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Visual Scan Patterns During Simulated Control of an Uninhabited Aerial Vehicle (UAV)

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Date 2004 Jun 17
PMID 15198280
Citations 1
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Abstract

Background: This study investigated pilots' visual scan patterns on an uninhabited aerial vehicle (UAV) flight display that used moving textbox symbology to emulate vertical moving pointers for the primary flight instruments.

Methods: Eye tracking measurements were recorded for five instrument-rated pilots. Dwell frequencies and mean dwell times were calculated for each instrument. The efficiency of instrument information presentation was evaluated based on mean dwell times and dwell histograms. The heading indicator, a strict digital readout, was used as the reference for pair-wise comparison with the moving textbox instruments.

Results: Instrument dwell frequencies differed significantly (p < 0.005, alpha = 0.006) with the attitude indicator being the most frequently scanned instrument followed by the vertical speed indicator, then the airspeed, heading, and altitude indicators. There was no difference in mean dwell times (p = 0.04-0.79, alpha = 0.008) or dwell histograms between the heading indicator and the primary moving textbox instruments. Pilot scan behavior was not significantly affected (p > 0.17) by workload. Also, subjects and historical controls did not differ (p > 0.30) in their frequency of engine instrument dwells.

Conclusion: The dwell frequencies for the primary flight instruments, particularly the vertical speed indicator, differed from those reported for more traditional aircraft. The moving textboxes required visual fixations that were typical of quantitative instruments, which is a cognitively inefficient way to present information. Pilots failed to increase engine instrument dwells in the absence of non-visual cues of engine performance, making them potentially vulnerable to missing early changes in engine performance.

Citing Articles

Designs and Algorithms to Map Eye Tracking Data with Dynamic Multielement Moving Objects.

Kang Z, Mandal S, Crutchfield J, Millan A, McClung S Comput Intell Neurosci. 2016; 2016:9354760.

PMID: 27725830 PMC: 5048099. DOI: 10.1155/2016/9354760.