Operator Selection for Unmanned Aerial Systems: Comparing Video Game Players and Pilots

Abstract

Popular unmanned aerial system (UAS) platforms such as the MQ-1 Predator and MQ-9 Reaper have experienced accelerated operations tempos that have outpaced current operator training regimens, leading to a shortage of qualified UAS operators. To find a surrogate to replace pilots of manned aircraft as UAS operators, this study evaluated video game players (VGPs), pilots, and a control group on a set of UAS operation relevant cognitive tasks. There were 30 participants who volunteered for this study and were divided into 3 groups: experienced pilots (P), experienced VGPs, and a control group (C). Each was trained on eight cognitive performance tasks relevant to unmanned flight tasks. The results indicated that pilots significantly outperform the VGP and control groups on multi-attribute cognitive tasks (Tank mean: VGP = 465 +/- 1.046 vs. P = 203 +/- 0.237 vs. C = 351 +/- 0.601). However, the VGPs outperformed pilots on cognitive tests related to visually acquiring, identifying, and tracking targets (final score: VGP = 594.28 +/- 8.708 vs. P = 563.33 +/- 8.787 vs. C = 568.21 +/- 8.224). Likewise, both VGPs and pilots performed similarly on the UAS landing task, but outperformed the control group (glide slope: VGP = 40.982 +/- 3.244 vs. P = 30.461 +/- 2.251 vs. C = 57.060 +/- 4.407). Cognitive skills learned in video game play may transfer to novel environments and improve performance in UAS tasks over individuals with no video game experience.