Benoit Figuet

Projekte

• Making I-CNS A Reality: New aviation technology for integrated communication, navigation, and surveillance / Teammitglied / laufend
• Auswirkungen von Störsignalen im Luftverkehr / Stellv. Projektleiter:in / abgeschlossen
• High Operational Reliability for Unmanned Systems / Stellv. Projektleiter:in / abgeschlossen
• Neuartiger generischer Collision-Avoidance-Algorithmus / Teammitglied / abgeschlossen

Publikationen

Beiträge in wissenschaftlicher Zeitschrift, peer-reviewed

• Felux, M. et al. (2024) ‘Impacts of global navigation satellite system jamming on aviation’, Navigation : Journal of the Institute of Navigation, 71(3), p. navi.657. doi: 10.33012/navi.657.
• Krauth, T. et al. (2024) ‘Advanced collision risk estimation in terminal manoeuvring areas using a disentangled variational autoencoder for uncertainty quantification’, Engineering Applications of Artificial Intelligence, 133, Part B(108137). doi: 10.1016/j.engappai.2024.108137.
• Figuet, B. et al. (2023) ‘Data-driven mid-air collision risk modelling using extreme-value theory’, Aerospace Science and Technology, 142, Part A(108646). doi: 10.1016/j.ast.2023.108646.

Schriftliche Konferenzbeiträge, peer-reviewed

• Figuet, B., Krauth, T. and Barry, S. (2026) ‘Generative short-term aircraft trajectory prediction with conditional flow matching’, in Journal of Open Aviation Science. TU Delft Open Publishing. doi: 10.59490/joas.2026.8468.
• Felux, M. et al. (2025) ‘Navigating turbulence : understanding new GNSS risks in conflict zones’. IEEE, pp. 245–264. doi: 10.23919/cycon65856.2025.11103718.
• Waltert, M., Figuet, B. and Felux, M. (2025) ‘Evaluating potential fuel-savings of external alternative ground propulsion systems’, in Journal of Open Aviation Science. TU Delft Open Publishing. doi: 10.59490/joas.2024.7888.
• Olive, X. et al. (2025) ‘Filtering techniques for ADS-B trajectory preprocessing’, in Journal of Open Aviation Science. TU Delft Open Publishing. doi: 10.59490/joas.2024.7882.
• Felux, M. et al. (2025) ‘Navigating interference : examining in-flight GNSS spoofing patterns and signal disruptions’, in Proceedings of the 2025 International Technical Meeting of The Institute of Navigation. Manassas, VA: Institute of Navigation. doi: 10.33012/2025.19966.
• Waltert, M. and Figuet, B. (2023) ‘Using ADS-B trajectories to measure how rapid exit taxiways affect airport capacity’, in Journal of Open Aviation Science. TU Delft Open Publishing. doi: 10.59490/joas.2023.7207.
• Figuet, B. et al. (2023) ‘Analysing the impact of go-around occurrences at Large European airports’, in Journal of Open Aviation Science. TU Delft Open Publishing. doi: 10.59490/joas.2023.7219.
• Figuet, B., Monstein, R. and Steven, B. (2023) ‘Data-driven airborne collision risk modelling using a probability density function’, in 15th Air Traffic Management Research and Development Seminar, Savannah, USA, 5-9 June 2023. ATM Seminar. doi: 10.21256/zhaw-28806.
• Krauth, T. et al. (2023) ‘Collision risk assessment in terminal manoeuvring areas based on trajectory generation methods’, in 15th Air Traffic Management Research and Development Seminar, Savannah, USA, 5-9 June 2023. ATM Seminar. doi: 10.21256/zhaw-28805.
• Felux, M. et al. (2023) ‘Analysis of GNSS disruptions in European airspace’, in Proceedings of the 2023 International Technical Meeting of The Institute of Navigation. Manassas: Institute of Navigation, pp. 315–326. doi: 10.33012/2023.18626.
• Figuet, B. et al. (2022) ‘GNSS jamming and its effect on air traffic in Eastern Europe’, in Engineering Proceedings. MDPI, p. 12. doi: 10.3390/engproc2022028012.
• Monstein, R. et al. (2022) ‘Large landing trajectory dataset for go-around analysis’, in Engineering Proceedings. MDPI, p. 2. doi: 10.3390/engproc2022028002.
• Figuet, B. et al. (2022) ‘Impact of GNSS outage on mid-air collision’, in Proceedings of the IWAC2022. Tokyo: Electronic Navigation Research Institute, pp. 41–48.
• Figuet, B. et al. (2022) ‘HORUS : High Operational Reliability for Unmanned Systems’, in 48th European Rotorcraft Forum (ERF), Winterthur, Switzerland, 6-9 September 2022. European Rotorcraft Forum. doi: 10.21256/zhaw-27218.
• Krauth, T. et al. (2021) ‘Synthetic aircraft trajectories generated with multivariate density models’, in Engineering Proceedings. MDPI, p. 7. doi: 10.3390/engproc2021013007.
• Figuet, B. et al. (2020) ‘Predicting airplane go-arounds using machine learning and open-source data’, in Proceedings. MDPI. doi: 10.3390/proceedings2020059006.
• Figuet, B., Monstein, R. and Felux, M. (2020) ‘Combined multilateration with machine learning for enhanced aircraft localization’, in Proceedings. MDPI. doi: 10.3390/proceedings2020059002.

Forschungsdaten

Monstein, Raphael; Figuet, Benoit; Krauth, Timothé; Waltert, Manuel; Dettling, Marcel, 2022. Large landing trajectory data set for go-around analysis. Zenodo. Verfügbar unter: https://doi.org/10.5281/zenodo.7148117

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