Temporal and Spatial Distribution of Airspace Complexity for Air Traffic Controller Workload-Based Sectorization

*† We develop an Air Traffic Controller (ATC) workload-based methodology for airspace sectorization. As an initial step, we partition the US National Airspace into three layers with different altitude ranges. The range of each layer is based on the operational levels in low, high, and ultra-high airspace. Each layer is further tiled to 2,566 hexagonal cells (hex-cells) with 24 nautical mile sides. These hex-cells are assumed to be the finite elements of airspace and ATC workload is modeled for each hex-cell using various airspace metrics. We simulate a one-day scenario of the entire National Airspace System (NAS) and calculate the ATC workload for each hex-cell. Furthermore, we apply new visualization techniques to analyze the temporal and spatial distribution of the controller workload. Having the workload values for each cell for the entire day, we develop clustering algorithms using optimization theory to cluster cells and construct sectors. Our effort concentrates on simulation as a means to evaluate cognitive workload for the elements of airspace regardless of current sector and center boundaries.