Air Traffic Management (ATM) will be more complex in the coming decades due to the
growth and increased complexity of aviation and has to be improved in order to maintain …

Advances in the trusted autonomy of air-traffic management (ATM) systems are currently
being pursued to cope with the predicted growth in air-traffic densities in all classes of …

Airport arrival and departure movements are characterized by high dynamism, stochasticity,
and uncertainty. Therefore, it is of paramount importance to predict and analyze surface taxi …

Accurate aircraft trajectory predictions are necessary to compute exact traffic demand
figures, which are crucial for an efficient and effective air traffic flow and capacity …

This study presents three different machine learning (ML) models to estimate the flight block
time for commercial airlines. The models rely only on explanatory variables that airlines …

With the increased use of intelligent Decision Support Tools in Air Traffic Management
(ATM) and inclusion of non-traditional entities, regulators and end users need assurance …

Punctuality is a sensitive issue in large airports and hubs for passenger experience and for
controlling operational costs. This paper presents a real and challenging problem of …

The European Air Traffic Management Network (EATMN) is comprised of various
stakeholders and actors. Accordingly, the operations within EATMN are planned up to six …

Abstract Flight Take-Off Time (TOT) delay prediction is essential to optimizing capacity-
related tasks in Air Traffic Management (ATM) systems. Recently, the ATM domain has put …

AI methods referred to as interpretable are often discredited as inaccurate by supporters of
the existence of a trade-off between interpretability and accuracy. In many problem contexts …