Improving Bank Angle Representation on the Primary Flight Display Using Static Monocular Depth Cues

Evaluating the effect of static monocular depth cues on attitude indicator interpretation using misleading motion cues

Master thesis (2024)

Authors

C. Van Droogenbroeck Aerospace Engineering

Contributors

H.M. Landman (supervisor 1)
O. Stroosma (supervisor 1)
Max Mulder (supervisor 1)
M.M. van Paassen (supervisor 1)
Faculty
Aerospace Engineering
Copyright: © 2024 Chloë Van Droogenbroeck
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Published Date

13-02-2024

Language

English

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Faculty

Aerospace Engineering

Abstract

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.