On the perturbation of self-organized urban street networks

Jérôme G.M. Benoit, Saif Eddin G. Jabari

Research output: Contribution to journalArticle

Abstract

We investigate urban street networks as a whole within the frameworks of information physics and statistical physics. Urban street networks are envisaged as evolving social systems subject to a Boltzmann-mesoscopic entropy conservation. For self-organized urban street networks, our paradigm has already allowed us to recover the effectively observed scale-free distribution of roads and to foresee the distribution of junctions. The entropy conservation is interpreted as the conservation of the surprisal of the city-dwellers for their urban street network. In view to extend our investigations to other urban street networks, we consider to perturb our model for self-organized urban street networks by adding an external surprisal drift. We obtain the statistics for slightly drifted self-organized urban street networks. Besides being practical and manageable, this statistics separates the macroscopic evolution scale parameter from the mesoscopic social parameters. This opens the door to observational investigations on the universality of the evolution scale parameter. Ultimately, we argue that the strength of the external surprisal drift might be an indicator for the disengagement of the city-dwellers for their city.

Original languageEnglish (US)
Article number49
JournalApplied Network Science
Volume4
Issue number1
DOIs
StatePublished - Dec 1 2019

Keywords

  • Big data
  • City science
  • Entropic equilibrium
  • Information physics
  • Interdisciplinary physics
  • MaxEnt
  • Power law
  • Self-organizing networks
  • Statistical physics
  • Surprisal
  • Urban street networks
  • Wholeness

ASJC Scopus subject areas

  • General
  • Computer Networks and Communications
  • Computational Mathematics

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