Leans Illusion in Hexapod Simulator Facilitates Erroneous Responses to Artificial Horizon in Airline Pilots

Objective We tested whether a procedure in a hexapod simulator can cause incorrect assumptions of the bank angle (i.e., the “leans”) in airline pilots as well as incorrect interpretations of the attitude indicator (AI). Background The effect of the leans on interpretation errors has previously been demonstrated in nonpilots. In-flight, incorrect assumptions can arise due to misleading roll cues (spatial disorientation). Method Pilots (n = 18) performed 36 runs, in which they were asked to roll to wings level using only the AI. They received roll cues before the AI was shown, which matched with the AI bank angle direction in most runs, but which were toward the opposite direction in a leans-opposite condition (four runs). In a baseline condition (four runs), they received no roll cues. To test whether pilots responded to the AI, the AI sometimes showed wings level following roll cues in a leans-level condition (four runs). Results Overall, pilots made significantly more errors in the leans-opposite (19.4%) compared to the baseline (6.9%) or leans-level condition (0.0%). There was a pronounced learning effect in the leans-opposite condition, as 38.9% of pilots made an error in the first exposure to this condition. Experience (i.e., flight hours) had no significant effects. Conclusion The leans procedure was effective in inducing AI misinterpretations and control input errors in pilots. Application The procedure can be used in spatial disorientation demonstrations. The results underline the importance of unambiguous displays that should be able to quickly correct incorrect assumptions due to spatial disorientation.


INTRODUCTION
In modern aircraft, the main task of airline pilots is to monitor the automatic systems and intervene when the automation fails. Such interventions often require a prompt and correct interpretation of the instruments, which Strauch, 2017).
nerabilities in pilot knowledge and skills were Federal Aviation Administration [FAA], 2013). Over 60% of investigated accidents involved manual handling errors, and these errors strongly cooccurred with transitions from automated control (FAA, 2013, p. 231).
In several recent accidents involving manual handling errors, confusion about the bank angle was implied. Examples include Kenya Airways Cameroon Civil Aviation Authority, 2010 Bureau d'Enquêtes et d'Analyses pour la Sécurité de l'Aviation Civile, 2009(Aircraft Accident Investigation Bureau, 2002. input opposite to the required direction, which is also referred to as a roll reversal error. It has been argued that these errors may result from indicator (AI), which is the main display system to determine the aircraft bank angle (e.g., Johnson & Roscoe, 1972;Previc & Ercoline, 1999;Roscoe, 1968).
The conventional inside-out or moving --2022, Vol. 64(6) 962-972 rotates in the opposite direction of the control inputs. In other words, it is designed to mimic the outside view ("principle of pictorial realism"; Roscoe, 1968; see Figure 1). However, this principle may not be optimal for the AI, as displays inside the cockpit are thought to be than the outside scenery (Previc & Ercoline, 1999). In the case of the AI, the "principle of the moving part" (Johnson & Roscoe, 1972) may be more important, which states that humans tend to control the part of a display that moves and perceive static elements as being the background. This principle is violated in the design of high workload, surprise, or stress, pilots may revert to heuristics, and be inclined to control as if it were the aircraft symbol.
In experiments intended to evaluate the AI, pilots were found to make 4.5%-8.7% roll reversal errors when rolling to level from previously unknown bank angles (Beringer et al., 1975;Müller et al., 2018 formed better with 1.5%-4.9% errors (Beringer et al., 1975;Hasbrook & Rasmussen, 1973;. These outcomes show that there is indeed an ambiguity of the AI indicated bank direction, even for pilots. In tions regarding the bank angle was not tested. However, in the accident examples mentioned earlier, spatial disorientation seemed to have contributed to the fatal outcome. Spatial disorientation refers to having an erroneous sense of the aircraft attitude and motion relative to the earth, caused by misleading vestibular or other motion cues. Spatial disorientation has been estimated to have contributed to 12% of loss of control accidents, and to 24% of all fatalities in air carrier operations between 1996and 2010(Belcastro et al., 2017). An incorrect assumption of the bank angle is the most prevalent form of spatial disorientation in aviation, called the "leans" (Gillingham, 1992;Holmes et al., 2003;Pennings et al., 2020). It is a somatogyral illusion that can occur because the semicircular canals of our vestibular system do not sense low roll accelerations or sustained roll motions. A subthreshold roll acceleration may cause a level while it is actually banked. Then, when an unnoticed bank has developed, a superthe pilot to incorrectly assume a bank angle toward the opposite side. Illusions like the leans are most likely to occur when outside visibility is low, forcing pilots to use their instruments for determining the aircraft attitude.
Recent studies have shown that an incorrect assumption of the bank angle increases the like- Landman et al., 2019;Landman et al., 2020). Error rates increased from 5%-9.8% when no bank angle was expected to 63%-75% when a bank angle was expected in the opposite direction. These experiments were, however, performed with nonpilots. Thus, the leans motion cues, on the occurrence of roll reversal errors in airline pilots. Pilots may not be as susceptible to these errors as nonpilots, as they are trained and experienced in ignoring misleading motion cues, as well as in reading the AI. A recent simulator study found that pilots indeed performed better than nonpilots in leans motion cues, but this was without having the AI visible ( ). A second objective was to develop a new procedure order to instill the leans illusion as accurately as possible. It was assumed that if pilots made interpretation and control errors corresponding with the motion cues, this would indicate leans illusion. A third objective of the current study was to test whether more experienced than less experienced pilots.

