Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
Discussion On Density-Based Clustering Methods Applied for Automated Identification of Airspace Flows
Year:2018
Research Areas
  • Flight control,
  • Air traffic control,
  • Air traffic management,
  • Air transport,
  • Civil aviation
Information
Abstract
Air Traffic Management systems generate a huge amount of track data daily. Flight trajectories can be clustered to extract main air traffic flows by means of unsupervised machine learning techniques. A well-known methodology for unsupervised extraction of air traffic flows conducts a two-step process. The first step reduces the dimensionality of the track data, whereas the second step clusters the data based on a density-based algorithm, DBSCAN. This paper explores advancements in density-based clustering such as OPTICS or HDBSCAN*. This assessment is based on quantitative and qualitative evaluations of the clustering solutions offered by these algorithms. In addition, the paper proposes a hierarchical clustering algorithm for handling noise in this methodology. This algorithm is based on a recursive application of DBSCAN* (RDBSCAN*). The paper demonstrates the sensitivity of these algorithms to different hyper-parameters, recommending a specific setting for the main one, which is common for all methods. RDBSCAN* outperforms the other algorithms in terms of the density-based internal validity metric. Finally, the outcome of the clustering shows that the algorithm extracts main clusters of the dataset effectively, connecting outliers to these main clusters.
International
Si
Congress
37th Digital Avionics Systems Conference (DASC 2017)
960
Place
Londres
Reviewers
Si
ISBN/ISSN
978-1-5386-4112-5
Start Date
23/09/2018
End Date
27/09/2018
From page
584
To page
593
Discussion On Density-Based Clustering Methods Applied for Automated Identification of Airspace Flows
Participants
  • Autor: Cristian Eduardo Verdonk Gallego (UPM)
  • Autor: Victor Fernando Gomez Comendador (UPM)
  • Autor: Fco. Javier Saez Nieto (UPM)
  • Autor: Miguel García Martínez (CRIDA A.I.E.)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Navegación Aérea
  • Departamento: Sistemas Aeroespaciales, Transporte Aéreo y Aeropuertos
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