Recurrent training is crucial to helping pilots maintain or upgrade their flying skills. However, constantly monitoring and scrutinising pilots during training can lead to performance pressure. If pilots who are under pressure feel that their behaviour is affected it may ultimately reduce the effectiveness of recurrent training. To study the effects of performance pressure on pilot behaviour and learning, pilots (n=17) holding an airline transport pilot licence and type rating for large multi engine aircraft were invited to participate in a simulator experiment where they would learn a new autopilot system. The low-pressure group flew a series of training scenarios under no performance pressure whereas the high-pressure group flew the same training scenarios with prompts designed to induce performance pressure and raise their anxiety. It was hypothesised that the high-pressure group would be less incentivised to explore different functions of the autopilot due to the performance pressure, therefore leading to a lower quality of training which would be reflected in poorer knowledge of the autopilot system. Ultimately, whilst the high-pressure group did in fact undergo training with a significantly higher state anxiety. This was found to have no significant effect on their behaviour during training or their performance in a test scenario. The findings also suggest that the experiment would benefit from being repeated with more guidance given during training and more constrained scenarios to reduce the variation in the data.

Roll reversal errors, where the pilot tries to steer the aircraft back to wings-level but unintentionally increases the bank angle instead, have contributed to several accidents. Previous studies have shown that these errors can be caused by misinterpreting the attitude indicator (AI), with the figure-ground relations cited as contributing to this misinterpretation. A modified AI was developed, which uses several static monocular depth cues (color gradient, linear perspective lines, and shadow-light relationship) to strengthen the figure-ground relationship.
The modified version of the AI was compared to a baseline AI in a two-part flight simulator experiment where pilot reaction time and error rate, severity, and duration were measured. The first part induced the leans illusion making use of physiological adaptation to roll angle, distraction, and surprise. The second part simulated the leans illusion by simply rolling the simulator to the left or right. A group of 25 experienced commercial airline pilots performed a roll-to-level task in a moving-base simulator, which also provided spatially disorienting motion cues, using both the baseline and modified versions of the AI. While the modified
display had a lower error rate in the motion-opposite scenario when using the novel method (4.91% compared to 6.07%), no significant difference was found between the error rate of the two displays. The only significant difference was found in the reaction time, where the modified AI caused an increase in reaction time. The error rates and reaction times of the first part of the experiment did not match previous research. The novel disorientation method seemed to work best in a surprise scenario. While no significant differences were found between the modified AI and the baseline AI, it is still recommended to continue testing the modified AI with a new experiment setup, especially analyzing its effect in more extreme attitudes.

This study investigated the effect of manual and autopilot control on hazard and failure detection in aviation, in cases where the autopilot can masks or diminishes cues of aircraft movement. This mechanism could result in loss of situation awareness, upsets and ultimately accidents. Twenty airline pilots participated in an experiment in which two scenarios, an engine failure and icing accumulation hazard, were flown in both manual and autopilot control conditions. Results show no significant difference in detection time for the engine failure scenario between the two modes, but a marginally significant difference in the icing accumulation scenario and a clear difference in the way pilots detected the failure/hazard. Manual control may provide clearer cues, but automation may lower workload and allow for better monitoring. Monitoring of the flight controls was found to be an important factor in hazard detection, with pilots who had their hands resting on the controls having significantly lower detection times. The study provides insights on the importance of active monitoring of flight controls and on the impact of non-backdriven controls. The findings suggest that understanding the advantages and disadvantages of autopilot use is crucial for training pilots effectively.

