thereby highlighting the vulnerability of the transport system and underscoring the necessity of prioritizing these elements in urban planning, infrastructure development, and resilience strategies.
About the Author
M. A. Bekov
Siberian Transport University
Russian Federation
Russian Federation
Mikhail A. Bekov – Postgraduate Student of the Information Technologies in Transport Department
Novosibirsk
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For citations:
Bekov M.A. Application of centrality metrics for finding critical nodes and assessing their impact on the transport network. Bulletin of Siberian State University of Transport. 2025;(3):42-52. (In Russ.) https://doi.org/10.52170/1815-9265_2025_75_42
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