|dc.description.abstract||General aviation (GA) loss of control accidents, in the United States, have continued to occur
despite efforts by government and non-government research agencies. The lack of data
during loss of control events (due to the absence of data recorders in small aircraft) does not
allow for an accurate reconstruction of the accidents, causing accident investigators to focus
on generic causes like pilot error.
Flight test research has shown that there are various systems induced causal factors that can
potentially set up an aircraft to depart controlled flight and do not aid pilot efforts. An
example of these causal factors is the flap configuration change on certain GA aircraft.
Although there is sufficient data on aircraft systems, there is a lack of data regarding pilot
cognition in single-pilot operating airplanes, calling for an exploratory study to design a
method to complement the already accumulated knowledge (through systems flight testing)
with human-focused data.
This study provides a novel flight test method that allows for human-systems integration
between aircraft dynamics (the behavior of the aircraft), and pilot cognition (the behavior of
the pilot). The dissertation contributes to the field of flight analysis and human-systems integration by exploring this new method that integrates the Critical Decision Method
(CDM) cognitive modeling technique with virtual reality simulations. Given the critical
and dangerous nature of loss of control, this study provides a high fidelity, high realism
simulation environment in VR. The flight test method involves a novel framework that
requires knowledge elicitation (KE) sessions in the form of protocol analysis and critical
decision method, validated through integrated cognitive mapping during VR simulated flight
tests. To consolidate the VR simulation experimental setup, this dissertation also includes
usability tests to demonstrate the applicability and validity of VR as a substitute for
traditional aerospace simulation methods.
This study is divided into three main phases: cognitive modeling through KE, usability tests
for VR use in aerospace research, and cognitive modeling through VR flight tests. The KE
sessions included six expert pilots, the usability nine expert pilots, and the VR flight tests
included eight expert pilots. The expert pilots were all certified flight instructors (CFIs)
except for one GA domain expert.
The cognitive modeling through KE provided fundamental data in understanding the
cognitive functions present during traffic pattern operations. The cognitive modeling through
VR flight tests (with aircraft dynamics) showed however a difference in the way the descent
is performed. While the KE results focus more on “mental simulations”, the VR tests
reported a dominance of “mental model development”, indicating that the traffic pattern is
flown as a unified flight segment. The cognitive modeling provided in this document also describes niches for LOC, especially
with details on flap configuration changes. It was found that trim change should be more
system-centered and less human-centered, and that LOC can be mitigated through the use of
energy management training in GA, through adequate aircraft design changes (i.e. modifying
aerodynamic parameters by modifying the actual design), and through the use of situation
awareness enhancing technology like augmented reality visuals.
Finally, recommendations are provided to improve the method and collect further data to
continue the efforts of mitigating LOC in aviation. The novel method was also identified as a means of enhancing (or defining) design requirements for multiple applications (e.g.
aviation, automotive, control rooms, etc.), training (e.g. using expert cognitive modeling as
a baseline for proper cognitive activity and identify lackings of student pilots’ cognitive
activity), and even automation (including artificial intelligence - AI).||en_US