Cluster-based Analysis of Airline Adherence to Flight Plan

Abstract

Airlines plan the trajectory of their flights in advance. However, this plan is not always followed since, during the actual flight, aircraft deviate either horizontally by rerouting, or vertically by choosing a different Flight Level. The issue arises when some airlines frequently deviate from their flight plans frequently, to the disadvantage of other airspace users. With this research we analyse aircraft en-route trajectory deviations for clusters of European airlines. We focus on two metrics: vertical flight level deviation, and horizontal deviation. We analyze these deviations for clusters of airlines operating in the European Civil Aviation Conference (ECAC) airspace in 2017. The airline clusters are obtained using unsupervised machine learning algorithms with operational and Complex Network features. The results show that major Low-Cost Carriers deviate on average, per flight, 34% more vertically than major Network Carriers, while Network Carriers have on average, more efficient horizontal trajectories. However, NCs show a larger fraction of flights with equally planned and realized efficiency, which points to less horizontal deviations overall. The findings reflect a general, network-wide horizontal inefficiency in trajectory planning, and that LCCs deviate horizontally a larger percentage of their flights. Moreover, they manage to use the available Flight Levels consistently to their advantage. This research could be used for future policy-making on a fair and equitable routes and slot allocation.