Dynamically optimized departure and arrival funnels considering aircraft noise and weather conditions

Project information

© DFG

• Client: German Research Foundation
• Project duration: 01.11.2025 - 31.10.2028 (36 months)

The aviation industry must constantly reduce operating costs, minimize delays and emissions for competitive/environmental reasons. Multi-criteria trajectory optimization therefore plays a key role in ATM research. The optimization goals compete with each other, their mode of action must be understood and costs quantified. For the cruise phase, this has already found its way into daily operations, e.g. with the introduction of free route airspace or weather-dependent, optimal routes in the North Atlantic. However, when arriving at and departing from major airports, the high volume of traffic and airspace restrictions often force aircraft to take inefficient flight altitudes and detours.

Furthermore, aircraft noise at altitudes below 5,000 ft is a dominant social acceptance factor, the minimization of which is therefore also essential. So-called traffic flow funnels are being developed in this project. The funnels are designed as procedural spaces that extend current approach and departure routes by a 3D space. The aircraft flies its optimum altitude profile and flight path within the funnel. This allows the current weather and the wishes of airspace users to be taken into account to a much greater extent than before. However, the freedom of movement is also limited by the funnels in order to maintain predictability for air traffic control and thus safe and efficient operations.

Current statutory methods for noise calculation do not yet allow the integration of trajectory optimization, mainly because the weather (wind, temperature, relative humidity) is not taken into account. To overcome this, various machine learning approaches are applied to a large set of noise measurement and weather data to predict the noise under given conditions.

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© Sven Ellger

Research Associate

Name

Dipl.-Ing. Norman Peter

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Chair of Air Transport Technology and Logistics

Chair of Air Transport Technology and Logistics

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