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Fitting Planar Proximity Graphs on Real Street Networks

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Proceedings of ECCS 2014

Part of the book series: Springer Proceedings in Complexity ((SPCOM))

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Abstract

Due to the rising progress of sustainable urban infrastructures, modeling realistic street networks is a fundamental challenge. This study contributes to this modeling direction, by suggesting the utilization of planar proximity graphs, and specifically the \(\beta \)-skeleton graphs. Their goodness of fit on producing real-like urban street networks is verified by comparison to real data. In particular, the basic topological and geometrical properties derived from synthetic \(\beta \)-skeleton planar graphs are compared to the properties of five urban street network datasets, all represented using the Primal approach. A good agreement with empirical patterns is found and a possible explanation is discussed.

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Notes

  1. 1.

    In the samples where the entire set of these properties is not available, only the available properties are kept.

  2. 2.

    It should be noted that the normalized cost is not a measure of construction cost, but only an index of how long the wiring of the graph is, compared to the respective extreme planar graphs (MST and DT).

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Authors and Affiliations

  1. Department of Informatics and Telecommunications, University of Athens, Athens, Greece

    Dimitris Maniadakis & Dimitris Varoutas

Authors
  1. Dimitris Maniadakis
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  2. Dimitris Varoutas
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Corresponding author

Correspondence to Dimitris Maniadakis .

Editor information

Editors and Affiliations

  1. RAF, University of Zürich, Zürich, Switzerland

    Stefano Battiston

  2. CREATE-NET, Trento, Italy

    Francesco De Pellegrini

  3. IMT Lucca, Lucca, Italy

    Guido Caldarelli

  4. School of Science and Technology, University of Camerino, Camerino, Italy

    Emanuela Merelli

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Maniadakis, D., Varoutas, D. (2016). Fitting Planar Proximity Graphs on Real Street Networks. In: Battiston, S., De Pellegrini, F., Caldarelli, G., Merelli, E. (eds) Proceedings of ECCS 2014. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-319-29228-1_2

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