Participants
Eighteen airline pilots participated in the column or yoke (such as in Boeing aircraft), which was used in the experiment. Pilots were divided into two experience groups: low experience (n and high experience (n = 10) with more than are displayed in Table 1. This research complied with the tenets of the Declaration of Helsinki and was approved by the human research ethics committee of the university. Informed consent was obtained from each participant.

Apparatus
The experiment was performed in the Simona Research Simulator (SRS) at the faculty of Aerospace Engineering of the Delft University of Technology (see, Stroosma et al., 2003). The SRS is a six degrees-of-freedom full-motion simulator with a hydraulic hexa-ations below human vestibular perception (see Heerspink et al., 2005). The pilot was seated in the left-hand seat of the cockpit, which featured of view screen. The images were rendered by FlightGear software and projected with the use of high-resolution computer-generated images using three Digital Light Processing (DLP) projectors.
twinjet aircraft (Airbus A320). Participants were only able to control the roll axis using a control-loaded column. The only display that   AI, airspeed, vertical speed, altitude, and autopilot status. Audio simulation featured a constant engine and wind noise, and the autopilot disconnect alert. Pilots wore noise-canceling headphones to prevent them from hearing the simulator motion system, but they could hear the autopilot disconnect alarm. A 10-inch tablet was used for the secondary (distraction) task.

Briefing and Familiarization
The tasks were performed as single-pilot crews using the left-hand seat of the simulator. Pilots were tested either in the morning (9:00-12:00 AM) or in the afternoon (1:00-4:00 PM).
Pilots were told that the experiment was about "assuming manual control after a period of sounded, wait for the AI to appear, and then roll the aircraft level using the AI. They were instructed to respond immediately when the AI appeared, as "an intuitive response was desired and reaction time would be one of the outcome turns for approximately 3 min.

Stimuli
oped and tuned with nine nonpilots (see Landman et al., 2021, for a full description of this pilot study). Advantages of this motion pro--Bles, 2008) are as follows: (1) Cues sion (i.e., pitch or yaw cues, or a pronounced be implemented in a hexapod simulator. (3) The simulator platform is upright and steady when the pilot performs the response task. The latter is important to rule out the possibility that pilots are responding to simultaneously occurring of to the leans illusion. An overview of the stimuli and the intended sensation is displayed in Figure 3.
During the entire procedure, the speed the altitude at 10,000 feet. There was also a continuous light turbulence (using a Dryden model L = 2000, V = 200; Liepmann, 1952) added to the vertical axis of the simulator throughout the whole experiment, to mask motion onsets.
The procedure started with straight and level formed a distraction task, which was a version of the Multi Attribute Task Battery (MATB-II; Santiago-Espada et al., 2011). The MATB-II was performed on a tablet attached to the surface of the center pedestal to the pilots' righthand side, which required the pilot to slightly lean and be turned to the side. The tracking task of the MATB-II was not included.
( Figure 3), during which the simulator platform was slowly (in 60 s) tilted to a roll angle of 3.5° (.06 radian [rad]), while the AI and the outside --5 rad/s 2 and a maximum angular velocity of .001 rad/s were used for prepositioning, both of which are under the human perception thresholds of .0349 rad/ s 2 and .002 rad/s, respectively (Gundry, 1977;Heerspink et al., 2005).
After the prepositioning phase, a situation was simulated of the pilot being momentarily distracted from the instruments and from the outside view. The AI and the outside vision were covered (turned black) for the next 33 s, while the platform maintained a steady roll angle of 3.5° (Figure 3). This adaptation phase was included to induce vestibular adaptation to the roll angle. According to earlier studies (e.g., Crane, 2012), prolonged exposure to a roll quent roll angle toward the opposite direction is overestimated in that direction. The adaptation phase was also required to realistically simulate a situation in which the aircraft could roll below the pilots' perceptual threshold to a new bank angle.
At the end of the adaptation phase, the autopilot disconnect alert sounded, upon which the pilot was to prepare for intervention by facing the still-covered AI and by holding the control column. Two seconds after the alert, the simulator platform was tilted back to level in 2 s, with a maximum roll rate of .03 rad/s and roll acceleration of .075 rad/s 2 . This was above the documented perceptual threshold of the vestibular system (Gundry, 1977;Heerspink et al., 2005), while it also presented tactile cues as the motion shifted the pilot in the seat. One second after this super-threshold roll cue ended, the AI was shown again. The pilot would then use the AI to immediately roll to wings level.

