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European Strategic Traffic Forecasts and possible contribution for the TEM Master Plan Bratislava 9 February 2004. Benno Bultink DG Public Works, the Netherlands b.j.a.bultink@don.rws.minvenw.nl Ming Chen & Adrian Vilcan NEA Transport research and training mch@nea.nl / avi@nea.nl. Purpose:
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European Strategic Traffic Forecasts and possible contribution for the TEM Master PlanBratislava 9 February 2004 Benno Bultink DG Public Works, the Netherlands b.j.a.bultink@don.rws.minvenw.nl Ming Chen & Adrian Vilcan NEA Transport research and training mch@nea.nl / avi@nea.nl
Purpose: • Making Dutch know-how and experience available to CEC • Improving the efficiency of investments in central European infrastructure by applying this knowledge • Improving market opportunities to commercial partners on both sides
Partner for Roads, window:Roads and Regional Development To strengthen the link between road projects and regional development by assisting planning authorities to make this link visible. Put this into practice!
Ingredients of presentation: • TEN-STAC: objectives, approach • TEN-STAC: Phase 1 results • NEAC forecasting model • Possible integration TEN-STAC – TEM Master Plan • Main guidelines / approach • Data requirements • Possible products
The TEN-STAC project – objectives TEN-STAC project objectives: • traffic forecasts for 2020, including traffic assignment, estimate of international traffic load on the network and socio-economic and environmental impacts according to different scenarios, • a review of national transport infrastructure plans, and macroeconomic analysis to estimate potential public financing in transport infrastructure until 2020, • detailed analyses of 25 international corridors comprising screening of bottlenecks and environmental risks, and guidelines to select projects of high European interest within corridors, • broad financial plans for selected major projects
The TEN-STAC project A DG-TREN project dedicated to the Revision of the TEN Phase 1: January – July 2003 • Forecasts for 2020 freight and passengers • All modes • Assignment on the networks • Identify the main transport axes in Europe • Input for revision TEN Final D3 report available at: http:\\www.nea.nl\ten-stac Phase 2: August 2003 – March 2004 • Detailed analyses of the High Priority Projects of European interest: determine indicators per project / sub-section • Assessment of the projects • Financial analyses
COMMON MODELLING PLATFORM TEN-STAC EUFRANET Rail Freight modelling system • Accompanying Measures rail freight SCENES Freight modelling system Cost function parameters NEAC modelling system: freight demand modelling: generation / distribution, modal split multimodality and role of ports assignment modelling GISCO European networks: rail & road Level-Of-Service freight VACLAV: passenger assignment modelling GISCO European networks: rail & road Level-Of-Service freight VACLAV environmental impact social & cohesion impact Traffic flows on European networks, international, domestic, intra-regional – by mode, in vehicles Emissions: - CO2, CO, NOx, PM10 Accessibility by NUTS2 zone and mode Demand flows expressed by total generated/attracted flows: per NUTS 2 region for core study area, mode, transport chain (combination of modes), market segment, type of flow (international, domestic, intra regional), distance class in tonnes and vehicles (light and heavy trucks for road transport) The TEN-STAC project – main approach
Change in freight centrality, EUROPEAN scenario versus base year 2000 (NUTS2, indexed)
Change in NOx emissions road, EUROPEAN scenario versus base year 2000 (indexed)
Construction of NEAC database • identification of trade flows • identification of transhipment sites • regionalisation of country-to-country-total • extension with domestic transport
Trade forecast The computation of forecast of international trade flows
Modal-split model Segmentation of transport markets • commodity group • distance • total tonnage Relative change of costs + time of modes
More information on NEAC: www.nea.nl/neac
Transport demand determinants - freight GDP – Gross Domestic Product (per sector and per expenditure) – by NUTS2 region for the core area: • GDP/head • Agriculture, • Mining and quarrying, • Basic metal, • Construction, • Chemicals, petroleum, • Metal products, • Food consumption, • Residential construction, • Private final consumption.
Transport demand determinants - passenger Exogeneous variables for passenger demand generation, distribution and modal split: • Motorisation • Population by sex and age classes • Employment by sectors • GVA by sectors • Accommodation offer for leisure in relation with tourism trip purpose • GDP
Transport supply modeling variables – passenger & freight Transport times and costs: • absolute values base year 2000 and changes per mode for 2020 • by transport mode based on: • link/node attributes of GISCO networks as length, speed, capacity, resistance (impedance), link type, speed-flow function (road) • cost functions • route choice as from assignment modelling • specific model variables for rail - EUFRANET
Possible approach for linking TEN-STAC and TEM Master Plan • Get a consistent zoning system TEN-STAC – TEM. The description of the zoning system has been provided to the TEM project. • Identification of the TEM countries and other countries to be considered at the similar level of detail as most countries in the TEN-STAC study (NUTS2). - The supplementary data needed for the countries would cover: socio-economic trends, observed trade / transport and infrastructure data.
Possible approach for linking TEN-STAC and TEM Master Plan • Analyse different options after the Bratislava meeting. • One possible option is to build one scenario for horizon 2020 to give an example on how the linking process can be developed – focus on the road transport. • Integration at a certain level of detail of 2 TEM countries in the scenario could be considered. • socio-economic impact in terms of accessibility and environmental impact at country / regional level could be also considered as output of the scenario.