Understanding group behaviour during evacuations inside buildings

An exploratory agent-based modelling approach

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Abstract

Over the last decades, the world population has grown vastly and the percentage of people living in cities has increased. This process of urbanization has had a lot of implications for both safety management and research on evacuations. Due to this growth in urbanization, more high density gatherings are taking place, potentially resulting in more casualties during emergencies. A common method used to conduct research on evacuations is simulation models. Simulation models have already improved our understanding of human behaviour during evacuations, but researchers argue that most current models are still not able to accurately describe human behaviour during evacuations since they do not take into account the effect of groups. Empirical research has shown that social groups in crowds influence the dynamics of evacuations. For instance, when an emergency happens and groups have to decide where to go, groups sometimes just follow other groups. However, accurately modelling such notions is often complex and contains uncertainty. One of the ways to deal with uncertainty systematically is by applying exploratory modelling. This, however, has yet to be applied to evacuations. This study aims to address the need for models which include the notion of groups by analysing the effect of two decision-making schemes on the evacuation time; leader-follower decision-making and consensus decision-making. Furthermore, this study aims to provide a stepping stone for exploratory modelling in the realm of evacuation modelling. In order to do so, this study uses three methods; a literature study, agent-based modelling, and exploratory modelling. The literature study was conducted to lay the foundation of the agent based model, while exploratory modelling was used to explore the uncertainty space of the agent-based model. After the development of the model, it was verified and validated using multiple tests, and data from a previous study. Through extensive validation and verification, it was concluded that this model is fit for purpose. It is both able to generate behaviour in the same magnitude as previous empirical research, and show valid behaviour on the lower abstraction levels of the model. Results show that groups have a significant impact on evacuation time. The more groups are present, and the bigger they are, the higher the evacuation time will be. Furthermore, results show that there is almost no difference in leader-follower decision-making and consensus decision-making. These two only differ when no one is familiar in a building. When there is 0% familiarity, leader-follower behaviour will lead to lower evacuations times compared to consensus decision-making. Lastly, results show that the combination of groups being present and all people being familiar with a building may actually have adverse effects on the evacuation time in crowd densities between 0.07 and 0.36. In case of crowd densities up to 0.36, a high percentage of familiarity may actually lead to higher evacuation times. All in all, this study provides a stepping stone for modelling group behaviour using an exploratory agent-based modelling approach. This study was the first to lay focus on the effect of group decision-making schemes by incorporating it in an agent-based model and exploring its behaviour by running it numerous times under different parameter settings. Furthermore, this research has important implications. First, evacuations inside buildings should not only be evaluated by crowd density or familiarity, but also by exit capacity. Secondly, different crowd compositions have different effects on the evacuations time. Policymakers should, therefore, take into account what types of groups will most likely be present. As regards future research, future research should mainly focus on the effect of modelling leader-follower behaviour in different ways, modelling consensus groups in general, analysing the effect of groups on different segments of evacuation time, and adding more (social) factors to the model which influence evacuation behaviour.