An event-related potential (ERP)-based brain–computer interface (BCI) can be used to monitor a user’s cognitive state during a surveillance task in a situational awareness context. The present study explores the use of an ERP-BCI for detecting new planes in an air traffic controller (ATC). Two experiments were conducted to evaluate the impact of different visual factors on target detection. Experiment 1 validated the type of stimulus used and the effect of not knowing its appearance location in an ERP-BCI scenario. Experiment 2 evaluated the effect of the size of the target stimulus appearance area and the stimulus salience in an ATC scenario. The main results demonstrate that the size of the plane appearance area had a negative impact on the detection performance and on the amplitude of the P300 component. Future studies should address this issue to improve the performance of an ATC in stimulus detection using an ERP-BCI.

The aim of this paper is to explore the potential challenges associated with contextualizing handover instructions between different stakeholders in the context of a remotely piloted aircraft. The difficulty of synthesizing pilots' exchanges has already been highlighted. In this study, the operational framework focuses on both the construction of representations and narrative discourse to synthesize the situation. To conduct this study, subjects participated in an experiment in which they were asked to place themselves in a handover situation as an incoming and as an outgoing party. This study has made it possible to identify different strategies for constructing the representation of the situation and for transmitting instructions to contextualize an operation. Using an information gathering analysis method, it is possible to assess not only the relevant elements of the context, but also the narrative progression of these elements in the discourse. This is part of the development of an automated assistant that mediates the sequence and, more generally, the contextualization between two human operators or between a human operator and an artificial agent. Those primary results are the first step towards appropriate standardized protocols and checklists, the implementation of technological solutions such as automation and digital communication systems to improve situational awareness and communication skills. The aim is to identify and apply generic strategies that can be used as a framework for the automated development of effective handover protocols in future UAMs, piloted or remoted-piloted aircraft and other flight operations, contributing to safer and more efficient flight operations.

OLIVIA (OperationaL Intentions adVIser for Aviation) was developed in the HAIKU project. It is a flight deck tool providing support to mission-level decisions in complex situations by assessing and prioritizing route options according to operational intentions. It uses Artificial Intelligence to translate (1) operational intentions from pilots to route generation and optimization inputs and (2) route proposal KPIs into operational intention assessments. This paper reports on the final development of OLIVIA, the results from the human-in-the-loop experiments, and insights and recommendations regarding the development of similar assistants for the flight deck.