This paper describes the development of an automated mechanism to alert aviation traffic managers of the need to take action to adjust the rate of aircraft arriving into airports. When rates are too high, air traffic controllers are forced to do costly maneuvering and to hold aircraft to maintain required spacing. When arrival rates are too low, valuable airport landing capacity goes unused. In today's operations, mismatches between the planned and actual arrival rates often occur gradually and may not even be noticed until too late, after significant problems have materialized. This paper proposes an alerting mechanism that uses realtime signal metrics based on actual airspace operations to alert controllers of impending problems. Alerts would be triggered when signal metrics crossed their respective threshold values, which would be tailored for specific airspaces and generated with sufficient lead time to allow for mitigating actions. The alerting mechanism would reduce reliance on manual monitoring and thus reduce traffic manager workload. With historical flight data from airspace surrounding Atlanta International Airport an initial predictive model was developed and validated for one possible signal metric. Through discussions with subject matter experts, an analysis of various metric threshold values was also performed.
When severe weather is forecasted to affect air traffic operations, Federal Aviation Administration (FAA) traffic flow managers may decide to restrict the air traffic flow through the affected airspace. Sometimes the restrictions put in place may constrain more traffic than necessary for safe and expeditious management. This paper refers to this phenomenon as Traffic Management Initiative (TMI) over-conservatism and the goal of this study is to quantify the impact of TMI over-conservatism on delay. This study focuses on a specific type of TMI, known as an Airspace Flow Program (AFP), and estimates the amount of over-conservatism in setting rates for AFPs by estimating maximum throughput under observed severe weather conditions. The calculated estimate is a rough order of magnitude (ROM) and is meant as an input for investment decisions regarding potential improvements to Traffic Flow Management (TFM) capabilities.
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