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Optimized guidance for building fires considering occupants’ route choices

Author

Listed:
  • Lu, X.
  • Blanton, H.
  • Gifford, T.
  • Tucker, A.
  • Olderman, N.

Abstract

Occupants in building fires usually have difficulties to evacuate safely, and providing guidance may help them select proper routes. However, groups of occupants may not follow guidance because they make their own decisions and are affected by psychological factors. Their reactions to guidance should therefore be considered by an emergency guidance system. Most existing studies assumed that occupants would follow guidance, and congestions might occur if suggested routes were not used. To consider occupants’ route choices, the random utility theory is employed to characterize their reactions to guidance, and the guidance is optimized in a leader–follower​ (Stackelberg) game framework in this paper. To partially validate the effect of guidance and determine related parameters of psychological factors, data from virtual reality (VR) experiments are analyzed, where human participants were recruited and their probabilistic route choices were analyzed. Using parameters derived from VR experiments, numerical and simulation results demonstrate that optimized guidance is effective in terms of the overall risk and evacuation times because related congestions are alleviated. A sensitivity analysis is also performed to assess the impacts of different psychological factors on optimized guidance and evacuations.

Suggested Citation

  • Lu, X. & Blanton, H. & Gifford, T. & Tucker, A. & Olderman, N., 2021. "Optimized guidance for building fires considering occupants’ route choices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 561(C).
  • Handle: RePEc:eee:phsmap:v:561:y:2021:i:c:s0378437120306592
    DOI: 10.1016/j.physa.2020.125247
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    References listed on IDEAS

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    1. Ning Ding & Hui Zhang & Tao Chen, 2017. "Simulation-based optimization of emergency evacuation strategy in ultra-high-rise buildings," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 89(3), pages 1167-1184, December.
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    3. Vermuyten, Hendrik & Lemmens, Stef & Marques, Inês & Beliën, Jeroen, 2016. "Developing compact course timetables with optimized student flows," European Journal of Operational Research, Elsevier, vol. 251(2), pages 651-661.
    4. L. G. Chalmet & R. L. Francis & P. B. Saunders, 1982. "Network Models for Building Evacuation," Management Science, INFORMS, vol. 28(1), pages 86-105, January.
    5. Zhang, N. & Ni, X.Y. & Huang, H. & Duarte, M., 2017. "Risk-based personal emergency response plan under hazardous gas leakage: Optimal information dissemination and regional evacuation in metropolises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 237-250.
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    Cited by:

    1. Dong, Shiyu & Huang, Ping & Wang, Wei, 2022. "An optimization method for evacuation guidance under limited visual field," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).

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