EUR 23933 EN - 2009 

# Longer and Heavier Vehicles for freight transport

Panayotis CHRISTIDIS, Guillaume LEDUCThe mission of the JRC-IPTS is to provide cu stomer-driven support to the EU policy-making process by developing science-based responses to policy challenges that have both a socioeconomic as well as a scientific/technological dimension.

European Commission
Joint Research Centre Institute for Prospective Technological Studies

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JRC 52005

EUR 23933 EN
ISBN 978-92-79-12790-8
ISSN 1018-5593
DOI 10.2791/12276

Luxembourg: Office for Official Publ ications of the European Communities

© European Communities, 2009

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Printed in Spain

### TABLE OF CONTENTS

1 Overview ........................................................................................................................................................1

2 Comparison of main studies on LHVs............................................................................................. ...............3

3 Main factors affecting the impact of LHVs...................................................................................... ..............9

4 Monte-Carlo simulation......................................................................................................... .......................15

5 Simulation results ............................................................................................................. ............................17

6 Limiting the external impact................................................................................................... ......................22

7 Designing specific policy measures............................................................................................. .................23

8 Conclusions .................................................................................................................... ..............................24

9 Refere nces ..................................................................................................................... ...............................341 

## 1 Overview

The European Commission is considering the imp lications of allowing the use of Longer and

Heavier Vehicles a for road freight transport (abbreviated as LHVs in this study), measuring up to 25.25 m and weighing up to 60 tons, for the w hole of the European Union transport system. Such trucks are already in circulation in Fi nland and Sweden, while several Member States are considering their introduction.

The Directorate General Energy and Transport (DG TREN) commissioned a study to analyse

the technical characteristics of LHVs and estimate the potential impacts [TML, 2008]. The findings were very positive as regards the imp act of LHVs, both at th e level of individual vehicles and as regards their level of adoption at EU level. Since the s ubject is both important in economic terms and complicated in technical terms, the Community of European Railway and Infrastructure Companies (CER), a majo r affected stakeholder, commissioned an additional study to focus on the impact that L HVs would have on railways [ISI, 2008]. Even though the ISI study forecasts concerning the upt ake of LHVs were quite moderate, the resulting impact on railways raised some concer ns as regards the environmental impacts and the continuity of EU transport policy favouring ra ilways. In addition, studies at various levels

of detail have been carried out at member stat e level. An example of such an extensive study is the one carried out for the Department for Transport of the UK [TRL, 2008]. Since the analysis was mainly focused on the impacts at UK level, the expected improvements in overall efficiency and the degree of uptake of LHVs were considered as limited to the UK transport system and not transfer able to the rest of the EU.

The analysis of the impacts of LHVs is quite complicated since it entails the adoption of assumptions concerning the technical characteristic s of future LHVs, the evaluation of costs at truck level, the estimation of the repercussions on costs for the transported goods, the prediction of the market share of LHVs and the calculation of the external impacts, including environmental damage, accidents and wear and te ar. Since the three studies mentioned above used different assumptions and hypotheses, it is not surprising that their results differ significantly and no c onsensus can be found.

The Joint Research Centre, Institute for Prosp ective Technological Studies, carried out the present study in order to compare the assump tions of the three studies above and, after consulting additional sources of information, to identify the range of technical and economic factors assumed. Using these as input, an independent analysis was carried out, which encompasses both the scope of all three studie s and the range of values used in their assumptions. Since the initial assumptions influence the final results to a large extent, a Monte-Carlo analysis was carried out to allo w for different combinations of the various assumptions and to identify a range of potential costs and be nefits at a lower level of uncertainty.

The results of this analysis s uggest that the potentia l impacts of the intr oduction of LHVs at EU level can be positive in bot h economic and environmental te rms. The increased payloads per vehicle are expected to reduce transport cost s and lead to significant savings for operators, industry and consumers. Since fewer trucks woul d be required to tran sport the same volume

a Also called Mega-Trucks (MT), European Modular System (EMS), Ecocombi, Eurocomb is, gigaliners, etc. This report uses the term LHVs to encompass all freight vehicles exceeding the limits on weight and dimensions established in Directive

96/53/EC.2 of trade, the environmental and other external co sts of freight transport would also be lower, even though an individual LHV consumes and pollutes more than a conventional truck.

A successful policy for the introduction of LHVs w ould nevertheless need to ensure that they are used within specific boundary conditions. Th is would involve a combination of regulatory and economic measures to stimulate the use of LHVs in cases where they deliver real efficiency improvements. Defining suitable tec hnical standards for LHVs would assist in limiting the external impacts of individual vehicles and the infrastructure requirements for the whole road network. Identifying th e extent of the road network that they are allowed to use would influence their usability and uptake. Usi ng a charging system that internalizes their external costs would be an additional safegua rd against additional externalities and would

stimulate the rational use of LHVs.

The analysis was carried out under the assumpti on that the use of LHVs would be allowed across the EU, without any distinc tion of the type of road networ k used. As a result, the trade flows that are expected to be served by L HVs are spread across Europe, although a higher traffic is expected in Germany, Belgium, th e Netherlands, the UK and a number of specific corridors. The road network links where higher LHV traffic is expected would benefit from reduced total freight traffic and congestion levels , but may need to invest in infrastructure improvements, depending on the technical characte ristics of the LHVs that would be allowed to circulate. It is also expected that the main competition with the other modes will occur along these corridors. Limiting the use of LHVs to specific Member States or corridors would probably reduce their environmenta l impact and infrastructure requirements, as well as the

shift from other modes. But it would also lim it their uptake and the po tential overall benefit for the economy as a whole. A more detailed an alysis would be needed to analyse the impacts of a more limited use of LHVs, but in principle they are expected to be positive regardless of the scale of their application.

Additional research would be al so required in order to analys e short-distance road transport operations and estimate the potential overall effi ciency gains from the introduction of LHVs serving that part of the mark et. Although theoretically there is margin for improvement, the diversity of economic, organisational and tec hnical factors that affect freight transport planning at that level makes th e estimation of the uptake of L HVs for shorter trips rather

uncertain.

As is the case with most policy measures , introducing LHVs woul d produce winners and losers. The benefits would be spread among the economy and society as a whole, in the form of lower transport costs and environmental imp acts. On the other side of the coin however, other transport modes -especially rail- would become less competitive and lose market share. In the road sector itself, increases in effici ency would mean that fewer drivers would be necessary, but the ones remaining would tend to be better trained and paid. At territorial level, there is also the case of possible imbalances between costs and benef its; where improvements in infrastructure are required, the costs for a specific region may exceed the benefits, which may be enjoyed by users in other regions.

