Predicting Sector Capacity under Severe Weather Impact for Traffic Flow Management

Abstract

Sector capacity is dependent on the complexity of the traffic flows within the sector, as well as the presence or absence of hazardous weather. It is well-accepted that the sector capacity must be reduced when an area of severe weather overlaps part of the sector. However, no accepted algorithms for calculating the capacity under severe weather impact have been developed. This paper presents an approach to predict sector capacity under severe weather impact for airspace congestion management. The nominal sector capacity is predicted as a function of traffic flow patterns to capture the traffic complexity. Under severe weather impact, pilot deviation behavior models developed by Lincoln Laboratory are applied to identify the weather avoidance altitude field in the sector. Graph theory is applied to decide the available ratio of flow capacity. Given the predicted traffic flow pattern and the available capacity ratio of each flow, the nominal sector capacity is reduced based on the combination of the flows in the predicted traffic flow pattern. Results are presented for an example sector with example weather impact.