A Predictive Model of Situation Awareness with ACT-R

Abstract

Objective: The aim of this study is to model all levels of situation awareness (SA), which would be able to predict situation awareness quantitatively.BR Background: When measuring situation awareness, directly measuring SA methods such as SAGAT and SART have been utilized. Several approaches (cognitive modeling approaches) were introduced to model SA but level 3 SA was not completed. For real-life situation, however, it is necessary to detect the problematic level of SA rather than overall SA. Therefore, we proposed a new model of all levels of SA in this study.BR Method: In order to model all levels of SA, this study chose factors in ACT-R architecture through literature review. ATC (Air Traffic Control)-related simulation task was video-taped to analyze human behaviors in order to model all levels of SA including level 3.BR Results: As a result, regression analyses show that cognitive activities (neural activations) represented for all levels of SA were highly correlated with SAGAT.BR Conclusion: In conclusion, neural activations in ACT-R could be proved to be effective to model all levels of SA.BR Application: Our SA model could be used to predict all levels of SA quantitatively without directly measuring the SA of operators.