Overall though, the potential bene fits of LHVs clearly outweigh the associated costs. In addition, it is possible to introduce additional legislative measures to ensure that their introduction, in specific market segments a nd under certain conditions, maximises the benefits and compensates the stakeholders th at would be affected negatively.3 

## 2 Comparison of main studies on LHVs

TML consortium [TML, 2008]

This study was commissioned by DG TREN a nd was released end of 2008. It provides analytical and model-based results on the impact of LHVs on the EU transport market (e.g. road freight demand, rail demand, environmental im pact, safety and infrastructure). In broad terms, the TRANSTOOLS model is used fo r providing transport volume in 2020 (tonnevolume converted in tonne-km through the mo del RESPONSE) while the TREMOVE model is used for assessing the environmental impa ct in the EU, based on the traffic volume (vehicle-km) obtained from assumed loadi ng factors. A schematic overview of the methodology is given in Figure 1.

A set of four scenarios were developed for the year 2020:

• Scenario 1 or "Business as usual" scenario which assumes no changes to the road transport equipment constraints that were valid in 2000 and takes into account projected transport demand in Europe until 2020.

• Scenario 2 for which LHVs are allowed on all EU motorways (usage of LHVs in regional roads can be restricted).

• Scenario 3 for which LHVs are allowed in so me countries only, the rest sticking to the current restrictions (40t, 18.75m).

• Scenario 4 or "intermediate" scenario wh ere the EU allows the usage of up to 20.75m

and 44t trucks.

SET OF

ASSUMPTIONS • Discount factor: -20% • Load Factor (LHVs) = LF (HDVs) + LF (HDVs)*50% • No oil prices scenario • Transport elasticity fixed at -0.416 • Share of MTs within the total road transport

Tonne-volume

Tonne-km

Vehicle-km

Impacts on safety Impacts on fuel consumption

and emissions Impacts on

infrastructure Load factors RESPONSE

model
Impact on rail

demand

TREMOVE

model SET OF

ASSUMPTIONS • Discount factor: -20% • Load Factor (LHVs) = LF (HDVs) + LF (HDVs)*50% • No oil prices scenario • Transport elasticity fixed at -0.416 • Share of MTs within the total road transport

Tonne-volume

Tonne-km

Vehicle-km

Impacts on safety Impacts on fuel consumption

and emissions Impacts on

infrastructure Load factors RESPONSE

model
Impact on rail

demand

TREMOVE

model

Figure 1: Overview of th e approach used by TML4 Limitations of the TML study approach

• Only one price elasticity was used (- 0.416) and only one run was carried out. A sensitivity analysis would be required.

• Elasticity is suitable for modest price variations and for short term effects.

• Freight demand parameters (e.g. elasticities) are generally expre ssed in tonne-volume

and not in tonne-km. It can be difficult to compare the results with other studies.

• Need to distinguish between the different rail market segments (commodity group and distances).

• Technological potential improvements not covered (e.g. aerodynamics, new safety systems).

Summary of results (scenario 2 vs. reference)

Road freight market Modal shift En vironment Safety Infrastructure

416.0 / −= RR ε (ton-volume)

Tonne-volume rises by 0.99% (+0.76% in ton-km).

30% of heavy cargo traffic is carried out by LHVs.

Traffic volume (veh-km) of LHVs decreases by 12.9% (depending on the country).

Road transport cost reduced by 15-20%, on average. Rail demand decreases by3.8% (in tonvolume). 60 t vehicles are up to

12.45% more efficient

in terms of fuel consumed per ton-km.

CO2 emissions reduction by 3.58%.

Reduction of NOx emissions by 4.03%.

Reduction of PM by

8.39%. Impact depending on the

vehicle-km (rather positive in this aspect). Impact depending on

the vehicle-km (rather positive in this aspect).

ISI Fraunhofer [ISI, 2008]

This study was financed by the Community of European Railway and Infrastructure Companies (CER) and conducted by ISI Fraunhof er (Germany) in collaboration with TRT Trasporti e Territorio (Italy) and NESTEAR (Franc e). The objective is to assess the effect of introducing LHVs on long-term perspective, with the emphasis put on modal shifts effects between rail and road freight transport.

After reviewing some key outcomes from the literature and from two representative case studies in the EU, this st udy used the LOGIS model (fro m NESTEAR) and developed a System Dynamics model (from TRT and ISI Fr aunhofer) leading to the following conclusions for the EU-25 (plus Switzerland):

• The GIS analysis (LOGIS model) concluded that LHVs would account for 25% (in ton-km) of the total road market by 2020. L HVs would represent a 100% share in total HDVs for distances above 1000 km, concentrat ing on major corridors. On the other hand, LHVs will start playing a role in the road-road competition only for distances above 300 km. Rail container traffic may be reduced by up to 85% in case of EU-wide acceptance of 60 tons LHVs.5 • The Vensim model (System Dynamics) was used to assess the long-term impacts of LHVs (time horizon 2025) which take place in three phases:

1- From 3 to 6 years: decrease of CO 2 emissions due to efficiency gain on the road (0.5 million tons per year). 2- From 5 to 20 years: counter-balancing of CO 2 reduction (2 million tons per year). 3- From 15 to 30 years: road sector might re-gain overall CO 2 emission.

The study also concluded that reducing the maximu m gross weight from 60 tons to 50 tons is

not an efficient alternative.

Summary of results

Road freight Modal shift Environment

Between 20% and 30% cost saving potential from LHVs.

LHVs may take up to 20-30% HDV goods volumes (depending on the country). Container shipments may face losses of rail demand up to

50%. Traffic volumes lost by the railways due to 60t LHV:

[3-5%] reduction for bulk goods including heavy industry and chemical products [10-15%] reduction for food, food products and semi products [20-30%] reduction for

continental container traffic [10-20%] reduction for

maritime container traffic The results from the Vensim model concludes that the introduction of LHVs will end up in a negative climate gas balance due in the medium term.

Rebound effects will counter-balance the initial advantage of LHVs.

Limitations of the ISI study approach

• High uncertainties of the model parameters in Vensim. Therefore, results from the scenarios might be very different.

• Market-based analysis, focus on the impact on combined transport.

TRL study [TRL, 2008]

This mainly desk-based research assesses the li kely effects of allowing LHVs in the UK with regard to road safety, environment, infrastr uctures, operating costs, congestion, and other social and policy issues. Different vehicle configurations in le ngth and weight were analysed. Eight scenarios on the usage of LHVs in the UK were developed, based on a micro simulation freight model.

These scenarios present several combinations of maximum vehicle length (16.5m, 18.75m, 25.25m and 34m), weight (from 44t to 82t ) and number of axles (6, 8 and 11).6 Summary of results

Road freight Modal shift Envi ronment Safety Infrastructure

One-third of articulated vehicle trips could be

suitable for LHVs.

LHVs expected to be specialist vehicle working in 'niche' operations.

Around 5-10% of the ton-km carried by

articulated vehicles

could move to LHVs of 60 tons or more (i.e. a migration to around 11.8 bn ton-km per year). Important risk of shift

from rail to road.

Maximum of 8-18% of

all rail tons-km (especially for the deep sea container market) would migrate to

LHVs.

No shift expected from waterborne transport. Decrease in veh-km

Increase of fuel consumed per veh-km (up to 71% for 82 tons LHV).

Decrease of fuel consumed per unit of goods by around 8-28% depending on the

scenario.

Internal operational costs per ton-km would then be reduced by 18-

43%.

