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Developing an Improved ACT-R Model for Pilot Situation Awareness Measurement
- Source :
- IEEE Access, Vol 9, Pp 122113-122124 (2021)
- Publication Year :
- 2021
- Publisher :
- IEEE, 2021.
-
Abstract
- According to a previously built situation-awareness (SA) model based on attention allocation, with the ACT-R (Adaptive Control of Thought, Rational) theory for analyzing pilot cognitive processes for situation elements, an SA mathematical model was improved to predict pilot SA during exposure to different display interfaces and missions. An indicator-display monitoring task was performed under different experimental conditions for SA model verification, while the SA global assessment technique (SAGAT), performance measures, 10-dimensional SA rating technique (10-D SART), and eye movement measures were adopted to comprehensively assess the operator’s SA. The experimental results revealed that theoretical prediction values calculated using the improved SA model were strongly correlated with the operation performance, and thus confirming the model validation. The SAGAT was shown to be a more effective method than SART in this research, and the overall SAGAT accuracy rate, as well as the accuracy response time, are effective indices for SA measurement. Eye-movement indices, such as the fixation/saccade ratio, which corresponds to the mode of information perception and extraction, was examined to be sensitive to operator’s SA changes. The Advances of the improved SA model have been achieved in predicting and indicating SA by using human behaviors, including operation performance, SAGAT response behaviors, and visual behaviors. Thereby, it provides a new auxiliary tool for quantitative characterization of pilot’s SA during cockpit interface design optimization and ergonomic evaluation.
Details
- Language :
- English
- ISSN :
- 21693536
- Volume :
- 9
- Database :
- Directory of Open Access Journals
- Journal :
- IEEE Access
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.7925237a854192a3b162ddedbcfd4d
- Document Type :
- article
- Full Text :
- https://doi.org/10.1109/ACCESS.2021.3108438