Predicting eVTOL Simulator Performance Using Basic Performance Resources

Abstract

<div class="section abstract"><div class="htmlview paragraph">The rapidly advancing field of Advanced Air Mobility featuring electric Vertical Takeoff and Landing capable aircraft will create an increased demand for commercial pilots. In addition, the automation schemes for these new aircraft designs will likely change the skills required and demands placed on pilots of these vehicles. Therefore, recruiters and training facilities must understand which basic performance resources predict success to identify the best candidates to learn to fly this new class of aircraft. This study assesses the basic performance resources of ab initio students and experienced pilots in electric vertical takeoff and landing aircraft simulators. Researchers recruited 82 military volunteers to participate in this study by spending one day learning to fly one of the two simulators available. This study included approximately equal numbers of ab initio students and rated pilots. Researchers randomly assigned participants to either a highly augmented aircraft simulator or a minimally augmented aircraft simulator creating a two-by-two results matrix. Researchers compared 11 dimensions of pilot performance, assessed by experienced instructor pilots, and 32 basic performance resource measures evaluated through standardized tests to determine if performance measures were reliable and predictive of performance. Researchers then used standard parametric statistics to determine differences across platforms and participants. The data show several strong predictors of performance in the minimally-augmented aircraft simulation. However, in the highly-augmented aircraft simulation, there were no significant predictors of performance. This research suggests that increased aircraft automation reduced pilot candidates’ reliance on basic performance resources. In addition, flying experience didn’t significantly affect outcomes.</div></div>