Aggregate Network Model with Resilience Considerations for Air Traffic Flow Management

Abstract

In the U.S. National Airspace System (NAS), air traffic demand for infrastructure resources, such as airspace sectors and airports, must be balanced with the operational capacity of the resources. To maintain safety and avoid excessive service degradations – a key tenet of a resilient transportation network – traffic flow managers leverage Traffic Management Initiatives (TMIs) for re-balancing and alleviating the impacts of disruptions. Currently, such traffic flow management (TFM) actions and strategies are based on subject matter expertise, best practices, and real-time feedback from a variety of automation and decision-support systems. However, it remains challenging to evaluate, compare, and optimize TFM decisions quantitatively and strategically. To address this gap, we extend a lightweight model for flight delay dynamics within a network of airports using delay data from TFM actions obtained from MITRE’s Layered TMI (LTMI) data. We augment this model with an operationally relevant resilience metric that considers current and projected delay, capacity usage, schedule conformance, and network dynamics. Specifically, in this paper we (1) describe different NAS modes identified from LTMI data via clustering and explore the operational meaning of those modes; (2) describe how the delay dynamics model can be used to estimate delays at a future time; and (3) introduce a set of resilience metrics for NAS performance. These elements may be deployed and integrated within the TFM decision-making process.