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A mixed logit model for predicting exit choice during building evacuations

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  • Lovreglio, Ruggiero
  • Fonzone, Achille
  • dell’Olio, Luigi

Abstract

Knowledge on human behaviour in emergency is crucial to increase the safety of buildings and transportation systems. Decision making during evacuations implies different choices, of which one of the most important concerns is the escape route. The choice of a route may involve local decisions on alternative exits from an enclosed environment. This study investigates the effect of environmental (presence of smoke, emergency lighting and distance of exit) and social factors (interaction with evacuees close to the exits and with those near the decision-maker) on local exit choice. This goal is pursued using an online stated preference survey carried out making use of non-immersive virtual reality. A sample of 1503 participants is obtained and a mixed logit model is calibrated using these data. The model shows that the presence of smoke, emergency lighting, distance of exit, number of evacuees near the exits and the decision-maker and flow of evacuees through the exits significantly affect local exit choice. Moreover, the model indicates that decision making is affected by a high degree of behavioural uncertainty. Our findings support the improvement of evacuation models and the accuracy of their results, which can assist in designing and managing building and transportation systems. The main aim of this study is to enrich the understanding of how local exit choices are made and how behavioural uncertainty affects these choices.

Suggested Citation

  • Lovreglio, Ruggiero & Fonzone, Achille & dell’Olio, Luigi, 2016. "A mixed logit model for predicting exit choice during building evacuations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 92(C), pages 59-75.
    • Handle: RePEc:eee:transa:v:92:y:2016:i:c:p:59-75
    DOI: 10.1016/j.tra.2016.06.018
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    References listed on IDEAS

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    Cited by:

    1. Kinateder, Max & Warren, William H., 2021. "Exit choice during evacuation is influenced by both the size and proportion of the egressing crowd," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 569(C).
    2. Haghani, Milad & Sarvi, Majid, 2018. "Hypothetical bias and decision-rule effect in modelling discrete directional choices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 361-388.
    3. Gao, Dong Li & Xie, Wei & Ming Lee, Eric Wai, 2022. "Individual-level exit choice behaviour under uncertain risk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    4. Eliana Fischer & Alessio Emanuele Biondo & Annalisa Greco & Francesco Martinico & Alessandro Pluchino & Andrea Rapisarda, 2022. "Objective and Perceived Risk in Seismic Vulnerability Assessment at an Urban Scale," Sustainability, MDPI, vol. 14(15), pages 1-24, July.
    5. Wang, Xinjian & Liu, Zhengjiang & Loughney, Sean & Yang, Zaili & Wang, Yanfu & Wang, Jin, 2022. "Numerical analysis and staircase layout optimisation for a Ro-Ro passenger ship during emergency evacuation," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    6. Arellana, J. & Garzón, L. & Estrada, J. & Cantillo, V., 2020. "On the use of virtual immersive reality for discrete choice experiments to modelling pedestrian behaviour," Journal of choice modelling, Elsevier, vol. 37(C).
    7. Xu, Chenchen & Luo, Yiyang & Fuellhart, Kurt & Shao, Quan & Witlox, Frank, 2023. "Modeling exit choice behavior in airplane emergency evacuations," Journal of Air Transport Management, Elsevier, vol. 112(C).
    8. Tanaka, Masahiro & Yanagisawa, Daichi & Nishinari, Katsuhiro, 2018. "Exclusive queueing model including the choice of service windows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1481-1492.
    9. Haghani, Milad, 2021. "The knowledge domain of crowd dynamics: Anatomy of the field, pioneering studies, temporal trends, influential entities and outside-domain impact," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
    10. Haghani, Milad & Sarvi, Majid, 2019. "Laboratory experimentation and simulation of discrete direction choices: Investigating hypothetical bias, decision-rule effect and external validity based on aggregate prediction measures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 134-157.
    11. Guo, Chenglin & Huo, Feizhou & Li, Chao & Li, Yufei, 2023. "An evacuation model considering the phototactic behavior of panic pedestrians under limited visual field," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    12. Zhou, Zi-Xuan & Nakanishi, Wataru & Asakura, Yasuo, 2021. "Data-driven framework for the adaptive exit selection problem in pedestrian flow: Visual information based heuristics approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    13. Zhang, Dezhen & Huang, Gaoyue & Ji, Chengtao & Liu, Huiying & Tang, Ying, 2021. "Pedestrian evacuation modeling and simulation in multi-exit scenarios," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).

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