Evaluation of feasible machine learning techniques for predicting the time to fly and aircraft speed profile on final approach: Predictive dynamic support tool on final approach

currently, at many airports, the runway throughput is the limiting factor for the overall capacity. Among the most important constraining parameters is the separation minima expressed in distance. On the top of these minima, the difference of the leader and follower aircraft speed profiles imposes to consider buffer to cope with compression...

Why aircraft will fly more fuel-efficiently on FRIDAY: The FRIDAY route charges method

The Single European Sky is being introduced to improve the efficiency of flight and traffic operations by reforming the air traffic management system. Despite all of these technical advances, airlines choose detours to avoid high route charges. This mechanism is intensified when fuel prices are low. The single unit rate method has been proposed...

Large-Scale Flight Phase Identification from ADS-B Data Using Machine Learning Methods

With the increasing availability of ADS-B transponders on commercial aircraft, as well as the rapidly growing deployment of ground stations that provide public access to their data, accessing open aircraft flight data is becoming easier for researchers. Given the large number of operational aircraft, significant amounts of flight data can be...

Modeling and Inferring Aircraft Takeoff Mass from Runway ADS-B Data

Aircraft mass is an important parameter in many ways, either to build aircraft performance models, to predict flight trajectories, or to simulate air traffic. Mass data is usually considered as sensitive information for airlines and is, therefore, not disclosed to researchers publicly. In this paper, we use two methods to infer the mass of an...