Document Type
Conference Paper
Publication Date
2012
Publication Title
Selected Papers Presented at MODSIM World 2011 Conference and Expo
Pages
190-199
Conference Name
MODSIM World 2011 Conference and Expo, October 11-14, 2011, Virginia Beach, Virginia
Abstract
A task overload condition often leads to high stress for an operator, causing performance degradation and possibly disastrous consequences. Just as dangerous, with automated flight systems, an operator may experience a task underload condition (during the en-route flight phase, for example), becoming easily bored and finding it difficult to maintain sustained attention. When an unexpected event occurs, either internal or external to the automated system, the disengaged operator may neglect, misunderstand, or respond slowly/inappropriately to the situation. In this paper, we discuss an approach for Operator Functional State (OFS) monitoring in a typical aviation environment. A systematic ground truth finding procedure has been designed based on subjective evaluations, performance measures, and strong physiological indicators. The derived OFS ground truth is continuous in lime compared to a very sparse estimation of OFS based on an expert review or subjective evaluations. It can capture the variations of OFS during a mission to better guide through the training process of the OFS assessment model. Furthermore, an OFS assessment model framework based on advanced machine learning techniques was designed and the systematic approach was then verified and validated with experimental data collected in a high fidelity Boeing 737 simulator. Preliminary results show highly accurate engagement/disengagement detection making it suitable for real-time applications to assess pilot engagement.
Rights
"Distribution/Availability Statement: Unclassified-Unlimited"
Original Publication Citation
Zhang, G., Wang, W., Pepe, A., Xu, R., Schnell, T., Anderson, N., Heitkamp, D., Li, J., Li, F., & McKenzie, F. (2012). In Selected papers presented at MODSIM World 2011 Conference and Expo (pp. 190-199). NASA Center for AeroSpace Information.
Repository Citation
Zhang, Guangfan; Wang, Wei; Pepe, Aaron; Xu, Roger; Schnell, Tom; Anderson, Nick; Heitkamp, Dean; Li, Jiang; Li, Feng; and McKenzie, Frederick, "A Systematic Approach for Real-Time Operator Functional State Assessment" (2012). Electrical & Computer Engineering Faculty Publications. 363.
https://digitalcommons.odu.edu/ece_fac_pubs/363
ORCID
0000-0003-0091-6986 (Li)
Included in
Aviation Safety and Security Commons, Management and Operations Commons, Navigation, Guidance, Control and Dynamics Commons