Large-scale data-based collaborative air traffic optimization for congestion management

In a context of air transportation growth, it becomes essential to better manage the rising congestion levels. The present paper presents a large-scale destination-aggregated multicommodity flow model at the National Airspace system level, supported by a data-based network synthesis. It encomprises a departure queuing model to optimize the routing and delays of flights in the NAS. The flows are aggregated according to their destination to ensure a more compact linear optimization formulation without losing accuracy in the analysis. This model determines the nationwide impact of local constraints from historical data. It could serve as the basis to understand the propagation of congestion in the NAS, mitigate its effects by linking optimization results to operational constraints and actions, and support nationwide collaborative management of the airspace resources.