IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v5y2014i1d10.1038_ncomms6347.html
   My bibliography  Save this article

Predicting commuter flows in spatial networks using a radiation model based on temporal ranges

Author

Listed:
  • Yihui Ren

    (University of Notre Dame)

  • Mária Ercsey-Ravasz

    (Faculty of Physics, Babes-Bolyai University)

  • Pu Wang

    (School of Traffic and Transportation Engineering, Central South University)

  • Marta C. González

    (Massachusetts Institute of Technology)

  • Zoltán Toroczkai

    (University of Notre Dame)

Abstract

Understanding network flows such as commuter traffic in large transportation networks is an ongoing challenge due to the complex nature of the transportation infrastructure and human mobility. Here we show a first-principles based method for traffic prediction using a cost-based generalization of the radiation model for human mobility, coupled with a cost-minimizing algorithm for efficient distribution of the mobility fluxes through the network. Using US census and highway traffic data, we show that traffic can efficiently and accurately be computed from a range-limited, network betweenness type calculation. The model based on travel time costs captures the log-normal distribution of the traffic and attains a high Pearson correlation coefficient (0.75) when compared with real traffic. Because of its principled nature, this method can inform many applications related to human mobility driven flows in spatial networks, ranging from transportation, through urban planning to mitigation of the effects of catastrophic events.

Suggested Citation

  • Yihui Ren & Mária Ercsey-Ravasz & Pu Wang & Marta C. González & Zoltán Toroczkai, 2014. "Predicting commuter flows in spatial networks using a radiation model based on temporal ranges," Nature Communications, Nature, vol. 5(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms6347
    DOI: 10.1038/ncomms6347
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/ncomms6347
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/ncomms6347?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jiao, Junfeng & Azimian, Amin, 2021. "Measuring accessibility to grocery stores using radiation model and survival analysis," Journal of Transport Geography, Elsevier, vol. 94(C).
    2. Dimitrios Tsiotas & Vassilis Tselios, 2023. "Dimension Reduction in the Topology of Multilayer Spatial Networks: The Case of the Interregional Commuting in Greece," Networks and Spatial Economics, Springer, vol. 23(1), pages 97-133, March.
    3. Angelo Furno & Nour-Eddin El Faouzi & Rajesh Sharma & Eugenio Zimeo, 2021. "Graph-based ahead monitoring of vulnerabilities in large dynamic transportation networks," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-35, March.
    4. Dimitrios Tsiotas & George Aspridis & Ioannis Gavardinas & Labros Sdrolias & Dagmar Škodová-Parmová, 2019. "Gravity modeling in social science: the case of the commuting phenomenon in Greece," Evolutionary and Institutional Economics Review, Springer, vol. 16(1), pages 139-158, June.
    5. Yang, Yitao & Jia, Bin & Yan, Xiao-Yong & Zhi, Danyue & Song, Dongdong & Chen, Yan & de Bok, Michiel & Tavasszy, Lóránt A. & Gao, Ziyou, 2023. "Uncovering and modeling the hierarchical organization of urban heavy truck flows," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    6. Vanni, Fabio, 2024. "A visit generation process for human mobility random graphs with location-specific latent-variables: From land use to travel demand," Chaos, Solitons & Fractals, Elsevier, vol. 185(C).
    7. Ma, Xiaolei & Liu, Congcong & Wen, Huimin & Wang, Yunpeng & Wu, Yao-Jan, 2017. "Understanding commuting patterns using transit smart card data," Journal of Transport Geography, Elsevier, vol. 58(C), pages 135-145.
    8. Chaogui Kang & Yu Liu & Diansheng Guo & Kun Qin, 2015. "A Generalized Radiation Model for Human Mobility: Spatial Scale, Searching Direction and Trip Constraint," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-11, November.
    9. He, Kun & Xu, Zhongzhi & Wang, Pu, 2015. "A hybrid routing model for mitigating congestion in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 431(C), pages 1-17.
    10. Mark He & Joseph Glasser & Nathaniel Pritchard & Shankar Bhamidi & Nikhil Kaza, 2020. "Demarcating geographic regions using community detection in commuting networks with significant self-loops," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-31, April.
    11. Chao Fan & Yang Yang & Ali Mostafavi, 2024. "Neural embeddings of urban big data reveal spatial structures in cities," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.
    12. Albert Solé-Ribalta & Sergio Gómez & Alex Arenas, 2018. "Decongestion of Urban Areas with Hotspot Pricing," Networks and Spatial Economics, Springer, vol. 18(1), pages 33-50, March.
    13. Fangzhou Li & Zhiming Feng & Peng Li & Zhen You, 2017. "Measuring directional urban spatial interaction in China: A migration perspective," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-19, January.
    14. Srinivasan Venkatramanan & Jiangzhuo Chen & Arindam Fadikar & Sandeep Gupta & Dave Higdon & Bryan Lewis & Madhav Marathe & Henning Mortveit & Anil Vullikanti, 2019. "Optimizing spatial allocation of seasonal influenza vaccine under temporal constraints," PLOS Computational Biology, Public Library of Science, vol. 15(9), pages 1-17, September.
    15. Zhang, Yuan & Chen, Xiao-Jian & Gao, Song & Gong, Yongxi & Liu, Yu, 2024. "Integrating smart card records and dockless bike-sharing data to understand the effect of the built environment on cycling as a feeder mode for metro trips," Journal of Transport Geography, Elsevier, vol. 121(C).
    16. Wang, Hongping & Fang, Yi-Ping & Zio, Enrico, 2022. "Resilience-oriented optimal post-disruption reconfiguration for coupled traffic-power systems," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    17. Pascal P Klamser & Adrian Zachariae & Benjamin F Maier & Olga Baranov & Clara Jongen & Frank Schlosser & Dirk Brockmann, 2024. "Inferring country-specific import risk of diseases from the world air transportation network," PLOS Computational Biology, Public Library of Science, vol. 20(1), pages 1-26, January.
    18. 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.
    19. Silver, Grant & Akbarzadeh, Meisam & Estrada, Ernesto, 2018. "Tuned communicability metrics in networks. The case of alternative routes for urban traffic," Chaos, Solitons & Fractals, Elsevier, vol. 116(C), pages 402-413.
    20. 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.
    21. 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).
    22. Jiang, Jincheng & Xu, Zhihua & Zhang, Zhenxin & Zhang, Jie & Liu, Kang & Kong, Hui, 2023. "Revealing the fractal and self-similarity of realistic collective human mobility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    23. Huang, Zhiren & Wang, Pu & Zhang, Fan & Gao, Jianxi & Schich, Maximilian, 2018. "A mobility network approach to identify and anticipate large crowd gatherings," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 147-170.
    24. van Strien, Maarten J. & Grêt-Regamey, Adrienne, 2016. "How is habitat connectivity affected by settlement and road network configurations? Results from simulating coupled habitat and human networks," Ecological Modelling, Elsevier, vol. 342(C), pages 186-198.
    25. Hong, Inho & Jung, Woo-Sung, 2016. "Application of gravity model on the Korean urban bus network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 48-55.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms6347. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.