European Strategic Traffic Forecasts and possible contribution for the TEM Master
Plan Bratislava 9 February 2004
Benno BultinkDG Public Works, the [email protected]
Ming Chen & Adrian VilcanNEA Transport research and training
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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
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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!
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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
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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
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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
The TEN-STAC project
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The TEN-STAC project – main approach
Traffic flows on European networks, international, domestic, intra-regional – by mode, in vehicles
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 classin tonnes and vehicles (light and heavy trucks for road transport)
Emissions:- CO2, CO, NOx, PM10Accessibility by NUTS2 zone and mode
SCENES Freight modelling systemCost function parameters
NEAC modelling system: freightdemand modelling: generation / distribution, modal splitmultimodality and role of portsassignment modellingGISCO European networks: rail & road Level-Of-Service freight
VACLAV environmental impactsocial & cohesion impact
VACLAV: passengerassignment modelling GISCO European networks: rail & road Level-Of-Service freight
COMMON MODELLING PLATFORM TEN-STAC
EUFRANET Rail Freight modelling system-Accompanying Measures rail freight
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Forecasts 2020, three scenarios
Basic policy actions and accompanying measures (AM) of TEN policy packages
TEN policies SCENARIOS Baseline socio-economic trends Basic policy
actions: liberalisation and harmonisation
Accompanying measures for TEN package I
Accompanying measures for TEN package II
TEN-basic
TEN-policy package I
TEN-policy package II
TREND+
EUROPEAN
EUROPEAN+
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Growth international freight transport demand flows
International freight transport demand flows, TREND+ scenario
2020 (base year 2000), Mio tonnes (crude oil excluded)
Origin\Destination EU15+2 CEEC 12 Rest Europe Rest World
EU15+2 1,785 (1,130) 130 (59) 98 (41) 570 (288) CEEC 12 238 (125) 110 (46) 55 (23) 55 (21)
Rest Europe 329 (121) 212 (81) 74 (27) -
Rest World* 1146 (742) 63 (26) - -
-
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Growth international freight transport demand flows
Growth international freight transport demand flows, 2020/2000 - TREND+ scenario
Origin\Destination EU15+2 CEEC 12 Rest Europe Rest World
EU15+2 1.58 2.20 2.39 1.98 CEEC 12 1.90 2.39 2.39 2.62 Rest Europe 2.72 2.62 2.74 - Rest World* 1.54 2.42 - -
-
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Road freight flows total interregional, TREND+ scenario
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Changes Road Freight2000 – 2020 TREND+ scenario
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Rail freight international, TREND+ scenario
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changes rail freight 2000 – 2020 TREND+ scenario
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Inland Waterways flows, TREND+ scenario (KTON)
KOBENHAVN
RIGA
DUBLIN
LONDON
AMSTERDAM
BRUXELLES
BERLIN
PRAHA
VILNIUS
MINSK
PARIS
VADUZBERN
LUXEMBOURG
LJUBLJANA
BUDAPEST
BRATISLAVA
KISHINEV
MONACO
ROMA
SARAJEVO
BEOGRAD
SOFIYA
WARSZAWA
SKOPJE
BUCHAREST
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Sea motorways TREND+ 2020 excluding crude oil (*mio tonnes)
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Changes in traffic performance 2000-2020
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Change in freight centrality, EUROPEAN scenario versus base year 2000 (NUTS2, indexed)
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Change in NOx emissions road, EUROPEAN scenario versus base year 2000 (indexed )
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Demand Supply Capacity of the infrastructure
Local traffic volume
Long distance traffic volume
RESULT • Transport time • Congestions ?
Part i of corridor j
LOS/ Bottleneck ?
Road link analysis and information needs
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Economic corridors using the link Rotterdam - Antwerp
1 m illion t.
to ta l 18 m illion tonnes
R
A
1 m illion t.
2 m illion t.
2 m illion t.
2 m illion t.
2 m illion t.
5 m illion t.
3 m illion t.
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Flow types in corridor analysis
1 23
4 56
7 89 10
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Transport chains
Origin regionof th e
com m odity
D est inat ionregionof th e
com m odity
M odeat origin
M ode atdest inat ion
M ode in
betweentransh ipm ent
Origin regionof th e
com m odity
D est inat ionregionof th e
com m odityM odeat origin
M odeat dest inat ion
Transh ipm en t
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Construction of NEAC database
1. identification of trade flows2. identification of transhipment sites3. regionalisation of country-to-country-total4. extension with domestic transport
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Top-down approach
nationalregional data
transhipmentdata
direct transhipment
Belgianports
Germanports
trade flows
(direct) Belgianports
Germanports
Dutchports
Dutchports
COUNTRYTO
COUNTRY
REGIONTO
REGION
direct
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NEAC regions Europe
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Russian Federation (tonnes x 1000)
> 30001500 - 3000
600 - 1500300 - 600150 - 300
60 - 15030 - 60
< 30
(C) Copyright NEA 1999
rpc9
8.w
or
Domestic production by region of the Russian Federation, 1998rail, all routes, containerised
NEAC region Russian Federation
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trade m ode l andpassenger m ode l
scenarioeconom ic anddem ograph ic
scenarioin frastruc tu re andtransport po licy
netw ork
m oda l sp litm ode l
ass ignm entm ode l
fo recast flow s(O /D m atrices )
base yea r
m oda l sp lit(O /D m atrices)
tra fficon links
CLASSICAL MODEL APPROACH
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Trade forecast
The computation of forecast of international trade flows
)AA(*)
PP(*T=T 3
bj
pj2
bi
pib
ijpij
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Modal-split model
Segmentation of transportmarkets
• commodity group• distance• total tonnage
Relative change of costs + timeof modes
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trade m ode l andpassenger m ode l
scenarioeconom ic anddem ograph ic
scenarioin frastruc tu re andtransport po licy
netw ork
m oda l sp litm ode l
ass ignm entm ode l
fo recast flow s(O /D m atrices )
base yea r
m oda l sp lit(O /D m atrices)
tra fficon links
CLASSICAL MODEL APPROACH
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More information on NEAC:www.nea.nl/neac
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Transport demand determinants - freight
GDP – Gross Domestic Product (per sector and per expenditure) – byNUTS2 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.
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Transport demand determinants - passenger
Exogeneous variables for passenger demand generation, distributionand 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
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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
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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.
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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.