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Expert System based Predictions of Demand for Internal Transport in Europe


Expert System based Predictions of Demand for Internal Transport in Europe

Background & policy context: 

A more efficient, safe and environmentally friendly use of available infrastructures requires an appropriate management of traffic flows. The three main aims in this respect are:

  1. to contribute to the development, integration and validation of advanced traffic management systems, including the exchange between and the use of information systems;
  2. to establish a coherent, integrated transport management systems architecture across the transport chain;
  3. to fine tune demand management tools and policies and facilitate their deployment.

The EXPEDITE project addressed the last one, which is the third RTD objective “2.3 Modal and Intermodal Transport Management Systems” of the KA2 “Sustainable Mobility and Intermodality” of the 5th Framework Programme


The objectives of the EXPEDITE project were:

  • producing multi-modal demand forecasts up to 2020 for passengers and freight transport for Europe (using the NUTS2 zoning system for Europe, with about 250 zones in the study area, comprising the current member states and accession countries);
  • identifying market segments which react most to control measures;
  • formulating efficient policy bundles to achieve mode-switching in line with Common Transport Policy (CTP) objectives (this means substitution away from car and air transport for passengers and away from road transport in freight).

This project was closely linked to the THINK-UP thematic network, which was set up to describe the state-of-the-art methodologies in forecasting and to improve the mutual understanding of the results obtained.


The methodology which has been developed to deliver forecasts in EXPEDITE for transport demand, in Europe at the zonal level, is as follows.

1) Description of the planned interaction with THINK-UP, the thematic network that was set up to describe the state-of-the-art methodologies in transport forecasting and to improve the mutual understanding of the results obtained.

2) Review of existing national and international transport models. The EXPEDITE forecasts exploit existing international and national transport models.

3) Presentation of the base-year (1995) data;

4) Definition of a Reference Scenario for 2020 and the intermediate years and defined policies to be simulated;

5) Execution of runs with existing models: the SCENES European model and a number of national models for passenger and freight transport. For predictions focussing on long distance, inter-zonal transport EXPEDITE uses outcomes of runs with one or more European transport models, in particular new runs with the SCENES European model.

6) Creation, on the basis of the information of the above-mentioned runs, of two new models, the EXPEDITE meta-model for passenger transport and the EXPEDITE meta-model for freight transport. The EXPEDITE meta-model for freight is based on runs with four national freight transport models available within EXPEDITE, runs with the SCENES model, and runs with the NEAC model. For forecasts focussing on passenger transport with trip distances up to 160 km, EXPEDITE has developed the EXPEDITE meta-model for passenger transport, based on the outcomes of runs with five national passenger transport models, taken to represent behaviour of travellers. In EXPEDITE the results of these runs of the underlying models are transferred to other zones in Europe, corrected for specific factors such as may arise from specific geographical differences. Results of the meta-model for a specific zone are obtained by scaling results for a prototypical area to match known totals (e.g. from transport statistics, sector statistics, etc). For a large number of segments within a zone, the meta-model produces a levels matrix (distribution of tours and passenger-kilometres by mode and distance class) and switching matrices for different policy measures. For each zone, expansion factors were calculated depending on the importance of the segments in the zone (many of these weights could be zero for a specific zone). Within any of the five existing national passeng

Institution Type:
Institution Name: 
European Commission, Directorate-General for Energy and Transport (DG TREN)
Type of funding:
Key Results: 

The results of the project derive from the execution of runs with the models and concern the effectiveness of policy measures implemented. The results were grouped into two themes: freight transport and passenger transport.

1) Freight transport

  • In the period 1995-2020, under the assumptions of the Reference Scenario, the number of tonnes lifted in the study area will increase by 44% (lorry +39%) and tonne –kilometrage will grow by 79% (lorry +89%). A higher growth is predicted for the Central and Eastern European Countries (CEEC), for long distance transport and for general cargo.
  • If lorry costs increase, there will only be significant shifts at trip distances above 100 kilometres. Below 100 kilometres, road transport is the dominant mode. Policy measures are unable to change this situation below 100 kilometres: it is an insensitive market segment.
  • If the lorry transport time goes up, there will also be only significant mode shifts for consignments above 100 kilometres. For this change in transport conditions, most of the substitution is towards combined road-rail transport, but also to conventional rail transport.
  • If the rail/combined transport cost or time decreases, then for fuels and ores, metal products, basic and other chemicals, large machinery (but only above 100 kilometres) there will be a significant decline in lorry tonne-kilometrage, but a shift will also take place from inland waterways transport (where this mode exists).
  • If the cost or time of inland waterways transport decrease, then there will only be a significant reduction of lorry transport for specific.
  • If the sea shipping cost or time goes down, there will only be small shifts towards sea transport and no significant reduction for lorry.
  • In passenger transport an increase in transport time by x% has a bigger impact than an increase in transport cost by x%. This is not generally true in freight transport; in many situations an x% change in cost has a bigger impact than an x% change in time.
  • Elasticities keep increasing with distance after 100 kilometres (especially time elasticities).
  • Changes in tonne-kilometres are bigger than changes in tonnes for lorry, while the changes are close to being equal in tonnes and tonne-kilometres for rail and inland waterways. This shows that goods would mostly be transferred between modes in co

    Technical Implications


    Policy implications

    In the section “Key Results” the main the results of runs with the meta-models and the SCENES models for the Reference Scenario are given. It also reports on the policy runs carried out with those models and the evaluation of these policies in EXPEDITE. On the basis of these policy runs it is possible for policy makers to draw conclusions on the effectiveness of policy measures and on (in)sensitive market segments, which can support the development of new policies.



Heusch/Boesefeldt GmbH


Institute of Transport Economics (TØI)

TRANSEK A.B., Sweden

Swiss Federal Institute of Technology (ETHZ)

The Netherlands:
RAND Europe (Coordinator)

United Kingdom:
Imperial College of Science, Technology and Medicine - Department of Civil and Environmental Engineering – Centre for Transport Studies

RAND Europe
Newtonweg 1
2333 CP
Contact country:
(+31) 71 524 51 51
Fax Number: 
(+31) 71 524 51 91