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International audience; Air traffic management ensures the safety of flight by optimizing flows and maintaining separation between aircraft. After giving some definitions, some typical feature of aircraft trajectories are presented. Trajectories are objects belonging to spaces with infinite dimensions. The naive way to address such problem is to sample trajectories at some regular points and to create a big vector of positions (and or speeds). In order to manipulate such objects with algorithms, one must reduce the dimension of the search space by using more efficient representations. Some dimension reduction tricks are then presented for which advantages and drawbacks are presented. Then, front propagation approaches are introduced with a focus on Fast Marching Algorithms and Ordered upwind algorithms. An example of application of such algorithm to a real instance of air traffic control problem is also given. When aircraft dynamics have to be included in the model, optimal control approaches are really efficient. We present also some application to aircraft trajectory design. Finally, we introduce some path planning techniques via natural language processing and mathematical programming. | International audience; Air traffic management ensures the safety of flight by optimizing flows and maintaining separation between aircraft. After giving some definitions, some typical feature of aircraft trajectories are presented. Trajectories are objects belonging to spaces with infinite dimensions. The naive way to address such problem is to sample trajectories at some regular points and to create a big vector of positions (and or speeds). In order to manipulate such objects with algorithms, one must reduce the dimension of the search space by using more efficient representations. Some dimension reduction tricks are then presented for which advantages and drawbacks are presented. Then, front propagation approaches are introduced with a focus on Fast Marching Algorithms and Ordered upwind algorithms. An example of application of such algorithm to a real instance of air traffic control problem is also given. When aircraft dynamics have to be included in the model, optimal control approaches are really efficient. We present also some application to aircraft trajectory design. Finally, we introduce some path planning techniques via natural language processing and mathematical programming. | ||
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* [http://hal-enac.archives-ouvertes.fr/docs/00/91/32/43/PDF/Delahaye_EIWAC2013.pdf http://hal-enac.archives-ouvertes.fr/docs/00/91/32/43/PDF/Delahaye_EIWAC2013.pdf] | * [http://hal-enac.archives-ouvertes.fr/docs/00/91/32/43/PDF/Delahaye_EIWAC2013.pdf http://hal-enac.archives-ouvertes.fr/docs/00/91/32/43/PDF/Delahaye_EIWAC2013.pdf] | ||
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| + | * [http://link.springer.com/content/pdf/10.1007/978-4-431-54475-3_12 http://link.springer.com/content/pdf/10.1007/978-4-431-54475-3_12], | ||
| + | : [http://dx.doi.org/10.1007/978-4-431-54475-3_12 http://dx.doi.org/10.1007/978-4-431-54475-3_12] | ||
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| + | * [https://hal-enac.archives-ouvertes.fr/hal-00913243 https://hal-enac.archives-ouvertes.fr/hal-00913243], | ||
| + | : [https://hal-enac.archives-ouvertes.fr/hal-00913243/document https://hal-enac.archives-ouvertes.fr/hal-00913243/document], | ||
| + | : [https://hal-enac.archives-ouvertes.fr/hal-00913243/file/Delahaye_EIWAC2013.pdf https://hal-enac.archives-ouvertes.fr/hal-00913243/file/Delahaye_EIWAC2013.pdf] | ||
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| + | * [https://hal-enac.archives-ouvertes.fr/hal-00913243/document https://hal-enac.archives-ouvertes.fr/hal-00913243/document], | ||
| + | : [https://link.springer.com/chapter/10.1007/978-4-431-54475-3_12 https://link.springer.com/chapter/10.1007/978-4-431-54475-3_12], | ||
| + | : [https://hal-enac.archives-ouvertes.fr/hal-00913243 https://hal-enac.archives-ouvertes.fr/hal-00913243], | ||
| + | : [https://www.scipedia.com/public/Delahaye_et_al_2014a https://www.scipedia.com/public/Delahaye_et_al_2014a], | ||
| + | : [https://rd.springer.com/chapter/10.1007/978-4-431-54475-3_12 https://rd.springer.com/chapter/10.1007/978-4-431-54475-3_12], | ||
| + | : [https://link.springer.com/chapter/10.1007/978-4-431-54475-3_12/fulltext.html https://link.springer.com/chapter/10.1007/978-4-431-54475-3_12/fulltext.html], | ||
| + | : [https://academic.microsoft.com/#/detail/2218203127 https://academic.microsoft.com/#/detail/2218203127] | ||
Latest revision as of 16:31, 21 January 2021
Abstract
International audience; Air traffic management ensures the safety of flight by optimizing flows and maintaining separation between aircraft. After giving some definitions, some typical feature of aircraft trajectories are presented. Trajectories are objects belonging to spaces with infinite dimensions. The naive way to address such problem is to sample trajectories at some regular points and to create a big vector of positions (and or speeds). In order to manipulate such objects with algorithms, one must reduce the dimension of the search space by using more efficient representations. Some dimension reduction tricks are then presented for which advantages and drawbacks are presented. Then, front propagation approaches are introduced with a focus on Fast Marching Algorithms and Ordered upwind algorithms. An example of application of such algorithm to a real instance of air traffic control problem is also given. When aircraft dynamics have to be included in the model, optimal control approaches are really efficient. We present also some application to aircraft trajectory design. Finally, we introduce some path planning techniques via natural language processing and mathematical programming.
Original document
The different versions of the original document can be found in:
- https://hal-enac.archives-ouvertes.fr/hal-00913243/document,
- https://hal-enac.archives-ouvertes.fr/hal-00913243/file/Delahaye_EIWAC2013.pdf
- https://link.springer.com/chapter/10.1007/978-4-431-54475-3_12,
- https://hal-enac.archives-ouvertes.fr/hal-00913243,
- https://www.scipedia.com/public/Delahaye_et_al_2014a,
- https://rd.springer.com/chapter/10.1007/978-4-431-54475-3_12,
- https://link.springer.com/chapter/10.1007/978-4-431-54475-3_12/fulltext.html,
- https://academic.microsoft.com/#/detail/2218203127
Document information
Published on 01/01/2014
Volume 2013, 2014
DOI: 10.1007/978-4-431-54475-3_12
Licence: CC BY-NC-SA license
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