By Raymond L. Bisplinghoff, Holt Ashley, Robert L.Halfman
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This review is organised as follows. 1 we describe qualitatively the types of networks that can be used to describe the air traffic system. 2 we review some statistical descriptors of the topological properties of these 24 Fabrizio Lillo, Rosario N. Mantegna et al. ATM networks. 3 describes the application of the novel approach of community detection to air trafficÂ€networks and its use for the design of the airspace. 5 we consider the importance of complex networks in the analysis of the resilience and vulnerability of the air traffic system.
2013b) in the SESAR project POEM, touched upon in Chapter 2. Here, a Granger causality directed network hasÂ€ been constructed toÂ€investigate the propagation of delays. The Granger causality test is discussed in Chapter 7; for now, we note that it is capable of discriminating the causal relationship between two time series (Granger, 1969). In this network aÂ€directed link is set between airport A and airport BÂ€whenever the GrangerÂ€causality test indicates that the delays occurring in airport AÂ€induce delays in airport B.
In any form, the flight network is probably the most investigated network in air traffic studies. If mobility of passengers (or their delay) is the object under investigation, the representation of the airport network lacks important information. Passengers very often have to use more than one flight to get to their destination. If one considers only a static representation of the network, there is no way of knowing the real or even potential dynamics of passengers, that is, whether one would need to wait 2 or 10 hours in an airport before taking the next connecting flight.