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Paper CTT Danmarks Tekniske Universitet

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									                The Economic and Environmental Consequences of Regulating Traffic


     Integrated Traffic, Regional Economic, Impact and Assessment Models – MERGE (Model for
                             Exchanging Regionalised Geographic Entities)



                                           Jacob Kronbak & Steen Leleur
                                       Centre for Traffic and Transport (CTT)
                                   Technical University of Denmark (DTU)



Abstract
The prime aim of the TRIP project “Integrated Traffic, Regional Economic and Impact Models” is
to create a decision-making tool for use with transport policy initiatives and transport sector
projects, which takes into account both the economic and the environmental consequences of
alternative decisions. The decision-making tool is constructed through a GIS1-based linkage of
different types of models; a transport model, an interregional economic model, an environmental
impact model and an assessment model.
This paper presents the chosen framework for the modelling tool (MERGE - Model for Exchanging
Regionalised Geographic Entities) and describes the perspectives for qualifying the decision-
making process by integrating existing models. The above four mentioned models are applied to
develop MERGE in its first version. It should be noted that MERGE is given a modular structure
that allows other models – some are briefly described in the paper – to enter the framework. In this
way it becomes possible to tailor specific studies in accordance with specific demands and budget
means.
The paper also includes a description of how the framework will be used for evaluating a transport
policy initiative in the form of a road-pricing scenario in Denmark and finally the paper describes
conclusions and research perspective.




1
    Geographical Informations System
Introduction
The purpose of the paper is to give a presentation of the current status of the Danish TRIP project
2.3 which overall has been described as follows [TRIP (2000)]:
       “The prime aim of the project is to create a decision-making tool for use with
       transport policy initiatives and transport sector projects, which takes into account
       both the economic and the environmental consequences of alternative decisions. The
       decision-making tool will be tested in relation to road pricing in Denmark.”
More detailed the following elements have been identified in the modelling process:
      Development of a system of data exchange between transport models, regional economic
       models and impact models, specifically designed to facilitate environmental impact
       evaluation.
      Extension and improvement of existing models through increasing the quality of data
       relating to exogenous variables.
      Assessment of the predictive power of transport models and regional economic models.
      Development of a research framework for improvement of the existing models based on the
       experience of the project.
      Identification of the environmental consequences, economic efficiency and distributional
       implications of different policy options.
The paper sets off with an introduction to MERGE and the chosen transport, interregional
economic, environmental impact and assessment models. This is followed by a description of how
the framework will be used for evaluating a transport policy initiative in the form of a road-pricing
scenario in Denmark and finally the paper describes conclusions and research perspective.

MERGE
The keyword in MERGE (Model for Exchanging Regionalised Geographic Entities) is model
integration. First of all MERGE has to link the transport, interregional economic, environmental
impact and assessment models together into the desired decision-making tool by making procedures
for transferring in- and output data between the models.
For each type of models an existing model has been chosen for the decision-making tool:
          MERGE module A. The National Transport Model, LTM, developed by the Danish
           National Road Directorate and others.
          MERGE module B. The environmental and economic impact assessment tool TicMap,
           developed at the Technical University of Denmark.
          MERGE module C. The interregional economic model LINE, covering all Danish
           regions, developed by the Local Government Research Institute (AKF) in Copenhagen.
          MERGE module D. The Composite Model for Assessment (COSIMA) developed at the
           Technical University of Denmark.
The integration of these models addresses some questions that are not only relevant for the specific
models in question but also for a more general application. This means that some of the procedures
developed in MERGE are quite universal for model integration.
Instead of making MERGE a specific tool for integrating the LINE, LTM, TicMap and COSIMA
models, the starting point has been a more general approach to model integration (incl. data
transfer) and from there on to focus on the specific models.
This approach has the advantage that if other (or better) models become available they can be
utilised with less effort than if MERGE was specifically designed for the mentioned models. This
can be referred to as model modularity and leads to a structure of MERGE as illustrated in Figure 1.




