Optimierte Continuous Descent Operations unter unsicheren Umwelt- und Missionsbedingungen
Zusammenfassung der Projektergebnisse
This project aimed to bring trajectory optimization to a robust paradigm, while maintaining the optimization models as realistic as possible. The project mainly included four tasks: 1. modeling of uncertain environment and vehicle inputs and the resulting solution space, 2. robust descent trajectory optimization towards Continuous Descent Operations (CDO), 3. case studies, and 4. visualization and experimental study. In the first task, we modeled uncertainties in weather prediction based on a sensitivity analysis of uncertainties for a larger set of weather scenarios called “ensemble” on deterministic CDO trajectory optimization. We modeled the uncertainties in two approaches, i.e., with ensemble weather forecast and with Copula functions. In the second task, we formulated our CDO trajectory optimization problem considering the weather forecast uncertainties. We integrated a robust Optimal Control (OC) and a multiple-phase OC to formalize the problem. We introduced two key ideas specific to our robust formulation, i.e., the aggregation and the commonality constraints. We also applied the formulated OC problem to one of the PseudoSpectral (PS) methods to numerically solve the problem. We proposed an iterative process to determine the optimal number of discrete nodes required for the PS method. In the third task, we performed simulation and carried out case studies. We compared the robust trajectories to both Scenario-Optimal (SO) and generated Inappropriately Controlled (IC) trajectories, and confirmed that the robust ones come at lower operational costs among the overall weather scenarios. We also confirmed the robust trajectories always satisfied ICAO/EASA operational constraints, whereas the generalized IC trajectories cannot grant their satisfaction. In the fourth task, we developed a so-called Improved Decision Advisor (IDA) and prototyped it for the aircraft onboard Navigation Display (ND) and the Electronic Flight Bag (EFB). It provides visual information to pilots on how to execute the descent the best when in-flight, aiming to support their decision making for in-flight trajectory re-optimization. Due to the COVID-19 pandemic, we were not able to carry out experimental studies to evaluate the proposed system by inviting professional pilots and Air Traffic COntrollers (ATCOs) as usual. Instead, we realized a tailored questionnaire study. This research contributed to better trajectory planning under typical, thus uncertain weather conditions and allowed aircraft to fly with increased economic and environmental efficiency. This planning algorithm may be applied to in-flight trajectory re-optimization and negotiation between pilots and ATCOs. This research can be extended to multiple aircraft to solve sequencing problems under uncertainties, which will be part of the dissertation of the project's researcher. This research was carried out in a close collaboration between two research chairs at TU Dresden: the Chair of Air Transport Technology and Logistics led by Professor Hartmut Fricke, supported by the Chair of Econometrics and Statistics, esp. in the Transport Sector led by Professor Ostap Okhrin. Five publications could be placed in journals with scientific quality assurance. One publication won the best paper award in the track “trajectory planning” of the international conference “ATM Seminar 2021”.
Projektbezogene Publikationen (Auswahl)
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“Interpolation of Weather Conditions for a Flight Corridor,“ in Statistische Woche, oral presentation, Trier, 2019.
G. Chen & O. Okhrin
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CDO Sensitivity Analysis for Robust Trajectory Planning under Uncertain Weather Prediction. 2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC), 1-10. IEEE.
Kamo, Shumpei; Rosenow, Judith & Fricke, Hartmut
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"Robust CDO trajectory planning under uncertainties in weather prediction”, in 14th USA/Europe Air Traffic Management Research and Development Seminar (ATM Seminar), Online conference, 2021.
S. Kamo, J. Rosenow, H. Fricke & M. Soler
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Fundamental Framework to Plan 4D Robust Descent Trajectories for Uncertainties in Weather Prediction. Aerospace, 9(2), 109.
Kamo, Shumpei; Rosenow, Judith; Fricke, Hartmut & Soler, Manuel
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Importance of Weather Conditions in a Flight Corridor. Stats, 5(1), 312-338.
Chen, Gong; Fricke, Hartmut; Okhrin, Ostap & Rosenow, Judith
