Work Package 4 report____________________________________________________________
Date Issued: Author: Version: Status:
6 December 2005 Wermeskerken B. Van V 0.81 Final
Project Remove Work Package 4
Table of content
Revisions ........................................................................................................................................................ 1 1. Introduction................................................................................................................................... 2 1.1. Scope of problem caused by overloaded vehicles ............................................................... 2 1.2. Interaction with other work packages .................................................................................... 3 1.3. Reading guide .............................................................................................................................. 3 2. General approach ........................................................................................................................ 4 2.1. Costs .............................................................................................................................................. 4 2.2. Benefits ......................................................................................................................................... 5 2.3. Cost-Benefit Analysis ................................................................................................................. 5 2.4. Summary ...................................................................................................................................... 6 3. Boundary conditions................................................................................................................... 7 3.1. Research data .............................................................................................................................. 7 3.2. Costs .............................................................................................................................................. 7 3.3. Benefits ......................................................................................................................................... 7 3.4. Extrapolation of regional figures.............................................................................................. 8 3.5. Additional boundary conditions................................................................................................ 8 3.6. Sources of research data........................................................................................................... 8 4. Effectiveness and efficiency of enforcement ........................................................................... 10 4.1. Effectiveness of enforcement ................................................................................................. 10 4.2. Available research..................................................................................................................... 10 4.3. Efficiency of enforcement........................................................................................................ 11 5. Enforcement scenarios ............................................................................................................ 12 5.1. Considered scenarios ............................................................................................................... 12 5.2. Costs and efficiency of enforcement..................................................................................... 13 6. Damage to infrastructure....................................................................................................... 19 6.1. Damage to road pavement ..................................................................................................... 19 6.2. Damage to bridges ................................................................................................................... 21 6.3. Damage to road pavement on a European level................................................................ 21 7. Road safety .................................................................................................................................. 23 7.1. Reduced traffic safety because of overloading ................................................................... 23 7.2. Reduced traffic safety because of other safety deficiencies ............................................ 25 7.3. Reduced traffic safety due to road damage ........................................................................ 25 8. Unfair competition .................................................................................................................... 26 8.1. Gross vehicle loading ............................................................................................................... 26 8.2. Axle loading................................................................................................................................ 27 8.3. General effects of enforcement.............................................................................................. 27 9. Cost-Benefit Analysis ............................................................................................................... 29 9.1. Benefits of overloading enforcement .................................................................................... 29 9.2. Costs of overloading enforcement......................................................................................... 30 10. Conclusions and recommendations.................................................................................... 31 10.1. Conclusions ............................................................................................................................ 31 10.2. Recommendations ................................................................................................................ 31 Bibliography................................................................................................................................................. 32
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Revisions rev.
date
main changes
comments by
0.1
Jan 2005
Document outline
B. van Wermeskerken, F.J. van Loo
0.2
Apr 2005
First complete document
B. van Wermeskerken, F.J. van Loo
0.3
May 2005
0.4
Jun 2005
Comments of WP-4 members incorporated in the report
Andy Rooke
0.5
Aug 2005
Comments of Andy Rooke incorporated. Additional references added.
B. van Wermeskerken
0.6
Sept 2005
Finalising Recommendations and Conclusions
B. van Wermeskerken
0.7
Sept 2005
Comments and review.
Caroline Shipp/Andy Rooke
0.8
Dec 2005
Response on comments, pictures
Bastiaan van Wermeskerken
0.81
Dec 2005
Estimate unfair competition
Bastiaan van Wermeskerken
All members of REMOVE Work package 4
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1.
Introduction
This report describes the results of work package 4 of the REMOVE project, the CostBenefit Analysis. A Cost-Benefit Analysis is an important tool in the process of building political awareness regarding the advantages of the use of WIM as a tool to obtain higher compliance to legal load limits. Furthermore, Cost-Benefit Analyses are believed to become integral to the preparation of a business case of future WIM systems. Originally, WP4 was split in two parts. The first part focused on the negative effects of overloading, for example the fact that overloaded Large Goods Vehicles (LGV’s) poses a threat to road safety, and causes damage the Trans European Road Network (TERN). The second part made a comparison between the cost of advanced enforcement of offences of overloading, using WIM systems, on the one hand and the cost of the traditional enforcement methods on the other. This report combines these two parts into one Cost-Benefit Analysis. It must be stressed that the two parts of the project have not carried out new scientific studies; all calculations are based on existing research. Should a comprehensive CostBenefit Analysis of the enforcement of overloaded vehicles be required, it would require a full European project in its own right. For Project REMOVE the Cost-Benefit Analysis ‘only’ has a supporting role in the project itself, a limited level of resources were allocated as the project team felt that the level of effort required would detract from the other areas of work being undertaken. As a result of that this work package has only considered the costs and benefits at a high level.