Risks of adverse

environmental effects

due to the shift demand

from rail to road (depending also on the configuration). Increase safety risks per vehicle (depending on the configuration of the LHV).

However safety risks per unit of goods are reduced.

Risks could be mitigated by using new technologies. Large investments are necessary to upgrade parking facilities and to manage road

infrastructures.

Increase or decrease

of road wears depending on the configuration.

Impacts on bridges

need further research

work.

Limitations of the TRL study approach

• UK-specific study, cannot be extended to the rest of the EU.

• Wide range of effects obtained depending on the LHV configurati on (max length, max gross weight).

• Are these technical combinations realistic for the rest of Europe?

Other results from literature

Apart from the three relevant st udies briefly discussed above, a wide range of analyses and reports addressing LHVs is also available. So me focus on technical and/or economical issues

while others discuss the results of pilot projects. It is out of the scope of the present study to provide a detailed literature survey on the im pact of LHVs (see e.g. the literature review carried out by TML [TML, 2008]). The tables below present main outcomes from a (nonexhaustive) list of EU studies. The only commen t that can be made from this comparison is that there is no consensus on the impact of LHVs across Europe, something that is also highlighted in a recent paper from Pr of. McKinnon [McKinnon, 2008]. Depending on the country characteristics (road network, freight market, etc.), the model assumptions (road elasticities, cross elasticities, etc.) very differe nt positive or negative results can be obtained.7GLOBALLY POSITIVE POSITIONReference Road freight demandModal shift EnvironmentSafetyInfrastructureComments[Aurell, 2007](SE)Fuel consumption and airemissions reduced by at least18%.Modular combinationsshow better dynamicstability compared tostandard HDVs.Modular combinationsgenerally cause lesspavement wear thanstandard HDVs.Technical analysison the advantagesof the modularconcept.[Arcadis, 2006](NL)6000-12000 LHVs will replace 8000-16000 regularcombinations.Increase of road transport by 0.05%-0.1% and reductionof traffic volume (veh-km).Cost price per mile for LHVs increase by 6.5% but it iscompensated by the reduction of the number of rides.Total cost reduction in road transport amount to 1.8-3.4%.Decrease inrail transportby 1.4%-2.7%.Lower fuel consumption and CO2emissions.Congestion reduced by 0.7-1.4%.Traffic safety wouldincrease (since lower vehkm).Decrease in fatal accidentsby a factor 4-7 and injuriesby 13-25 (no statisticsbased approach wasavailable).Dutchpilotprojects.GermanAssociation ofthe AutomotiveIndustry (VDA)bIf 23% of all conventional truck trips in Germany weremade with EuroCombis (type of LHVs), 2.2 billionvehicle-km would be saved annually in long haul traffic.The savings would be 16% on operational costs whenusing EuroCombis instead of 40t trucks.A fully loaded EuroCombiconsumes 15% less fuel per tonkm compared to 40t trucks.No safety risks fromEuroCombis.EuroCombis cause lesspavement damage.Germany-basedanalysis.[VTI, 2008](SE)Model used for modal shift: SAMGODS (Swedish freighttransport model).Clearadvantages ofnot going backto smallertrucks.Model used for emissions:ARTEMISModel used for noise:HARMONOISEClear advantages of not goingback to smaller trucks.Clear advantages of notgoing back to smallertrucks.Clear advantages of notgoing back to smallertrucks.Modelling-basedstudy: fourscenarios wereanalysed.NEUTRAL POSITIONReference Road freight demandModal shift EnvironmentSafetyInfrastructure CommentsT&E2007cCost reduction by 20-25% but greater demand. Cross-elasticity:1.8 (rail).Reboundeffects due tomodal shift.Positive impacts only if loadsunder 50 tons, optimisingloading capacity is key issue.Best suited to highvolume, low-weightcargoes.Adaptation required.bhttp://www.vda.dechttp://www.transportenvironment.org/Downloads-req-getit-lid-453.html8GLOBALLY NEGATIVE POSITIONReference RoadfreightdemandModal shiftEnvironmentSafetyInfrastructureComments[BAST, 2006] GermanHighway ResearchInstituteImportant shift isexpected.Higher consequences of fires in tunnels due tolarger loading volume.Increase of severity of accidents in the case ofhead-on collisions. This could however beovercome through the use of modern assistancesystems (Lane keeping assistant, brake assistantwith interval radar).No increase in road damagesexpected from 8 axles (butwill occur due to transportdemand increase).Increase stress on bridges: itwould cost €4-8 billion.Problem at roundabouts, roadcrossings and intersections,parking spaces due to longervehicle lengths.EMS in 60 tonsversion only. Focuson road infrastructureand safety risks.K+P TransportConsultantsd(DE)TIM Consult2006eTrucking costsreduced by 20-25%.7 billion tons-kmwould shift from rail toroad in one year.Decrease of intermodaltraffic up to 55% withLHVs on the road(24% road freightincrease.CO2emissions reduction of1.1% to 7.3%.Focus on the impactsof LHVs oncombined transport(in German).[UBA, 2007] GermanFederal EnvironmentalAgencyCost per loadtonne isreduced by 20-25%.Significant shiftdemand from rail toroad (e.g. up to 5%decline in rail-freighttransport).Energy efficiency gain only forload rate greater than 77%.Pollutants emissions onlydecline when fully charged.Increase of noise emission dueto heavier motorization andhigher number of axles.Higher consequences in case of accident due toheavier weight.Parking space capacityreduced by 20% at servicestations.Negative impacts on bridges.dhttp://www.nomegatrucks.eu/deu/service/download/k-und-p-studie-2-langfassung.pdfewww.timconsult.de9 

## 3 Main factors affecting the impact of LHVs

The starting point of the economic assessment is the increase in loading capacity brought by LHVs, typically 40-50% higher than for conventi onal (40 tons) trucks. As a consequence, the introduction of LHVs can trigger a chain react ion leading to a relatively complex dynamic process that will affect the different freight markets. A conceptual model of the main interactions is provide d in Figure 2 below:



### Vehicle-km Rail demand

Additional road freight demand

Additional traffic, centralisation, stockholding, etc. 

### + 

## + Road freight price decreases (cost per ton-km) EXTRA LOAD CAPACITY

Road price elasticity = f (commodity, trip length, space, time,...)



## -

Tons-km Load factor Cross-elasticity = f (commodity, trip length, space, time, ...)

Share of LHVs over

total HDVs fleet



## -

External costs

(accidents, congestion, air pollution, climate change, etc.) 

## +

-

Vehicle-km Rail demand

Additional road freight demand

Additional traffic, centralisation, stockholding, etc. 

### + 

## + Road freight price decreases (cost per ton-km) EXTRA LOAD CAPACITY

Road price elasticity = f (commodity, trip length, space, time,...)



## -

Tons-km Load factor Cross-elasticity = f (commodity, trip length, space, time, ...)

Share of LHVs over

total HDVs fleet



## -

External costs

(accidents, congestion, air pollution, climate change, etc.) 

## +

-

Figure 2: Schematic view of the different interactions

1- The road freight market would benefit from this extra loading capacity through a substantial cost reduction per tonne-km.

