Explicit or implicit situation awareness? Situation awareness measurements of train traffic controllers in a monitoring mode

Abstract

Railway traffic control faces the challenge of ensuring a high infrastructure capacity to maintain a constant train traffic flow. The current study assesses the situation awareness (SA), as a predictor of decision-making, of train traffic controllers to gain novel insights in their cognition. This study puts emphasis on levels of implicit and explicit situation awareness in a monitoring mode, through measures of SAGAT, MARS and performance. A human-in-the-loop simulator, called the PRL game is used to simulate the workspace of train traffic controllers. Initial findings indicate rather low levels of explicit SA, on the contrary to higher subjective SA scores through MARS and observer ratings, and a high performance on the punctuality and unplanned stops of trains. © 2014 Springer International Publishing.