Continuous evolution of HMIs is necessary to keep operators in an optimal situation. In this context, we consider mental representations (MR) mobilized by operators as key elements for decisionmaking. Capturing and analysing these representations is not easy with existing tools. We propose a specific method (i.e. "MERIA" for Mental Representation Impact Analysis). Our case study focuses on a group of first officer (Airbus A320) in a dynamic situation with high time pressure. We are interested in cases where the HMI generates MRs that are inconsistent with the situation, resulting in a discrepancy between the prescribed activity and the actual activity. The goal is to identify the link between erroneous MR and the interface that created them. Our modelling structure allows us to create this link and place it in a proper temporal context. We observe that the constitution of the MR is different from one subject to another. However, invariants in the appearance of some erroneous MR make it possible to attribute the causality to an interface element well-defined in space and time. Thus, this analysis allows us to offer recommendations for HMI design to improve decision making. Our results show that the improvement does not lie in a drastic modification of the interfaces. Rather is allows a synchronization of the data coming from the cockpit with the pilot’s MR of those data.
& Andre, J.
(2019). A New HMI Evaluation Method (Meria) Based on Pilot's Mental Representations. 20th International Symposium on Aviation Psychology, 355-360.