Prospective decision modelling of Uncrewed Aerial Vehicle Operators to inform design recommendations for future systems

Uncrewed Aerial Vehicles (UAVs) are becoming widely used in search and rescue (SAR) applications, particularly to support operations involving missing persons. Generally, the payload data received from the UAV is consistently monitored to identify possible sightings. To free operators from constant monitoring, Image classification algorithms could be used to form part of a decision support system (DSS). When designing this aid, the decision-making processes of the human operators should be fully understood to ensure the system is embedded with appropriate support mechanisms. The current work analyzed the decision-making processes of operational SAR personnel using the Perceptual Cycle Model. A hypothetical scenario was presented to understand the typical responses of SAR teams. Therefore, a prospective approach was taken to understand the processes, users and tasks used during a UAV-equipped SAR mission. This understanding was used to propose design recommendations that could be embedded within a futuristic DSS integrated with autonomous functionality.