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Ergonomics Evaluation of Large Screen Display in Cockpit Based on Eye-Tracking Technology

  • Yanyan Wang
  • Qingfeng Liu
  • Wanli Lou
  • Duanqin Xiong
  • Yu Bai
  • Jian Du
  • Xiaochao GuoEmail author
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 527)

Abstract

Eye-tracking technology was used to study the visual sensitive area and the ergonomics of commonly used information encoding methods in large screen primary flight display (PFD) in order to optimize the interface design. Methods A total of 44 pilots (36 ± 6 years) attended the experiment. Seven typical flight human–machine interface images were adapted according to varied factors such as 12 quadrants, 6 colors, and 10 presentation encodings which would affect the ergonomics design. The pilots were asked to search a target picture with full information intercepted from the typical images, and the eye tracker was used to record the eye movement data during the task. The performance differences were analyzed among factors. Results The results of multivariate test showed that: (1) There are significant differences between 12 quadrants and 7 typical pictures (P < 0.01), and the interaction effect between pictures and quadrants is significant (P < 0.01). (2) There were significant differences among the 6 colors, 7 typical pictures, and 12 quadrants groups (P < 0.01); and the interaction among three factors were significant (P < 0.01). (3) There were significant differences among the 10 presentation encodings, 7 typical pictures, and 12 quadrants (P < 0.01). The interaction among three factors was significant (P < 0.01). Conclusion (1) The visual sensitive area of the large screen primary flight display is quadrant 1, 5, 7; the area of visual insensitivity is 10, 12. (2) According to colors, red was the optic color, yellow and green were the worst color. (3) According to presentation encodings, white character with white borders and white character with red shading borders are optic encoding, and black character with yellow borders and green shading was the worst.

Keywords

Eye-tracking technology Man–machine interface Ergonomics Primary flight display 

References

  1. 1.
    Kaber DB, Alexander AL, Stelzer EM, Kim SH, Kaufmann K, Hsiang SM (2008) Perceived clutter in advanced cockpit displays: measurement and modeling with experienced pilots. Aviat Space Environ Med 79:1007–1018CrossRefGoogle Scholar
  2. 2.
    Duchowski A (2007) Eye tracking methodology: theory and practice. Springer, New YorkzbMATHGoogle Scholar
  3. 3.
    Moacdieh NM, Sarter NB (2012) Eye tracking metrics: a toolbox for assessing the effects of clutter on attention allocation. Proc Hum Factors Ergon Soc Ann Meet 56(1):1366–1370CrossRefGoogle Scholar
  4. 4.
    Moacdieh NM, Prinet JC, Sarter NB (2013) Effects of modern primary flight display clutter evidence from performance and eye tracking data. Proc Hum Factors Ergon Soc Ann Meet 57(1):11–15CrossRefGoogle Scholar
  5. 5.
    Treisman AM, Gelade G (1980) A feature-integration theory of attention. Cog Psych 12:97–136CrossRefGoogle Scholar
  6. 6.
    TullisT S (1981) An evaluation of alphanumeric, graphic, and color information displays. Hum Factors 23(5):541–550CrossRefGoogle Scholar
  7. 7.
    Schum DA (1991) The weighting of testimony in judicial proceeding from sources having reduced credibility. Hum Factors 33(2):172–182CrossRefGoogle Scholar
  8. 8.
    Yeh M, Wickens CD (2001) Attentional filtering in the design of electronic map displays: a comparison of color coding, intensity coding, and decluttering techniques. Hum Factors 43(4):543–562CrossRefGoogle Scholar
  9. 9.
    Eckstein MP, Thomas JP, Palmer J, Shimozaki SS (2000) A signal detection model predicts the effects of setsize in visual search accuracy for feature, conjunction and disjunction displays. Percept Psychophys 62(3):425–451CrossRefGoogle Scholar
  10. 10.
    Backs RW, Walrath LC (1992) Eye movement and pupillary response indices of mental workload during visual search of symbolic displays. Appl Ergon 23:243–254CrossRefGoogle Scholar
  11. 11.
    Kasarsikis P, Stehwien J (2001) Comparison on expert and novice scan behaviors during VFR flight. In: The 11th international symposium on aviation psychology. The Ohio University, Columbus, pp 1–6Google Scholar
  12. 12.
    Schriver AT, Morrow DG, Wickens CD, Talleur DA (2008) Expertise differences in attention strategies related to pilot decision making. Hum Factors 50(6):864–878CrossRefGoogle Scholar
  13. 13.
    Guo X, Xiong D, Xiong Y, Yi L, Ma X (2007) Effects of the display formats on pilots’ cognitive performance with head-up display velocity, height and heading information in fighter. Chin J Aviat Med 18(2):84–90Google Scholar
  14. 14.
    Kim B, Dong Y, Kim S et al (2007) Development of integrated analysis system and tool of perception, recognition and behavior for web usability test: with-emphasis on eye-tracking,mouse-tracking and retrospective think aloud. In: Kim B (ed) Usability and internationalization. Springer, Berlin, pp 113–121Google Scholar
  15. 15.
    Gould JD, Peeples DR (1970) Eye movements during visual search and discrimination of meaningless, symbol, and object patterns. J Exp Psychol 85(1):51–55CrossRefGoogle Scholar
  16. 16.
    Damin Zhuang, Rui Wang (2003) Research of target identification based on cognitive characteristic. J Beijing Univ Aeronaut Astronaut 29(11):1051–1054 (in Chinese)Google Scholar
  17. 17.
    Narborough-Hall, Niebur E (2004) Texture contrast attracts overt visual attention in natural scenes. Eur J Neurosci 19(3):783–789CrossRefGoogle Scholar
  18. 18.
    Tinker MS (1958) Recent studies of eye movements in reading. Psychol Bull 55(4):215–231CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Yanyan Wang
    • 1
    • 2
  • Qingfeng Liu
    • 1
    • 2
  • Wanli Lou
    • 3
  • Duanqin Xiong
    • 2
  • Yu Bai
    • 2
  • Jian Du
    • 2
  • Xiaochao Guo
    • 2
    Email author
  1. 1.Beihang UniversityHaidian District, BeijingChina
  2. 2.Institute of Aviation Medicine PLAAFBeijingChina
  3. 3.Air Force Flight Test BureauXi’anChina

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