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Navigation in large subway networks: An informational approach

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  • Barberillo, Josep
  • Saldaña, Joan

Abstract

The structural properties of the subway network are crucial in effective transportation in cities. This paper presents an information perspective of navigation in four different subway networks: New York City, Paris, Barcelona and Moscow. We addressed our study to investigate what is that makes it complicated to navigate in these kinds of networks and we carried out a comparison between them and their intrinsic constraints. Our methodological approach is based on a set of cost/efficiency indicators which are defined in the complex networks literature. We find that the overall complexity in finding stations measured by the average search information S linearly increases as a function of the network size N. The direct implication of this finding is that from these basic levels of required information, the average value H(k) can be represented as a function of the node degree k. Finally, through analyzing subway networks in space P, we reveal the existing service modularity among subway routes using a rescaled expression of S.

Suggested Citation

  • Barberillo, Josep & Saldaña, Joan, 2011. "Navigation in large subway networks: An informational approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 374-386.
    • Handle: RePEc:eee:phsmap:v:390:y:2011:i:2:p:374-386
    DOI: 10.1016/j.physa.2010.09.017
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    References listed on IDEAS

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    1. Dorogovtsev, S.N. & Mendes, J.F.F., 2003. "Evolution of Networks: From Biological Nets to the Internet and WWW," OUP Catalogue, Oxford University Press, number 9780198515906, Decembrie.
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    Cited by:

    1. Zhang, Jianhua & Song, Bo & Zhang, Zhaojun & Liu, Haikuan, 2014. "An approach for modeling vulnerability of the network of networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 412(C), pages 127-136.
    2. Du, Zhouyang & Tang, Jinjun & Qi, Yong & Wang, Yiwei & Han, Chunyang & Yang, Yifan, 2020. "Identifying critical nodes in metro network considering topological potential: A case study in Shenzhen city—China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    3. Zhang, Hui & Zhuge, Chengxiang & Yu, Xiaohua, 2018. "Identifying hub stations and important lines of bus networks: A case study in Xiamen, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 394-402.
    4. Zhang, Jianhua & Zhao, Mingwei & Liu, Haikuan & Xu, Xiaoming, 2013. "Networked characteristics of the urban rail transit networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1538-1546.
    5. Zhang, Jianhua & Wang, Shuliang & Wang, Xiaoyuan, 2018. "Comparison analysis on vulnerability of metro networks based on complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 72-78.
    6. Zhang, Jianhua & Xu, Xiaoming & Hong, Liu & Wang, Shuliang & Fei, Qi, 2011. "Networked analysis of the Shanghai subway network, in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4562-4570.
    7. Svetla STOILOVA & Veselin STOEV, 2015. "An application of the graph theory which examines the metro networks," Transport Problems, Silesian University of Technology, Faculty of Transport, vol. 10(2), pages 35-48, June.

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