Emergency Trajectory Structure for UAVs
The study of the design of emergency trajectories of air vehicles is one of the key elements in improving airspace safety for air vehicles. The aim is to lighten pilots’ workload, offering quick and effective solutions. However, almost all flight optimizers proposed in the literature still need to b...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Aerospace |
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| Online Access: | https://www.mdpi.com/2226-4310/12/1/21 |
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| author | Maëva Ongale-Obeyi Damien Goubinat Daniel Delahaye Pierre-Loïc Garoche |
| author_facet | Maëva Ongale-Obeyi Damien Goubinat Daniel Delahaye Pierre-Loïc Garoche |
| author_sort | Maëva Ongale-Obeyi |
| collection | DOAJ |
| description | The study of the design of emergency trajectories of air vehicles is one of the key elements in improving airspace safety for air vehicles. The aim is to lighten pilots’ workload, offering quick and effective solutions. However, almost all flight optimizers proposed in the literature still need to be completed when it comes to resolving emergency contexts, which presents a significant disadvantage to the advancement of scientific research. This resolution is based on the following problems: (a) finding paths free of obstacles, (b) ensuring their flight capacity, and finally, (c) calculating trajectories optimizing several criteria with a calculation time constraint (a few minutes). This document analyzes the safety landing problem and proposes an architecture that effectively reduces complexity and ensures solvability within a reasonable computational time. This architectural framework is designed to be adaptable, allowing for testing several algorithms to provide a quick overview of their strengths and weaknesses in this context. The primary aim of these tests is to benchmark the computational time of the overall architecture, ensuring that this adaptable framework is fully capable of handling the problem’s complexity. It is important to note that the algorithms chosen address only a simplified version of the problem. The initial results are promising in terms of time response and the potential to enhance the representativeness and complexity of the problem. The next phase of our research will focus on striking the right balance between complexity, representativity, and computational time, aiming to impact emergency response significantly. |
| format | Article |
| id | doaj-art-90410558b00241e29c6b9822a0e71a43 |
| institution | Kabale University |
| issn | 2226-4310 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Aerospace |
| spelling | doaj-art-90410558b00241e29c6b9822a0e71a432025-01-24T13:15:29ZengMDPI AGAerospace2226-43102024-12-011212110.3390/aerospace12010021Emergency Trajectory Structure for UAVsMaëva Ongale-Obeyi0Damien Goubinat1Daniel Delahaye2Pierre-Loïc Garoche3Thales Avionics France, 31100 Toulouse, FranceThales Canada Inc., Montréal, QC H4S 2C2, CanadaEcole Nationale de l’Aviation Civile, Université de Toulouse, 31400 Toulouse, FranceEcole Nationale de l’Aviation Civile, Université de Toulouse, 31400 Toulouse, FranceThe study of the design of emergency trajectories of air vehicles is one of the key elements in improving airspace safety for air vehicles. The aim is to lighten pilots’ workload, offering quick and effective solutions. However, almost all flight optimizers proposed in the literature still need to be completed when it comes to resolving emergency contexts, which presents a significant disadvantage to the advancement of scientific research. This resolution is based on the following problems: (a) finding paths free of obstacles, (b) ensuring their flight capacity, and finally, (c) calculating trajectories optimizing several criteria with a calculation time constraint (a few minutes). This document analyzes the safety landing problem and proposes an architecture that effectively reduces complexity and ensures solvability within a reasonable computational time. This architectural framework is designed to be adaptable, allowing for testing several algorithms to provide a quick overview of their strengths and weaknesses in this context. The primary aim of these tests is to benchmark the computational time of the overall architecture, ensuring that this adaptable framework is fully capable of handling the problem’s complexity. It is important to note that the algorithms chosen address only a simplified version of the problem. The initial results are promising in terms of time response and the potential to enhance the representativeness and complexity of the problem. The next phase of our research will focus on striking the right balance between complexity, representativity, and computational time, aiming to impact emergency response significantly.https://www.mdpi.com/2226-4310/12/1/21emergencyautonomous decision support frameworkmultiple trajectory planning |
| spellingShingle | Maëva Ongale-Obeyi Damien Goubinat Daniel Delahaye Pierre-Loïc Garoche Emergency Trajectory Structure for UAVs Aerospace emergency autonomous decision support framework multiple trajectory planning |
| title | Emergency Trajectory Structure for UAVs |
| title_full | Emergency Trajectory Structure for UAVs |
| title_fullStr | Emergency Trajectory Structure for UAVs |
| title_full_unstemmed | Emergency Trajectory Structure for UAVs |
| title_short | Emergency Trajectory Structure for UAVs |
| title_sort | emergency trajectory structure for uavs |
| topic | emergency autonomous decision support framework multiple trajectory planning |
| url | https://www.mdpi.com/2226-4310/12/1/21 |
| work_keys_str_mv | AT maevaongaleobeyi emergencytrajectorystructureforuavs AT damiengoubinat emergencytrajectorystructureforuavs AT danieldelahaye emergencytrajectorystructureforuavs AT pierreloicgaroche emergencytrajectorystructureforuavs |