2- Depending on the price elasticity assumed, the reduction in price would generate an increase in road demand. This effect may be counterbalanced by the factthat more LHVs on

the road would mean much fewer conventional trucks.

3- Losing market to road, the rail freight demand would be probably reduced, depending on the cross-elasticity assumed. A similar shift would happen, to a lesser degree, away from the inland waterway sector.

4- Special attention should be paid to the load factor that will impact both the road price and

the traffic volume.

It has to be kept in mind that the impacts can vary considerably depending on the commodity

type , the distance travelled , the geographical area , time , whether ton-volume or ton-km are10 considered, etc. meaning that the degree of complexity, due to the number of dimensions involved is very high. In the following, some of the critical para meters are analysed.

Decrease in road haulage price

The split of cost to hauliers is available from several sources but it highly depends on the Member State, the distance travelled, the comm odity type, etc. Globally , costs for wages and

fuel account for more than half of the total co st, following by purchase, insurance and repair costs (Figure 3).

Repair

7%

Labour and

labour tax

45%

Fuel and fuel tax

26% Purchase

13% Insurance and

insurance tax

8% Ownership and registration tax

1%

Cost breakdown to EU hauliers for long distance freight

transport Source: [FM, 2008] Road tax

2% Interest 2% Tyres

1%

Vehicle

insurance

6% Fuel

30%

Wages

26% Overhead

18% Depreciation

10% Repair and

maintenance

5%

Share of the Total Operating Cost (TOC)

40 tons Tractor semitrailer combination Source: [Larsson, 2008]

Figure 3: Examples of cost breakdown to EU hauliers

Increasing the truck loading capacity would init ially reduce road haulage costs per tonne-km. As an example, McKinnon [McKinnon, 2005] repor ted that for the UK, the two historic weight limit increases from 38 tons to 40 tons (in 1999) and from 41 tons to 44 tons (in 2001) reduced road haulage costs by respectively 7% and 11%. Due to the much higher loading capacity (60 tons) offered by LHVs, cost reduc tions would probably ra nge between 20% and 30% compared to conventional 40 tons HDVs.

According to the ISI Fraunhofer study [ISI, 2008] , driver costs would decrease by one third while fuel costs would decrease by up to 25% if fully loaded. Oxera [Oxera, 2007] reported

that the introduction of LHVs would reduce cost per ton-km by 14.2% to 15.3% depending on

the scenario. A decrease cost in cost of around 23% was estimated for a 84-tonne truck.

Demand elasticities

Price demand elasticities i.e. the degree at wh ich demand reacts at changes in prices, are key parameters and need to be carefully addressed. Th ey are used to assess the impact of the price decrease expected from the introduction of LHVs on both road freight and non-road freight demand especially the rail sector which it wi ll mainly compete with, depending on the trip length. Therefore two types of de mand elasticities should be cons idered: the price elasticity of demand for road freight transport and the cro ss-elasticity for rail demand related to road freight price variation. A detaile d description of these two qu antities is given by [TML, 2008].11 It is essential to bear in mind that these parameters are usually integrated values since they depend on a wide number of variables:

)time... space, group, commodity length,trip( f Elasticity =

Road freight demand

There are many elasticity estimates available in literature leading to very different orders of magnitude, depending on the level of complex ity assumed. A review of freight demand elasticities was undertaken by Graham and Glaister [Graham, 2004]. It was underlined that:

• A limited number of studies focused on elas ticities for different trip length or have distinguished demand between frei ght transport (tonnage) and freight traffic (ton-km).

• Very different estimates were found across different commodities and for different geographical areas.

• Treatment of time and the distinction between long and short-run effects is rather vague.

• Road freight demand studies are relatively scarce.

Even if Graham and Glaister [Graham, 2004] conc luded that "it would be imprudent to offer a

firm conclusion about the order of magnitude of the pr ice elasticity of dema nd for road freight movement", their literature revi ewed provided a range of price elasticity estimates which is already a relevant source of in formation. It was estimated that the price elasticity given in literature range from -7.92 to 1.72, with a mean at -1.07. Two thirds of the estimates ranged from -0.5 to -1.3; 42% fall betw een -0.4 and -0.8 while only 13% of estimates were greater than -0.4 and 2% were positive. Overall, it wa s found that the price demand elasticity is likely to fall between -0.5 and -1.5, meaning that the elasticity is negativ e and rather elastic.

Cross-elasticity for rail demand

As in the case of road freight demand elastic ity, literature provides a wide range of crosselasticity values meaning that it is very difficult to get accurate and reliable data. The elasticity estimates are positive and typically range from 0.3 to 2 depending on the trip length and commodity type.

A brief literature review providing some ra nges of road demand elasticities and crosselasticities is given in Table 1 below:12 Reference Road freight elasticities Cross elasticities (rail) Comments [Quinet, 1994] [-0.9; -0.7] 1.3 Long distance
[UBA, 2007] 1.9 Assuming a 20% cost

reduction
[TRL, 2008] 0.29 [0.4-0.9] Rail bulk markets Assuming a 20% cost

reduction
[Oxera, 2007] -1.2 0.74 Tonne-km

SD: -1.06

SD: -0.58 SD: 0.11

SD: 0.08 Tonne-km

Tonne-volume Assuming a 5% cost

reduction [Beuthe, 2001]

LD: -1.31

LD: -0.63 LD: 0.67

SD: 0.14 Tonne-km

Tonne-volume Assuming a 5% cost

reduction
[Bonilla, 2008] -1.42 (foodstuffs) -1.75 (building materials) -0.43 (oil and coal) Tonne-km (for Denmark)

SD: -0.7 Tonne-km Setra f

LD: -1.0 Tonne-km
[TML, 2008] -0.416 (TRANSTOOLS model)

[-1.2; -0.3] (analytical approach) Tonne-volume

Tonne-km

[Graham, 2004] Typically [-1.5; -0.5] Range from literature review. But it highly depends on commodity groups, trip length, etc.

Table 1: Example of elasticity range estimates

Loading capacity

The loading rate of LHVs is doubtless the mo st important factor. The challenge is to maximise or at least optimise the payload of L HVs in order to get the maximum benefits from them (e.g. in terms of cost per ton- km or energy consumed per ton-km). With regard to energy efficiency, the UBA st udy [UBA, 2007] reported that the potential of LHVs to reduce fuel consumption per tonne load ed is highly dependent on the optimised use of loading capacity. As long as the payload is not clearly above 77% of the full capacity (i.e. corresponding to 40 pallets out of a maximum 52), the average fuel consumption per palletkm would be lower than for a fully loaded st andard HDV. This point will be discussed in chapter 4.

Moreover, it is difficult to get data about th e share of empty running on the total vehicle-km. This will depend on the distance travelled, the availability of backloads and the type of commodity transported. However, due to the economical disadvantages of running an empty LHV over long distances, one can expect that hau liers would optimise thei r routes in order to get maximum profit.

f See e.g. the position paper of the European Rail Infrastructure Managers (EIM) at: http://www.eimrail.org/documents/EI MStatementonLHVspresentation06082008_000.pdf13 There is debate about a potential minimum pa yload required for LHVs. A close monitoring of the payload of LHVs seems to be unavoidable (weight-based or volume-based measurements by means for instance of weigh-in-motion systems might be a solution).

