Statistical characterization of deviations from planned flight trajectories in air traffic management

Abstract

Understanding the relation between planned and realized flight trajectories and the determinants of flight deviations is of great importance in air traffic management. In this paper we perform an in-depth investigation of the statistical properties of planned and realized air traffic on the German airspace during a 28 day periods, corresponding to an AIRAC cycle. We find that realized trajectories are on average shorter than planned ones and this effect is stronger during night-time than day-time. Flights are more frequently deviated close to the departure airport and at a relatively large angle-to-destination. Moreover, the probability of a deviation is higher in low traffic phases. All these evidences indicate that deviations are mostly used by controllers to give directs to flights when traffic conditions allow it. Finally we introduce a new metric, termed di-fork, which is able to characterize navigation points according to the likelihood that a deviation occurs there. Di-fork allows to identify in a statistically rigorous way navigation point pairs where deviations are more (less) frequent than expected under a null hypothesis of randomness that takes into account the heterogeneity of the navigation points. Such pairs can therefore be seen as sources of flexibility (stability) of controllers traffic management while conjugating safety and efficiency.

Review of the network risk propagation research

“…[34][35][36][37][38] However, for specific systems, researchers tend to choose the analysis of endogenous risks, such as a financial risk in an economic system 39 and flight delays in air transport networks(ATN) ( Figure 2). [40][41][42]…”

An empirically grounded agent based model for modeling directs, conflict detection and resolution operations in air traffic management

“…Specifically we calibrate our model to reproduce the intraday evolution of the deviation rate metric that has been recently introduced in Ref. [ 26 ].…”

“…The deviation rate introduced in Ref. [ 26 ] quantifies the deviations observed from the planned flight trajectories. We call deviation the event such that an aircraft passing over a scheduled navigation point does not go to the next planned one.…”

“…re-routing and direct. In [ 26 ] it is shown that, in relative terms, directs are mainly issued during night-time i.e. in low traffic conditions while they are relatively less issued during day-time.…”

Weather Impact on Airport Performance

“…The gate-to-gate perspective focuses on the flown part of the trajectory whilst an air-to-air approach would give more relevance to airport ground operations which move the flight from arrival to departure ensuring the adherence to reliable departure times. Typical standard deviations for airborne flights are 30 s at 20 min before arrival [2,3], but could increase to 15 min when the aircraft is still on the ground [4]. As shown in Figure 1a, the average time variability (measured as standard deviation) during the flight phase (5.3 min) is higher than in the taxi-out (3.8 min) and in the taxi-in (2.0 min) phases, but it is still significantly lower than the variability of both the departure (16.6 min) and arrival (18.6 min) phases [1].…”