Towards a sensitive measure of situation awareness in adaptively automated systems

Abstract

The objective of this research was to assess the effectiveness of the Situation Awareness Global Assessment Technique (SAGAT) as an indicator of automation state changes in adaptive automation (AA) of a complex, dynamic control task. An air traffic control (ATC)-related simulation was developed to present automation of four different information processing (IP) functions, including information acquisition, information analysis, decision making, and action implementation, as well as to simulate a completely manual control condition. Eight participants operated the ATC simulation under the five conditions. SAGAT data revealed only a general effect of automated versus manual control, but no significant effects of the modes of AA on SA. These results suggested that SAGAT was not a sensitive measure in the ATC-related task. Consequently, a modified SAGAT measure is proposed with relevance weighting of environmental stimuli to promote sensitivity and reliability of measurement of SA in the target domain.