Deepak Kulkarni’s paper on Ground Delay Programs (GDP) to manage air traffic has been accepted for publication in the 11th AIAA Aviation Technology, Integration, and Operations Conference (ATIO). The paper employs statistical methods to develop predicative models of Ground Delay Programs, which often run over or under what is actually needed for airspace control.
BACKGROUND: To manage demand and capacity imbalances in national airspace, the FAA uses Ground Delay Programs (GDP) to manage air traffic. Initially planned GDP duration often turns out to be an under- or overestimate of actual GDP duration. This, in turn, results in avoidable airborne or ground delays in the system. Therefore, better models of actual duration have the potential of reducing delays in the system. This study aims to develop such models based on GDP logs.
NASA PROGRAM FUNDING: Airspace Systems Program
Contact: Deepak Kulkarni