TenConnect (Trans-Tools version 2)

1. TenConnect (Trans-Tools version 2) Christian Overgård Hansen

2. Contents • The TenConnect study • Results of infrastructure project evaluation • Model adjustments • Lessons learnt

3. TenConnect Study Client: European Commission Directorate-General Energy and Transport Purpose: Assessment study of infrastructure projects Project period: 1 ½ year from September 2007 to January 2009

4. Study objectives (ToR) Building on earlier studies, the study shall produce updated transport scenarios, trade and traffic forecasts, and detailed analyses of corridors of the trans-European transport network including also the neighbouring countries. It will comprise the following five major tasks: • Traffic forecasts and assignment for 2020 and 2030; • Identification of major transnational axes most relevant for the Single market and Cohesion; • Identification of bottlenecks affecting traffic flows along the axes or stemming from the traffic using these axes; • Assessment of the economic, environmental and social impacts of policy and infrastructure packages aiming at removing the bottlenecks; • Analysis of transport costs along competing trade routes. The contractor is encouraged to use, if feasible, the Trans-Tools modelling framework.

5. Consortium • Tetraplan A/S, Denmark (Project Manager) • DTU Transport, Denmark • Rapidis ApS, Denmark • BMT – Transport Solutions, Germany • Christian Albrechts University in Kiel (CAU), Germany • Institute for Transport Studies, University of Leeds, UK • Institute for System Integrating Studies, Italy • MCRIT, Spain • SYSTEMA, Greece Subcontractors: • Ramböll, Finland • Informi, Denmark • University of Belgrade, Serbia • Technical University of Vilnius, Lithuania • Sudop, Czech Republic • University of Szczecin, Poland

6. Road traffic (AADT) Baseline 2030 versus 2005

7. Fehmarn BeltRoad traffic differences to Baseline 2030

8. GDP after chocks - example

9. Incentives to update and improve TT v. 1 Motivations for improving TT v.1 for assessment of infrastructure project in TenConnect study e.g.: • Base year 2005 required for TenConnect • Low spatial resolution in new member states (Bulgaria and Rumania), Turkey and some East European countries • Passenger model underestimates local and regional trips • Passenger model difficult to apply to user specified forecast assumptions • Freight trade model uses simple unconstrained formula producing illogical forecasts

10. Implemented updates and improvements • Network updates to 2005 • Refinement to zonal structure • 2005 passenger demand matrices for pivot-point • New passenger model • Modification to assignment procedures • New trade and economic models

11. Zonal system TT v.1: 1269 zones TT v.2: 1441 zones

12. 5 main modes: Car driver Car passenger (new) Train Air Bus (new) 4 purposes: Home-Business (HB) Home-Private (HP) Home-Vacation (HH) Home-Work (HW) (new) 2005 base year passenger matrices

13. New passenger demand model, short trips Definition: Trips of less than 100 km Data source: Danish Transport Panel Survey Data/OTM extended to European level by observed income differences Specifications: • 4 trip purposes and 4 travel modes (air traffic is not included) • A nested logit model type with a trip frequency model at the top and a joined mode/destination choice model below it • Accessibility feedback between the model levels • Linear utility function specification • Country specific VoT based on PPP (Purchasing Power Parity) • The mode/destination choice model is calibrated both against mode totals and against zone attractions (simultaneously)

14. New passenger demand model, long trips Definition: Trips of more than 100 km Data source: DATELINE Specifications: • Three home based purposes (commute not included) • Nested logit model for trip frequency, destination choice and mode choice • LoS feedback (log.sums) • Non-linear utility functions • Country specific VoT based on PPP

15. Modifications road traffic assignment • Assignment of long distance passenger cars • Country specific VoT (forecasted into future by GDP) • Split of diesel and petrol as fuel • Improved links to impact models • Environmental, energy, safety • Preload of local traffic (intra zonal trips) in future scenarios • Automatic procedures to generate growth factors to existing preloads • Automatic procedure to estimate preloads on new roads

16. Modification of air transport assignment Access and egress modelling: • Air network combined with road and rail network to estimate access/egress LOS • Access and egress model (logit) • Assignment of access and egress on road and rail network Route choice modelling: • No. of departures (headway) have been added into the route choice function to time and fare • Country specific VoT

17. Trade prediction model (TPM) Trade model developed by CAU Step 1: Prediction of international trade • Gravity type model • Impediments include distance, border barriers of importing country, common border, close affinity of languages, and free trade agreements e.g. EU Step 2: Prediction freight flows between zones • Converting values to tonnes • Updating based on regional GDP changes restricted by step 1

18. Sensitivity analysis of trade with respect to increase in GDP of 10%

19. Passenger model structure TT v. 2

20. Freight model structure TT v. 2

21. Performance measurementsComparison at EU level for 2005

22. Divergence in tonkm by truck, 2005 (EU25)Comparison with Pocketbook

23. Divergence in tonkm by rail, 2005 (EU25)Comparison with Pocketbook

24. Baseline 2020/30. Lifted tonnes by mode

25. Baseline 2020/30. Lifted tonnes by NSTR group

26. Baseline 2030. Growth in truck tonkm

27. Baseline 2030. Growth in rail tonkm

28. Lessons learnt • Validation and test of new model takes time – long time!! • TT should not be used to assess local projects • Inconsistencies in freight model e.g. trade model based on 2005- data whereas model choice and logistics models are based on data from 2000 • Use of stochastic variability needs elaboration because it may produce illogical benefits and convergence problems • It is recommended to update end extend networks e.g. around London • Data shortcomings – need to open more data bases