External costs

Broadly speaking, external costs can be defined as costs that result from the transport users activity but affect the rest of the society.

External costs associated to heavy duty vehicl es are generally attri butable to accidents, congestion, infrastructure, noise and emissions (climate change and air pollution). The study carried out by Piecyk and McKinnon [Piecyk, 2007] reported the to tal external costs of heavy goods vehicles (HGVs) activity in the UK. The co st breakdown is shown in Figure 4. It was

found that 40% of the total extern al costs is due to congestion, 23% to infrastructure, 19% to traffic accidents, 15% to air pollution and greenhouse gas emissions and 2% to noise (note also that climate change costs would represent around 8% of the total ex ternal costs of road freight transport in the UK).

Figure 4: Total external costs of HDV activity in the UK

Source: [Piecyk, 2007]

Also, the INFRAS/IWW study [INFRAS, 2004] provi des data about the external costs related to road freight transport, for different years and at European level (EU15 + Switzerland and Norway). In this study, external costs are attrib utable to accidents, noise, air pollution, climate change, nature and landscape, urban effects, congestion and up/downstream processes.

There is limited literature analysing the impact of LHVs on external costs at European level. As a first order analysis, it is expected that L HVs would have lower external costs per ton-km compared to standard HDVs. This is discus sed by Piecyk and McKinnon [Piecyk, 2007]. But the equation is more complex since second orde r effects need to be taken into account.

In its study on the impact of LHVs on external costs of UK fr eight transport, Oxera [Oxera, 2007] concluded that although the introduction of LHVs would seem to reduce external costs, this benefit will be counterbalanced by taking in to account the switch of demand from rail to road, as discussed previously. They estimated that the additional road freight demand generated by LHVs will cost around £907 million per year, to be supported by the society. The results are presented in Table 2 below.14 Change Cost (£ million)

Switch from HDVs to LHVs -44

Switch from rail to road +71 Road freight generation +907 Net overall impact of LHVs +934

Table 2: Impact of LHVs on the external costs of UK freight transport

Source: [Oxera, 2007] (see also [UIC, 2008])

However, as underlined by Prof. McKinnon [M cKinnon, 2008], Oxera "give no indication of the likely source of this large amount of additiona l freight traffic. Its econometric analysis is detached from the real world of production and logistics management. There is strong counter evidence too to suggest that it grossly ex aggerates any traffic generation effect."15 

## 4 Monte-Carlo simulation

Based on the analysis above, a model following the structure described in Figure 2 was built.

The model covers most factors mentioned in lite rature that may affect the uptake and impact

of LHVs. Given that th e values for these factors differ significantly, the model developed

allows for the use of different combinations of assumptions, covering the full range of possible values given by the studies consulte d, literature, histori cal data and model projections.

An additional input to the analysis came fr om the projections of the TRANSTOOLS model (v. 1.7.4) for year 2020. The demand for freight tr ansport between all comb inations of origin and destination at NUTS 2 level (region) ac ross Europe was differentiated according to product group (following the NSTR 1-digit cl assification system used by TRANSTOOLS)

and distance band. Three distance bands were select ed in order to test the impact of different levels of uptake of LHVs depending on the dist ance. Accordingly, different elasticities were

used for each combination.

The main parameters, their range of values a nd the sources used to define their range are given in Table 3 below:

Parameter Mean Assumptions/comments

Cost decrease of

LHVs 20% Cost per tonne-kilometre would be reduced by 20-25% over long-haul runs (see e.g. [TML, 2008], [TRL, 2008], [UBA, 2007]).

5-30% is assumed as a consistent range for cost decrease (but it depends

of course on the load factor and distances). A normal distribution is

assumed with a mean of 20%.

Average payload 14 t (<800 km) 21 t (>800 km) Refers to average payload of HDVs. Range distribution has been adapted from literature.

Elasticity road (<800 km) From 0 to 50% of elasticity for

distances

between 800 and

1500 km As for the longer distances, but due to the uncertainty concerning the degree of competition with rail at shor ter distances lower values are used.

Elasticity road (800-1500 km) -0.8 In their literature review, Graham and Glaister [Graham, 2004] reported a mean of -1.07 which was obtained from values ranging from -7.92 and 1.72. Most of the estimates fall between -0.5 to -1.5 but this range should be somewhat extended e.g. from -0.3 to -2. Mean value estimated at -0.8. Distribution has been designed accordingly (see e.g. [Graham, 2004]).

Elasticity road very (>1500 km) -1.1 Same approach as above, except that the elasticities will be moved to higher estimates. One can assume the ra nge [-0.5; -2.2] with a mean value

fixed at -1.1. Distribution has been designed accordingly (see e.g. [Graham, 2004]).

Increase of payload per trip percentage
increase of current payload, ranging from

20% to 50% Payload of LHVs (depending on the configuration) can range from 0 (totally empty) to 38-40 tons (fully loaded). - For standard HDVs (i.e. tractor + se mi-trailer and truck semi-trailer), the maximum payload is around 24-26 tons (see e.g. [Aurell, 2007]). - For LHVs, the maximum payload can vary between 37.5 tons and 40 tons (see e.g. [Aurell, 2007]).16 Parameter Mean Assumptions/comments

A maximum additional payload of 50% is assumed (Note that in volume terms, LHVs can carry up to 160 m 3 instead of 101

m 3 i.e. more than 50%.)

Increased external cost per

veh-km 25% See e.g. the impact of LHVs on the external costs of UK freight transport [Oxera, 2007].

Share of LHVs

in total tons lifted (road) 2-15% (<800km) 10-40% (800- 1500 km) 5-75% (>1500 km) It is e.g. estimated that around 10% of the total long-haul fleet in Sweden are modular vehicles [CEDR, 2007]. Different shares are available from literature, but 5-10% seems to be a minimum for long haul trips. See also the ISI study [ISI, 2008].

Table 3: List of variables and their associ ated ranges assumed in the present study

The mean value for the average payload of conven tional trucks for year 2020 is assumed to be 14t for short distance trips and 21t for long dist ance trips. The range used in the Monte Carlo simulation was 11t to 17t and 16t to 26t resp ectively. Since the actual increase in payload does not depend only on the increase in capacity , a range between 20% and 50% was used. In order to take the share of LHVs into account, a normal distribution with a mean of 8%, 25%

and 50% was used for the three distance band s, assuming that the level of uptake would

increase with distance.

As regards elasticities, an importa nt reason for differences in the results of other studies, the present analysis uses the ones refe rring to original demand for freight , i.e. the tons lifted at the point of origin. It was considered that us ing the price elasticity of demand referring to transport performance, i.e. ton-km, can lead to distortions in the analysis by addressing an output indicator instead of the real demand. The range of values used was based on the values and probability distribution available from literature.

