By Gerard de Jong

Describes a shipping version that's quick and straightforward to exploit, that distinguishes among inhabitants segments and covers delivery over daily distances. within the EXPEDITE undertaking, this sort of version was once built and utilized in forecasting and coverage simulation for passenger and freight shipping.

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Extra resources for Expedite: Expert-System Based Predictions of Demand for Internal Transport in Europe

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This contains information for each NUTS2 zone on population, age structure, household types, sectoral employment, car ownership, wealth and travel time and cost by mode for 2005, 2010, 2015 and 2020. This Reference Scenario does not contain any new policy measures (that is, only included are measures to which there is already a commitment). 3). 1 Overview of existing Reference Scenarios For 2020 several reference scenarios have been developed recently in a number of EU projects. These are reviewed in some detail in EXPEDITE Deliverable 3.

Exp ected impacts : modification in the travel demand matrix structure ; modification in the transport costs ; modification in the modal repartition of freight carriers. g. g. g. teleworking policies). However, other policy elements induce an indirect impact on the attributes that are contained in the model, and merit further investigation before the beginning of policy tests: either to determine which attribute is likely to be the most affected by the policy measure or the extent of its variation.

An analysis on the five countries with EXPEDITE national models was not chosen here, because there is only limited variation in road network density categories within each of those c ountries. The multiplicative factors used in the meta -model are in Table 22. Table 22. 09 The higher the road density, the higher the number of car tours and kilometres per person. Correction factors based on rail network density For rail too, the classification used in the meta -model is based on the SCENES networks.

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