Figure 1: Schematic structure of the MERGE modular structure.
The principle is that other models can be ”snapped” on to MERGE and used in coherence with the
other models in the modelling framework (examples of other present and future models are listed in
Table 1).
Besides the modularity of MERGE another important factor in the model integration is consistency.
One of the objectives of MERGE is to provide data exchange between the transport, regional
economic, impact and assessment models. All these types of models rely to a certain extent on
spatially distributed data but not necessarily on data with the same spatial distribution. When
integrating the models into a decision support system, it is important to ensure a common consistent
basis so that results and conditions to some extent are identical or at least consistent. It is especially
important to be able to reproduce results and datasets.
It might sound simple, but if e.g. a model requires 50 zones, MERGE has to be able to generate this
number of zones, preferably from any base dataset, under a number of different conditions e.g.
equal number of inhabitants within the zone; equal area of the zones etc. At the same time it has to
be possible to keep track of where data originated from and to give some estimates of the accuracy
of not only the original data, but also the generated data. This is commonly known as metadata (or
data on data).
Generation of new datasets from an existing dataset is where GIS have been proven as a very
powerful tool. Results and input data all have some kind of spatial attributes e.g. population data
can be on a municipal or a parish level. It is not necessary that all the integrated models actually use
the spatial reference but the spatial reference can be used in MERGE to generate and exchange
datasets.
LTM – MERGE module A
The Danish Road Directorate (VD), the Danish National Rail Company (DSB), the Danish National
Rail Agency, and the Danish Ministry of Transport have jointly developed the Danish National
Transport Model (LTM). The model provides an assessment of the national and regional passenger
transport by car, rail, bus, ferry and aeroplane in Denmark. The model assesses both the
development of the total transport effort in Denmark, as well as the link flows.
The zoning structure of the model is based on Danish parishes (sogne), making the zoning structure
quite detailed with approximately 1,100 zones. In Copenhagen the zoning structure is based on the
Greater Copenhagen Transport Model (HTM). All border crossings to Germany and all ferry
connections abroad are linked to each of their port zones.
The road network consists of approximately 10,000 links with information on travel speed, link
length and traffic counts. The rail network is based on information on routes, travel times,
frequencies, cost structure and passenger counts. The model also contains a bus network of
approximately 1,100 lines with information on routes and travel costs.
Finally, the model contains a network of domestic air routes.
The socio-economic data is obtained from the national travel habit surveys. The present version of
the model is based on interviews from this survey of October 1994 to September 1995, involving
approximately 14,000 people.
The model is maintained in EMME/2 that calculates supply data (travel time, distance, travel cost
etc.) between each zone pair. The resistance matrices produced are then used in the hierarchical
logit-model FREDERIK, consisting of four sub-models:
   1.   Model of car ownership based by zone
   2.   Model of trip frequency by zone
   3.   Model of destination choice
   4.   Modal split model (car, bus, train, aeroplane, bicycle/walk).
The sub-models of FREDERIK are applied once for each of 9 trip purposes:
   1.   Business trips
   2.   Private long distance trips
   3.   Home-work trips
   4.   Leisure trips, weekday
   5.   Shopping trips, weekday
   6.   Other trips, weekday
   7.   Leisure trips, weekend
   8.   Shopping trips, weekend
   9.   Other trips, weekend.
FREDERIK undertakes the analyses based on the information on supply and socio-economic data
on population and workplaces by zone as well as assumptions on the taxation and travel cost
structure and development in the economy.

TICMAP – MERGE module B
The TicMap (Traffic Impact and Cost MAPping) model [Wass-Nielsen, M. & Hviid Steen, C.
(2001)] is a MapInfo tool for traffic impact calculation. The basis of TicMap is four impact models
for:
   1.   Accidents
   2.   Noise
   3.   Emission
   4.   Severance and perceived risk
Each of these impact models are based on Danish impact assessment models and the can be run
individually from within MapInfo.
The results from the impact models are used to make a assessment of the impacts on each road
segment in the network. For a closer description of the impact models see e.g. [Wass-Nielsen, M. &
Hviid Steen, C. (2001)], [Clausen, F., Wätjen, W. & Leleur, S. (1991)] or [Leleur, S. (2000)]

