SO6C: Compressed Trajectories in Air Traffic Management

Abstract

Air traffic management is facing a tremendous increase in the amount of available flight data. Parallel to the decreasing time and cost necessary to produce ATM data, computational requirements for storage and analysis of the bulk of data are steeply increasing. Compression is a key technology to deal with this challenge – often referred to as big data science.In this paper,we propose a new technique for compressing 4D-trajectories of the Demand Data Repository provided by EUROCONTROL. While standard compression algorithms compress such a trajectory file as a large chunk of consecutive text, we propose to look at different streams in the trajectory files. Changing the traversal scheme with a focus on streams already improves compression rates beyond state-of-the-art. Based on the notion of streams, we design encoding techniques for each stream separately, by analyzing potential dependencies and redundancies in the SO6 files, following the principle: if it can be computed, then it does not need to be stored explicitly.In our evaluation we achieve a compression ratio of approx. 40:1 for all traffic over European airspace within one week, a reduction of more than 80 percent compared to the best standard compression technique 7zip. In addition, our new compression technique is almost four times faster than 7zip, while being only slightly slower than other out-of-the-box compression tools. Therefore, we are convinced that efficient, yet fast, compression of 4D-trajectories is possible on modern hardware and should be exploited.