Visualising agent-based model outputs to enhance decision-making in search and rescue operations
In search and rescue (SAR), time is critical, and successfully finding a lost person in the least amount of time is the goal. Part of a successful search is the development of accurate and relevant search areas. Planning these search areas for lost people can be improved by developing and using spatial models. Spatial models allow for the prediction of a lost person’s movement through the interaction between human navigation behaviour and the underlying terrain. However, they are not often used in real-time SAR. This research looks at spatial models in SAR and outlines the development of an Agent-based model for more accurate search planning and rapid decision-making. The output of the model is discussed, and strategies to engage SAR in the uptake of spatial modelling results are outlined. By incorporating spatial modelling results, it is hoped that search areas can be designed more effectively, which will, in turn, improve the outcomes for lost people.
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