Abstract
In recent years, drones have transitioned from cutting-edge technology to an integral part of daily life. Uncrewed Aerial Vehicles (UAVs) are now used for a variety of applications, ranging from recreational use to critical commercial and governmental purposes. While there has been a great deal of human factors (HF) research on UAVs and uncrewed ground vehicles (UGVs), according to Chen et al., current designs still experience high instances of errors. This challenge is exacerbated by the increase in the volumes of UAVs and the increasing influence of Artificial Intelligence (AI) incorporated in drone design. AI adds additional HF challenges associated with situation awareness, trust, and over-trust. According to the Federal Aviation Administration, further research is also needed to focus on HF challenges with UAVs including workload, stress, situational awareness, communication, automation trust, performance, training cognition, and team interactions. The goal of this paper is to provide a construct and tool for HF practitioners to optimize design focus for various mission user interfaces to improve AI applications for drone performance and operator ease of use and satisfaction.
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