Departure Taxi Time Predictions Using ASDE-X Surveillance Data

Abstract

urate prediction of departure taxi times will help airlines to proactively manage push-times, to optimally assign scarce ramp resources, and to propagate delay information to destination airports in a more timely fashion. Air Traffic Control (ATC) will benefit via improved demand forecasts for the terminal area and enroute air sectors. An ancillary benefit to such predictions is the ability to discern factors contributing to longer taxi times. To facilitate accurate predictions, we will analyze the utility of the Airport Surface Detection Equipment, Model X (ASDE-X) surface surveillance data. Months of archived data support both historical analysis (i.e., under similar conditions, what happened in the past?) and a more dynamic real-time surface analysis (e.g., aircraft positions, queues, and runway utilization).

Original document

The different versions of the original document can be found in:

• http://pdfs.semanticscholar.org/248a/823309af6f24f0e8c085c4d238cb2b1e3576.pdf

• http://arc.aiaa.org/doi/pdf/10.2514/6.2008-8958,

http://dx.doi.org/10.2514/6.2008-8958

• https://arc.aiaa.org/doi/10.2514/6.2008-8958,

https://thehill.com/sites/default/files/Sensis_ATIO_08_Legge_0.pdf,

https://academic.microsoft.com/#/detail/2041069838