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    Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10259/6849

    Título
    A data-driven approach for dynamic and adaptive aircraft trajectory prediction
    Autor
    Rodríguez-Sanz, Álvaro
    Cordero García, José Manuel
    García Ovies-Carro, Icíar
    Iglesias, Enrique
    Publicado en
    R-Evolucionando el transporte
    Editorial
    Universidad de Burgos. Servicio de Publicaciones e Imagen Institucional
    Fecha de publicación
    2021-07
    ISBN
    978-84-18465-12-3
    DOI
    10.36443/10259/6849
    Descripción
    Trabajo presentado en: R-Evolucionando el transporte, XIV Congreso de Ingeniería del Transporte (CIT 2021), realizado en modalidad online los días 6, 7 y 8 de julio de 2021, organizado por la Universidad de Burgos
    Resumen
    Traffic Prediction (TP) is a key element in Air Traffic Management (ATM), as it plays a fundamental role in adjusting capacity and available resources to current demand, as well as in helping detect and solve potential conflicts. Moreover, the future implementation of the Trajectory Based Operations (TBO) concept will impose on aircraft the compliance of very accurately arrival times over designated points. In this sense, an improvement in TP aims at enabling an efficient management of the expected increase in air traffic strategically, with tactical interventions only as a last resort. To achieve this objective, the ATM system needs tools to support traffic and trajectory management functions, such as strategic planning, trajectory negotiation and collaborative de-confliction. In all of these tasks, trajectory and traffic prediction represents a cornerstone. The problem of achieving an accurate and reliable trajectory and traffic prediction has been tackled through different methodologies, with different levels of complexity. There are two main aspects to be considered when assessing the most appropriate forecasting methodology: (a) timehorizon: depending on the timescale (anticipation before the day of operations), the level of uncertainty associated to the prediction will be different; and (b) input data: both the source and the quality of the input data (completeness, validity, accuracy, consistency, availability and timeliness) are key characteristics when assessing the viability of the prediction. This study develops a methodology for TP and traffic forecasting in a pre-tactical phase (one day to six days before the day of operations), when few or no flight plans are available. This should be adjusted to different time scales (planning horizons), taking into account the level of predictability of each of them. We propose a data-driven, dynamic and adaptive TP framework, which can be accommodated to different Airspace Users’ characteristics and strategies.
    Palabras clave
    Aeropuertos
    Airports
    Materia
    Ingeniería civil
    Civil engineering
    Transportes
    Transportation
    URI
    http://hdl.handle.net/10259/6849
    Versión del editor
    https://doi.org/10.36443/9788418465123
    Aparece en las colecciones
    • Congreso de Ingeniería del Transporte CIT 2021 (14º. 2021. Burgos)
    Ficheros en este ítem
    Nombre:
    Rodríguez_CIT2021_29-60.pdf
    Tamaño:
    1.205Mb
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