Modern cockpit environments present pilots with an overwhelming volume of visual information, increasing cognitive workload and the risk of critical cues being overlooked. This study explores an adaptive human-machine interface designed to enhance pilot situational awareness using real-time eye-tracking data. By dynamically adjusting visual elements based on gaze behavior, the system ensures that essential information remains within the pilot’s attentional focus.

The developed system integrates a Tobii eye tracker with a Python-based interface, featuring a dynamic map display with NATO-standard symbology. Initially, pilots interacted with a standalone eye-tracking interface, but trials revealed that the task was too simple, leading to a revised experimental setup. A dual-screen configuration was implemented, with Microsoft Flight Simulator providing realistic flight scenarios while the adaptive system tracked and responded to pilots' gaze patterns. If a pilot failed to fixate on a critical object for a predefined duration, the interface introduced visual alerts to redirect attention.

A certified pilot trainer evaluated the system and highlighted key improvement areas, including modifying alert mechanisms and optimizing screen arrangement for ecological validity. Based on this feedback, a refined system design was proposed, incorporating auditory and visual enhancements and a vertically stacked screen layout to better align with cockpit ergonomics.

Findings support the integration of adaptive eye-tracking interfaces in aviation, demonstrating their potential to improve situational awareness, reduce workload, and enhance decision-making. Future research will focus on refining adaptation strategies and evaluating long-term usability in operational environments.