RobustOC: Robust Approach Flight Trajectory Optimization to achieve powerful Aircraft Sequencing and Spacing under Uncertainties

Project Information

© DFG

• Funded by the DFG
• Project duration: 3 years (Oct. 2026 – Sept. 2029)

Description

During arrival operations, uncertainties in aircraft mass estimates, weather conditions, and aircraft flight intent can affect predicted trajectories and estimated time of arrival. Air Traffic Control must account for these uncertainties when planning arrival sequences and maintaining separation minima. To accommodate uncertainty and maintain safe traffic flow, additional separation buffers, such as speed or time, may be necessary. However, these measures can limit arrival throughput, increase fuel consumption, and flight time. The challenge is to optimize trajectories and arrival efficiency while maintaining the required level of safety.

Previous research at the Chair for Air Transport Technology and Logistics established robust descent trajectory optimization methods for individual aircraft and laid the foundation for integrating trajectory and sequence optimization under weather forecast uncertainty. Conventional arrival scheduling determines aircraft order and target arrival times without explicitly optimizing the trajectories needed to achieve them. This project builds on the preliminary work to investigate how multiple aircraft can follow efficient, operationally feasible trajectories while meeting sequencing and separation requirements under uncertainty.

The project combines Optimal Control for Robust Trajectory Optimization with sequencing and spacing methods. Two strategies are investigated: optimizing spacing along a common descent path, and coordinating trajectories with arrival order and times at a metering or merging fix. The integrated framework will support Arrival Management through an enhanced Arrival Manager (AMAN) concept, AMAN+.

Objectives

Development of Robust Optimization Methods for Trajectories using Optimal Control

The project aims to investigate and quantify how uncertainties affect flight trajectories and inter-aircraft spacing. It will develop optimal control methods for multiple aircraft and integrate them with sequence optimization while accounting for aircraft dynamics and operational constraints. The computational performance of the integrated approach and the trade-offs between flight efficiency, traffic throughput, and environmental performance will be evaluated.

Decision Support for Sequence Optimization and Evaluation

The outcome of the robust optimization will translate the results into AMAN+ advisories for air traffic controllers. The operational applicability of the resulting decision support system will be assessed through simulations and human-in-the-loop experiments using Leipzig/Halle Airport scenarios, considering Point Merge and trombone approach procedures.

Collaborators