Using the Decision Ladder to understand human decision-making processes during a UAV-equipped SAR mission

Abstract

The uptake of Uncrewed Aerial Vehicles (UAVs) within the Search and Rescue (SAR) application is becoming ubiquitous owing to the way in which UAVs can support and extend SAR responses. During a SAR mission, UAVs are deployed to offer a birds-eye perspective of the search space which is captured by the onboard payload sensors and transmitted to human operators in real time. Currently, this data stream is processed manually by a Payload Operator to identify any hazards or signs of human life on the ground. However, the task of identifying and extrapolating information using the display technology is highly challenging. This is primarily due to the high levels of cognitive effort which must be expended over time to detect sightings that are likely to be camouflaged or obscured by the surrounding terrain. For this reason, system engineers are looking to develop image classification modules capable of autonomous object detection and labelling to streamline the information acquisition process from the UAV. When looking to introduce novel functionality, such as an image classification module, it is important to consider how decision-making processes are currently undertaken by the team of human operators. In doing so, a greater understanding is yielded on how the current ways of working could be supported through further design intervention. The current work aims to capture these processes using the representational medium of the Decision Ladder. Rasmussen (1974) developed the Decision Ladder to define the different information processing activities undertaken by a decision-maker when identifying an appropriate course of action within a given situation. In order to develop the Decision Ladder for the UAV-equipped SAR scenario, knowledge elicitation activities were conducted using interviews with SAR personnel.The final amalgamated Decision Ladder was populated using the responses from the interviews. The decision model demonstrated the complexity of utilising UAVs to support a SAR mission due to the regulatory and technological constraints associated with the UAV. In addition, the importance of a validation activity was emphasised by the SAR personnel which would be conducted to determine the accuracy of any information presented by the automated system. Here, the decision ladder was able to identify the broad set of information aspects that would be reviewed by the human-UAV team. The subsequent knowledge obtained would be used to identify the relevance of a sighting and determine the most appropriate response using the limited resources available within the SAR environment. This insight provided from the Decision Ladder was used to propose a set of novel design recommendations that could extend the capabilities of the image classification module within the SAR context. Therefore, this work advocates the use of a user-centred design approach to support the development of technologies based on the tasks and cognitive processes of the end-user.

Keywords: Human Factors, Automation, Decision-making, UAVs

DOI: 10.54941/ahfe1004123