کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
526566 | 869136 | 2013 | 16 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Modelling delay propagation within an airport network Modelling delay propagation within an airport network](/preview/png/526566.png)
We describe an analytical queuing and network decomposition model developed to study the complex phenomenon of the propagation of delays within a large network of major airports. The Approximate Network Delays (AND) model computes the delays due to local congestion at individual airports and captures the “ripple effect” that leads to the propagation of these delays. The model operates by iterating between its two main components: a queuing engine (QE) that computes delays at individual airports and a delay propagation algorithm (DPA) that updates flight schedules and demand rates at all the airports in the model in response to the local delays computed by the QE. The QE is a stochastic and dynamic queuing model that treats each airport in the network as a M(t)/Ek(t)/1 queuing system. The AND model is very fast computationally, thus making possible the exploration at a macroscopic level of the impacts of a large number of scenarios and policy alternatives on system-wide delays. It has been applied to a network consisting of the 34 busiest airports in the continental United States and provides insights into the interactions through which delays propagate through the network and the often-counterintuitive consequences. Delay propagation tends to “smoothen” daily airport demand profiles and push more demands into late evening hours. Such phenomena are especially evident at hub airports, where some flights may benefit considerably (by experiencing reduced delays) from the changes that occur in the scheduled demand profile as a result of delays and delay propagation.
► In this study we model an airport network using an analytical queuing model.
► We introduce a stochastic and dynamic queuing engine to estimate local delays.
► We use a network decomposition approach to propagate delays through the network.
► We show the importance of taking into account delay propagation in an airport network model.
► High delay propagation leads to demand smoothing and counter-intuitive benefits for many airport users.
Journal: Transportation Research Part C: Emerging Technologies - Volume 27, February 2013, Pages 60–75