I built an Agent-Based model for my initial search and rescue model. This type of model consists of three elements, which are the agents, the environment and the interactions between the agents and the environment. The environment is where phenomena occur, and agents inhabit that environment.

ABMs have commonly been used to model human movement for environmental management. These models allow land managers to make informed decisions regarding the increase in human use of the environment whilst still maintaining ecological purity. Many of these models deal primarily with the issue of collision avoidance and track and facility planning and management.

ABMs have also been developed for search and rescue. In addition to the model I built, Mohibullah has developed two ABMs that model lost person behaviour using known lost person behaviour strategies, moving on linear features. Hashimoto created a functional ABM that used data from real search and rescue incidents and took into account both landscape data and known lost person behaviour strategies to determine likely lost person behaviour.

One of the key features of an ABM is the autonomy of an agent and their ability to make decisions based on the state of the environment at the time. This makes ABMs ideal for modelling human movement, with agents being able to make autonomous decisions using accurate terrain data and known human navigation behaviours.

Click here for a demonstration video of my lost person ABM