Loss of Control (LOC) accidents are a major threat for aviation, and contribute the highest risk for fatalities in all aviation accidents. The major contributor to LOC accidents is pilot spatial disorientation (SD), which accounts for roughly 32% of all LOC accidents. A pilot experiences SD during flight when the pilot's expectation of the aircraft's state deviates from reality. This deviation results from a number of underlying mechanisms, such as distraction, failure to monitor flight instruments, and vestibular illusions. Previous researchers have developed computational models to understand those mechanisms. However, these models are limited in scope as they do not model the pilot's knowledge of the aircraft dynamics. This research proposes a novel model to predict the best-possible-pilot-expectation of the aircraft state given vestibular and visual cues. The proposed model uses a Model-Based Observer (MBO) as the infrastructure needed to establish an “expert pilot”. Expert pilots are known to form an internal model of the operated system through training and experience, which allows the expert to generate better internal expectations of the system states. Pilots' internal expectations are enhanced by the presence of information fed through the pilots̕ sensory systems. Thus, the proposed model integrates pilot's knowledge of the system dynamics (i.e. an aircraft model) with a continuous vestibular sensory model and a discrete visual-sampling sensory model. The computational model serves to investigate the underlying mechanisms of SD during flight and provide a quantitative analysis tool to support flight deck and countermeasure designs.

This thesis demonstrates how a model-based observer can be applied to estimate the reference pilot expectation that can be achieved with any instrument scanning behavior and established models of vestibular inputs. The MBO, developed by the Georgia Tech Cognitive Engineering Center, is applied here in both simple maneuvers examining spatial disorientation and full Air Traffic Control concepts of operations examining loss of energy state awareness. The computational experiments presented in this thesis examine how different effects (i.e., instrument scan pattern, accuracy of pilot perception of flight display information, and awareness of control surface deflections) can prevent or mitigate the susceptibility to spatial disorientation and loss of energy state awareness, thus setting requirements for intervention and countermeasure designs in terms of the scanning behavior they must foster.