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Self-propelled pedestrian dynamics model: Application to passenger movement and infection propagation in airplanes

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  • Namilae, S.
  • Srinivasan, A.
  • Mubayi, A.
  • Scotch, M.
  • Pahle, R.

Abstract

Reducing the number of contacts between passengers on an airplane can potentially curb the spread of infectious diseases. In this paper, a social force based pedestrian movement model is formulated and applied to evaluate the movement and contacts among passengers during boarding and deplaning of an airplane. Within the social force modeling framework, we introduce location dependence on the self-propelling momentum of pedestrian particles. The model parameters are varied over a large design space and the results are compared with experimental observations to validate the model. This model is then used to assess the different approaches to minimize passenger contacts during boarding and deplaning of airplanes. We find that smaller aircrafts are effective in reducing the contacts between passengers. Column wise deplaning and random boarding are found to be two strategies that reduced the number of contacts during passenger movement, and can potentially lower the likelihood of infection spread.

Suggested Citation

  • Namilae, S. & Srinivasan, A. & Mubayi, A. & Scotch, M. & Pahle, R., 2017. "Self-propelled pedestrian dynamics model: Application to passenger movement and infection propagation in airplanes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 248-260.
  • Handle: RePEc:eee:phsmap:v:465:y:2017:i:c:p:248-260
    DOI: 10.1016/j.physa.2016.08.028
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    References listed on IDEAS

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    Cited by:

    1. Bouchnita, Anass & Jebrane, Aissam, 2020. "A hybrid multi-scale model of COVID-19 transmission dynamics to assess the potential of non-pharmaceutical interventions," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    2. Pierrot Derjany & Sirish Namilae & Dahai Liu & Ashok Srinivasan, 2020. "Multiscale model for the optimal design of pedestrian queues to mitigate infectious disease spread," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-21, July.
    3. Pereira, Francisco & Costa, Joana Martinho & Ramos, Ricardo & Raimundo, António, 2023. "The impact of the COVID-19 pandemic on airlines’ passenger satisfaction," Journal of Air Transport Management, Elsevier, vol. 112(C).

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