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Road traffic: A case study of flow and path-dependency in weighted directed networks

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  • Bono, Flavio
  • Gutiérrez, Eugenio
  • Poljansek, Karmen

Abstract

How much can we tell about flows through networks just from their topological properties? Whereas flow distributions of river basins, trees or cardiovascular systems come naturally to mind, more complex topologies are not so immediate, especially if the network is large and heterogeneously directed. Our study is motivated by the question of how the distribution of path-dependent trails in directed networks is correlated to the distribution of network flows. As an example we have studied the path-dependencies in closed trails in four metropolitan areas in England and the USA and computed their global and spatial correlations with measured traffic flows. We have found that the heterogeneous distribution of traffic intensity is mirrored by the distribution of agglomerate path-dependency and that high traffic roads are packed along corridors at short-to-medium trail lengths from the ensemble of nodes.

Suggested Citation

  • Bono, Flavio & Gutiérrez, Eugenio & Poljansek, Karmen, 2010. "Road traffic: A case study of flow and path-dependency in weighted directed networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5287-5297.
    • Handle: RePEc:eee:phsmap:v:389:y:2010:i:22:p:5287-5297
    DOI: 10.1016/j.physa.2010.06.058
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    Cited by:

    1. Johan Rose Santos & Nur Diana Safitri & Maya Safira & Varun Varghese & Makoto Chikaraishi, 2021. "Road network vulnerability and city-level characteristics: A nationwide comparative analysis of Japanese cities," Environment and Planning B, , vol. 48(5), pages 1091-1107, June.
    2. Bono, Flavio & Gutiérrez, Eugenio, 2011. "A network-based analysis of the impact of structural damage on urban accessibility following a disaster: the case of the seismically damaged Port Au Prince and Carrefour urban road networks," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1443-1455.
    3. Zhou, Jin & Xu, Weixiang & Guo, Xin & Ding, Jing, 2015. "A method for modeling and analysis of directed weighted accident causation network (DWACN)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 263-277.

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