Determining the value of information for minimizing controller taskload: A graph-based approach

In the future, air traffic controllers will most likely come to rely on decision-support tools and increased levels of automation to help manage and separate aircraft. Conflict detection and conflict resolution are examples of two key areas where increased automation and improved accuracy are considered imperatives to the future efficiency of airspace systems. The inclusion of decision-support tools for conflict-detection and resolution is expected to reduce controller workload by decreasing the mental stress associated with identifying potential conflicts and maintaining aircraft separation. Despite the benefits of such systems, there has been little study into the best methods to implement conflict-detection and resolution algorithms in practice, and what is the resulting controller taskload. In this paper, we examine how the capabilities and implementation strategy of conflict-detection and resolution tools affect controller taskload. Our goal is to understand how conflict-detection and resolution decision-support tools can best be designed and implemented to support human-based control of aircraft.