Impact of multi-criteria optimized trajectories on European airline efficiency, safety and airspace demand

Rosenow, Judith; Fricke, Hartmut

doi:10.1016/j.jairtraman.2019.01.001

Cited by 29 publications

(23 citation statements)

References 5 publications

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“…With the implementation of the 4D trajectory management, aircraft will not be constrained by waypoints and flight levels any more. Hence, air traffic will be more homogeneously distributed in the upper air space [20][21][22] . Therewith, the available capacity (i.e.…”

Section: Air Traffic Flow Managementmentioning

confidence: 99%

“…The resultant air traffic flow can be analysed with measures such as airspace capacity, controller's taskload and number and characteristics of separation infringements. Therewith, the ATFM can be assessed and compared with the reference scenario [20][21][22] . Until now, conflict resolution is not implemented in TOMATO because, each trajectory is individually optimised and because the computational effort has already reached the limits of a personal computer.…”

Section: Tomato Simulation Environmentmentioning

confidence: 99%

“…Furthermore, non-constant air speeds and cruising altitudes spread the aircraft more widely within the airspace and therewith increase the possible airspace capacity (i.e. maximum number of aircraft, integrated over the whole European airspace) 21,22 although wind speed and wind direction are considered in the optimisation function, amongst others. In the scenario of optimised trajectories, 1,637 artificial airspaces out of 2,739 (61°l ongitude times 39°latitude) artificial airspaces are used by aircraft during this hour, whereas in the reference scenario, only 1,554 artificial airspaces out of 2,739 artificial airspaces are used (compare Fig.…”

Section: Impact Of Optimised Trajectories On the Atfmmentioning

confidence: 99%

“…To date, these tasks have been treated separately. First analyses of the capability of TOMATO showed numerical and implementational difficulties in the analysis of investigations concerning the ATFM 20 , which have been solved by analysing the demand of individual aircraft on airspace capacity and its impact on the controller’s taskload 22 and regarding the distribution of conflicts as imminent separation infringements between individual aircraft 21 .…”

Section: Introductionmentioning

confidence: 99%

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Impact of optimised trajectories on air traffic flow management

et al. 2019

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Multicriteria trajectory optimisation is expected to increase aviation safety, efficiency and environmental compatibility, although neither the theoretical calculation of such optimised trajectories nor their implementation into today’s already safe and efficient air traffic flow management reaches a satisfying level of fidelity. The calibration of the underlying objective functions leading to the virtually best available solution is complicated and hard to identify, since the participating stakeholders are very competitive. Furthermore, operational uncertainties hamper the robust identification of an optimised trajectory. These uncertainties may arise from severe weather conditions or operational changes in the airport management. In this study, the impact of multicriteria optimised free route trajectories on the air traffic flow management is analysed and compared with a validated reference scenario which consists of real flown trajectories during a peak hour of Europe’s complete air traffic in the upper airspace. Therefore, the TOolchain for Multicriteria Aircraft Trajectory Optimisation (TOMATO) is used for both the multicriteria optimisation of txrajectories and the calculation of the reference scenario. First, this paper gives evidence for the validity of the simulation environment TOMATO, by comparison of the integrated reference results with those of the commercial fast-time air traffic optimiser (AirTOp). Second, TOMATO is used for the multicriteria trajectory optimisation, the assessment of the trajectories and the calculation of their integrated impact on the air traffic flow management, which in turn is compared with the reference scenario. Thereby, significant differences between the reference scenario and the optimised scenario can be identified, especially considering the taskload due to frequent altitude changes and rescinded constraints given by waypoints in the reference scenario. The latter and the strong impact of wind direction and wind speed cause wide differences in the patterns of the lateral trajectories in the airspace with significant influence on the airspace capacity and controller’s taskload. With this study, the possibility of a successful 4D free route implementation into Europe’s upper airspace is proven even over central Europe during peak hours, when capacity constraints are already reaching their limits.

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Section: Air Traffic Flow Managementmentioning

confidence: 99%

Section: Tomato Simulation Environmentmentioning

confidence: 99%

Section: Impact Of Optimised Trajectories On the Atfmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Impact of optimised trajectories on air traffic flow management

et al. 2019

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“…Technically, it would be possible to reduce uncertainties in the predicted trajectories to a minimum by operating all aircraft along deterministic 4D trajectories with defined Required Time of Arrival (RTA) at fixes along the flight path, as proven with flight tests in Seattle [2]. However, this will ultimately sacrifice the potential for optimization [3][4][5], which is an imperative for the efficiency and ecological targets defined by SESAR [1]. Therefore, a continuous trade-off between a high predictability of flight tracks for ATM and the freedom to optimize trajectories individually is required.…”

Section: Introductionmentioning

confidence: 99%

Interdependent Uncertainty Handling in Trajectory Prediction

2019

Self Cite

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The concept of 4D trajectory management relies on the prediction of aircraft trajectories in time and space. Due to changes in atmospheric conditions and complexity of the air traffic itself, the reliable prediction of system states is an ongoing challenge. The emerging uncertainties have to be modeled properly and considered in decision support tools for efficient air traffic flow management. Therefore, the subjacent causes for uncertainties, their effects on the aircraft trajectory and their dependencies to each other must be understood in detail. Besides the atmospheric conditions as the main external cause, the aircraft itself induces uncertainties to its trajectory. In this study, a cause-and-effect model is introduced, which deals with multiple interdependent uncertainties with different stochastic behavior and their impact on trajectory prediction. The approach is applied to typical uncertainties in trajectory prediction, such as the actual take-off mass, non-constant true air speeds, and uncertain weather conditions. The continuous climb profiles of those disturbed trajectories are successfully predicted. In general, our approach is applicable to all sources of quantifiable interdependent uncertainties. Therewith, ground-based trajectory prediction can be improved and a successful implementation of trajectory-based operations in the European air traffic system can be advanced.

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Dynamic Airspace Configuration: A Short Review of Computational Approaches

Graña

2019

Computational Collective Intelligence

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Impact of multi-criteria optimized trajectories on European airline efficiency, safety and airspace demand

Cited by 29 publications

References 5 publications

Impact of optimised trajectories on air traffic flow management

Impact of optimised trajectories on air traffic flow management

Interdependent Uncertainty Handling in Trajectory Prediction

Dynamic Airspace Configuration: A Short Review of Computational Approaches

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