Understanding how people behave during the fire evacuation is fundamental to predict the required time to evacuate buildings and transportation systems and enhance their safety. To date, several studies have been carried out to investigate the impact of several social and environmental factors on how evacuees choose exits while moving towards safe places. However, none of the existing studies has identified individual-specific taste preferences for exit choice behavior. As such, they do not allow the analyses of individual-specific preferences across heterogeneous decision makers. This work overcomes this limitation through a Hierarchical Bayes estimation approach, which allows the estimation of individual-specific parameters. The methodology is applied to the data of non-immersive Virtual Reality-based stated preference experiments. With the individual-level knowledge, analyses show more granular insights of decision makers’ trade-off of different factors, including two distinct groups of people as “followers” or “non-followers” and the impact of age, nationality, and education on the herding behavior during the fire evacuation.

了解人员在火灾疏散过程中的行为方式，对于预测撤离建筑物和运输系统并增强其安全性所需的时间至关重要。迄今为止，已经进行了一些研究来调查一些社会和环境因素对撤离者在选择安全场所时如何选择出口的影响。但是，现有的研究都没有发现出口选择行为的个人特定口味偏好。因此，它们不允许跨异构决策者分析特定于个人的偏好。这项工作通过Hierarchical Bayes估计方法克服了这一限制，该方法允许估计特定于个人的参数。该方法适用于基于非沉浸式虚拟现实的陈述偏好实验的数据。