In innovating and designing new concepts in the railway sector, the Dutch railway infrastructure manager ProRail uses different types of simulations to identify and tackle possible bottlenecks in future infrastructure design. Computer simulation tools are used in earlier stages of the design process, followed by the application of gaming simulations where the design is fine tuned together with railway traffic operators before it is put into operation. This study focuses on providing insights into the use of a human-in-the-loop simulator in which an organizational research question investigates the impact of multiple geographical workspace designs, while in parallel human factors research is conducted to investigate the concept of team situation awareness from an academic research interest. Finding a balance between the practical and academic implications in one research design and its findings does not rely on a trivial approach. The current article aims to contribute on several levels: (1)to illustrate the balance between research for practice and research for academia through the applications of gaming simulations; (2)to illustrate the use of gaming simulations for railway traffic operations and (3)to provide insights in team SA development in railway traffic operations using gaming simulations.

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.