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

    author={Xavier {Olive}},
    journal={Journal of Open Source Software},
    title={traffic, a toolbox for processing and analysing air traffic data},

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

  • S. Corrado, T. Puranik, O. J. Pinon-Fischer and D. Mavris
    A clustering-based quantitative analysis of the interdependent relationship between spatial and energy anomalies in ADS-B trajectory data
    Transportation Research Part C: Emerging Technologies, vol. 131, pp. 103331, 2021
  • A. Filippone and B. Parkes
    Evaluation of commuter airplane emissions: A European case study
    Transportation Research Part D: Transport and Environment, vol. 98, pp. 102979, 2021
  • A. Filippone, B. Parkes, N. Bojdo and T. Kelly
    Prediction of aircraft engine emissions using ADS-B flight data
    The Aeronautical Journal, vol. 125, issue 1288, pp. 988–1012, 2021
  • S. Corrado, T. Puranik, O. J. Pinon-Fischer, D. Mavris, R. Rose, J. Williams and R. Heidary
    Deep Autoencoder for Anomaly Detection in Terminal Airspace Operations
    Proceedings of the AIAA aviation forum, 2021
  • J. Sun
    The 1090 Megahertz Riddle: A Guide to Decoding Mode S and ADS-B Signals
    ISBN: 978-94-6366-402-8, 2021
  • X. Olive, J. Sun, A. Lafage and L. Basora
    Detecting Events in Aircraft Trajectories: Rule-based and Data-driven Approaches
    Proceedings of the 8th OpenSky Symposium, 2020
  • J. Sun, H. Vû, X. Olive and J. Hoekstra
    Mode S Transponder Comm-B Capabilities in Current Operational Aircraft
    Proceedings of the 8th OpenSky Symposium, 2020
  • X. Olive, A. Tanner, M. Strohmeier, M. Schäfer, M. Feridun, A. Tart, I. Martinovic and V. Lenders.
    OpenSky Report 2020: Analysing in-flight emergencies using big data.
    Proceedings of the 39th Digital Avionics Systems Conference (DASC), 2020
  • G. Lui, R. Liem and K. Hon.
    Towards understanding the impact of convective weather on aircraft arrival traffic at the Hong Kong International Airport
    IOP Conference Series: Earth and Environmental Science, vol. 569, pp. 012067, 2020
  • X. Olive and L. Basora
    Detection and identification of significant events in historical aircraft trajectory data.
    Transportation Research Part C: Emerging Technologies, vol. 119, pp. 102737, 2020
  • A. Pellegrini, P. Di Sanzo, B. Bevilacqua, G. Duca, D. Pascarella, R. Palumbo, J. J. Ramos, M. À. Piera and G. Gigante.
    Simulation-Based Evolutionary Optimization of Air Traffic Management.
    IEEE Access, vol. 8, pp. 161551-161570, 2020
  • X. Olive and J. Sun
    Detecting and Measuring Turbulence from Mode S Surveillance Downlink Data.
    Proceedings of the 9th International Conference on Research in Air Transportation, 2020
  • X. Olive, L. Basora, B. Viry and R. Alligier
    Deep Trajectory Clustering with Autoencoders.
    Proceedings of the 9th International Conference on Research in Air Transportation, 2020
  • S. Proud.
    Go-Around Detection Using Crowd-Sourced ADS-B Position Data.
    Aerospace, 2020, 7(2), 16
  • M. Schultz, X. Olive, J. Rosenow, H. Fricke, S. Alam.
    Analysis of airport ground operations based on ADS-B data. Proceedings of the 1st conference on Artificial Intelligence and Data Analytics in Air Transportation (AIDA-AT), 2020
  • M. Schultz, J. Rosenow and X. Olive.
    A-CDM Lite: situation awareness and decision making for small airports based on ADS-B data.
    Proceedings of the 9th SESAR Innovation Days, 2019.
  • X. Olive and L. Basora.
    Air Traffic Data Processing using Python: Trajectory Clustering.
    Proceedings of the 7th OpenSky Workshop, 2019.
  • M. Schäfer, X. Olive, M. Strohmeier, M. Smith, I. Martinovic, V. Lenders.
    OpenSky Report 2019: Analysing TCAS in the Real World using Big Data.
    Proceedings of the 38th Digital Avionics Systems Conference (DASC), 2019
  • 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 8th 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.