Updating National Air Passenger Demand from Traffic Counts: The Case of a Secondary Airport in an Underdeveloped Region

Demand models allow to estimate the choices made by users on different alternatives. Demand models depend on the characteristic attributes of the users and transport networks, as well as on parameters. Their significance translates into the reliability of the model in reproducing users' choices as demand values. Traffic counts are aggregated data that can be used to update demand values of O/D matrix and/or for re-calibrating parameters from sets of parameters obtained in different situations or at different times in the same scenario using a reverse assignment modal. This paper provides the use of passenger counts to update national air transport demand by calibrating a hierarchical logit model. The application focuses on estimating the demand values for a secondary airport of an underdeveloped European region with the calibration of the logsum parameter working between distribution and modal choice. The updated model can be used to test new conditions for the supply of a new service or to increase the frequency or to modify the ticket level by means of public service obligations. The results show that the introduction of public obligations in the secondary airport in an underdeveloped region is crucial for future sustainability. Considering the decline in the economic, social and environmental sustainability in the region, the airport is central to economic and social development at the same time as being important for environmental sustainability, as it limits the impacts on the territory related to the construction of large transport infrastructures.

Automated summary

Demand models rely on user and network attributes, as well as parameters, to estimate choices accurately. Traffic counts can be used to update demand values and recalibrate parameters, as demonstrated in this paper using passenger counts to update airport demand.