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Human Mobility in a Continuum Approach

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  • Filippo Simini
  • Amos Maritan
  • Zoltán Néda

Abstract

Human mobility is investigated using a continuum approach that allows to calculate the probability to observe a trip to any arbitrary region, and the fluxes between any two regions. The considered description offers a general and unified framework, in which previously proposed mobility models like the gravity model, the intervening opportunities model, and the recently introduced radiation model are naturally resulting as special cases. A new form of radiation model is derived and its validity is investigated using observational data offered by commuting trips obtained from the United States census data set, and the mobility fluxes extracted from mobile phone data collected in a western European country. The new modeling paradigm offered by this description suggests that the complex topological features observed in large mobility and transportation networks may be the result of a simple stochastic process taking place on an inhomogeneous landscape.

Suggested Citation

  • Filippo Simini & Amos Maritan & Zoltán Néda, 2013. "Human Mobility in a Continuum Approach," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-8, March.
    • Handle: RePEc:plo:pone00:0060069
    DOI: 10.1371/journal.pone.0060069
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    References listed on IDEAS

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    Cited by:

    1. Inho Hong & Woo-Sung Jung & Hang-Hyun Jo, 2019. "Gravity model explained by the radiation model on a population landscape," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-13, June.
    2. Jiao, Junfeng & Azimian, Amin, 2021. "Measuring accessibility to grocery stores using radiation model and survival analysis," Journal of Transport Geography, Elsevier, vol. 94(C).
    3. Yuqi Chen & Zongyao Sun & Liangwa Cai, 2021. "Population Flow Mechanism Study of Beijing-Tianjin-Hebei Urban Agglomeration from Industrial Space Supply Perspective," Sustainability, MDPI, vol. 13(17), pages 1-15, September.
    4. Johari, F. & Peronato, G. & Sadeghian, P. & Zhao, X. & Widén, J., 2020. "Urban building energy modeling: State of the art and future prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 128(C).
    5. Lin Li & Lei Yang & Haihong Zhu & Rongrong Dai, 2015. "Explorative Analysis of Wuhan Intra-Urban Human Mobility Using Social Media Check-In Data," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-19, August.
    6. Huang, Feihu & Qiao, Shaojie & Peng, Jian & Guo, Bing & Xiong, Xi & Han, Nan, 2019. "A movement model for air passengers based on trip purpose," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 798-808.
    7. Lenormand, Maxime & Bassolas, Aleix & Ramasco, José J., 2016. "Systematic comparison of trip distribution laws and models," Journal of Transport Geography, Elsevier, vol. 51(C), pages 158-169.
    8. Chen, Ya & Li, Xue & Zhang, Richong & Huang, Zi-Gang & Lai, Ying-Cheng, 2020. "Instantaneous success and influence promotion in cyberspace — how do they occur?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    9. Varga, Levente & Tóth, Géza & Néda, Zoltán, 2017. "An improved radiation model and its applicability for understanding commuting patterns in Hungary," MPRA Paper 76806, University Library of Munich, Germany.
    10. Yong Wang & Xiaolei Ma & Yong Liu & Ke Gong & Kristian C Henricakson & Maozeng Xu & Yinhai Wang, 2016. "A Two-Stage Algorithm for Origin-Destination Matrices Estimation Considering Dynamic Dispersion Parameter for Route Choice," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-24, January.

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