Conditions
The procedure described above was repeated in a number of runs, with each run featuring one of the following variations of the procedure: 1. Filler runs. The AI shown after the motion cues was banked 30° in the same direction as the super-threshold roll cue. The AI shown at 98 s in Figure 3 would thus be banked to the left. This variation was used to have the pilots gain trust in er runs, the platform remained steady and upright throughout the whole procedure and the AI shown at the end was presented wings level. This variation was included to reduce the possibility of pilots being surprised by not having to give an input in the leans-level condition described below. 2. Baseline condition runs. In this variation, the platform remained steady and upright throughout the procedure, while the AI was shown at the end with bank angle of 30° (left or right). This simulated an angle. The error rate was expected to be around lators (Beringer et al., 1975;Müller et al., 2018). 3. Leans-opposite condition runs. This variation is shown in Figure 3. The AI shown after the motion cues is banked 30° in the opposite direction situation was simulated of a subthreshold roll to a bank angle of 33.5°, followed by a super-threshold rollback to 30°. 4. Leans-level condition runs. This variation featured the same leans cues as the baseline and leansopposite runs, but the AI at the end (Figure 3; 98 s) gle of 3.5°, and then a super-threshold rollback to level. This condition was included to test whether pilots made spontaneous errors that were based directly on the leans cues, while neglecting the AI.

The pilots performed the runs in two sessions
There was a 10-min break between the sessions. subsequent 12 runs of each session, there were test conditions (i.e., baseline, leans-opposite, motion and wings-level AI) was featured in the an equal number of runs with the fast roll cue toward the left and right. Several sequences of the last 12 runs in each session were created using the Latin Square method, so that none of the test condition runs were systematically preceded by a certain type of run. Each session in all sequences ended with a test condition run, and the sequences were counterbalanced between the experience groups. Table 2 shows

Dependent Measures
The following variables were obtained in the test conditions.
Errors. away from level following AI presentation, which caused the control column to exceed 1° 2020).
Error severity. When an error was detected, the maximum bank angle deviation toward the wrong direction was measured. The initial aircraft bank angle when starting the response was subtracted.
Reaction time. This was the time between correct inputs only. If there was an initial incorrect interpretation before a correct response, there may be a moment of hesitation and starting the correct response may thus require more time.
Subjective workload of the distraction task. As a check that the distraction task jective workload of this task was rated on the NASA Task Load Index (NASA-TLX; Hart & Staveland, 1988) after each session was completed. In this scale, workload is rated separately

Hypotheses
More errors, more severe errors, and longer reaction times were expected in the leans-opposite condition than in the baseline condition, due to the leans protocol. More errors and more severe errors were expected in the leans-opposite condition compared to the leans-level condition, due to the possibility of misinterpreting the AI (i.e., experiencing a hori-dition. High experience was expected to lead to fewer and less severe errors, as well as shorter reaction times, especially in the leans-opposite condition due to fewer misinterpretations. No ings of the distraction task.

Data Analysis
tests were performed for ordinal data (error percentage), with the factors: Group (low and high experience), Condition (baseline, leans-level, interaction. For linear data (error severity Condition) analysis of variance (ANOVA) was performed. As reaction time was limited to correct responses, the leans-level condition was not included in this analysis.
Post-hoc comparisons between conditions were performed with Wilcoxon signed rank (for ordinal data) or paired-samples t-tests (for linear data). Two comparisons were performed: between the leans-opposite and baseline condition, and between the leans-opposite and leans-level condition. We corrected for two comparisons using Bonferroni correction (required p = .025).
the error frequency in the whole group in the that in the last run of each condition using a McNemar test.
Workload ratings were compared between the groups using independent-samples t-tests.

RESULTS
None of the pilots reported any motion sickness issues when asked halfway into the experiment and at the end. Table 3 shows an overview of the performance outcomes.