Distance band mean min max

< 800 km -0.21 -0.79 0

800 – 1500 km -0.83 -1.79 -0.31

> 1500 km -1.15 -2.44 -0.22

Table 4: Price elasticities per distance band (road transport, demand in tonnes)

The simulation results suggested that the degree of uptake of LHVs in the short distance band (<800 km) affects the overall results significantly , since their large scale introduction would imply an increase in the load factors for that distance band. This hypothesis has been discussed extensively in the literature and it s eems rather improbable that such a development is plausible. In order to remove the distortion of that assumption and to make the analysis comparable to the ISI study [ISI , 2008], an additional simulation was made assuming that the penetration of LHVs for short di stance trips would be 0% (i.e. a sub-scenario of the general simulation).17 

## 5 Simulation results

Given the increase in payload brought by LHVs, the number of vehicle-km needed to move the same volume of transport decreases in all combinations of penetration rates and elasticities. The simulation trials for year 2020 show an average decrease of 2.3% (although it ranges from close to 0% to over 4%) with tr ips over 1500 km being more affected (average decrease by 16.7%). The short distance trips ar e expected to have a decrease of 2% on average but, since they constitute the largest part of the trip, bring most benefits in absolute

terms.

The significant cost reductions would also attract traffic from other modes, especially rail. The exact volume of modal shift depends on th e reaction of the market in the various geographic and product market segments and aggregate approaches based on simple elasticities can obviously give just an indicati on. The range of results of the simulation does however suggest that LHVs can be very comp etitive towards railways , especially for long distance bands and for non-bulk products. On av erage, the simulations show a shift of 73.3 million tons lifted/year from rail to road, corresponding to 18.1 billion ton-km of transport volume per year. For railways that would repres ent a 2.1% decrease compar ed to its expected traffic in year 2020, while for road it would represent an increase of 0.6%. For long trip

distances the effect on rail can be even more negative though, with lo ses on average of 56%, reaching 100% in many trials of the simulation (that combine extreme values of elasticities and cost reductions from LHVs).

The overall share of LHVs in the fleet is e xpected to be 8.2% (mean value). This value depends on the assumptions concerning the upta ke in the various distance bands and the expected freight demand for each segment. Load factors would increase from 21 tons to 23.9 tons on average for trips over 1500 km, and from 14 tons to 14.4 tons for trips below 800 km.

The main benefit from the introduction of LHVs would be the decrease in transport costs as a result of higher payloads per truck. The average of the simula tion trials indicates potential savings of almost €3 billion/year, but with a high level of uncertainty caused by the underlying assumptions. Excluding trips below 800 km from the analysis gives a smaller -but less uncertain- figure of €500 million/year.

The environmental benefits of using fewer tr ucks -even though many would be bigger than they are today- are also impor tant. Accounting for higher extern al costs per km for LHVs, still gives a positive balance. On average it is estimated at about €400 million/year (€130 million/year if short distances are excluded).

There would be negative impacts as regards external costs though, as a result of the shift of traffic from other modes to road. Since trips wi th LHVs would replace tr ips with (cleaner and safer) rail, the external costs of the traffic shif ted would rise. On average this would amount to €313 million/year, a significant amount but still lower than the decrease in external cost brought by the reduction of trips.18 Figure 5: Comparison of costs and benefits

The net welfare impact of a large scale intr oduction in the EU woul d be positive in all possible combinations of values for the input variables. If the use of LHVs for all distance bands is assumed, the total net welfare would be €1.5 billion per year. However, the range of possible values would be very wide, from 0 in the case of minimal introduction to over €5

billion when the maximum level of LHVs for all distance bands is assumed.

The sensitivity analysis allows the identification of the variables that contribute most to the variance of the estimated total net welfare gain:19 Figure 6: Sensitivity analysis of the total net welfare gain

Three main messages can be found in the results of the sensitivity analysis:

• The net welfare gain has a high correlation with the level of uptake of LHVs. Since higher numbers of LHVs would imply higher savings in transport costs, maximizing the share of LHVs would be positive for th e economy as a whole. The maximum level however can not be set by policy makers, sin ce it is up to the market itself to find the optimum level. Most studies analysing the issue doubt the possibility of LHVs reaching high shares of the market since a small part only of shipments are of sufficient size to exploit the advantages of LHVs.

• The average increase in payload (in absolute terms, i.e. tonnes) is also an important factor, especially in the case of shorter trip s (<800 km). The reason for this is that the current average payload for such trips is very low and increasing it would lead to important transport cost savings. The same point though leads to a more pessimistic estimate of the potential uptake of LHVs for short distances: given that the actual fleet is used rather inefficiently for this distan ce band, shippers and operators will not have the incentive to use LHVs. This effect has been highlighted in some of the studies

reviewed and the results of the present analysis also s upport it. It is therefore proposed

to assume that the share of LHVs for shorter trips is assumed as minimal.

• The third important variable is the assume d increase of external costs of LHVs compared to conventional trucks on a per km basis. This affects the increase or20 decrease of environmental damage, accidents and infrastructure use costs from the change of the fleet mix but also the overall in crease in external costs from the shift of transport activity away from rail and inland waterways.

The above considerations imply that a more mo derate scenario for th e introduction of LHVs is most probable. Assuming that the share of LH Vs will be higher at higher distance bands the range of the expected imp acts would be the following:

Variable Unit Mean value Min Max

Share of LHVs in road freight 3.2% 0.5% 5%

Decrease in road transpor t activity veh*kms 2.3 billion

1.1% 0.4% 3.2 billion

1.6%

Increase in road transport volume Tonnes

lifted 33 million

0.15% 10 million

0.05% 50 million

0.30%

Decrease in rail transport activity Ton*kms 13 billion

1.5% 10 billion

1.2% 15 billion

1.8%

Decrease in external costs from more efficient shipments € 230 million 180 million 260 million

Increase in external costs from modal split € 230 million 130 million 300 million

Decrease of transport costs € 1.4 billion 500 million 2 billion

Net welfare gain € 700 million 200 million 1 billion

Table 5: Summary of results, LHV uptake depending on trip distance, year 2020

The mean values of the above table as regard s cost reductions and th e new average shipment

sizes that would result from the introductio n of LHVs were used as input for the TRANSTOOLS model (applying a road transpor t assignment for the revised O-D matrices that correspond to the distance bands and product groups affected). This allowed the identification of the main corridors where increased traffic of LHVs is expected. The following messages can be derived from the resulting map:

• Given the level of economic integration e xpected by year 2020, th e trade flows that can be served by LHVs are spread across Europe. There is a higher concentration in Germany, Belgium, the Netherlands and the UK, but several important corridors are

also visible in other Member States.

• The areas where these corridors belong to will benefit from the decreased traffic and congestion levels resulting from the replac ement of conventional trucks with LHVs. They would also bear though the costs of improving the design characteristics of infrastructure where necessary in order to accommodate the special requirements of LHVs. However, the benefits of decreased transport costs will be enjoyed by users and consumers and the origin and de stination of the shipments.