LINE – MERGE module C
LINE is an interregional general equilibrium model that has been developed at The Local
Government Research Institute (AKF) in Copenhagen [Madsen, B.; Jensen-Butler, C. & Dam, P.U.
(2001)]. In relation to the project proposal two characteristics of LINE are important. First the
model incorporates the consequences of changes in transport costs for regional competitiveness and
through this, the level of regional economic activity and relocation of economic activity and
households. Second, LINE can model changes in interaction and thereby changes in origins and
destinations for different types of traffic.
Two basic economic processes form the skeleton of LINE. These two processes are denoted the real
circle and the cost-price circle. The real circle is the demand-production-demand process and is an
iterative or a round-by-round process: Regional demand determines regional production, which
generates regional income, which in turn influences regional demand. This forms a circle, where
round-by-round impacts add up to a total impact.
In the cost-price circle, regional level of wages and prices of intermediate consumption
commodities determine the cost of production. Regional production cost is transformed into
regional prices of commodities (basic prices), which in turn determine regional prices in markets
and thereby intermediate consumption cost and final demand prices (buyers prices). This cost-price
circle also includes a round-by-round process, where cost-price changes are passed into the regional
and interregional production system [Madsen, B.; Jensen-Butler, C. & Dam, P.U. (2001)].

The LINE real circle
A simplified illustration of the LINE real circle for modelling the consequences for production,
income and employment are show in Figure 2.
Figure 2: The LINE real circle [Madsen, B.; Jensen-Butler, C. & Dam, P.U. (2001)].
The regional economic impacts calculated in LINE can be summed up like this: Reductions in the
price of commodities influence the disposable income for households. An increase in the regional
disposable income influences the private consumption. An increase in private consumption
influences the amount of commodities purchased by the households under the assumption that the
composition of commodities is assumed unchanged. The increase in private consumption again
influences the supply of commodities to an area either by an increase in the Danish production (by
place of production) or an increased import. An increase in production leads to an increase in
disposal income for the households (by place of household). An increase in production will at the
same time lead to an increase in demand for raw material (by place of demand) that again will lead
to an increase in production of raw material (by place of production) etc. (under the assumption that
the composition of raw material for each industry is unchanged). This demand circle shows in other
words how changes in the economic activity in one area influence the surrounding areas through a
series of mechanism e.g. household consumption, commodity trade and commuting [Madsen, B.;
Jensen-Butler, C. & Dam, P.U. (2001)].

The LINE cost-price circle
The prices of commodities are first of all determined by the cost of production. But the price of
commodities is also influenced by changes in transport cost both when raw material is transported
to the place of production, when commodities are transported from the place of production to the
market and when the commodities are transported from the market to the consumer. Besides that the
disposal income of the households is also influenced by the cost of commuting.
The influences on prices are shown on Figure 3. The figure shows (in a simplified way) how cost
and price changes in the production influence the cost of commodities on the market, which again
influences cost and prices in production etc. At the same time the figure shows how LINE
calculates the changes in regional production cost and the price of commodities.
Figure 3: The LINE cost-price circle [Madsen, B.; Jensen-Butler, C. & Dam, P.U. (2001)].
As it can be seen on Figure 3, the production prices of specific commodities are determined by the
sum of production cost meaning cost of row material, wages and profit. The costs of transport are
added to the basic cost when commodities are transported from the producer to the market and
thereby the production cost is made into the selling price. The commodities are purchased by either
the households (private consumption on address) or by other industries (raw material after place of
production). The price of the commodities – from the households point of view – are hereby added
the cost of the transport from the marked to the household. The cost of transport thereby influences
the disposable income of the household. The price – from the industries point of view – includes the
cost of transport of raw material to the place of production. The commodities from these industries
are then again added the cost of transport – meaning that the households or industries in the next
change of the production chain will have these costs added to the price etc.
The cost of transport also directly influences the disposable income and wages. If the cost of
commuting is lowered then the disposable income – all other things equalled – will go up [Madsen,
B.; Jensen-Butler, C. & Dam, P.U. (2001)].

