2015
DOI: 10.1016/j.trc.2015.10.014
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Operating cost sensitivity to required time of arrival commands to ensure separation in optimal aircraft 4D trajectories

Abstract: Trajectory optimisation has shown good potential to reduce environmental impact in aviation. However, a recurring problem is the loss in airspace capacity that fuel optimal procedures pose, usually overcome with speed, altitude or heading advisories that lead to more costly trajectories. This paper aims at the quantification in terms of fuel and time consumption of implementing suboptimal trajectories in a 4D trajectory context that use required times of arrival at specific navigation fixes. A case study is pr… Show more

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Cited by 22 publications
(12 citation statements)
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“…Ref. [5] concludes that this coordinated distributed strategy can render very efficient results. through the said future collaboration frameworks.…”
Section: Concept Of Operationsmentioning
confidence: 97%
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“…Ref. [5] concludes that this coordinated distributed strategy can render very efficient results. through the said future collaboration frameworks.…”
Section: Concept Of Operationsmentioning
confidence: 97%
“…as the authors presented in Ref. [5]; whereas in the noncooperative case the trajectory prediction could only rely on current and historical data to produce the immediate future states (these cases will be further studied in future work). Additionally, even if only one conflict is assumed in the results, the implemented separation strategy is easily extrapolated to multiple conflicts.…”
Section: Conclusion and Further Workmentioning
confidence: 99%
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“…This means that aircraft attitude (pitch angle) will not be used, and the task can be further simplified by adopting a two-dimensional point-mass model with two DOF (velocity and flight-path angle) [19]. This approach is often used when referring to aircraft scheduling problems [20,21].…”
Section: Aircraft Point-mass Modelmentioning
confidence: 99%
“…CONOPT was chosen as the NLP solver, as it was designed to cope with various NLP problems, also with the ones with a small number of DOF. This solver was used many times in previous studies for trajectory optimization during descent [20,21]. The design variables were flight-path angle, thrust, velocity, and Mach number.…”
Section: A Experimental Setupmentioning
confidence: 99%