Predicting Congestion in the Northeast U.S.: A Search for Indicators

Abstract

The Northeast U.S. is arguably the most congested airspace in the world. Four major New York airports have very high total operations counts and are concentrated geographically. Improvements are needed for traffic managers’ decision support systems to support proactive intervention leading to smoother arrival flows. A team at The MITRE Corporation’s Center for Advanced Aviation System Development (CAASD) addressed this issue by investigating predictive indicators of the future balance of air traffic demand and capacity at airport resources. Most flights in the Northeast last less than 70 minutes, so predictions of airspace congestion at least one hour ahead would be most useful, because flow control could therefore extend to pre-departure. Predictions are needed especially during visual meteorological conditions, when congestion is not necessarily an expected outcome.The approach was to conduct an analysis in two phases. In phase one the team postulated four different indicators and used off-line and real-time tools with archived flight data to evaluate the indicators’ potential for predicting congestion. The indicators evaluated in phase one were as follows:•Airport arrival rate and arrival fix crossing rate, expressed in terms of capacity vs. demand•Close-in and further-out (from the Terminal Radar Approach Control [TRACON]) distance-based demand aircraft counts for major arrival flows•Wedge-shaped airspace arrival aircraft counts into the TRACON•Sector counts, including red and yellow alerts when thresholds are exceededIn phase two, the indicator with the most potential (airport and arrival fix crossing rates) was evaluated in more detail to determine if it did indeed predict congestion successfully. The team again examined historical data, in search of air traffic management situations identifiable as problematic or problem-free. These situations were then replayed using an integrated real-time model, combining two previously built CAASD systems, Self Managed Arrival Resequencing Tool (SMART) and Collaborative Routing Coordination Tool (CRCT). The simulation clock was halted one hour prior to the known situation (congested or not), and the indicator was evaluated. This paper documents the successful discovery of a congestion prediction indicator.