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Optimizing evacuation efficiency under emergency with consideration of social fairness based on a cell transmission model

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  • Xuedong Yan
  • Xiaobing Liu
  • Yulei Song

Abstract

Traffic assignment and management objectives are considered as two significant parts in developing the emergency evacuation plan, which can directly influence the evacuation performance and efficiency. From the perspective of disaster response operators, the evacuation objective frequently is to minimize the total evacuation time to reduce losses, which may lead to an unreasonable and unfair phenomenon where people in highest risk areas may be forced to sacrifice their priorities of evacuation to improve the system evacuation efficiency. In this paper, considering both efficiency and social fairness in emergency evacuation, a weight function consisting of risk evaluation index as variable and the emphasis degree of managers on social fairness principle as coefficient was initially proposed and embedded in system optimal (SO) objective function. Combining the weight function and other constraints based on an extended cell transmission model (CTM), the linear program (LP) model was established to realize the simulation of dynamic traffic assignment in emergency evacuation. Employing this model, the impact of the management strategy of balancing both efficiency and social fairness on evacuation results was studied in the “Tianjin Explosions” case. In the end, the conclusion of “balancing social fairness is valuable during evacuation” was obtained.

Suggested Citation

  • Xuedong Yan & Xiaobing Liu & Yulei Song, 2018. "Optimizing evacuation efficiency under emergency with consideration of social fairness based on a cell transmission model," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-21, November.
    • Handle: RePEc:plo:pone00:0207916
    DOI: 10.1371/journal.pone.0207916
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    References listed on IDEAS

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    2. Liu, Zheng & Liu, Jia-lin & Li, Ya-ping & Zhang, Shi-qing, 2022. "Multiclass dynamic emergency traffic collaborative optimization considering multiple solutions with stage-based algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).

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