Abstract

With increasing requirements to become more flexible in structuring and operating the airspace, it is important to take new ideas for traffic management into account. Our approach of demand depending traffic structuring is able to create a self-structuring main flow network based on a given set of planned flight trajectories automatically. The resulting main flow network is close to the course of the flights, even when assuming unstructured free-routing flights. Our goal is a compromise between the flexibility of great circle or free routing trajectories and the easier surveillance for air traffic controllers in case of a predefined route-network. Usually, trajectories are defined as a sequence of waypoints, e.g. entry and exit points of sectors or turning points. Instead, we define a trajectory as a sequence of intersection points with the routes of all other flights planned in the observed airspace region (common points). Based on these common points, a network structure is created and the flight trajectories are adapted to this structure. Tests with free-routing and great-circle traffic samples led to routes, which are very close to the planned trajectories and comparable in length. Furthermore, a structural complexity metric to measure the complexity of the airspace structure is introduced and the results are very promising. The new algorithm is tested using three different scenarios: Baseline, free routing within a selected airspace region and great-circle between origin and destination airport. The results show the ability of the presented approach to build a route network based on planned or demand data. This can be used to adapt the structure on a daily basis and in case of unforeseen events like thunderstorms. The resulting short and dynamic routes have the advantage that traffic streams better cope with actual demand than standard routings and at the same time air traffic controllers can supervise the traffic streams more easily than free routing patterns. When flexible sector authorization and single controller operations are applied, the presented approach helps to reduce controller workload and increase productivity.

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