Probabilistic TFM: Preliminary Benefits Analysis of an Incremental Solution Approach
The National Airspace System (NAS) is the collection of airports, airspace, and other resources which enable air transportation in the U.S. When considered in light of the interactions with airspace users (airlines and non-commercial flight operations) and environmental conditions (e.g., winds and weather), this larger gestalt is quite complex. One of its notable attributes is uncertainty—there is uncertainty in nearly every aspect: flight take-off times, airport and airspace capacities, effects of decisions made by airspace users and airspace managers, etc. Traffic Flow Management (TFM) is the function, performed by the Federal Aviation Administration (FAA), which seeks to balance demand and capacity for airspace/airport resources. Also, more informally called "resource management", TFM typically must manipulate air traffic demand, since resource capacity (e.g., weather impacting air routes, or runway repair impacting airport operations rate) is typically non-negotiable.
In the last years, a new idea in the area of TFM planning and analysis has evolved, known as "Probabilistic TFM" (PTFM) [[GNC 2004][ATM 2005][Hunter and Ramamoorthy, 2006]. PTFM pursues an explicit recognition of uncertainty—it attempts to incorporate probability theory and thereby to improve the decision-making.
