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 …

Classical approaches for modelling aircraft taxi-speed assume constant speed or use a
turning rate function to approximate taxi-timings for taxiing aircraft. However, those …

Local delay predictions are crucial for optimizing airport capacity management, enhancing
overall resilience, efficiency, and effectiveness of airport operations. This paper delves into …

Airside taxi delays have adverse consequences for airports and airlines globally, leading to
airside congestion, increased Air Traffic Controller/Pilot workloads, missed passenger …

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 …

Artificial Intelligence (AI) is recognized as advanced technology that assists in decision-
making processes with high accuracy and precision. However, many AI models are …

Airport Collaborative Decision Making (ACDM) is an important initiative that aims at more
efficient and optimised use of airport resources. Variable taxi time prediction is one of the …

This paper presents a machine learning-based approach for predicting the taxi-out time, with
the departure process decomposed into two components: the time taken to travel from the …

The continuous search for improvements in our Airports is essential, both in technologies
and in more innovative processes that aim to guarantee the improvement of the efficiency of …