Aircraft arrival management

Abstract

This Thesis is based around the Air Traffic Control Arrival Management problem of scheduling the landing of aircraft on runways, where aircraft must respect minimum separation distances based on wake-vortex criteria.  Existing scheduling approaches and methods of assessing their effects on Air Traffic Control are reviewed.  Several polynomial-time dynamic programming algorithms are proposed for determining optimal landing sequences.  Six sequencing algorithms and four delay-sharing strategies are linked into a discrete-event simulation model of Stockholm Arlanda arrival airspace.  The procedures for generating traffic samples, and important output performance indicators, are validated against 16 recorded traffic samples of arrivals from autumn 2003 through hypothesis tests, confidence intervals and tests of dynamic behaviour.  Several statistical methods are used to analyse experiment output from the Stockholm Arlanda model.  These include graphical methods, EDFIT analysis, regression metamodels, variance metamodels and logit models.  A series of detailed experiments on the model do not find tremendous benefits to Air Traffic Control airport runway capacity from advanced sequencing, above the benefits that occur from using first-come first-serve sequences.  However, changes to the Air Traffic Control system are found in holding time, time in approach sectors and stability of the advice generated.

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