Disasters affect millions of people annually, causing large social impacts, including high numbers of fatalities, the displacement of communities, and detrimental economic impacts. Emergency professionals recurrently tackle these impacts and therefore need assessment methods to understand potential consequences and deliver sustainable resolutions, regularly with incomplete information. Current models simulating human behaviours and movement exist but are bespoke in nature and non-transferable (solving one problem only), meaning it is not possible to keep software “current” or future proofed. The aim of this research is to create an agent-based modelling (ABM) framework tool, incorporating robust models of human behaviour, to help management professionals develop and test their contingency plans for emergency scenarios. The focus has been on creating a macroscale evacuation ABM for a case study area, to assess whether the inclusion of varied population characteristics and group behaviours affect evacuation time. This research has found that by enhancing the representation of human behaviour more accurate predictions of evacuation time can be produced. To produce more robust human behaviour, models must include: (1) population characteristics (such as age, sex, and mobility), (2) grouping of agents, and (3) a walking speed ratio. Without the inclusion of adequate population characteristics, e.g. using agents with only a 1.34 m/s (3mph) walking speed, the evacuation model produced misleading evacuation times, potentially increasing by 109% for some population types. This may result in knock-on effects, such as significant increases in fatalities, or injuries as populations cannot leave their homes to safety in the expected time.

灾难每年影响数百万人，造成巨大的社会影响，包括大量的死亡，社区流离失所和不利的经济影响。紧急专业人员经常应对这些影响，因此需要评估方法来了解潜在的后果并定期以不完整的信息提供可持续的解决方案。目前存在模拟人类行为和动作的模型，但是它们是定制的，并且是不可转让的（仅解决一个问题），这意味着不可能使软件保持最新状态。”或将来证明。这项研究的目的是创建一个基于代理的建模（ABM）框架工具，其中包含强大的人类行为模型，以帮助管理专业人员制定和测试其针对紧急情况的应急计划。重点一直放在为案例研究区域创建大型疏散反弹道导弹，以评估是否包括不同的人口特征和群体行为会影响疏散时间。这项研究发现，通过增强人类行为的表示，可以对撤离时间做出更准确的预测。为了产生更健壮的人类行为，模型必须包括：（1）人口特征（例如年龄，性别和流动性），（2）行为体分组以及（3）步行速度比。没有包括适当的人口特征，例如 使用仅步行速度为1.34 m / s（3英里/小时）的代理，疏散模型产生了误导性的疏散时间，对于某些人口类型，疏散时间可能增加109％。这可能会导致连锁反应，例如死亡人数的大幅增加，或由于人们无法在预期的时间内离开家园而造成伤害的伤害。