COSIMA – MERGE module D
The COSIMA model (composite model for assessment) has been worked out to provide a more
comprehensive assessment of transport initiatives than made possible by applying a conventional
cost-benefit analysis (CBA). Thereby COSIMA deals with a mix of CBA effects and non-CBA
effects. Typically the non-CBA effects - when seen from a modelling viewpoint - are more difficult
to handle as compared to the CBA effects where handbook approaches (pricing and procedures) are
available for many transport planning problems. In brief we will refer to the CBA effects as effects
where pricing manuals and procedures exist and to the non-CBA effects as multi-criteria analysis
(MCA) effects as this type of analysis, stemming from operations research, becomes relevant for the
extension of the conventional CBA. The idea of COSIMA can briefly be described by the following
seven steps as formulated for the assessment of a number of alternative by-pass projects for a
Danish town currently in need of relieving of the through traffic [Leleur, S. (2001)]:
   1. The first task is to determine the CBA effects being relevant for the concrete appraisal study.
      In the by-pass example, following the Danish Road Directorate’s standard model, the effects
      are: travelling time, vehicle operating costs, accidents, maintenance costs, noise, air
      pollution and severance & perceived risk. The investment enters the analysis denominated
      as the construction costs.
   2. The next task is to determine the MCA effects of relevance. These may be measured either
      in some type of quantitative unit, an example could be changes in strategic mobility see
      [Kronbak, J. (1998)], or by judgement using a +5, .., 0, .., -5 scale. In the example below three
      MCA effects are taken into account by using such a point scale: network accessibility, urban
      planning and landscape.
   3. With CBA and MCA effects laid down the so-called “anchoring” part of the model
      formulation can take place. Hereby is meant determining the importance of the MCA effects
      against the CBA effects and in-between each other. Several MCA techniques are relevant
      here: direct weights, pairwise comparison, swing weights, etc. see [Leleur, S. (2000)].
      Criteria importance is denominated by weights on the individual criteria adding up to 100%.
   4. At this stage the base case scenario termed A is modelled and presented to the decision-
      makers together with the assumed interesting assessment questions; these concern issues
      that may have a principal influence on the decisions to be made from the study. The
      decision-maker involvement may lead to revision of both the kind of MCA impacts included
      and their weights in scenario A. Part of this exchange with decision-makers is also to
      formulate suitable additional scenarios; in the by-pass example these are the scenarios B, C
      and D.
   5. Afterwards COSIMA is run for all the scenarios and the assessment questions are
      scrutinised and related to possible sources of uncertainty. This “deterministic run” of the
      model and the identification of “varying levels” of information give intermediate results that
      in the following model step are examined as concerns their “feasibility risks” which indicate
      that a result in the deterministic run may be associated with such uncertainty that precaution
      is needed.
   6. Next the so-called “stochastic run” of COSIMA is undertaken. This in fact is a Monte Carlo
      simulation where parameters and data have been replaced with suitable probability
      distributions that can represent the actual information level. In the by-pass example used as
      background for this overview of steps in COSIMA both distributions arrived at empirically
      by data fitting and distributions set on the basis of reasoning are made use of. One could
      refer to those as “objective” and “subjective” probability assessments.
   7. At this stage the assessment questions are addressed on the basis of the model results and
      the assumptions behind and a second exchange with the decision-makers is carried out. With
      the layout of the COSIMA model as a transparent tool box two principal possibilities are
      available now. The study may simply end here if the decision-makers are confident about
      the model outcome, or the decision-makers may want to feed back in the process and re-
      address some of the previous model settings to shed light on some issues.
It should be noted that COSIMA is more or less tailored dependent on the concrete application. As
should appear from the overview of methodological steps above, features for applying both
scenarios and risk examinations are available. When incorporating COSIMA in the MERGE model
software, the way the other three model categories are set for the actual planning problem will
influence the possibilities for the assessment analyses to be carried out in the COSIMA module.
Other models
The following is a listing of other models of interest for the MERGE development.

Table 1. Other models with present or future possibility of use in connection with MERGE.
       Name                                     Description                                             Reference

Transport Models
HH/KR         traffic   The Copenhagen/Ringsted (K/R) model.                           The model has been developed at the national
model                                                                                  Danish railway agency in cooperation with the
                                                                                       Centre for Traffic and Transport – Technical
                                                                                       University of Denmark (CTT-DTU).
COMPAS model            The COMPAS (Copenhagen Model for Passenger Activity            The model are to be developed at The Danish
                        Scheduling) model is planned as an activity-based model        Transport Research Institute (DTF).
                        for modelling of individual transport demand based on
                        individual choices of activities in various locations.
OK traffic model        The OK (Oslo - København) traffic model                        Principles have been worked out by TetraPlan
                                                                                       and CTT-DTU.
TSM                     The TSM (Traffic Sketch Model) is a simple traffic model       The model has been used at the Centre for
                        designed only to sketch out the future traffic.                Traffic and Transport – Technical University
                                                                                       of Denmark in connection with student theses
                                                                                       and simple (sketch) traffic modelling.

