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Memorias de investigación
Artículos en revistas:
Assessment of airport arrival congestion and delay: Prediction and reliability
Año:2019
Áreas de investigación
  • Ingeniería mecánica, aeronaútica y naval
Datos
Descripción
Air traffic networks are highly dependent on airport arrival processes, which are common triggers for capacity constraints and delay propagation. Arrival Manager tools aim to improve arrival flows at airports. To do so they need reliable, accurate assessments of potential congestion and delay issues. This paper sets out a methodology for predicting and evaluating the operational state of the airport arrival system. This methodology is structured in two steps: the prediction stage and the reliability stage. The prediction model is based on a Bayesian Network approach, which reflects the stochastic and time-varying nature of airport operations. It also provides insights into the interdependencies between factors contributing to airport performance. The reliability model uses a Multi-State System structure, as the airport arrival system has a large number of performance levels. It is developed via a Markov process technique. By combining these prediction and reliability models we can assess the characteristics of the airport arrival system: stationary state, availability, performance and degradation. The methodology is applied to a case study at a busy European airport, using real data from peak traffic months. Results for the scenarios analyzed show that the factors that have a greatest impact on delay and congestion are the level of saturation at arrival processes, the time frame of the day (which determines the arrival declared capacity) and the meteorological conditions. Moreover, arrival states of congestion reduce the airport?s ability to maintain optimal performance rates. The model represents an evolution from the traditional corrective and binary vision of performance analysis towards a predictive and multi-state approach. The results can be applied to derive operational strategies and draw conclusions regarding arrival performance and management.
Internacional
Si
JCR del ISI
Si
Título de la revista
Transportation Research Part C-Emerging Technologies
ISSN
0968-090X
Factor de impacto JCR
3,968
Información de impacto
Datos JCR del año 2017
Volumen
DOI
10.1016/j.trc.2018.11.015
Número de revista
98
Desde la página
255
Hasta la página
283
Mes
SIN MES
Ranking
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Alvaro Rodriguez Sanz (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Departamento: Sistemas Aeroespaciales, Transporte Aéreo y Aeropuertos
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