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Network Centrality of Metro Systems

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  • Sybil Derrible

Abstract

Whilst being hailed as the remedy to the world’s ills, cities will need to adapt in the 21st century. In particular, the role of public transport is likely to increase significantly, and new methods and technics to better plan transit systems are in dire need. This paper examines one fundamental aspect of transit: network centrality. By applying the notion of betweenness centrality to 28 worldwide metro systems, the main goal of this paper is to study the emergence of global trends in the evolution of centrality with network size and examine several individual systems in more detail. Betweenness was notably found to consistently become more evenly distributed with size (i.e. no “winner takes all”) unlike other complex network properties. Two distinct regimes were also observed that are representative of their structure. Moreover, the share of betweenness was found to decrease in a power law with size (with exponent 1 for the average node), but the share of most central nodes decreases much slower than least central nodes (0.87 vs. 2.48). Finally the betweenness of individual stations in several systems were examined, which can be useful to locate stations where passengers can be redistributed to relieve pressure from overcrowded stations. Overall, this study offers significant insights that can help planners in their task to design the systems of tomorrow, and similar undertakings can easily be imagined to other urban infrastructure systems (e.g., electricity grid, water/wastewater system, etc.) to develop more sustainable cities.

Suggested Citation

  • Sybil Derrible, 2012. "Network Centrality of Metro Systems," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-10, July.
    • Handle: RePEc:plo:pone00:0040575
    DOI: 10.1371/journal.pone.0040575
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    1. Parthasarathi, Pavithra & Levinson, David, 2018. "Network structure and the journey to work: An intra-metropolitan analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 292-304.
    2. Huang, Jie & Levinson, David M., 2015. "Circuity in urban transit networks," Journal of Transport Geography, Elsevier, vol. 48(C), pages 145-153.
    3. Sadayuki, Taisuke, 2018. "Measuring the spatial effect of multiple sites: An application to housing rent and public transportation in Tokyo, Japan," Regional Science and Urban Economics, Elsevier, vol. 70(C), pages 155-173.
    4. Mohammad Zaher Serdar & Sami G. Al-Ghamdi, 2021. "Resiliency Assessment of Road Networks during Mega Sport Events: The Case of FIFA World Cup Qatar 2022," Sustainability, MDPI, vol. 13(22), pages 1-15, November.
    5. David Giacomin & Luke James & David Levinson, 2012. "Trends in Metropolitan Network Circuity," Working Papers 000106, University of Minnesota: Nexus Research Group.
    6. Rui Ding & Norsidah Ujang & Hussain Bin Hamid & Mohd Shahrudin Abd Manan & Rong Li & Safwan Subhi Mousa Albadareen & Ashkan Nochian & Jianjun Wu, 2019. "Application of Complex Networks Theory in Urban Traffic Network Researches," Networks and Spatial Economics, Springer, vol. 19(4), pages 1281-1317, December.
    7. Wang, Xiangrong & Koç, Yakup & Derrible, Sybil & Ahmad, Sk Nasir & Pino, Willem J.A. & Kooij, Robert E., 2017. "Multi-criteria robustness analysis of metro networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 19-31.
    8. Jia Hou Chin & Kuru Ratnavelu, 2016. "Detecting Community Structure by Using a Constrained Label Propagation Algorithm," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-21, May.
    9. Hyun Kim & Yena Song, 2018. "An integrated measure of accessibility and reliability of mass transit systems," Transportation, Springer, vol. 45(4), pages 1075-1100, July.
    10. Suchat Tachaudomdach & Auttawit Upayokin & Nopadon Kronprasert & Kriangkrai Arunotayanun, 2021. "Quantifying Road-Network Robustness toward Flood-Resilient Transportation Systems," Sustainability, MDPI, vol. 13(6), pages 1-16, March.
    11. Kermanshah, A. & Derrible, S., 2016. "A geographical and multi-criteria vulnerability assessment of transportation networks against extreme earthquakes," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 39-49.
    12. Cats, Oded, 2017. "Topological evolution of a metropolitan rail transport network: The case of Stockholm," Journal of Transport Geography, Elsevier, vol. 62(C), pages 172-183.
    13. Li, Peilin & Zhao, Pengjun & Schwanen, Tim, 2020. "Effect of land use on shopping trips in station areas: Examining sensitivity to scale," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 969-985.
    14. Jungyeol Hong & Reuben Tamakloe & Soobeom Lee & Dongjoo Park, 2019. "Exploring the Topological Characteristics of Complex Public Transportation Networks: Focus on Variations in Both Single and Integrated Systems in the Seoul Metropolitan Area," Sustainability, MDPI, vol. 11(19), pages 1-26, September.
    15. Luo, Ding & Cats, Oded & van Lint, Hans & Currie, Graham, 2019. "Integrating network science and public transport accessibility analysis for comparative assessment," Journal of Transport Geography, Elsevier, vol. 80(C).
    16. Elisa Frutos Bernal & Angel Martín del Rey, 2019. "Study of the Structural and Robustness Characteristics of Madrid Metro Network," Sustainability, MDPI, vol. 11(12), pages 1-24, June.
    17. Jiangang Shi & Shiping Wen & Xianbo Zhao & Guangdong Wu, 2019. "Sustainable Development of Urban Rail Transit Networks: A Vulnerability Perspective," Sustainability, MDPI, vol. 11(5), pages 1-24, March.
    18. Hu, Xinlei & Huang, Jie & Shi, Feng, 2019. "Circuity in China's high-speed-rail network," Journal of Transport Geography, Elsevier, vol. 80(C).
    19. Amirhassan Kermanshah & Sybil Derrible, 2017. "Robustness of road systems to extreme flooding: using elements of GIS, travel demand, and network science," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 86(1), pages 151-164, March.
    20. Zhang, Mengyao & Huang, Tao & Guo, Zhaoxia & He, Zhenggang, 2022. "Complex-network-based traffic network analysis and dynamics: A comprehensive review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).

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