Using Eye-Tracking for Adaptive Human-Machine Interfaces for Pilots: A Literature Review and Sample Cases

Abstract This paper explores the potential of eye-tracking technology in adaptive human-machine interfaces for pilots in aviation. We argue that an interface able to adjust its layout and elements based on pilots’ real-time eye-tracking data can prevent errors and enhance their performance. The study presents a literature review on the use of eye-tracking for various pilot cases, including flight simulator games, drone pilots, and cockpit pilots. Results in most cases showed that eye-tracking has been employed to improve interactions, enhance spatial awareness, guide pilots’ gaze to relevant areas, and provide insights into pilots’ information processing and task load. The paper discusses two sample cases demonstrating the potential of eye-tracking in adaptive human-machine interfaces. In the first case, during challenging drone simulations, eye-tracking identified areas where an adaptive human-machine interface could aid navigation and reduce cognitive load. In the second one, based on real drone flights, when signal loss incidents occurred, eye-tracking data showed that the interface should adapt to pilots’ needs by providing critical information to help them to improve situational awareness. The paper concludes that eye-tracking technology has significant potential in adaptive human-machine interfaces for aviation, emphasising the importance of refining these technologies to meet pilots’ specific needs and enhance flight safety.