Macroscopic Capacity Model with Individual Sector Closing Speed Estimates

Abstract

Reliable airspace capacity estimates are important both for operational air traffic management and for airspace design. Air traffic management relies on manual procedures. Hence, controller workload determines the capacity of most sectors. Yet the current operational model for estimating capacity in United States airspace does not account for workload from conflict avoidance tasks. Aircraft closing speeds and airspace separation standards determine the rate of aircraft conflicts. Numerically, conflict workload intensity is the product of the conflict rate and the mean controller time required to service a conflict. As workload intensity approaches unity, the sector reaches capacity. We determine unknown model parameters by fitting capacity calculations against peak traffic observations for en route sectors. The result is an analytical model for capacity that is more accurate than the current operational model. The mean closing speed of all pairs of aircraft in a volume of airspace determines the conflict rate. This paper reports an effort to refine the conflict component of the model by replacing its original global closing speed estimate with local traffic-based closing speed estimates for individual sectors. Exact calculation of mean closing speed requires full position and velocity information for all flight tracks. The database that we used to obtain the peak traffic counts includes initial heading, speed, and altitude fields for all traffic entering a sector. Without positional coordinates and intersector track information, these data fields provide only crude closing speed estimates. We examined these estimates as possible indicators of sector route and altitude complexity in the New York Center. Individual sector closing speed estimates based on these observations did not improve the model fit for the 30 New York sectors.