Transport and Covid-19: responses and resources

The ITF Modelling Framework (PASTA 2023)

The International Transport Forum has developed a set of modelling tools to build its forward-looking scenarios of transport activity. The tools are unified under a single framework: PASTA (Policy Ambitions and Sustainable Transport Assessment), covering all modes of transport, for both freight and passenger.

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 how this demand may be satisfied. The second step includes a detailed modelling of mode choice. Finally, the models compute the activity and CO2 emissions from transport. Additionally, depending on the sector, other transport-related variables, externalities, or indicators are calculated.

The ITF framework can assess the effect of many policies and exogenous impacts. Policies that may impact transport demand or the related CO2 emissions become input parameters in all models. The models are constantly improved and updated. All of the models are developed entirely by the ITF and do not rely on commercial (transport) modelling software.

Modelling Chart

The most recent model documentation are accessible via the following links:

  • Global urban passenger transport model – see here
  • Global freight transport model – see here
  • Global non-urban passenger transport model – see here
  • Global fleet transport model – see here

The information below provides a brief overview of each model.

The urban passenger transport model

The ITF global urban passenger transport model is a strategic tool built to test the impacts of policies and technology trends on urban travel demand, related CO2 emissions and accessibility indicators. Outputs for various scenarios can be obtained to 2050. The model represents passenger mobility at the macro Functional Urban Areas (mFUAs) scale.

The model is designed as a systems dynamic model (stock and flow model) to evaluate the development of urban mobility in all cities with over 50 000 inhabitants worldwide. It combines data from various sources that form one of the most extensive databases on global city mobility to account for 18 transport modes. These range from the conventional private car and public transport to new alternative modes such as shared mobility services.

The urban passenger model represents travel activity for 18 transport modes by modelling aggregate travel behaviour by traveller segment. The segment is defined by travellers' socio-economic characteristics (e.g., gender, income level and age). While the model is built at the mFUA level, the final analysis is carried out for 19 world regions.

It produces estimates on urban passenger trip numbers, travel distances, modal splits, modal trip shares, passenger kilometres (pkm), vehicle-kilometres (vkm) and related CO2 and pollutant emissions, as well as accessibility, resilience, space consumption and road safety indicators.

The urban freight transport model

The ITF Urban Freight Model estimates the impact of policy measures on decarbonising urban freight transport under different scenarios. It applies innovative ways to overcome the general lack of data describing urban freight movements.

The first version of the model was developed for a single urban area, Groot-Rijnmond in the Netherlands. The model was then expanded to all European functional urban areas (FUAs) and eventually to those of the rest of the world. The FUAs are divided into a grid of smaller zones of two by two kilometres for obtaining more detailed results with higher spatial resolution.

The model applies a classic four-step modelling approach. It accounts for different commodity types that can impact shipment characteristics. In the freight generation step, freight production and consumption of a zone, per commodity type, are estimated with a generalised linear model (GLM), based on spatial characteristics of the urban area (such as information on employment and retail space). In the next step, freight flows for six distance ranges are estimated, again for each commodity type. Here, a distance bin split model assesses the shares of shipments falling into each distance bin depending on city characteristics. In the third step, the obtained flows for each distance bin and commodity type are converted into trips using specific vehicle types. For this, an iterative procedure is applied that uses information on the likelihood of using specific vehicle types for the different commodities. Finally, the emissions of each trip are calculated based on the vehicle type and ton-kilometres of each trip.

This model estimates urban freight trip numbers, travel distances, modal splits, tonne-kilometres (tkm), vkm and cargo weights and their related CO2 and pollutant emissions.

The non-urban passenger transport model

The ITF non-urban passenger model is a strategic tool that tests the impacts of multiple policies and trends on the non-urban passenger sector. The model provides scenario forecasts for non-urban transport activity and its related CO2 emissions up to 2050. The model estimates activity between urban areas (intercity travel) and passenger activity locally in non-urban areas (intra-regional travel). The latter includes travel in peri-urban and rural areas. The model is developed to assess the impact of transport, economic and environmental policy measures (air liberalisation, carbon pricing, etc.), and technological developments and breakthroughs (electric and hydrogen aviation, autonomous vehicles, etc.).

The model accounts for six modes: air, rail, car, bus, motorcycle, and ferry. It builds on two older ITF models, the international passenger aviation and the domestic non-urban passenger. The new non-urban model combines and enhances these two models, now accounting for all multimodal passenger activity outside urban areas. The model structure comprises eleven sub-models (or modules).

This model estimates for passenger trip numbers, pkm and related CO2 emissions for all modes available for travel between urban areas (both intercity and international travel) and locally in non-urban areas (regional travel), accounting for multimodal passenger activity.

The non-urban freight transport model

The ITF non-urban freight transport model assesses and provides scenario forecasts for freight flows around the globe. It is a network model that assigns freight flows of all major transport modes to specific routes, modes, and network links. Centroids, connected by network links, represent zones (countries or their administrative units) where goods are consumed or produced.

The most recent version of the ITF freight model integrates the (previously distinct) surface and international freight models. International and domestic freight flows are calibrated on data on national freight transport activity (in tonnes-kilometres, tkm) as reported by ITF member countries. Reported data is also used to validate the route assignment of freight flows. Trade projections in value terms stem from the OECD trade model and are converted into cargo weight (tonnes). These weight movements are then assigned to an intermodal freight network that develops over time in line with scenario settings. These define infrastructure availability, available services and related costs.

The current version of the model estimates freight transport activity for 19 commodities based on trade projections from the ENV-Linkages trade model from OECD for all major transport modes, including sea, road, rail, air and inland waterways. The underlying network contains more than 8 000 centroids, where goods are consumed and produced. Several attributes describe each of the more than 150 000 links of the network. These include length, capacity, travel time (incl. border crossing times), and travel costs (per tkm).

The model estimates tkm and vkm by mode and commodity type, as well as other transport flows and stock (e.g. airport and port throughput) and connectivity indicators.

Fleet model

This model, newly developed for the ITF Transport Outlook 2023, combines data on the age and technologies of vehicle fleets around the world with forecasts of vkm from the ITF passenger and freight models for every vehicle type and region. It uses these to estimate how vehicle fleets will evolve over time using scrappage probabilities. Projected future fleets are combined with scenarios on technology adoption and energy efficiencies to estimate CO2 and air-pollutant emissions.