Conference
Deep Learning in Aeronautics: Air Traffic Trajectory Classification Based on Weather Reports
| العنوان: | Deep Learning in Aeronautics: Air Traffic Trajectory Classification Based on Weather Reports |
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| المؤلفون: | Jiménez-Campfens, Néstor, Colomer, Adrián, Núñez, Javier, Mogollón, Juan Manuel, Rodríguez, Antonio L., Naranjo Ornedo, Valeriana |
| المساهمون: | Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions, European Commission |
| بيانات النشر: | Springer |
| سنة النشر: | 2020 |
| المجموعة: | Universitat Politécnica de Valencia: RiuNet / Politechnical University of Valencia |
| مصطلحات موضوعية: | Air Traffic Management, Weather reports, METAR, Trajectory prediction, Deep learning, TEORIA DE LA SEÑAL Y COMUNICACIONES |
| الوصف: | [EN] New paradigms in aviation, as the expected shortage of qualified pilots and the increasing number of flights worldwide, present big challenges to aeronautic enterprises and regulators. In this sense, a concept known as Single Pilot Operations arises in the task of dealing with these challenges, for which, automation becomes necessary, especially in Air Traffic Management. In this regard, this paper presents a deep learning-based approach to leveraging the job of both ground controllers and pilots. Making use of Meteorological Terminal Air Reports, obtained regularly from every aerodrome worldwide, we created a model based on a multi-layer perceptron capable of determining the approach trajectory of an aircraft thirty minutes prior to the expected landing time. Experiments on aircraft trajectories from Toulouse to Seville, show an accuracy, recall and F1-score higher than 0.9 for the resultant predictive model. ; This work has received funding from the Clean Sky 2 Joint Undertaking (JU) under grant agreement No 831884. The Titan V used for this research was donated by the NVIDIA Corporation ; Jiménez-Campfens, N.; Colomer, A.; Núñez, J.; Mogollón, JM.; Rodríguez, AL.; Naranjo Ornedo, V. (2020). Deep Learning in Aeronautics: Air Traffic Trajectory Classification Based on Weather Reports. Springer. 148-155. https://doi.org/10.1007/978-3-030-62365-4_14 ; 148 ; 155 ; Pilot and technical outlook: Seattle. Boeing Commercial Airplanes, WA (2015) ; Wolter, C.A., Gore, B.F.: NASA/TM-2015-218480: A validated task analysis of the Single Pilot Operations concept, no. January 2015 (2015) ; Harris, D.: A human-centred design agenda for the development of single crew operated commercial aircraft. Aircr. Eng. Aerosp. Technol. 79(5), 518–526 (2007) ; Bailey, R.E., Kramer, L.J., Kennedy, K.D., Stephens, C.L., Etherington, T.J.: An assessment of reduced crew and single pilot operations in commercial transport aircraft operations. In: AIAA/IEEE Digital Avionics System Conference - Proceedings, vol. 2017-September, no. February ... |
| نوع الوثيقة: | conference object |
| اللغة: | English |
| Relation: | Intelligent Data Engineering and Automated Learning ¿ IDEAL 2020; Lecture Notes in Computer Science;12490; info:eu-repo/grantAgreement/EC/H2020/831884/EU/HUMAN AIRCRAFT ROADMAP FOR VIRTUAL INTELLIGENT SYSTEM/; 21st International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2020); Noviembre 04-06,2020; Online; https://doi.org/10.1007/978-3-030-62365-4_14; http://hdl.handle.net/10251/160616 |
| DOI: | 10.1007/978-3-030-62365-4_14 |
| الاتاحة: | http://hdl.handle.net/10251/160616 https://doi.org/10.1007/978-3-030-62365-4_14 |
| Rights: | http://rightsstatements.org/vocab/InC/1.0/ ; info:eu-repo/semantics/openAccess |
| رقم الانضمام: | edsbas.D9DEF5E8 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1007/978-3-030-62365-4_14 |
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