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Scaling in Transportation Networks

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  • Rémi Louf
  • Camille Roth
  • Marc Barthelemy

Abstract

Subway systems span most large cities, and railway networks most countries in the world. These networks are fundamental in the development of countries and their cities, and it is therefore crucial to understand their formation and evolution. However, if the topological properties of these networks are fairly well understood, how they relate to population and socio-economical properties remains an open question. We propose here a general coarse-grained approach, based on a cost-benefit analysis that accounts for the scaling properties of the main quantities characterizing these systems (the number of stations, the total length, and the ridership) with the substrate's population, area and wealth. More precisely, we show that the length, number of stations and ridership of subways and rail networks can be estimated knowing the area, population and wealth of the underlying region. These predictions are in good agreement with data gathered for about subway systems and more than railway networks in the world. We also show that train networks and subway systems can be described within the same framework, but with a fundamental difference: while the interstation distance seems to be constant and determined by the typical walking distance for subways, the interstation distance for railways scales with the number of stations.

Suggested Citation

  • Rémi Louf & Camille Roth & Marc Barthelemy, 2014. "Scaling in Transportation Networks," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-8, July.
  • Handle: RePEc:plo:pone00:0102007
    DOI: 10.1371/journal.pone.0102007
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    References listed on IDEAS

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    Cited by:

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    3. Luiz G A Alves & Renio S Mendes & Ervin K Lenzi & Haroldo V Ribeiro, 2015. "Scale-Adjusted Metrics for Predicting the Evolution of Urban Indicators and Quantifying the Performance of Cities," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-17, September.
    4. Luce Prignano & Lluc Font-Pomarol & Ignacio Morer & Sergi Lozano, 2023. "Infrastructures connecting people: A mechanistic model for terrestrial transportation networks," Environment and Planning B, , vol. 50(8), pages 2254-2272, October.
    5. Tasnuva Mahjabin & Susana Garcia & Caitlin Grady & Alfonso Mejia, 2018. "Large cities get more for less: Water footprint efficiency across the US," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-17, August.
    6. Joao Meirelles & Camilo Rodrigues Neto & Fernando Fagundes Ferreira & Fabiano Lemes Ribeiro & Claudia Rebeca Binder, 2018. "Evolution of urban scaling: Evidence from Brazil," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-15, October.
    7. Michael Mc Gettrick, 2020. "The role of city geometry in determining the utility of a small urban light rail/tram system," Public Transport, Springer, vol. 12(1), pages 233-259, March.
    8. Slavko, Bohdan & Glavatskiy, Kirill S. & Prokopenko, Mikhail, 2021. "Revealing configurational attractors in the evolution of modern Australian and US cities," Chaos, Solitons & Fractals, Elsevier, vol. 148(C).
    9. De Bona, Anderson Andrei & de Oliveira Rosa, Marcelo & Ono Fonseca, Keiko Verônica & Lüders, Ricardo, 2021. "A reduced model for complex network analysis of public transportation systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    10. Oded Cats & Rafal Kucharski & Santosh Rao Danda & Menno Yap, 2022. "Beyond the dichotomy: How ride-hailing competes with and complements public transport," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-17, January.

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