The ITF Modelling Framework
The International Transport Forum has developed a set of modelling tools to build its own forward-looking scenarios of transport activity. Covering all modes of transport, freight and passenger, the tools are unified under a single framework. In contrast to existing transport and energy models, the ITF framework first estimates the demand for transport, based on a set of socio-economic drivers (population, Gross Domestic Product, trade, etc.) before analysing the way this demand may be satisfied. This second step includes a detailed modelling of mode choice. Finally, the models compute the CO2 emissions linked to transport and, depending on the sector, other transport-related variables. For instance, the urban module estimates emissions of local pollutants; the international freight model is able to assess congestion at ports. The ITF framework can assess the effect of a large range of policies and exogenous impacts. In all models, policies which may impact transport demand or the related CO2 emissions become input parameters. Particular attention was paid to urban policies, such as transit infrastructure provision, parking or land-use strategies, and to their impact on mode shares.
The international freight model projects transport activity in tonne-kilometres up to 2050 based on OECD-produced trade scenarios. It first split trade projections into the different modes and then converts trade values, expressed in currency terms, into tonnes using a weight-to-value module. Finally, an assignment procedure allocates the flows between the different routes. The model differentiates between 19 commodities and works with a zoning system of 333 regions.
Domestic surface freight
Projections for domestic freight are done at the national level, where most data is available. They are based on a statistical analysis of the relationship between freight transport demand and other socio-economic drivers. They also take the geographical position of countries to account for the potential of transit freight because available surface freight data accounts for both national freight, taking place within the borders of a country, and transit freight, which may origin or end in another country.
International passenger aviation
The ITF air passenger model derives the evolution of international passenger volumes (number of passengers and passenger-kilometres) combines a gravity-type module to assess passenger demand and a route-choice module which splits the demand between two regions among the different possible itineraries. The calibration of the model relies on in-flight demand data, as well as a sample of observed itinerary choices. In this model, the scenarios relate to the expansion of the air network, which liberalisation policies or fuel prices, among others, can influence.
Urban passenger mobility
The urban transport model analyses mobility in all the 1 667 cities with 300 000 inhabitants or more, and then extrapolate results to all urban areas of the world. The model simulates the evolution of variables that shape transport demand in cities, such as land use, availability of roads, quantity and quality of public transport before analysing the impact of these variables of transport demand and mode choice.
The model derives levels of transport activity and mode shares in different policy scenarios, e.g. for policies that favour public transport or for declining fuel prices. It is calibrated on a dataset resulting from an extensive collection from various institutions and covering all the main regions of the world.
Non-urban passenger mobility
To complement the module on urban mobility, the ITF has developed a tool to analyse non-urban mobility. Based on observations at the country level, this module derives non-urban passenger transport demand based on socio-economic factors and connectivity indicators by mode. These indicators contain information on two crucial elements: the quality of the infrastructure and the geographical organization, and in particular the size, of countries. An aggregate mode share model then splits the demand between the different available modes.