A Meta-model for Passenger Transport in Europe Integrating Existing Models
G de Jong, H Gunn, RAND Europe, NL
In the recent White Paper on European Transport Policy in 2010 ?Time to Decide?, the European Commission accepts that at the European level, as at local and national levels, the answer to traffic emissions, accidents and chronic delays cannot just be to build new infrastructure and open up markets. A large number of pricing and regulatory policy measures is proposed to shift the balance between modes of transport, notably to reduce the growth of road and air traffic. Little is known about the effectiveness of these measures at the European scale and about the groups of society that will be affected most.
In Europe, many transport models are available for forecasting and policy simulation at the national and regional level. Furthermore, there are models at the European scale (either for the current 15 member states of the European Union or also covering countries that will join the Union in 2004). However, these are usually network-based models with considerable run times. Moreover, these large European models can only provide a limited number of segmentations of the population and policy sensitivities, especially for short distance transport (more than 90% of all passenger travel in European countries is on trips below 30 km).
Therefore, there is a need for a model with the following characteristics:
* The model is fast and easy to use, so that it can be run for many policies and bundles of policies;
* The model distinguishes between many different segments of the population, so that differences in behaviour can be incorporated, as well as differences in how policy measures affect the population segments;
* The model focuses on representing transport over everyday distances, up to 160 kilometres, to complement the long-distance models developed for trans-European travel.
In the EXPEDITE project, carried out for the European Commission, such a model was developed and applied in forecasting and policy simulation. This model, called the ?EXPEDITE meta-model?, integrates outcomes of five national passenger transport models and four national freight models and results of the European models. The meta-model is not intended to replace detailed network-based models, but to offer the possibility of a quick scan for the effects of a large number of policy measures. More detailed studies for promising measures and for the assessment of specific infrastructure projects should then be done using the network models. The paper will discuss the EXPEDITE meta-model for passenger transport. Freight transport is dealt with in another paper.
Meta-analysis can be described as the statistical analysis of analyses. It is a research method for systematically describing and analysing existing findings on some quantitative relationship. These definitions also apply to the EXPEDITE meta-model, but this meta-model differs from the usual approach in meta-analysis. Most meta-models are based on results from the literature, whereas the EXPEDITE meta-model integrates results from runs with ?underlying? models, that have been carried out within the EXPEDITE project itself.
The EXPEDITE meta-model has been developed because there is a need to explore a large number of policy options and the impacts on many segments of the transport markets in the European context. In this extension, it is not of vital importance that models for all countries in the EU are included, but that the most relevant segments of the travelling population in the EU are included in the models used and expanded properly, and that the outcomes are calibrated to observed base-year distributions for transport in the respective zones.
The EXPEDITE meta-model for passenger transport integrates results from the following models:
* Five national models:
- the Dutch National Model System (NMS or LMS);
- the Norwegian National Model (NTM-4);
- the Italian National Model (SISD);
- the Danish National Model;
- the Swedish National Model (SAMPERS).
* The SCENES European model.
A large number of runs have been carried out (up to 80 runs per model) with each of the above national models and with the SCENES model for passenger transport. To the maximum possible extent, the same runs were done with each of the models. For the base-year (1995), outcomes were generated in the form of ?levels matrices? for tours and passenger kilometres. The levels matrices for tours give the number of tours per person per year by mode and distance band. A ?tour? is defined as a round trip, starting and ending at home. The levels matrices for passenger kilometres give the number of kilometres travelled per person per year, by mode and distance band. There are different levels matrices for different travel purposes and for many population segments.
Besides levels matrices for 1995, the outcomes of the national model runs also consist of switching matrices: changes in tours or in passenger kilometres (same units as the levels matrices), as a result of a change in a policy-related model input variable.
For each segment, the levels and switching matrices in tours and kilometres from all five national models were averaged (unweighted) to get the ?prototypical? matrices that are used in the meta-model to forecast for Europe. For long-distance transport, results from the SCENES model were added.
The zoning system used (NUTS-2) consists of around 250 zones in the current European Union and Central and Eastern Europe. For each zone, expansion factors were calculated depending on the importance of the population segments in the zone. By multiplying the tours and passenger kilometres from the prototypical matrices with the expansion factors, initial predictions for each of the zones are derived. These are forecasts for all travel demand generated in the zone, by mode, distance class, travel purpose and population segment.
These initial forecasts are first corrected for differences in travel behaviour by area type and by road and rail network type. The model forecasts for 1995 that result after applying the area and network type correction factors have been validated against observed data on the use of each mode (if available by distance class), by country. This has resulted in a set of mode-specific, distance-class-specific and country-specific correction factors, which are also kept in forecasting. In this way, the meta-model accounts for ?residual? factors affecting travel demand, such as climate, hilliness and historical developments.
This meta-model for passenger transport also includes area-wide speed-flow curves to take account of the feedback effect of changes in congestion due to policies that change the amount of car use. An approximation was developed in EXPEDITE to explore different levels of changes in policy variables and combinations of policies, allowing for non-linear effects on travel demand.
The scenario-forecast results for years up to 2020 generated by EXPEDITE for this project were restricted to one single Reference Scenario, a scenario in which the population, economy, and car-ownership were assumed to grow more or less in lines with past trends in the 90?s. Costs of travel were assumed unchanged from 1995, and it was assumed that provision of new road capacity would be such as to maintain speeds at 1995 levels. Changing any of these assumptions would change our output travel demand consequences.
The EXPEDITE meta-model gives for this Reference Scenario large increases in car-kilometres in Eastern European countries (more than doubling %-wise in some countries between 1995 and 2020), and a relative stability in the high-car-owning countries of the existing EU15 (e.g. Italy, Germany, Austria).
The underlying forecasts can be interrogated in a multitude of ways, to look at the types of driver and sorts of journey causing the increases in car travel.
A number of the policies (e.g. from the ?Time to Decide? White Paper) put forward to reduce car kilometres (some were packages of measures) have been evaluated in EXPEDITE in terms of effectiveness (modal shift from road to other modes), impact on internal and external costs and required investment, operation and maintenance costs. Policies penalizing motorists through parking or road charging are best. Cost internalisation, fuel price increases and lower maximum speeds are next; in the same league for effectiveness, but hitting the users harder. Policies to affect land use by densification, or making public transport more attractive, come bottom of the league; they are simply ineffective.
The paper will discuss the methodology and main results (both for the Reference Forecast for 2020 and for many policy measures) of the EXPEDITE meta-model for passenger transport.
Association for European Transport