Advertisement

A Methodical Approach for Developing Valid Human Performance Models of Flight Deck Operations

  • Brian F. Gore
  • Becky L. Hooey
  • Nancy Haan
  • Deborah L. Bakowski
  • Eric Mahlstedt
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6776)

Abstract

Validation is critically important when human performance models are used to predict the effect of future system designs on human performance. A model of flight deck operations was validated using a rigorous, iterative, model validation process. The process included the validation of model inputs (task trace and model input parameters), process models (workload, perception, and visual attention) and model outputs of human performance measures (including workload and visual attention). This model will be used to evaluate proposed changes to flight deck technologies and pilot procedures in the NextGen Closely Spaced Parallel Operations concept.

Keywords

Visual Attention Visual Fixation Model Input Parameter Federal Aviation Administration Output Validation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    JPDO, Joint Planning and Development Office: Concept of operations for the next generation air transportation system. In: Joint Planning and Development Office (Ed.), vol. 3. JPDO, Washington, DC (2009)Google Scholar
  2. 2.
    Gore, B.F.: Chapter 32: Human Performance: Evaluating the Cognitive Aspects. In: Duffy, V. (ed.) Handbook of Digital Human Modeling. Taylor and Francis/CRC Press, NJ (2008)Google Scholar
  3. 3.
    Hooey, B.L., Foyle, D.C.: Advancing the state of the art of human performance models to improve aviation safety. In: Hooey, B.L., Foyle, D.C. (eds.) Human Performance Modeling in Aviation, pp. 321–349. CRC Press/Taylor & Francis, Boca Raton (2008)Google Scholar
  4. 4.
    Gore, B.F.: An emergent behavior model of complex human-system performance: An aviation surface related application. VDI Bericht 1675, 313–328 (2002)Google Scholar
  5. 5.
    Gore, B.F.: Man-machine integration design and analysis system (MIDAS) v5: Augmentations, motivations, and directions for aeronautics applications. In: Cacciabu, P.C., Hjalmdahl, M., Luedtke, A., Riccioli, C. (eds.) Human Modelling in Assisted Transportation. Springer, Heidelberg (2010)Google Scholar
  6. 6.
    Wickens, C.D., McCarley, J.M.: Applied Attention Theory. Taylor and Francis/CRC Press, Boca Raton (2008)Google Scholar
  7. 7.
    Gore, B.F., Hooey, B.L., Wickens, C.D., Scott-Nash, S.: A computational implementation of a human attention guiding mechanism in MIDAS v5. In: Duffy, V.G. (ed.) ICDHM 2009. LNCS, vol. 5620, pp. 237–246. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  8. 8.
    Arditi, A., Azueta, S.: Visualization of 2-D and 3-D aspects of human binocular vision. Paper Presented at the Society for Information Display International Symposium (1992)Google Scholar
  9. 9.
    Ericsson, K.A., Kintsch, W.: Long-term working memory. Psychological Review 102(2), 211–245 (1995)CrossRefGoogle Scholar
  10. 10.
    Gugerty, L.: Evidence from a partial report task for forgetting in dynamic spatial memory. Human Factors 40(3), 498–508 (1998)CrossRefGoogle Scholar
  11. 11.
    Fitts, P.M.: The information capacity of the human motor system in controlling the amplitude of movement. Journal of Experimental Psychology 47, 381–391 (1954)CrossRefGoogle Scholar
  12. 12.
    Gore, B.F., Hooey, B.L., Haan, N., Socash, C., Gacy, M., Wickens, C.D., et al.: Evaluating NextGen Closely Spaced Parallel Operations Concepts with Human Performance Models. NASA Ames Research Center, Moffett Field (2011)Google Scholar
  13. 13.
    Keller, J.W., Leiden, K., Small, R.: Cognitive task analysis of commercial jet aircraft pilots during instrument approaches for baseline and synthetic vision displays. In: Foyle, D.C., Goodman, A., Hooey, B.L. (eds.) Aviation Safety Program Conference on Human Performance Modeling of Approach and Landing with Augmented Displays (NASA/CP-2003-212267). NASA Ames Research Center, Moffett Field (2003)Google Scholar
  14. 14.
    Gore, B.F., Hooey, B.L., Salud, E., Wickens, C.D., Sebok, A., Hutchins, S., Koenecke, C., Bzostek, J.: Identification Of Nextgen Air Traffic Control and Pilot Performance Parameters for Human Performance Model Development in the Transitional Airspace. In: NASA Final Report. ROA 2006 NRA # NNX08AE87A, SJSU, San Jose (2009)Google Scholar
  15. 15.
    Campbell, G.E., Bolton, A.E.: HBR validation: interpreting lessons learned from multiple academic disciplines, applied communities, and the AMBR project. In: Gluck, K.A., Pew, R.W. (eds.) Modeling Human Behavior with Integrated Cognitive Architectures: Comparison, Evaluation and Validation, pp. 365–395. Lawrence Erlbaum & Associates, New Jersey (2005)Google Scholar
  16. 16.
    McCracken, J.H., Aldrich, T.B.: Analysis of Selected LHX Mission Functions: Implications for Operator Workload and System Automation Goals (Technical note ASI 479-024-84(b)). Anacapa Sciences, Inc. (1984)Google Scholar
  17. 17.
    Hamilton, D.B., Bierbaum, C.R.: Operator Workload Predictions for the Revised AH-64A Workload Prediction Model: Volume I: Summary Report (AD-254 198). Anacapa Sciences, Inc., Alabama (1992)Google Scholar
  18. 18.
    Hooey, B.L., Foyle, D.C.: Aviation Safety Studies: Taxi Navigation Errors and Synthetic Vision System Operations. In: Hooey, B.L., Foyle, D.C. (eds.) Human Performance Modeling in Aviation, pp. 321–349. CRC Press/Taylor & Francis, Boca Raton (2008)Google Scholar
  19. 19.
    Anders, G.: Pilot’s Attention Allocation during Approach and Landing:  Eye- and Head-Tracking Research in an A330 Full Flight Simulator. In: Proceedings of the 11th International Symposium on Aviation Psychology, Columbus, OH, USA (2001)Google Scholar
  20. 20.
    Mumaw, R.J., Sarter, N., Wickens, C.D.: Analysis of pilots’ monitoring and performance on an automated flight deck. In: Proceedings of the 11th International Symposium on Aviation Psychology. The Ohio State University, Columbus (2001)Google Scholar
  21. 21.
    Hüettig, G., Anders, G., Tautz, A.: Mode Awareness in a modern Glass Cockpit – Attention Allocation to Mode Information. In: Proceedings of the 10th International Symposium on Aviation Psychology, Columbus, OH, USA (1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Brian F. Gore
    • 1
  • Becky L. Hooey
    • 1
  • Nancy Haan
    • 2
  • Deborah L. Bakowski
    • 1
  • Eric Mahlstedt
    • 1
  1. 1.San Jose State University at NASA Ames Research CenterMoffett Field
  2. 2.Dell Services Federal GovernmentMoffett Field

Personalised recommendations