Regional Economic Models
ASTRID                  New regional economic model                                    The model is under development at the
                                                                                       Institute of Local Government Studies (AKF).
POINTER                 The POINTER (Potential Interaction) model describes the        The model has been developed at the Centre
                        potential for interaction, based on the transport system and   for Traffic and Transport – Technical
                        the spatial distribution of the population.                    University of Denmark and has been used in
                                                                                       several theses and EU projects.
JOINTER                 The JOINTER (Joining of Territories) takes its offspring in    The model has been developed at the Centre
                        the POINTER model but describes the potential for              for Traffic and Transport – Technical
                        economic interaction.                                          University of Denmark in cooperation with the
                                                                                       Transport Studies Unit – University of
                                                                                       Oxford.

Impact Models
COPE                    The COPE (Corridor Planning and Evaluation) model is a         The model has been developed at the Centre
                        GIS based model for planning and evaluation transport          for Traffic and Transport – Technical
                        corridors.                                                     University of Denmark and has been used in
                                                                                       several theses.
SEAM                    The SEAM (Scenario-based appraisal methodology)                The model has been developed at the Centre
                        model can make scenario based project evaluation.              for Traffic and Transport – Technical
                                                                                       University of Denmark and has been used in
                                                                                       several theses.

Assessment models
VD-model                The Vejdirektorat (Danish Road Directorate) has a well-        Danish Road Directorate
                        proven assessment framework for CBA of new road
                        infrastructure investments.
EUNET                   As part of the EUNET project a comprehensive framework         The EUNET project had among others as its
                        for innovative cost-benefit/multicriteria decision analysis    main objectives to develop an innovative cost-
                        methodology has been developed.                                benefit/multicriteria decision analysis
                                                                                       methodology and to develop a methodology
                                                                                       for measurement and valuation of socio-
                                                                               economic development effects.
PlanTIS             The PlanTIS (Transportation Information System) model is   The PlanTIS model has been developed by
                    a GIS-based project database and presentation tool. It     PLANCO Consult as a part of the TEN-Invest
                    forms a strong base for implementing assessment tools.     project for the European union.




Road Pricing Scenario
The description for the TRIP project “Integrated Traffic, Regional Economic and Impact Models”
states the following [TRIP (2000)]:
          A choice will be made of a suitable empirical example for application of the
          modelling framework. A relevant case is introduction of road pricing in Denmark.
          This change in paradigm from single car and gasoline taxes to advanced user
          charging clearly influences emissions, the regional economy, the traffic system,
          accessibility and their interrelations. The model complex will permit evaluation of the
          environmental and economic consequences of the policy instrument.”
In Denmark different schemes for road pricing has been dealt with in detail in the FORTRIN
research programme [Kildebogaard, J. & Ildensborg-Hansen, J. (2001)].
The main focus of the TRIP Road Pricing Scenario (TRIP-RPS) is, however, to demonstrate the
framework and not to make a comprehensive analysis of road pricing scenarios in Denmark. Due to
that the case study will be based on one of the scenarios from the FORTRIN project but it will in no
other way be related to the FORTRIN project.
One of the main points in using GIS as the base for MERGE is the possibility to include the spatial
dimension within the modelling framework. This indicates, that the TRIP-RPS should differ
spatially within Denmark. There are many other - spatial and non-spatial - parameters that would be
interesting to change in a road pricing scenario, but the TRIP-RPS aims at being relative simple in
order to focus on the advantage and weakness of the model framework and not necessarily on the
results.
This means that the following limitations have been included in the TRIP-RPS.
    –     There are no redistribution effects. This means that possible revenue from RP will not be
          used to e.g. subsidy public transport.
    –     The RPS should only be link based – meaning that it will only influence the network
          impedance (cost) and not (in short term) change the car ownership (as modelled in the LTM-
          FREDERIK model).
    –     It would be an advantage if the exchange of data to the LTM could be tabular (as with the
          LINE model).
One of the RP schemes in the FORTRIN project is the “Goal Orientation Management Scenario”.
In this scheme the tariff structure is drawn up in order to support two independent objectives
[Kildebogaard, J. & Ildensborg-Hansen, J. (2001)]:
         The total CO2-emission from the transport sector should be reduced, and
         Traffic in the urban and residential areas should be reduced. The road users should be
          motivated to follow the intentions of the local traffic plans, ie. use the trunk roads as far as
          possible.
The FORTRIN “Goal Orientation Management Scenario” has, however, a quite elaborated
differentiation between: 3 vehicle types, 2 time periods, 3 road types and 3 area types. This gives a
total combination of 54 different road prices.
It is, however, for the TRIP-RPS, impractical to differentiate between so many vehicle types, time
periods, road types and area types. Instead the TRIP-RPS will focus on 2 vehicle types: Car and
Truck and only differentiate between two types of areas: Urban and Rural. This gives a TRIP-RPS
tariff structure with 4 different road prices as shown in Table 2.