Spatial disorientation (SD) is one of the main causes of incidents and accidents in aviation. While most studies have investigated the effect of SD on the control task, we tested the effect of SD on cognitive performance in an operationally representative environment.
Thirteen Dutch military helicopter pilots flew scenarios with six different SD events using an AH-64 Apache flight model in virtual reality in a 6-DoF motion simulator. The SD events used were: “False Horizon”, “Featureless Terrain”, “the Leans”, “Brownout”, “Somatogyral Illusion” and “Night Vision Goggles (NVGs)”. Corresponding scenarios without the SD events were performed to obtain baseline measures of cognitive performance. When performing the scenarios, participants had either the role of pilot flying or pilot monitoring.
To test the cognitive performance, participants performed a mathematical processing task. The corrected reaction time and error rate were significantly higher during the SD events than during the baseline events.
These effects were most prominent in the “Featureless Terrain” and “the Leans” scenarios. The results indicate that SD has a negative impact on the cognitive performance of military helicopter pilots. These findings underline the importance of SD awareness training for pilots, as well as the use of workload management procedures when experiencing SD.

Today, most fatal accidents in commercial aviation are caused by loss of control in flight. Due to the increased reliance on automation and pilots being moved out of the loop, startling and surprising events can be contributing factors. To more effectively train pilots, startle and surprise are to be included in training scenario’s. A subjective scale indicating the level of startle and surprise is being developed to help build these training programs, but an objective baseline of whether pilots are startled or surprised is needed in order to validate and further develop this scale. In this way, the scale can be used in flight simulators to asses the pilot’s perceived level of startle and surprise during novel training scenario’s. This work aims to test a startle and surprise detection method using physiological data. Electromyography, electrocardiography and electroencephalography data were collected. A validation of the occurrence of physiological effects related to both startle and surprise was performed, after which a detection algorithm was constructed. Validation of effects was performed on data of 22 participants using a three-stimulus oddball task with additional auditory startling stimuli. It was found that all considered physiological effects related to startle can be reliably observed. Contrary, not all physiological effects related to surprise were observed. The detection algorithm was tuned on data of twelve participants and showed to generalise well to the other ten data points. Startle detection could be performed with high accuracy, although surprise detection was poor.

In current spatial orientation models, vertical acceleration (heave) is not coupled with pilot pitch perception, although such a coupling may be present. Therefore, in this study it is investigated whether a heave cue can increase perceived pitch in pilots.

Airline pilots (n = 20) performed a pitch perception task in a hexapod simulator. A level change maneuver, with the simulator cabin pitching up and back down, was presented with different maximum pitch angles. After the maneuver, pilots indicated the maximum perceived pitch angle. This motion was presented either with or without a brief (1.25s or 1.5s) heave cue, that was timed to the onset of the pitch motion. Two timings and magnitudes of the heave cue were used to investigate these factors.

The results indicate that the heave cue significantly increased pilot pitch perception by 1.88°, p < 0.001. The maximum pitch angle was 2.69° underestimated without heave and 1.42° underestimated with heave. A higher heave magnitude, relative to a lower, resulted in a significantly larger estimation of the pitch angle, δ = 0.47°, p = 0.009. Earlier timing of the heave cue resulted in marginally significantly higher pitch perception than later timing, δ = 0.43°, p = 0.069. Interestingly, if heave was presented without pitch motion, pilots still estimated 2.66° pitch on average.

The results suggest that heave cueing increases perceived pitch in pilots, even when the heave cues are shorter in duration than cues that would be present in the actual maneuver in flight. Heave cues timed to the onset of pitch motions can thus possibly be used to enhance pilot pitch perception in hexapod simulators.

Startle and surprise training interventions developed and tested in previous research have shown how falling back to mnemonic aid procedures when experiencing an unexpected event during flight can ameliorate the effects of startle and surprise responses. The current research follows up on the recommendations provided by Van Middelaar et al. on the implementation of the COOL procedure which, in some cases, was also found too demanding to execute and somewhat distracting from ensuring a safe flight path. A new procedure featuring the steps Aviate Breathe Check (ABC) was developed to explicitly allow for task prioritisation (i.e. aviating over troubleshooting) and to be shorter in its execution while still addressing stress management related steps. We tested the ABC procedure with an experiment involving 25 airline pilots divided into an experimental group (n=13) and a control group (n=12) both of which experienced the same simulation scenarios designed to evoke startle and surprise. No significant effects of the type of training intervention on flying performance, on stress levels and on mental effort were found. Following events involving a sudden upset, the ABC procedure was overall shown to have a higher implementation rate compared to the COOL procedure evaluated in previous research in relation to the same test scenarios. This suggests that the ABC procedure could be more easily implemented on the flight deck. In an operational environment the ABC procedure could hence be integrated in recurrent pilot training programmes and translated into operational practice, without requiring extensive training. It is recommended to further test the procedure in a follow up experiment involving multi-crew operations and/or pilots with a more diverse training background.

