Assessing situation awareness in multitasking supervisory control using success rate of self-terminating search

The purpose of this study is to investigate measuring situation awareness (SA) by using the success rate of self-terminating visual search (STVS) in a multitasking supervisory control environment. Currently, many researchers have focused on developing unobtrusive SA metrics in a multitasking environment. Although some of the advanced eye-tracking metrics can estimate the operator's SA during a task, certain methodological issues remain for measuring SA in a supervisory control and multitasking environment. In this study, participants performed a distributed control task with the multi-attribute task battery. To measure the participant's SA, situation awareness global assessment technique (SAGAT) was used during the experiment. SA performance was compared to the success rate of STVS. An eye-head integrated tracking system was used to measure the rate of STVS based on the participants' eye movements and head positions in different monitoring conditions. The results showed that task-switching activity was influenced by salient features in a display. It causes a significant difference on SA between different monitoring conditions, and the difference is also monitored in the success rate of STVS. Furthermore, the study found that the attention level in visual searching influences situational awareness in a supervisory control environment. The findings from this study suggest that the success rate of STVS could be used as a new metric for measuring SA related to the visual perception of the elements in a multitasking supervisory control environment.