Predictive Models of Duration of Ground Delay Programs in New York Area Airports

Initially planned GDP duration often turns out to be an underestimate or an overestimate of the 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. The overall objective of this study is to develop such models based on logs of GDPs. In a previous report, we described descriptive models of Ground Delay Programs. These models were defined in terms of initial planned duration and in terms of categorical variables. These descriptive models are good at characterizing the historical errors in planned GDP durations. This paper focuses on developing predictive models of GDP duration. Traffic Management Initiatives (TMI) are logged by Air Traffic Control facilities with The National Traffic Management Log (NTML) which is a single system for automated recoding, coordination, and distribution of relevant information about TMIs throughout the National Airspace System. (Brickman, 2004 Yuditsky, 2007) We use 2008-2009 GDP data from the NTML database for the study reported in this paper. NTML information about a GDP includes the initial specification, possibly one or more revisions, and the cancellation. In the next section, we describe general characteristics of Ground Delay Programs. In the third section, we develop models of actual duration. In the fourth section, we compare predictive performance of these models. The final section is a conclusion.