Reinforcement learning (RL) has emerged as a powerful tool for addressing complex
decision making problems in various domains, including aviation. This paper provides a …

This study investigates the potential for mitigating the non-CO 2 climate impact induced by
air traffic operations at the network scale. Due to the spatiotemporal dependency of non-CO …

With the burgeoning expansion of air transportation, the imbalance between airspace
capacity and demand is significantly prominent around the world. Air traffic flow …

Air traffic flow prediction is vital for its supporting function for collaborative decision making in
Air Traffic Management. However, due to the inherent spatial and temporal dependencies of …

This paper proposes an innovative operational framework for strategic online en-route
operations, in the trajectory-based operations context. This framework captures the …

Thunderstorms can cause a decrease in airports' dynamic capacity, and taxiway runway
capacity is a key element of airport airfield operations. In this paper, based on the cell …

Accurately predicting air traffic flow in terminal areas is critical for balancing demand and
capacity, particularly under challenging weather conditions. However, the complex …

The development of trajectory-based operations and the rolling network operations plan in
European air traffic management network implies a move towards more collaborative …

A multilayer network approach to model and analyze air traffic networks is proposed. These
networks are viewed as complex systems with interactions between airports, airspaces …

Meeting the demand with the available airspace capacity is one of the most challenging
problems faced by Air Traffic Management. Nowadays, this collaborative Demand–Capacity …