Congresos de la Universitat Politècnica de València, CIT2016. Congreso de Ingeniería del Transporte

Por defecto: 
Reduction of Uncertainty Propagation in the Airport Operations Network
Álvaro Rodríguez Sanz, Fernando Gómez Comendador, Rosa Arnaldo Valdés

Última modificación: 05-06-2016


Airport operations are a complex system involving multiple elements (ground access, landside, airside and airspace), stakeholders (ANS providers, airlines, airport managers, policy makers and ground handling companies) and interrelated processes. To ensure appropriate and safe operation it is necessary to understand these complex relationships and how the effects of potential incidents, failures and delays (due to unexpected events or capacity constraints) may propagate throughout the different stages of the system. An incident may easily ripple through the network and affect the operation of the airport as a whole, making the entire system vulnerable. A holistic view of the processes that also takes all of the parties (and the connections between them) into account would significantly reduce the risks associated with airport operations, while at the same time improving efficiency. Therefore, this paper proposes a framework to integrate all relevant stakeholders and reduce uncertainty in delay propagation, thereby lowering the cause-effect chain probability of the airport system (which is crucial for the operation and development of air transport).

Firstly, we developed a model (map) to identify the functional relationships and interdependencies between the different stakeholders and processes that make up the airport operations network. This will act as a conceptual framework. Secondly, we reviewed and characterised the main causes of delay. Finally, we extended the system map to create a probabilistic graphical model, using a Bayesian Network approach and influence diagrams, in order to predict the propagation of unexpected delays across the airport operations network. This will enable us to learn how potential incidents may spread throughout the network creating unreliable, uncertain system states.

Policy makers, regulators and airport managers may use this conceptual framework (and the associated indicators) to understand how delays propagate across the airport network, thereby enabling them to reduce system vulnerability, and increase its robustness and efficiency.


Palabras clave

Uncertainty; airport operations; process modelling; delays; propagation; Bayesian Networks

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