An investigative study into the use of eye-tracking technology and human-machine-interface as an alert trigger for air traffic controllers

• Main Author: Koh, Benjamin Jia Hao
• Other Authors: Lye Sun Woh
• Format: Final Year Project
• Language: English
• Published: 2019
• Subjects: DRNTU::Engineering::Mechanical engineering
• Online Access: http://hdl.handle.net/10356/77994
• Institution: Nanyang Technological University

With the air traffic demand expected to grow exponentially and an increasing sophisticated air route structure, Air Traffic Controllers (ATCOs) are expected to constantly deliver albeit the addition external workload. Past incident reports have identified that if alert triggers were in place, ATCOs would be able to better respond to situation and the average workload can be lightened. Past research studies have discovered that there is indeed a positive correlation between alert trigger parameters with eye-tracking and Human-Machine-Interface (HMI) metrics. However, these past researches tend to be limited by airspace complexity criteria and that it does not encompass a macroscopic approach of airspace factor. This project aims to investigate the use of eye-tracking and HMI inputs parameters as a basis of accentuating abnormalities and hence provide an alternative approach in deriving an alert trigger. Fixation count and fixation duration on the aircraft from the eye tracker, as well as the number of aircraft label selected (SAA) from HMI inputs was used as the metric for this study. It was found that the use of these parameters in the fifteen-minute block analysis was able to capture and accentuate details to a great value than compared to the one-hour block analysis. Furthermore, differences between ATCOs with different level of expertise were clear when these parameters were intervolved with one another. This would provide the foundation for future development in predictive aids to help ATCOs in maintaining the safety of every airspace regardless of workload with utmost confidence.