Influence of atmospheric uncertainty, convective indicators, and cost-index on the leveled aircraft trajectory optimization problem

Soler, Manuel; González-Arribas, Daniel; Sanjurjo-Rivo, Manuel; García-Heras, Javier; Sacher, Danièl; Gelhardt, Ulrike; Lang, Jürgen; Hauf, T.; Simarro, Juan

doi:10.1016/j.trc.2020.102784

Cited by 14 publications

(9 citation statements)

References 34 publications

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“…Lovegren et al [28][29][30] improved the fuel efficiency of aircraft by optimizing the altitude and speed profile. Soler et al [31] studied the influence of atmospheric uncertainty, convective indicators, and cost-index on the leveled aircraft trajectory optimization. For the horizontal profile, Patron et al [32] considered the wind direction during cruise and used genetic algorithms to select an optimal flight path for the aircraft in the pre-tactical stage.…”

Section: Introductionmentioning

confidence: 99%

Predicting Fuel Consumption Reduction Potentials Based on 4D Trajectory Optimization with Heterogeneous Constraints

Liu

Xie

et al. 2021

Sustainability

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Investigating potential ways to improve fuel efficiency of aircraft operations is crucial for the development of the global air traffic management (ATM) performance target. The implementation of trajectory-based operations (TBOs) will play a major role in enhancing the predictability of air traffic and flight efficiency. TBO also provides new means for aircraft to save energy and reduce emissions. By comprehensively considering aircraft dynamics, available route limitations, sector capacity constraints, and air traffic control restrictions on altitude and speed, a “runway-to-runway” four-dimensional trajectory multi-objective planning method under loose-to-tight heterogeneous constraints is proposed in this paper. Taking the Shanghai–Beijing city pair as an example, the upper bounds of the Pareto front describing potential fuel consumption reduction under the influence of flight time were determined under different airspace rigidities, such as different ideal and realistic operating environments, as well as fixed and optional routes. In the congestion-free scenario with fixed route, the upper bounds on fuel consumption reduction range from 3.36% to 13.38% under different benchmarks. In the capacity-constrained scenario, the trade-off solutions of trajectory optimization are compressed due to limited available entry time slots of congested sectors. The results show that more flexible route options improve fuel-saving potentials up to 8.99%. In addition, the sensitivity analysis further illustrated the pattern of how optimal solutions evolved with congested locations and severity. The outcome of this paper would provide a preliminary framework for predicting and evaluating fuel efficiency improvement potentials in TBOs, which is meaningful for setting performance targets of green ATM systems.

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Section: Introductionmentioning

confidence: 99%

Predicting Fuel Consumption Reduction Potentials Based on 4D Trajectory Optimization with Heterogeneous Constraints

Liu

Xie

et al. 2021

Sustainability

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“…To overcome the sensitivity to the initial guess, a randomized initialization is proposed, leading to a range of local optima. In [20], an OCP is solved to obtain efficient trajectories based on convection indicators. Alternatively, the so-called Reach-Avoid (RA) is applied for thunderstorm avoidance in [21].…”

Section: Trajectory Planning Methodologiesmentioning

confidence: 99%

“…The work by [22] relies on Model Predictive Control to avoid moving ellipsoidal storms in a deterministic framework. These works [19,20,21] are based on optimal control principles, which can be used with rather complex nonlinear dynamical systems, but lack the flexibility to integrate operational constraints.…”

Section: Trajectory Planning Methodologiesmentioning

confidence: 99%

RRT*-Based Algorithm for Trajectory Planning Considering Probabilistic Weather Forecasts

Andrés

Kamgarpour

Soler

et al. 2021

Lecture Notes in Electrical Engineering

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“…González-Arribas et al applied robust optimal control for cruise flight with an uncertain wind condition by employing ensemble prediction systems (EPS) [28] and confirmed the method could reduce the impact of uncertain wind on the planning, taking as reference one year of trajectory data and multiple origin-destination pairs [29]. This robust planning method was extended in [30] to the consideration of exposure to convection and cost-index based profiles. Recently, the same authors proposed a heuristic method based on parallel graphics processing unit (GPU) computation [31], finding robust trajectories in computational times that are compatible with real operations (∼1 s), and considering not only the level flight, but step-climbs and step-descents.…”

Section: Introductionmentioning

confidence: 99%

Fundamental Framework to Plan 4D Robust Descent Trajectories for Uncertainties in Weather Prediction

et al. 2022

Self Cite

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Aircraft trajectory planning is affected by various uncertainties. Among them, those in weather prediction have a large impact on the aircraft dynamics. Trajectory planning that assumes a deterministic weather scenario can cause significant performance degradation and constraint violation if the actual weather conditions are significantly different from the assumed ones. The present study proposes a fundamental framework to plan four-dimensional optimal descent trajectories that are robust against uncertainties in weather-prediction data. To model the nature of the uncertainties, we utilize the Global Ensemble Forecast System, which provides a set of weather scenarios, also referred to as members. A robust trajectory planning problem is constructed based on the robust optimal control theory, which simultaneously considers a set of trajectories for each of the weather scenarios while minimizing the expected value of the overall operational costs. We validate the proposed planning algorithm with a numerical simulation, assuming an arrival route to Leipzig/Halle Airport in Germany. Comparison between the robust and the inappropriately-controlled trajectories shows the proposed robust planning strategy can prevent deteriorated costs and infeasible trajectories that violate operational constraints. The simulation results also confirm that the planning can deal with a wide range of cost-index and required-time-of-arrival settings, which help the operators to determine the best values for these parameters. The framework we propose is in a generic form, and therefore it can be applied to a wide range of scenario settings.

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Influence of atmospheric uncertainty, convective indicators, and cost-index on the leveled aircraft trajectory optimization problem

Cited by 14 publications

References 34 publications

Predicting Fuel Consumption Reduction Potentials Based on 4D Trajectory Optimization with Heterogeneous Constraints

Predicting Fuel Consumption Reduction Potentials Based on 4D Trajectory Optimization with Heterogeneous Constraints

RRT*-Based Algorithm for Trajectory Planning Considering Probabilistic Weather Forecasts

Fundamental Framework to Plan 4D Robust Descent Trajectories for Uncertainties in Weather Prediction

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