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How congestion shapes cities: from mobility patterns to scaling.

Rémi Louf1, Marc Barthelemy1

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Urban growth models reveal power-law scalings for city indicators. Our stochastic theory explains these, showing congestion sensitivity dictates urban sustainability, particularly for traffic-dependent cities.

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Area of Science:

  • Urban studies
  • Complex systems
  • Network theory

Background:

  • Cities exhibit power-law scalings between population and socio-economic/structural indicators.
  • Recent data availability enables analysis of these urban scaling laws.

Purpose of the Study:

  • To propose a stochastic theory of urban growth.
  • To explain observed urban scaling laws related to population size.
  • To confirm theoretical predictions using empirical data from US and OECD cities.

Main Methods:

  • Development of a stochastic urban growth theory.
  • Analysis of urban scaling laws, including road network length, traffic delay, and CO2 emissions.
  • Empirical validation using data from US and OECD cities.

Main Results:

  • A single parameter, sensitivity to congestion, governs multiple urban indicators' dependence on population size.
  • Observed scalings for daily miles driven, road network length, traffic delay, gasoline consumption, and CO2 emissions are explained.
  • The relationship between urban area and population is also linked to congestion sensitivity.

Conclusions:

  • Diseconomies of congestion scale superlinearly with city population.
  • Cities heavily reliant on traffic-sensitive transportation modes are unsustainable, even with polycentric structures.
  • Congestion sensitivity is a key factor in determining urban sustainability.