• The corridors where rail will lose traffic coin cide to a large extent with the main LHV

corridors.21 • It is assumed that LHVs will be allowe d for all trade inside the EU and with neighbouring partners. Opt-outs by some member states or prohibition by some trading partners would probabl y change the picture significa ntly. In a similar fashion, different charging schemes for LHVs c ould lead to additional distortions.

• The impact on combined transport and espe cially Ro-Ro is unclear. It depends on several factors, including organisational issu es of road and other mode operators, as well as on pricing policies.

Figure 7: Expected main corri dors of LHV traffic, TRANSTOOLS results for year 202022 

## 6 Limiting the external impact

From the economic point of view, there seems to be a consensus concerning the benefits that LHVs can bring for operators and the econ omy as a whole. Even though there is no conclusive evidence concerning the external im pacts of LHVs on a vehi cle basis, the results of the present analysis imply that at aggregate level the net impact would be positive: the total external cost of freight transport would decr ease. However, some of the studies reviewed identify potential problems raised by the intro duction of LHVs that in most cases concern their external impacts.

The question of the impact on CO 2 emissions from transport was highlighted in the ISI report [ISI, 2008]. Even though a reduction of emissions is expected as a result of the improvement of the efficiency in road transport in the shor t-term, the study warns that in the medium term

the effect on modal shift may lead to a rebound and even an increase in total CO 2 emissions. Our analysis elaborated on the factors that influence the net balance. There is naturally

consensus on the fact that LHVs would still em it more than rail per ton of goods transported

and that modal shift from rail to road would le ad to an increase of emissions. However, our simulations for the long term (2020) suggest that the main benefits of LHVs –and their main market- would come from the replacement of conventional trucks and the reduction of

emissions as a result of fewer conventional truc ks on the road clearly outweighs the increase as a result of modal split. Additionally, two m easures could ensure that the impact from

modal shift is limited:

• Introducing a minimum load for LHVs: improvi ng the degree of utilization of loading capacity tends to limit the increase in emi ssions from modal shift. The Monte-Carlo simulations suggest that setting a minimum of 70% of loading capacity would limit

the increase in CO 2 emissions and other externalities significantly 7

.

• Internalizing the real extern al cost of LHVs through a su itable vignette/charge: the "right price" for LHVs would help optimize their use. The shift from rail to road

would be moderated as a resu lt, while operators would have an additional stimulus to opt for more efficient solutions in the use of LHVs.

The second main area for concern raised in so me studies seems to be the need to adapt infrastructure for the use of LHVs, mainly as regards road surface, bridges, geometric design and parking areas. The current de finition of LHVs is broad e nough to allow for a wide range of possible vehicle setups, each having different weight and length combinations. Estimates on the total cost of infrastructure for specific ro ad segments or the system as a whole are as a

result difficult to make. There are however certain factors that can be controlled and/or

standardized in order to minimize the external cost of infrastructure use, most notably the maximum allowable weight per axle. Although the findings from theory and laboratory experiments do not yet allow for a clear answer , it seems that several designs of LHVs can actually decrease surf ace wear. Where technical solu tions are not enough to limit the externalities and their cost, it is important to design suitable schemes that would allow the providers of infrastructure to recover the invest ments needed or the costs incurred as a result

of LHVs.

7 Such a measure is technically feasible, but would entail control measures that would increase the costs of LHVs

and should be also taken into account . Additionally, if such a measure is applied for LHVs, the applicability and impact of a similar measure for conventional trucks as a means of incr easing efficiency would also need to be

addressed.23 

## 7 Designing specific policy measures

The impact of LHVs depends to a large extent on the conditi ons under which they will be introduced. Although the economic impact is in principle expected to be positive and environmental consequences would be limited in most cases, a complete impact assessment can be performed only when specific policy meas ures for their introduction are available.

This analysis can serve as a preliminary comp arison of the range of costs and benefits of LHVs. The results suggest that the efficiency gains brought by LHVs are significant and that, overall, the impacts on welfare are positive. It also identified the areas of uncertainty, as well as technical and economic aspect s that influence the final impact. These aspects can form the basis for the design of more detailed policy measures that aim at improving the expected result and the acceptability of LHVs. The main el ements of such policy measures that have been revealed from the present analysis are:

• Geographical coverage: expected costs and benefits may va ry significantly depending on the economic structure, transport industry conditions or geographic position of each EU member state. It can be expected that some member states may wish to opt out

from the introduction of LHVs. The overall bene fits for the EU would be different in that case and the efficiency of the measure would probably be lower.

• LHV typology: the introduction of specific type s of LHVs can be considered to serve specific market requirements. For example, the cases of two-vehicle combinations weighing up to 44 tonnes on 5 axles, or 48 tonnes on 6 axles, or vehicles that can accommodate 45ft containers can be specifically analysed.

• Efficiency/utilization standards: tec hnological solutions such as aerodynamic improvements or utilisation requirements such as minimum load limit can be enforced in order to limit fuel consumption and emissions.

• Internalisation measures: the level of internal isation of the external cost of LHVs and the schemes to allow infrastructure provide rs to recover their costs would influence the uptake of LHVs by the market and equity in the distribution of costs and benefits.

• Infrastructure requirements: the typology of LHVs that would be allowed to be used would influence the requirements for infr astructure, ranging from the geometric design of roads to parking and refuelling areas. In case a design that cannot be served by the current networks EU-wide is select ed, the usable road network would be limited and- as a result- both the uptake a nd the benefits of LHVs would be reduced.

• Efficiency in logistics and distribution: Apart from the improvement of transport operations, the introduction of L HVs can also influence the e fficiency of operations in either end of the road trip as a result of the changes in shipment size and frequency.

The direction and the order of magnitude of the impact is, however, rather unclear.

The results of the simulations suggest that the success of the introduction of LHVs depends to a large extent on the degree of substitution of c onventional trucks with LHVs. As long as the price signals are correct, LHVs should increase the overall efficiency of the transport system and the net impact would be positive.24 

## 8 Conclusions

The analysis presented here explored the range of potential impacts using the rationale and the assumptions of several studies that have analysed the issue extensively. The objective was neither to forecast the precise sh are of LHVs in the future, nor to provide an exact evaluation of their impact. Instead, the analysis aimed to address the uncertainty in the technical and economic aspects of LHVs and derive so me policy relevant messages through the

identification of the main factors th at influence the potential impacts.

The main conclusion of the analysis is that th e introduction of LHVs w ould be beneficial for the EU economy and -under certain conditions- environment and society as a whole. LHVs can increase the efficiency of the EU transpor t system and reduce friction. From an EU policy point of view, facilitating the introduction of LHVs is in line with the objectives of the Common Transport Policy and would help impr ove the internal market. Naturally, improving road transport would worsen the competitive position of other modes, but a balance can be found through investments and improvements in the other modes as well. Limiting the use of LHVs to specific member states or corridor s would pose practical obstacles and greatly reduce the uptake and positive impacts of LHVs.