In previous studies it was shown that both pilots and non-pilots sometimes make roll reversal errors (RREs) when the aircraft bank angle is presented on a moving horizon type attitude indicator. This incorrect input has been shown to be caused by a misinterpretation of the horizon symbol on such an attitude indicator. The figure-ground relation of the aircraft symbol and horizon symbol on the attitude indicator has been cited as being a contributing factor to this misinterpretation. A Multi-Layer Display (MLD) is tested as a possible intervention tool for these interpretation errors. With this display type, the horizon symbol is presented on a physically deeper layer, making it possibly more easily interpreted as being in the background, and the aircraft symbol is presented on a second layer on the foreground. A group of 23 non-pilots and 18 pilots were tasked to perform a recovery task on a desktop-based simulator without outside visuals and only an Attitude indicator on both a MLD as well as a conventional Single Layer Display for repeated-measures. Although roll reversal errors were observed at a comparable level to previous research, no significant difference were observed on the error rate between the two display types. A possible explanation is that the stereoscopic depth of the MLD dissipates when the subject sits still and remains exactly in front of the display. This leaves open the possibility that other types of depth cues, such as monocular cues, can be added and used to enhance the figure-ground relation in displays.

In previous studies, pilots made roll reversal errors (RREs) when responding to a ‘moving- horizon’ type attitude indicator (AI). It was argued that it was the ambiguity of this display leading to RREs. Later, using non-pilots, it was found that RREs were in many cases caused by expectation-induced misperception of the AI bank angle, which can arise from a pilot experiencing spatial disorientation. The current study evaluated the role of expectation in the control strategy of professional pilots using a hexapod simulator. First, an effective man-in-the-loop spatial disorientation scenario was developed, based on the ‘leans’ illusion. Here, the expectation of ten experienced and eight novice pilots was manipulated with the simulator motion without the AI, after which they had to turn the aircraft back level when the AI was shown again. An error was made in 16.7% of the runs where the bank angle on the AI was opposite to the earlier given physical motion cues, which is 2.9 times more compared to a baseline condition in which no motion, and thus no manipulated expectation, was present. In a third condition where a motion-induced expectation of the bank angle was present, but a level AI was shown later, no errors were made. It was also found that experienced pilots made slightly more errors than novice pilots and that their reaction time was on average half a second higher.
It was concluded that an initially induced expectation about the bank angle does not directly influence the control strategy of pilots, but that it does make them more vulnerable to misinterpretations of the AI, leading to RREs being made. This should be taken into account when developing new displays and technologies, as it should at all times guide pilots in their decision-making, minimizing the chance of misinterpretations.

Loss of Control In-Flight is the most prevalent cause of fatal accidents in commercial aviation. Surprise and startle are commonly suspected as contributing factors. Aviation authorities recommend to include surprise in training. However, studies indicate current training is in some cases too predictable as variations are brought to a minimum, with a focus on predetermined responses.

This study aims to test if using unpredictability and variety in training better prepares pilots for surprise situations. Toward this end, a flight simulator experiment was designed in which 21 airline pilots, divided over two groups, participated. Each group was provided with a short training containing half an hour of flight time. One group was given a predictable training without variety while the other group was given an unpredictable training with variety. Results show that with minimal impact on the training, performance is better in a surprise scenario related to the training. In a surprise scenario unrelated to the training, no effect was found.

The results suggest that using unpredictability and variety in pilot training improves performance in surprise situations, underlining the need to make pilot training less predictable.