Table 2: The tariff structure for the TRIP-RPS.
Road Price        Urban area      Rural area
Car                   X               X
Truck                 X               X



The TRIP-RPC will be calculated for one full “circle” in the MERGE model structure as illustrated
in Figure 4.




Figure 4: The dataflow in one circle of the TRIP-PRS.


The sequence in the TRIP-RPS for one full circle can be illustrated as in Figure 4:
      1. Network, Traffic Analyse Zones (TAZ) and link traffic are sent from the LTM to MERGE.
      2. MERGE sends the link traffic to TicMap for impact calculation.
      3. TicMap returns the calculated environmental impacts to MERGE.
      4. MERGE calculates the resistance matrices based on the TRIP-RPS and the LTM network
         and sends the matrices to LINE.
      5. LINE returns the modelled regional economic development to MERGE. MERGE transforms
         the results from municipalities to parishes.
   6. MERGE sends the socio-economic data from LINE and the new transport prices from the
      TRIP-RPS to LTM.
   7. LTM calculates new link traffic based on the output from LINE and the TRIP-RPS and
      sends the result to MERGE.
   8. MERGE sends the new link traffic to TicMap for impact calculation.
   9. TicMap returns the environmental impacts based on the TRIP-RPS to MERGE and
      MERGES calculates the changes in environmental impact for the TRIP-RPS.
   10. MERGE sends all results to COSIMA for assessment.

Conclusion and research perspective
The paper has presented the MERGE modelling structure with emphasis on integration and
modularity. Major results to be obtained with the project can be listed as follows:
      Development of a system of data exchange between transport models, regional economic
       models and impact models, specifically designed to facilitate environmental impact
       evaluation.
      Extension and improvement of existing models through increasing the quality of data
       relating to exogenous variables.
      Development of a research framework for improvement of the existing models based on the
       experience of the project.
      Assessment of the predictive power of transport models and regional economic models and
       of the enhanced applicability of the impact and assessment models supported by case
       calculations.
Currently, the different modules are tested on case calculations. In the remaining part of the TRIP
project the full MERGE model will be tested and the different findings reported. Even as this
should be considered as only a preliminary conclusion the results obtained so far indicate that the
MERGE software will make it possible to undertake a range of interesting examinations within
practical transport planning that have so far not been dealt with due to shortcomings of existing
software tools and not the least their practical interlinking.

Literature
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Concerted Action 1.1.
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kørselsafgiftssystem – tekstscenarier og økonomi”, Center for Trafik og Transport, Danmarks
Tekniske Universitet.
Kronbak, J. (1998). Trafikplanlægning og GIS-baserede konsekvensberegninger, Ph.D. dissertation,
Department of Planning, Technical University of Denmark.
Kronbak, J. (2002): “Data exchange between transport models, regional economic models and
impact models, specifically designed to facilitate environmental impact evaluation”, Paper at
“Trafikdage in Aalborg”.
Leleur, S. (2000): “Road Infrastructure Planning – A Decision-Oriented Approach”, Polyteknisk
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Leleur, S. (2001). Transport Infrastructure Planning: Modelling of Socio-Economic Feasibility
Risks, Proceedings of the EUROSIM Congress, Delft, 2001.
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2001 (http://www.akf.dk/eng2001/line_model.htm).
TRIP (2000): “TRIP 2.3: Integrated Traffic, Regional Economic and Impact Models”, Project
description, TRIP 2000.
Vejdirektoratet (2002): ”Trafikøkonomiske enhedspriser 2000”, The Danish Road Directorate,
Ministry of Transport, Denmark 2002.
Wass-Nielsen, M. & Hviid Steen, C. (2001): ”Development of a MapInfo tool for mapping and
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af trafikale effekter). Centre for Traffic & Transport, Technical University of Denmark.

								
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