Tower Controllers' Assessment of the Spot and Runway Departure Advisor (SARDA) Concept

Airports are often a capacity-limiting constraint for the rest of the National Airspace System (NAS). A recent effort investigated methods to improve surface operations by supplying optimized scheduling and sequencing advisories for the Ground and Local controllers working at Air Traffic Control Towers. The tool is collectively known as the Spot and Runway Departure Advisor (SARDA). A series of high fidelity human-in-the-loop simulations was conducted to assess scheduling performance and their effects on the human operators. This paper documents the impact of the advisories on controllers' workload, situation awareness (SA), and usability. Fifty-six high fidelity human-in- the-loop simulations were conducted using a matrix of traffic level (normal and high) and advisory display formats (data tag and timeline). Results revealed that the high traffic level increased perceived workload for both Ground and Local controllers. Local and Ground controllers also reported a decrease in subjective SA in the high traffic condition. There was no significant effect of traffic level or advisory usage on the objective SA measure, although their interaction was statistically significant. For Ground, objective SA decreased in the high traffic but not during the normal traffic level. Ground controllers showed a preference for using the timeline format by reducing scans for information and aiding with future planning. Feedback also revealed that future work should focus on harmonization between the optimization model and the human planning model, thus providing a transparent planning and execution strategy. Keywords-component; surface scheduler; optimizer; airport simulator; human factors; workload; situation awareness; usability