Currently, over 600 electric vertical takeoff and landing (eVTOL) aircraft are in production (Vertical Flight Society, 2022). This new class of aircraft will require its own flight standards and curricula to train a new generation of pilots. However, to date, no data on eVTOL flight performance exists to build these standards or curricula. In this paper, we examine the influence of sets of eVTOL flight features that are human-controlled, automated, or augmented on human flight performance. In a quasi-experimental design, simulated flight performance was measured across two groups of participants (ab initio=40, rated pilots=40) and two eVTOL aircraft. Both eVTOL aircraft are in the prototype phase and vary in the extent to which sets of flight controls are automated and augmented. A simulated flight profile was designed involving a series of waypoints in an urban environment that requires multiple takeoffs and landings. Participants repeated the same profile six times, demonstrating a variety of eVTOL flight competencies including hovering, takeoff, landing, and basic aircraft control. Each competency was broken down into different phases of flight determined by changes in the direction of momentum. Performance was measured using a multi-modal assessment approach including 1) system-based objective data from the simulator representing physics data and 2) an observer-based assessment tool that captures ratings from experts. Data collection is currently underway and will be completed in Summer 2022. We predict that, in general, flight performance will improve with greater levels of automation and augmentation; however, particular attention will be given to scenarios where this is not the case and to situations in which automation and augmentation lead to reduced flight knowledge (as assessed by pre-/post-test). Results of the experiment will be used to inform eVTOL flight standards, develop training programs, and influence design decisions in the aircraft.

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Military Rank Andrew Anderson