SOUTH
Step 3. Airport Choice Model Validation. The probabilities (shares) of passengers originating from each analysis zone using the three existing airports are
1. The majority of air freight moves in the bellies of wide-bodied aircraft. The availability of spare belly space at a particular airport is likely to have a very
2.11 ROUTE CHOICE MODELS
Another important subject of demand modeling is predicting airline traffic through exist-ing hubs or even potential hubs. The very large, relative volumes of transit and transfer traffic cannot be predicted satisfactorily using the techniques previously described in this chapter. The trips are generated externally to the hub and are not dependent on the socioeconomic characteristics of the area or region in which the hub is situated.
Instead, the hub attracts traffic which is related to the level of air service provided by the hubbing facility. Variables which have been used to describe this service level are:
• Frequency of departures
• Connection time at the hub
• Capacity of route in terms of available seats
• Average journey time through the hub
The models which have been calibrated to describe and to forecast route choice are extensive and are of complex mathematical formulation. A model calibrated in the United Kingdom on British CAA data was of the form (46)
p(a, r)= p(r/a), p(a) (2.34)
p(r/a)= exp [V (a, r)]
exp R(a) (2.35)
p(a)= exp[δR R(a)]
a∗EA
exp[δR R(a∗)] (2.36)
where
A= set of departure airports
p(a, r)= probability of a passenger using a route r served by a departure airport a p(r/a)= conditional probability of choosing a route served from a
p(a)= marginal probability of a
R = expected maximum utility (EMU) or inclusive value from a set of routes R R = set of routes available from each airport
δR = inclusive value (or EMU) coefficient, which measures the correlation among the random terms due to route-type similarities at a departure airport, a
V = utility function of form
= β1(access time)+ β2(weekly flight frequency on a route) + β3(average connection time at hub airport)
+ β4(weekly available aircraft seats on a route) + β5(average journey time)
+ β6(route specific constant)
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