Random planar graphs and the London street network
Interdisciplinary Physics
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Abstract
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.
PACS
89.75.-k Complex systems 89.75.Da Systems obeying scaling laws 89.65.Lm Urban planning and constructionPreview
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References
- 1.M. Batty, Cities and Complexity (The MIT Press, Cambridge, Massachussets, 2005)Google Scholar
- 2.G.K. Zipf, Human Behaviour and the Principle of Least Effort (Addison-Wesley Press, 1949)Google Scholar
- 3.M. Batty, P. Longley, Fractal cities (Academic Press, London and San Diego, 1996)Google Scholar
- 4.P. Blanchard, D. Volchenkov, Mathematical Analysis of Urban Spatial Networks (Springer Verlag Berlin, Heidelberg, 2009)zbMATHGoogle Scholar
- 5.K.J. Kansky, Structure of transportation networks (University of Chicago, Chicago, 1963)Google Scholar
- 6.B. Jiang, C. Claramunt, Environ. Plann. B 31, 151 (2004)CrossRefGoogle Scholar
- 7.L. Euler, Comm. Acad. Sci. I. Petropol. 8, 128 (1736)Google Scholar
- 8.A.P. Masucci, G.J. Rodgers, Phys. A 387, 3781 (2008)CrossRefGoogle Scholar
- 9.V. Colizza, A. Vespignani, Phys. Rev. Lett. 99, 148701 (2007)CrossRefADSGoogle Scholar
- 10.A. Wilson, J.R. Soc. Interface 5, 865 (2008)CrossRefGoogle Scholar
- 11.S. Porta, P. Crucitti, V. Latora, Phys. A 369, 853 (2006)CrossRefGoogle Scholar
- 12.A.L. Barabási, R. Albert, H. Jeong, Phys. A 272, 173 (1999)CrossRefGoogle Scholar
- 13.R. Diestel, Graph Theory (Springer-Verlag Heidelberg, New York, 2005)zbMATHGoogle Scholar
- 14.M. Rosvall, A. Trusina, P. Minnaghen, K. Sneppen, Phys. Rev. Lett. 94, 028701 (2005)CrossRefADSGoogle Scholar
- 15.J. Simmie, Planning London (UCL Press, London, UK, 1994)Google Scholar
- 16.M. Barthélemy, A. Flammini, Phys. Rev. Lett. 100, 138702 (2008)CrossRefADSGoogle Scholar
- 17.S. Gerke, C. McDiarmid, Comb. Probab. Comput. 13, 165 (2004)zbMATHCrossRefMathSciNetGoogle Scholar
- 18.R. Bruegmann, Sprawl: a compact history (University of Chicago Press, Illinois, 2005)Google Scholar
- 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.A.P. Masucci, G.J. Rodgers, Adv. in Compl. Syst. 12, 113 (2009)zbMATHCrossRefMathSciNetGoogle Scholar
- 21.M.A. Serrano, M. Boguñá, R. Pastor-Satorras, Phys. Rev. E 74, 055101 (2006)CrossRefADSGoogle Scholar
- 22.S. Lämmer, B. Gehlsen, D. Helbing, Phys. A 363, 89 (2006)CrossRefGoogle Scholar
- 23.L. Figueiredo, L. Amorim, 6th International Space Syntax (Istanbul, Turkey, 2007)Google Scholar
- 24.D.J. Watts, S.H. Strogatz, Nature 393, 440 (1998)CrossRefADSGoogle Scholar
- 25.V. Kalapala, V. Sanwalani, A. Clauset, C. Moore, Phys. Rev. E 73, 026130 (2006)CrossRefADSGoogle Scholar
- 26.M. Boguñá, R. Pastor-Satorras, A. Vespignani, Eur. Phys. J. B 38, 205 (2004)CrossRefADSGoogle Scholar
- 27.L.C. Freeman, Social Networks 1, 215 (1979)CrossRefGoogle Scholar
- 28.M. Batty, Envir. and Plann. B 6, 191 (2009)CrossRefGoogle Scholar
- 29.
- 30.
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