Evaluation of the impact of data communications equipage level on air traffic controller workload using the functional near infra-red imaging technique

• Main Authors: Willems, Ben, Hah, Sehchang, Schulz, Ken
• Format: Conference Proceeding
• Language: English
• Subjects: Air traffic control; Aircraft; Atmospheric modeling; Brain; Data communication; Radar; Workstations
• ISSN: 2155-7195; 2155-7209
• DOI: 10.1109/DASC.2011.6096107

The Federal Aviation is modernizing the National Airspace System to accommodate an anticipated growth and diversification of air traffic. Several technologies are necessary to move from the current air traffic control system to the Next Generation Air Transportation System (NextGen). One of these technologies, Data Communications, will move the air traffic control system from a mostly voice-based communications environment to a digital environment. In this digital environment, voice- based communications will still be in use for time- critical situations, but text-based communications will be available for most other situations. Such a drastic shift in operations potentially poses technical challenges and human factors issues. Technical challenges include the need to design highly reliable systems that allow controllers to rely on the availability of the Data Comm system while providing an acceptable response time. Human factors challenges include the integration of Data Comm messaging in controller tasks, the provision of more information without creating clutter, and providing more automation without increasing workload or reducing situation awareness. In earlier studies, we found that the availability of a high percentage of Data Comm equipped aircraft in the en route environment resulted in a large reduction of subjective workload even at high traffic levels. In the current study we manipulated the percentage of equipped aircraft at constant traffic levels to determine if the reduction in workload is present at other equipage levels. We collected subjective workload ratings and physiological measures of cognitive workload.