The European Physical Journal B

, Volume 71, Issue 2, pp 259–271 | Cite as

Random planar graphs and the London street network

  • A. P. MasucciEmail author
  • D. Smith
  • A. Crooks
  • M. Batty
Interdisciplinary Physics


In this paper we analyse the street network of London both in its primary and dual representation. To understand its properties, we consider three idealised models based on a grid, a static random planar graph and a growing random planar graph. Comparing the models and the street network, we find that the streets of London form a self-organising system whose growth is characterised by a strict interaction between the metrical and informational space. In particular, a principle of least effort appears to create a balance between the physical and the mental effort required to navigate the city.


89.75.-k Complex systems 89.75.Da Systems obeying scaling laws 89.65.Lm Urban planning and construction 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    M. Batty, Cities and Complexity (The MIT Press, Cambridge, Massachussets, 2005)Google Scholar
  2. 2.
    G.K. Zipf, Human Behaviour and the Principle of Least Effort (Addison-Wesley Press, 1949)Google Scholar
  3. 3.
    M. Batty, P. Longley, Fractal cities (Academic Press, London and San Diego, 1996)Google Scholar
  4. 4.
    P. Blanchard, D. Volchenkov, Mathematical Analysis of Urban Spatial Networks (Springer Verlag Berlin, Heidelberg, 2009)zbMATHGoogle Scholar
  5. 5.
    K.J. Kansky, Structure of transportation networks (University of Chicago, Chicago, 1963)Google Scholar
  6. 6.
    B. Jiang, C. Claramunt, Environ. Plann. B 31, 151 (2004)CrossRefGoogle Scholar
  7. 7.
    L. Euler, Comm. Acad. Sci. I. Petropol. 8, 128 (1736)Google Scholar
  8. 8.
    A.P. Masucci, G.J. Rodgers, Phys. A 387, 3781 (2008)CrossRefGoogle Scholar
  9. 9.
    V. Colizza, A. Vespignani, Phys. Rev. Lett. 99, 148701 (2007)CrossRefADSGoogle Scholar
  10. 10.
    A. Wilson, J.R. Soc. Interface 5, 865 (2008)CrossRefGoogle Scholar
  11. 11.
    S. Porta, P. Crucitti, V. Latora, Phys. A 369, 853 (2006)CrossRefGoogle Scholar
  12. 12.
    A.L. Barabási, R. Albert, H. Jeong, Phys. A 272, 173 (1999)CrossRefGoogle Scholar
  13. 13.
    R. Diestel, Graph Theory (Springer-Verlag Heidelberg, New York, 2005)zbMATHGoogle Scholar
  14. 14.
    M. Rosvall, A. Trusina, P. Minnaghen, K. Sneppen, Phys. Rev. Lett. 94, 028701 (2005)CrossRefADSGoogle Scholar
  15. 15.
    J. Simmie, Planning London (UCL Press, London, UK, 1994)Google Scholar
  16. 16.
    M. Barthélemy, A. Flammini, Phys. Rev. Lett. 100, 138702 (2008)CrossRefADSGoogle Scholar
  17. 17.
    S. Gerke, C. McDiarmid, Comb. Probab. Comput. 13, 165 (2004)zbMATHCrossRefMathSciNetGoogle Scholar
  18. 18.
    R. Bruegmann, Sprawl: a compact history (University of Chicago Press, Illinois, 2005)Google Scholar
  19. 19.
    J. Buhl, J. Gautrais, N. Reeves, R.V. Solé, S. Valverde, P. Kuntz, G. Theraulaz, Eur. Phys. J. B 49, 513 (2006)CrossRefADSGoogle Scholar
  20. 20.
    A.P. Masucci, G.J. Rodgers, Adv. in Compl. Syst. 12, 113 (2009)zbMATHCrossRefMathSciNetGoogle Scholar
  21. 21.
    M.A. Serrano, M. Boguñá, R. Pastor-Satorras, Phys. Rev. E 74, 055101 (2006)CrossRefADSGoogle Scholar
  22. 22.
    S. Lämmer, B. Gehlsen, D. Helbing, Phys. A 363, 89 (2006)CrossRefGoogle Scholar
  23. 23.
    L. Figueiredo, L. Amorim, 6th International Space Syntax (Istanbul, Turkey, 2007)Google Scholar
  24. 24.
    D.J. Watts, S.H. Strogatz, Nature 393, 440 (1998)CrossRefADSGoogle Scholar
  25. 25.
    V. Kalapala, V. Sanwalani, A. Clauset, C. Moore, Phys. Rev. E 73, 026130 (2006)CrossRefADSGoogle Scholar
  26. 26.
    M. Boguñá, R. Pastor-Satorras, A. Vespignani, Eur. Phys. J. B 38, 205 (2004)CrossRefADSGoogle Scholar
  27. 27.
    L.C. Freeman, Social Networks 1, 215 (1979)CrossRefGoogle Scholar
  28. 28.
    M. Batty, Envir. and Plann. B 6, 191 (2009)CrossRefGoogle Scholar
  29. 29.
  30. 30.

Copyright information

© EDP Sciences, SIF, Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  1. 1.Centre for Advanced Spatial Analysis, University College LondonLondonUK

Personalised recommendations