Publications

http://joss.theoj.org/papers/10.21105/joss.01518/status.svg

If you find this project useful for your research and use it in an academic work, you may cite it as:

@article{olive2019traffic,
    author={Xavier {Olive}},
    journal={Journal of Open Source Software},
    title={traffic, a toolbox for processing and analysing air traffic data},
    year={2019},
    volume={4},
    pages={1518},
    doi={10.21105/joss.01518},
    issn={2475-9066},
}

The following list contains publications from research using the traffic library:

  • X. Olive and L. Basora
    Identifying Anomalies in past en-route Trajectories with Clustering and Anomaly Detection Methods. Proceedings of the 13th Air Traffic Management R&D Seminar, 2019
  • X. Olive, J. Grignard, T. Dubot and J. Saint-Lot.
    Detecting Controllers’ Actions in Past Mode S Data by Autoencoder-Based Anomaly Detection. Proceedings of the SESAR Innovation Days, 2018
  • X. Olive and P. Bieber.
    Quantitative Assessments of Runway Excursion Precursors using Mode S Data. Proceedings of the 8th International Conference on Research in Air Transportation, 2018 (Best paper award)
  • X. Olive and J. Morio.
    Trajectory clustering of air traffic flows around airports. Aerospace Science and Technology 84, 2019, pp. 776–781.

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