A. Srinivasamurthy, P. Motlicek, M. Singh, Y. Oualil, M. Kleinert et al., Iterative learning of speech recognition models for air traffic control, Proceedings of the International Conference on Spoken Language Processing, pp.3519-3523, 2018.

S. V. Subramanian, P. F. Kostiuk, and G. Katz, Custom IBM Watson speech-to-text model for anomaly detection using ATC-pilot voice communication, Proceedings of the Aviation Technology, Integration, and Operations Conference, p.3979, 2018.

M. Schäfer, M. Strohmeier, V. Lenders, I. Martinovic, and M. Wilhelm, Bringing up OpenSky: A large-scale ADS-B sensor network for research, Proceedings of the 13th international symposium on Information processing in sensor networks, pp.83-94, 2014.

S. Cafieri and N. Durand, Aircraft deconfliction with speed regulation: new models from mixed-integer optimization, Journal of Global Optimization, vol.58, issue.4, pp.613-629, 2014.
URL : https://hal.archives-ouvertes.fr/hal-00935215

C. Allignol, N. Barnier, P. Flener, and J. Pearson, Constraint programming for air traffic management: a survey, The Knowledge Engineering Review, vol.27, issue.3, pp.361-392, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00934670

N. Durand, J. Alliot, and J. Noailles, Automatic aircraft conflict resolution using genetic algorithms, Proceedings of the symposium on Applied Computing, pp.289-298, 1996.
URL : https://hal.archives-ouvertes.fr/hal-00937685

D. Gianazza, Forecasting workload and airspace configuration with neural networks and tree search methods, Artificial intelligence, vol.174, issue.7-8, p.530, 2010.
URL : https://hal.archives-ouvertes.fr/hal-01020725

Y. Lü, Y. Duan, W. Kang, Z. Li, and F. Wang, Traffic flow prediction with big data: A deep learning approach, IEEE Transactions on Intelligent Transportation Systems, vol.16, issue.2, pp.865-873, 2015.

C. D. Ciccio, H. Van-der-aa, C. Cabanillas, J. Mendling, and J. Prescher, Detecting flight trajectory anomalies and predicting diversions in freight transportation, Decision Support Systems, vol.88, pp.1-17, 2016.

X. Olive and P. Bieber, Quantitative assessments of runway excursion precursors using Mode S data, Proceedings of the International Conference for Research in Air Transportation, 2018.
URL : https://hal.archives-ouvertes.fr/hal-02078299

F. Nicol, Functional principal component analysis of aircraft trajectories, Proceedings of the 2nd International Conference on Interdisciplinary Science for Innovative Air Traffic Management, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00867957

Y. Liu, M. Hansen, D. J. Lovell, and M. O. Ball, Predicting aircraft trajectory choice -a nominal route approach, Proceedings of the International Conference for Research in Air Transportation, 2018.

M. Brittain and P. Wei, Autonomous aircraft sequencing and separation with hierarchical deep reinforcement learning, Proceedings of the International Conference for Research in Air Transportation, 2018.

M. Gariel, A. N. Srivastava, and E. Feron, Trajectory clustering and an application to airspace monitoring, IEEE Transactions on Intelligent Transportation Systems, vol.12, issue.4, pp.1511-1524, 2011.

M. Conde-rocha-murca, R. Delaura, R. J. Hansman, R. Jordan, T. Reynolds et al., Trajectory clustering and classification for characterization of air traffic flows, Proceedings of the 16th Aviation Technology, Integration, and Operations Conference, 2016.

S. Das, B. L. Matthews, A. N. Srivastava, and N. C. Oza, Multiple kernel learning for heterogeneous anomaly detection: algorithm and aviation safety case study, Proceedings of the 16th international conference on Knowledge discovery and data mining, pp.47-56, 2010.

B. Matthews, D. Nielsen, J. Schade, K. Chan, and M. Kiniry, Automated discovery of flight track anomalies, Proceedings of the 33rd Digital Avionics Systems Conference, 2014.

W. Lee, J. Ortiz, B. Ko, and R. Lee, Time series segmentation through automatic feature learning, 2018.

T. Dubot, Predicting sector configuration transitions with autoencoderbased anomaly detection, Proceedings of the International Conference for Research in Air Transportation, 2018.

M. Gonen and E. Alpaydin, Multiple kernel learning algorithms, Journal of Machine Learning Research, pp.2211-2268, 2011.