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Air Transport Demand Module

The purpose of the Air Transport Demand Module is to predict real origin/ultimate destination passenger and freight demand within the global air transportation network and convert them to segmented flows along different routes.


Whilst in future versions it will be possible to extend the coverage of transportation modes, the global scope of AIM requires a relatively simple starting model for which data is available for all world regions. Therefore, aviation demand between a city pair is initially modelled as a function of several key variables (with appropriate elasticities): their greater metropolitan area populations; average local per capita incomes and cost to the passenger of travelling between them (including ticket price, costs in getting to/from the airport as well as a passenger’s value of their time which may be affected by excessive delay). Binary variables taking into account any special qualities a city may have which affect demand (e.g. tourism) are also included. Historical data and future projections of these input variables (i.e., population, income, cost and special quality flag) are obtained from external sources such as the UN and World Bank publications. The model’s parameters are estimated with existing demand data (e.g. the ICAO global OFOD database and the US O&D survey). Within the constraints of the available data we are able to distinguish between passenger and freight transport demand, while potential future developments include distinguishing between business and leisure travellers too.

Once demand has been estimated for a set of city-pairs, it needs to be converted into a flight schedule, which is defined by flight routing and frequency. This task is shared between the Scaled Routing Model of the Demand Module and the Flight Scheduling section of the Airport Activity Module. First, demand between city-pairs is converted to demand per flight segment, which requires determination of the proportions of traffic taking different routes within the hub-and-spoke system. In the base year (currently 2005), we reproduce the routing from existing databases using, for example, the US Hub database, ICAO OFOD and the OAG. Currently, we scale the existing hub-and-spoke traffic according to the projected increase in origin-destination demand, assuming that the future proportion of traffic along each potential route remains unchanged. While these steps have already been accomplished for an initial, limited set of 50 major U.S. airports (currently accounting for nearly 20% of global air travel), a more complex model is under development that takes into account routing alterations resulting from airline response to congestion at hub airports. This task, along with the assignment of aircraft classes and a schedule to the segmented demand, is carried out in the Airport Activity Module, and will be discussed in that section.

The integrated nature of AIM allows the interdependencies between demand and other key factors to be investigated. For example, an increase in the number of flight activities at constant airspace and airport capacities will lead to an increase in air traffic delays, which in turn influences travel demand via the value of time term in the demand formulation. Similarly, higher aircraft operating costs (through higher fuel or technology costs) can affect ticket prices, which in turn affect travel demand via the price elasticity term. These effects are dealt with by a feedback loop operating between the Air Transport Demand Module, Airport Activity and Aircraft Technology & Cost Modules. In future, feedbacks with the Regional Economics Module could also be added. For example, an increase in the number of passengers using a particular airport leads to an increase in local airport-related employment, which in turn can lead to an increase in the local population and average income, thus influencing travel demand.

Finally, the demand module is designed to take as input various policy options which affect travel costs, either by increasing ticket price directly or by applying charges to the airline which are then passed on to the passenger (dealt with by the Technology and Cost Module). Both local and global measures can be modelled. Examples of specific policy measures which may be applied directly in the demand module include economic instruments such as ticket VAT or increased Air Passenger Duty.