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Objective:A conceptual model is proposed in order to explain pilot performance in surprising and startling situations.Background:Today’s debate around loss of control following in-flight events and the implementation of upset prevention and recovery training has highlighted the importance of pilots’ ability to deal with unexpected events. Unexpected events, such as technical malfunctions or automation surprises, potentially induce a “startle factor” that may significantly impair performance.Method:Literature on surprise, startle, resilience, and decision making is reviewed, and findings are combined into a conceptual model. A number of recent flight incident and accident cases are then used to illustrate elements of the model.Results:Pilot perception and actions are conceptualized as being guided by “frames,” or mental knowledge structures that were previously learned. Performance issues in unexpected situations can often be traced back to insufficient adaptation of one’s frame to the situation. It is argued that such sensemaking or reframing processes are especially vulnerable to issues caused by startle or acute stress.Conclusion:Interventions should focus on (a) increasing the supply and quality of pilot frames (e.g., though practicing a variety of situations), (b) increasing pilot reframing skills (e.g., through the use of unpredictability in training scenarios), and (c) improving pilot metacognitive skills, so that inappropriate automatic responses to startle and surprise can be avoided.Application:The model can be used to explain pilot behavior in accident cases, to design experiments and training simulations, to teach pilots metacognitive skills, and to identify intervention methods.

In the present study, we investigated whether the perception of heading of linear self-motion can be explained by Maximum Likelihood Integration (MLI) of visual and non-visual sensory cues. MLI predicts smaller variance for multisensory judgments compared to unisensory judgments. Nine participants were exposed to visual, inertial, or visual-inertial motion conditions in a moving base simulator, capable of accelerating along a horizontal linear track with variable heading. Visual random-dot motion stimuli were projected on a display with a 40° horizontal × 32° vertical field of view (FoV). All motion profiles consisted of a raised cosine bell in velocity. Stimulus heading was varied between 0 and 20°. After each stimulus, participants indicated whether perceived self-motion was straight-ahead or not. We fitted cumulative normal distribution functions to the data as a psychometric model and compared this model to a nested model in which the slope of the multisensory condition was subject to the MLI hypothesis. Based on likelihood ratio tests, the MLI model had to be rejected. It seems that the imprecise inertial estimate was weighed relatively more than the precise visual estimate, compared to the MLI predictions. Possibly, this can be attributed to low realism of the visual stimulus. The present results concur with other findings of overweighing of inertial cues in synthetic environments.

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The brain is able to determine angular self-motion from visual, vestibular, and kinesthetic information. There is compelling evidence that both humans and non-human primates integrate visual and inertial (i.e., vestibular and kinesthetic) information in a statistically optimal fashion when discriminating heading direction. In the present study, we investigated whether the brain also integrates information about angular self-motion in a similar manner. Eight participants performed a 2IFC task in which they discriminated yaw-rotations (2-s sinusoidal acceleration) on peak velocity. Just-noticeable differences (JNDs) were determined as a measure of precision in unimodal inertial-only and visual-only trials, as well as in bimodal visual-inertial trials. The visual stimulus was a moving stripe pattern, synchronized with the inertial motion. Peak velocity of comparison stimuli was varied relative to the standard stimulus. Individual analyses showed that data of three participants showed an increase in bimodal precision, consistent with the optimal integration model; while data from the other participants did not conform to maximum-likelihood integration schemes. We suggest that either the sensory cues were not perceived as congruent, that integration might be achieved with fixed weights, or that estimates of visual precision obtained from non-moving observers do not accurately reflect visual precision during self-motion.

Objective:This study tested whether simulator-based training of pilot responses to unexpected or novel events can be improved by including unpredictability and variability in training scenarios.Background:Current regulations allow for highly predictable and invariable training, which may not be sufficient to prepare pilots for unexpected or novel situations in-flight. Training for surprise will become mandatory in the near future.Method:Using an aircraft model largely unfamiliar to the participants, one group of 10 pilots (the unpredictable and variable [U/V] group) practiced responses to controllability issues in a relatively U/V manner. A control group of another 10 pilots practiced the same failures in a highly predictable and invariable manner. After the practice, performance of all pilots was tested in a surprise scenario, in which the pilots had to apply the learned knowledge. To control for surprise habituation and familiarization with the controls, two control tests were included.Results:Whereas the U/V group required more time than the control group to identify failures during the practice, the results indicated superior understanding and performance in the U/V group as compared to the control group in the surprise test. There were no significant differences between the groups in surprise or performance in the control tests.Conclusion:Given the results, we conclude that organizing pilot training in a more U/V way improves transfer of training to unexpected situations in-flight.Application:The outcomes suggest that the inclusion of U/V simulator training scenarios is important when training pilots for unexpected situations.

Objective: The aim of this study was to test if performance of airline pilots, in performing an aerodynamic stall recovery procedure, decreases when they are surprised, compared to when they anticipate a stall event.Background: New flight-safety regulations for commercial aviation recommend the introduction of surprise and startle in upset prevention and recovery training. This calls for more evidence on the effects of surprise on pilot performance, as well as methods to effectively induce surprise in training simulators.Method: The study took place in a motion-base simulator with a poststall aerodynamic model. Using a within-subjects design, the recovery performance of 20 pilots was tested in 2 conditions: 1 anticipated condition, and 1 surprise condition. In addition to flight parameters, subjective and physiological data relating to surprise and startle were measured.Results: Pilots had significantly more difficulties with adhering to the recovery procedure in the surprise condition compared to the anticipation condition. The subjective and physiological measures confirmed that the manipulation mainly increased surprise, and to a lesser extent also startle.Conclusion: The results suggest that pilots have more difficulty in managing an upset situation (i.e., an aerodynamic stall) when this situation is presented unexpectedly, underlining that upset prevention and recovery training should include elements of surprise.