<div class="section abstract"><div class="htmlview paragraph">Most emerging electric vertical takeoff and landing (eVTOL) aircraft feature distributed electric propulsion systems with automation features that simplify operations for future pilots. In theory, increasing automation levels should reduce pilot workload, decrease training time, and improve performance consistency. Air Education and Training Command Detachment 62 (AETC/Det 62) sought to test this theory as part of a larger study involving 70+ participants, two eVTOL platform simulators, and multimodal assessments of flight performance. In the present report, we compared expert ratings of flight performance of pilots who do not have prior pilot experience or training (herein referred to as ab initio pilots; i.e., 0 flight hours) to those of experienced pilots (i.e., >300 flight hours) in either a semi-automated or highly-automated simulated eVTOL platform. All participants received a brief orientation of the controls, then flew a scripted flight profile four times with guidance from an instructor pilot. The fourth and final flight profile was flown without any instructional guidance in order to assess unassisted performance. Instructor pilots rated the quality of hover, takeoff, en-route navigation, and approach and landing maneuvers on a 4-point scale. Experienced pilots overall outperformed ab initio pilots; however, the two groups showed similar learning trajectories for basic eVTOL flight operations over a 2-hour period of learning. In some cases (e.g., takeoff in the highly-automated platform), ab initio pilots reached similar performance levels as experienced pilots during the learning profile. Although the present study focused only on basic flight skills, results suggest that both ab initio and experienced pilots can rapidly gain proficiency in basic eVTOL operations.</div></div>
<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>
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