Optimization of traffic flow under adverse weather conditions

This study addresses trajectory optimization, a fundamental element of air traffic management, with a specific focus on the challenges of flight route planning under convective weather conditions. The main objective of trajectory optimization is to enhance operational efficiency by making air traffic flow more safety and efficient. Convective weather conditions involve elements such as hail, wind shear, lightning, and severe icing, posing safety risks for aircraft. Hence, it is essential for pilots to avoid these regions. However, deviations from planned routes due to weather conditions lead to disruptions and delays in air traffic flow. Avoidance of convective areas and resolution of conflicts are addressed using deterministic and stochastic models. In the deterministic model, convective areas are assumed to be fixed, and the optimization involves aircraft avoiding these areas without conflicts. The stochastic model incorporates wind uncertainties, and the problem is addressed more realistically by considering the dynamics of convective areas with the Rolling Horizon Control approach. The aim of the models is to minimize total flight time. The study reveals the advantages of the stochastic model over the deterministic model. The obtained results provide an important basis for controllers and pilots to make more effective decisions. The algorithms, built upon decision support and/or automation systems, have the potential to enable more effective and coordinated planning of the routes of aircraft. The implementation of this approach is expected to reduce workload for both pilots and controllers, accordingly, will have positive results in terms of safety, efficiency and air traffic management capacity.