Optimizing aircraft trajectories under convective weather conditions

Abstract This study focuses on trajectory optimisation in air traffic management (ATM), addressing the challenges of flight planning under convective weather conditions. Convective weather, including hail, wind shear and severe icing, can pose significant operational risks and require aircraft to avoid these areas. Deviations from planned trajectories lead to additional flight distances, delays and operational disruptions, highlighting the need for effective trajectory planning approaches. In this study, deterministic and stochastic models were developed to optimise aircraft trajectories, with the stochastic model accounting for wind uncertainties. A rolling horizon control (RHC) approach was implemented to address the dynamic behaviour of convective areas, enhancing model realism. The models aim to minimise total flight time while maintaining conflict-free operations and avoiding convective weather areas. Results demonstrate the effect of incorporating wind uncertainty through the stochastic model on ATM performance, particularly under convective weather conditions. The proposed algorithms support decision-making and automation, enabling coordinated trajectory planning and reducing workload for pilots and air traffic controllers. This approach improves ATM safety, efficiency and capacity under adverse weather conditions.