LHVs would bring important efficiency impr ovements but their exte nt is limited by the inefficiency of the structure and profile of the freight market. Since the actual loading capacity of conventional trucks is under-utilise d, LHVs would currently have an impact on specific market segments of high value goods, la rge shipment sizes and long trip distances. Combining their introduction wi th measures to improve overa ll transport and logistics efficiency would lead to additional positive results.

Improving the efficiency of the road sector would obviously worsen the competitive position of other modes, especially rail transport. Since LHVs –as road transport in general- does not compare favourably with rail, a shift from rail to road would result in an increase of the external cost of the part of the transport ac tivity that would be shifted. As long as LHVs replace a sufficient number of conventional trucks though, the over all impact in both economic and environmental terms would still be positive.

The positive impact of LHVs can be increased through measures that maximise efficiency gains and minimise the external costs:

• Improvements in vehicle design to reduce fuel consumption, environmental damage

and accident risks.

• Enforcement of minimum load limits and/or maximum percentage of empty trips.

• Standardisation of vehicl e sizes and loading units.

• Suitable charging systems to internalise ex ternal costs and minimize the impact on

other modes.

• Common infrastructure design specifications for Trans-European Transport Networks.25 

## ANNEX I - Probability distributions of input variables2627 

## ANNEX II – Probability distributio ns of forecast variables (results)28293031 

## ANNEX III – Sensitivity test s for main forecasts323334 

## 9 References

[Arcadis, 2006] Monitoringsonderzoek vervolgpro ef lzv resultaten van de vervolgproef met langere of langere en zwaardere voertu igcombinaties op de Nederlandse wegen, ARCADIS, May 2006 (report in Dutch, su mmary and results available in English).

[Aurell, 2007] Aurell, J., Wadm an, T., Vehicle combinations based on the modular concept,

Committee 54: Vehicles and Trans ports, Report 1/2007, Nordic Road Association, 2007.

[Bast, 2006] Effects of new vehicle concepts on the infrastructure of the federal truck road network, Final Report, Federal Highway Research Institute (Bast), November 2006 (abstract available at http://www.bast.de ).

[Beuthe, 2001] Beuthe, M., Jourqu in, B., Geerts, J-F., Ha, C., Fr eight transportation demand elasticities: a geographic multimodal transportation network analysis, Transportation Research Part E, 37, pp.253-266, 2001.

[Bonilla, 2008] Bonilla, D., Salling, K., Energy Consumption And Truck Freight Transport Demand: Is Denmark a special case? Work in progress, 2008.

[CEDR, 2007] Rapport sur les véhicules de 60-t, Conference of European Directors of Roads CEDR, October 2007.

[FM, 2008] Reducing Greenhouse Gas Emissions from Heavy-Duty Vehicles, The Role of the European Commission, Interim Report 1, Initial Review of Measures and Policies, Fauber Maunsell, March 2008.

[Graham, 2004] Graham, D., J., Glaister, S., Road Traffic Demand Elasticity Estimates: A Review, Transport Reviews, Vol. 24, 3, pp. 261-274, 2004.

[INFRAS, 2004] External Costs of Transpor t –Update Study, INFRAS/IWW, Final Report, Zurich/Karlsruhe, October 2004.

[ISI, 2008] Long-term Climate Impacts of the Introduction of Mega-Tru cks, ISI Fraunhofer study for the Community of European Railway and Infrastructure Companies (CER), final draft report, July 2008.

[Larsson, 2008] Larsson presentati on at IEA Workshop New Ener gy Indicators for Transport: The Way Forward, 28-29 January 2008, Paris.

[McKinnon, 2005] McKinnon, A., C., The economic a nd environmental benefits of increasing maximum truck weight: the British experien ce, Transportation Research Part D, Vol.10, pp. 77-95, 2005.

[McKinnon, 2008] McKinnon, A., C., Should the Maxi mum Length and Weight of Trucks beIncreased? A Review of European Resarch, Logistics Research Centre, HeriotWatt University, Edinburgh, 2008.

http://www.sml.hw.ac.uk/logistics/downloads/l hvstudy/McKinnon%20-%20LHV%20paper%20- %20final%20-%20ISL%20conference%202008.pdf35 [Oxera, 2007] The road, rail and extern al impacts of LHVs, Oxera, May 2007.

[Piecyk, 2007] Piecyk, M., McKinnon, A., C., Inte rnalising the Extern al Costs of Road Freight Transport in the UK, Heri ot-Watt University, November 2007.
http://www.greenlogistics.org/Site Resources/1fbb59ff-3e5a-4011-a41e18deb8c07fcd_Internalisation%20report%20(final).pdf

[TML, 2008] Transport and Mobility Leuven, Eff ects of adapting the rules on weights and dimensions of heavy commercial vehicl es as established within Directive 96/53/EC, TML final report for DG TREN, November 2008.

[TRL, 2008] Knight, I., Newton, W., McKinnon, A. et al., Longe r and/or Longer and Heavier Goods Vehicles (LHVs) – a Study of the Li kely Effects if Permitted in the UK: Final Report, TRL study for the UK DfT, June 2008.

[UBA, 2007] Longer and Heavier on German Ro ads. Do Megatrucks Contribute Towards Sustainable Transports? Umwelt Bundes Amt (UBA), August, 2007.
http://www.umweltbundesamt.de/uba-info-pre sse-e/hintergrund/riesenlkw-englisch.pdf

[UIC, 2008] Mega-Truckss versus Rail freight? What the admission of LHVs would really mean for Europe, brochure from th e rail freight and rail community organisations, July 2008.

[VTI, 2008] Vierth, I., Berell, H., McDaniel, J., Haraldsson, M., Hammarström, U., Yahya, M-R., Lindberg, G., Carlsson, A., Ögren, M ., Björketun, U., The effects of long and heavy trucks on the transport syst em, Report on a government assignment, VTI Report, 2008.
http://www.vti.se/EPiBrow ser/Publikationer%20-%20English/R605A.pdf36 European Commission

EUR 23933 EN – Joint Research Centre – Institute for Prospective Technological Studies Title: Longer and heavier vehi cles for freight transport Authors: Panayotis Christidis, Guillaume Leduc Luxembourg: Office for Official Publications of the European Communities

2009

EUR – Scientific and Technical Research series – ISSN 1018-5593
ISBN 978-92-79-12790-8
DOI 10.2791/12276

Abstract

The European Commission is considering the implications of allowing the use of LHVs, vehicles measuring up to 25.25 m and weighing up to 60 tons, for the whole of the European Union transport system. The introduction of such trucks on the European road network will gene rate environmental impacts, safety and infrastructure

costs.
<br> The present study aims at carrying out an uncertainty an alysis of the technical and economic aspects of LHVs based on assumptions and results ranges taken from r ecent literature. The results suggest that the potential impacts of the introduction of LHVs at EU level can be positive –under certain conditions- in both economic and environmental terms. The increased payloads per vehicl e are expected to reduce tr ansport costs and lead to significant savings for operators, industry and consumers. Since fewer trucks would be required to transport the same volume of trade, the environmental and other external costs of freight transport would also be lower, even though an individual LHV consumes and pollutes more than a conventional truck. An analysis of the potential benefits to the economy and the society as a whole has been carried out.

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