Errors
The GEE analysis of the error percentage 2 = 9.16, p = .002, but not for between the leans-opposite (median = 25%) Leans-level ------and baseline condition (median = 0%), Z = p = .007, and between the leans-opposite and leans-level condition (median = 0%), Z = p which the direction of the fast roll cue matched with the shown AI.
The McNemar test showed that there was a condition. Seven pilots, or 38.9%, made an p = .016. The error percentage decreased linearly over the four runs. In the baseline condition, two pilots level condition.

Error Severity
All errors are displayed in Figure 4. The severity of the errors was, as expected, highest in the leans-opposite condition ( Figure 4 and Table 3); however, no statistical test could pilots making an error in both conditions.

Reaction Time
On average, pilots responded around 2 s following the AI presentation. There was no -F(1,16) = 9.20, p = .008. The high experienced group responded on average .46 s slower than the low experience group, which was in contrast to our hypothesis.

Subjective Workload of the Distraction Task
Pilots rated the mental demand of the secondary task at 62.4 points (Table 4), which is around the midpoint of the scale (i.e., 50). The   high experience group gave higher ratings to physical demand, t(1,16) = 2.19, p = .043, and frustration t(1,16) = 2.09, p = .043, than the low experience group.

DISCUSSION
We presented pilots with a leans protocol, which featured a roll motion cue in the opposite bank direction of a subsequently shown AI. We roll to 33.5° bank, and a super-threshold rollback to 30°. In response to these cues, 38.9% of pilots ter, and 19.4% errors were made on average in higher than in the baseline condition (6.9%), which featured no roll motion cues followed by a banked AI. This indicates that the errors were indeed caused by the leans protocol. The error rate level condition (0.0%), which featured the same roll motion cue but followed by a wings-level AI. This indicates that the leans cues induced an interpretation error of the AI, and that pilots were not responding based only on what they felt. In line with previous experiments (Landman et al., 2019;Landman et al., 2020), this points towards bank angle indication.
The error rate found in this study for airline pilots is lower than that in nonpilots, whose expectation of bank angle was manipulated in a Landman et al., 2020 error rate; Landman et al., 2019). This is to be expected, considering the pilot's experience with both leans cues and reading the AI. Interestingly, the error rate in the leans-level condition was especially much lower in our pilots (0.0%) than Landman et al., 2019), indicating that pilots are more inclined to base their response on the instrument instead of on the roll motion cues. The error rate we found in our baseline condition without motion (6.9%) is similar to that in comparable conditions in (5.1%-8.7%; Beringer et al., 1975;Müller et al., 2018). Our experiment shows that the error rate in the baseline condition, even though it is already high from a safety perspective, is likely an underquickly to the AI when spatially disoriented.
When interpreting the error rates, it is important to note that we asked pilots to respond immediately, forcing them to make an intuitive response. This was done in order to simulate a response to recreate controllably in a simulated setting. The errors we found were quickly corrected and did not exacerbate into dangerous situations. Despite our instruction, pilots responded somewhat slowly (ca. 2.0 s reaction time) compared to nonpilots in a comparable experiment (ca. .5 s; Landman et al., 2020). Perhaps pilots are more inclined to respond slower as this would be a more realistic response not protect against these errors. However, the slower than the low experience group, which is the groups (Table 1; ). In contrast to nonpilots (Landman et al., 2020 pilots, as none of the pilots made an error in the fourth run. This is very promising for the use of hexapod simulators for spatial disorientation awareness training, as it suggests that pilots can ing roll cues on their responses. The long-term clear. The results indicate that, even within the limitations of a hexapod simulator, the leans can be induced without additional unrealistic cues, to such an extent that it leads to erroneous inputs even in experienced pilots who have the AI as static roll angle, distraction, and prepositioning of the simulator. The advantages compared to form is upright and steady following the cue, and that it features roll cues only. One pilot indicated that he had recently experienced the leans, and that the sensation in the simulator was highly similar. Some pilots did not consciously notice the super-threshold roll motion cues, but they still responded in line with the hypotheses. The developed leans procedure can be used to test the -(e.g., Beringer et al., 1975;Ewbank et al., 2016). However, it is important to note that the simulation has not been validated yet by comparing it In conclusion, the current experiment shows that the bank angle direction on the movingprofessional pilots expected an opposite bank direction due to the leans protocol we develsimulator leans procedure that can be used in spatial disorientation awareness training, so that pilots may experience the illusion and its con-cedure can be integrated in a more complex and

KEY POINTS
rientation (leans) cues on interpretation of the attitude indicator was investigated. For this, a new leans procedure and simulator simulator. The disorienting motion cues caused an increase in roll reversal errors by a factor of almost 3. The results show that incorrect expectations can and underline the importance of intuitive display design.
tive, can be used for spatial disorientation research simulator.