Quantifying Effects of Departure Time Uncertainty on Ground Delay Program Control Parameters

抄録

Well-executed strategic air traffic flow management (ATFM) such as ground delay programs and controlled enroute delays account for numerous uncertainties. Such initiatives aim to minimize unnecessary airborne and ground delays while maintaining sufficient arrival runway pressure. This can be achieved through setting a cap on the maximum allowable airborne delay, i.e. the GDP buffer. Previous studies have shown that the ideal buffer is influenced by anticipated traffic levels. This study examines the uncertainties in departure time predictions, such as those arising from delayed passengers, maintenance problems, or late aircraft arrivals, and explores their impact on buffer efficiency and potential losses due to inappropriate buffer selections. Cumulative ground delay, airborne delay and throughput loss (capacity loss) are used as metrics. A day of arrival traffic at a hub Japanese airport is modeled and the ATFM necessity is demonstrated. To investigate operational aspects such as predictability and air traffic control workload, the number of flights with airborne delay exceeding the buffer is evaluated for several departure time prediction uncertainty models. It is concluded that modeling departure time uncertainties is important for optimal buffer selection. These results also highlight the importance of actual operational data which will allow for such models to be developed.