In air transport network management, in addition to defining the performance behavior of the system’s components, identification of their interaction dynamics is a delicate issue in both strategic and tactical decision-making process so as to decide which elements of the system are “controlled” and how. This paper introduces a novel delay propagation model utilizing epidemic spreading process, which enables the definition of novel performance indicators and interaction rates of the elements of the air transportation network. In order to understand the behavior of the delay propagation over the network at different levels, we have constructed two different data-driven epidemic models approximating the dynamics of the system: (a) flight-based epidemic model and (b) airport-based epidemic model. The flight-based epidemic model utilizing SIS epidemic model focuses on the individual flights where each flight can be in susceptible or infected states. The airport-centric epidemic model, in addition to the flight-to-flight interactions, allows us to define the collective behavior of the airports, which are modeled as metapopulations. In network model construction, we have utilized historical flight-track data of Europe and performed analysis for certain days involving certain disturbances. Through this effort, we have validated the proposed delay propagation models under disruptive events.


    Access

    Download


    Export, share and cite



    Title :

    A Data-Driven Air Transportation Delay Propagation Model Using Epidemic Process Models


    Contributors:
    B. Baspinar (author) / E. Koyuncu (author)


    Publication date :

    2016




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




    Data-Driven Modeling of Systemic Air Traffic Delay Propagation: An Epidemic Model Approach

    Shanmei Li / Dongfan Xie / Xie Zhang et al. | DOAJ | 2020

    Free access

    Delay Propagation and Delay Management in Transportation Networks

    Dollevoet, Twan / Huisman, Dennis / Schmidt, Marie et al. | Springer Verlag | 2018


    A data-driven method to assess the causes and impact of delay propagation in air transportation systems

    Giannikas, Vaggelis / Ledwoch, Anna / Stojković, Goran et al. | Elsevier | 2022


    Delay Propagation in Large Railway Networks with Data-Driven Bayesian Modeling

    Li, Boyu / Guo, Ting / Li, Ruimin et al. | Transportation Research Record | 2021


    Disinfection and epidemic prevention material transportation robot

    YANG JUN / DING ZHIBING / ZHI XUANLE et al. | European Patent Office | 2024

    Free access