Abstract
To maximize the capacity of airports by optimally allocating available resources such as runways, the arrival times of individual aircraft need to be computed. However, accurately predicting arrival times is difficult because aircraft trajectories are frequently vectored off the standard approach procedures. This paper introduces a new framework for predicting aircraft arrival times by incorporating probabilistic information for the types of trajectory patterns that will be applied by human air traffic controllers. The major patterns of the trajectories are identified, and the probabilities of those patterns are computed based on the patterns of the preceding aircraft. The proposed method is applied to traffic scenarios in real operations to demonstrate its performance.
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