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A method of examining the structure and topological properties of public-transport networks

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  • Dimitrov, Stavri Dimitri
  • Ceder, Avishai (Avi)

Abstract

This work presents a new method of examining the structure of public-transport networks (PTNs) and analyzes their topological properties through a combination of computer programming, statistical data and large-network analyses. In order to automate the extraction, processing and exporting of data, a software program was developed allowing to extract the needed data from General Transit Feed Specification, thus overcoming difficulties occurring in accessing and collecting data. The proposed method was applied to a real-life PTN in Auckland, New Zealand, with the purpose of examining whether it showed characteristics of scale-free networks and exhibited features of “small-world” networks. As a result, new regression equations were derived analytically describing observed, strong, non-linear relationships among the probabilities of randomly chosen stops in the PTN to be serviced by a given number of routes. The established dependence is best fitted by an exponential rather than a power-law function, showing that the PTN examined is neither random nor scale-free, but a mixture of the two. This finding explains the presence of hubs that are not typical of exponential networks and simultaneously not highly connected to the other nodes as is the case with scale-free networks. On the other hand, the observed values of the topological properties of the network show that although it is highly clustered, owing to its representation as a directed graph, it differs slightly from “small-world” networks, which are characterized by strong clustering and a short average path length.

Suggested Citation

  • Dimitrov, Stavri Dimitri & Ceder, Avishai (Avi), 2016. "A method of examining the structure and topological properties of public-transport networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 373-387.
    • Handle: RePEc:eee:phsmap:v:451:y:2016:i:c:p:373-387
    DOI: 10.1016/j.physa.2016.01.060
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    References listed on IDEAS

    as
    1. Hadas, Yuval, 2013. "Assessing public transport systems connectivity based on Google Transit data," Journal of Transport Geography, Elsevier, vol. 33(C), pages 105-116.
    2. Chen, Yong-Zhou & Li, Nan & He, Da-Ren, 2007. "A study on some urban bus transport networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 747-754.
    3. Sybil Derrible & Christopher Kennedy, 2010. "Characterizing metro networks: state, form, and structure," Transportation, Springer, vol. 37(2), pages 275-297, March.
    4. C. von Ferber & T. Holovatch & Yu. Holovatch & V. Palchykov, 2009. "Public transport networks: empirical analysis and modeling," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 68(2), pages 261-275, March.
    5. Jingyi Lin & Yifang Ban, 2013. "Complex Network Topology of Transportation Systems," Transport Reviews, Taylor & Francis Journals, vol. 33(6), pages 658-685, November.
    6. Mishra, Sabyasachee & Welch, Timothy F. & Jha, Manoj K., 2012. "Performance indicators for public transit connectivity in multi-modal transportation networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(7), pages 1066-1085.
    7. Latora, Vito & Marchiori, Massimo, 2002. "Is the Boston subway a small-world network?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 314(1), pages 109-113.
    8. Xu, Xinping & Hu, Junhui & Liu, Feng & Liu, Lianshou, 2007. "Scaling and correlations in three bus-transport networks of China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 374(1), pages 441-448.
    9. Hadas, Yuval & Ranjitkar, Prakash, 2012. "Modeling public-transit connectivity with spatial quality-of-transfer measurements," Journal of Transport Geography, Elsevier, vol. 22(C), pages 137-147.
    10. Seaton, Katherine A. & Hackett, Lisa M., 2004. "Stations, trains and small-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(3), pages 635-644.
    11. Chung-Yuan Huang & Chuen-Tsai Sun & Hsun-Cheng Lin, 2005. "Influence of Local Information on Social Simulations in Small-World Network Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 8(4), pages 1-8.
    12. Sybil Derrible & Christopher Kennedy, 2011. "Applications of Graph Theory and Network Science to Transit Network Design," Transport Reviews, Taylor & Francis Journals, vol. 31(4), pages 495-519.
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