Explicit or implicit situation awareness? Measuring the situation awareness of train traffic controllers

Previous research on situation awareness (SA) predominantly focused on its explicit, reasoned, conscious features rather than on the implicit, intuitive, unconscious aspects that are often identified with expert operators. This research investigated implicit levels of SA of train traffic controllers (TTCs) in order to contribute to the body of knowledge on rail human factors research and SA. A novel approach was used to uncover levels of implicit SA through a set of three analyses: (1) fairly low SAGAT values with correlations between SAGAT scores and multiple performance indicators; (2) negative correlations between work experience and SAGAT scores; and (3) structurally lower level-1 SA (perception) scores in comparison to level-2 SA (comprehension) scores in accordance with Endsley's three-level model. Two studies were conducted: A pilot study which focused on SA measurements with TTCs in a monitoring mode (N = 9) and the main study, which involved TTCs from another control center (N = 20) and three different disrupted conditions. In the pilot study, SA was measured through the situation-awareness global assessment technique (SAGAT), perceived SA and observed SA, and performance was measured through punctuality and unplanned stops of trains before red signals. In the main study, SA was measured through SAGAT, and perceived SA and multiple performance indicators, such as arrival and departure punctuality and platform consistency, were assessed. In both studies, the set of three analyses showed consistent and persistent indications of the presence of implicit SA. Endsley's three-level model and related SAGAT method can be constrained by the presence of these intuitive, unconscious processes and inconsistent findings on correlations between SAGAT scores and performance. These findings provide insights into the SA of TTCs in the Netherlands and can support the development of training programs and/or the design of a new traffic management system. (C) 2016 Elsevier Ltd. All rights reserved.