1.1. Scope of problem caused by overloaded vehicles The reasons behind the overloading of goods vehicles may vary. In the first instance a transport company may be overload their vehicles with the intention of achieving an economic advantage when compared to other transport companies that obey the rules. Secondly, overloading may also take place unintentionally, for example in the case of a transport company is not aware of the overloading problem or when the transport company is not in a position to influence the real load, this may be particularly so when considering container transport. It is recognised that there are a number of problems caused by overloaded vehicles. A well documented problem is that of the considerable damage caused to the road pavement and other road infrastructure, to include bridges and tunnels. It is due to the use of the European road network by goods vehicles, but most particularly overloaded large goods vehicles that the road infrastructure deteriorates faster than planned, which ultimately leads to an increase in maintenance costs and/or a decrease in the expected life span of the roads and associated infrastructure. Other issues which are caused by the movement of overloaded large goods vehicles is the reduction in road safety to other road users, combined with the phenomenon of unfair competition which emerges within the transport industry when overloading becomes the norm. Despite the fact that these two issues are addressed less frequently within currently available literature, they may in fact be considered more important than the abovementioned damage to infrastructure. Overloaded large goods vehicles put pressure on road safety because of their reduced vehicle handling characteristics which makes them more likely to be involved in accidents, with the possible result of more severe injuries because of their higher vehicle mass. The issue of unfair competition is rather more straightforward, by overloading goods vehicles, particularly large goods vehicles less trips are needed to transport a load,
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which reduces costs, and leads to an economic advantage being gained over companies that transport goods within the legal limits.
1.2. Interaction with other work packages There is within the REMOVE project a strong relationship between all work packages. For WP-4 the strongest relationship exists with work package 3, Operational Issues, which deals with the different applications of Weigh-in-Motion for enforcement. These applications are the basis for the scenarios considered in WP-4. Furthermore the work prepared in the future strategy describes how the different enforcement applications can be best used in cooperation with each other, each covering a specific part of the overloading problem. The enforcement scenarios considered by WP-4 were developed in anticipation of the principles in the proposed future strategy.
1.3. Reading guide Chapter 2 describes the general approach of the work done in this work package. The boundary conditions limiting the approach and the scope are more precisely described in chapter 3. The efficiency and effectiveness of the different enforcement scenarios are discussed in chapter 4. Chapter 5 describes the enforcement scenarios that are considered and the costs that are involved for each scenario. Chapter 6, 7 and 8 describe the benefits which would result from a reduction in overloading, and respectively the damage to infrastructure, increased road safety and the reduction of unfair competition. Finally, in chapter 10 conclusions and recommendations are presented.
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2.
General approach
Weigh-in-motion is a tool that can be used in order to increase the compliance by goods vehicles with vehicle loading regulations and weight restrictions. The use of WIM as a tool can be used in several applications/scenarios, which are described in detail in the REMOVE report “Applications Terms Utilized in Vehicle Weighing” [@ref]. The possible applications/scenarios are: Manual Selection, Statistics & Planning, Pre-selection, Problem Solving, Direct Enforcement, and Intelligence & Wider Applications. For each scenario a separate Cost-Benefit analysis can be presented. However due to the limitation of time, and available information it has only been possible for an explicit Cost-Benefit Analysis to be prepared for some of the scenarios. Nevertheless, by discussing only the limited set of scenarios a good indication has been given of the cost and benefit aspects that could result from the other applications. A general flowchart for a single Cost-Benefit Analysis is shown in Figure 1. The costs and the benefits are determined in separate branches, which function as the input for the final Cost-Benefit Analysis.
scenario
costs
benefits
cost benefit analysis Figure 1 – general flowchart Cost-Benefit Analysis
It is important to note that one WIM-system can be used for more than one different enforcement applications at the same time. This means that in these cases the costs should be divided by the number of applications that are being used.
2.1. Costs The branch where costs are involved in a scenario is relatively straightforward; one would consider both fixed costs and variable costs. The following actual costs are considered: Purchasing cost of the measurement equipment (e.g. static scales or weigh in motion);
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Ongoing maintenance costs of measurement equipment and the measurement site; Supporting equipment (e.g. cars and administrative systems); Depreciation of measurement equipment and supporting equipment; Cost of man hours (e.g. the time spent by the people carrying out the enforcement strategy);
2.2. Benefits The branch which considers the benefits which result from an increase in compliance with the rules is more complex. Basically it can be split into two separate parts: The effect of the enforcement, and The effects of overloading. The effect of an enforcement scenario is the effect that all enforcement efforts within that scenario have on the amount of overloading. These effects can be on the number of overloaded axles/vehicles, on the severity of the overloading or on both. The negative effects of overloading can be divided into the damage to infrastructure, reduction in road safety and unfair competition. Any reduction of the negative effects, due to a reduction of overloading by compliance, will result in a benefit. The benefit branch from the scenario to the considered benefits is shown in the flowchart Figure 2, below;
scenario
efficiency of enforcement
decrease overloaded vehicles
reduction increase damage to road infrastructure safety
reduction unfair competition
Figure 2 – benefits flowchart
2.3. Cost-Benefit Analysis Preferably, both the costs and benefits should be expressed in a monetary value, so that comparing advantages and disadvantages becomes a rather more straightforward calculation. However, because WP-4 is restricted to existing research, comparing in such
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manner can only be done when research expressing costs and benefits in a monetary value is available. In the case where such research does not exist, any Cost-Benefit Analysis has been restricted to a general discussion. It showed that the effects of overloading on traffic safety and on unfair competition were not available in a monetary value. Here only a discussion is given of the principles that apply.
2.4. Summary Work package 4 of the REMOVE-project has carried out a number of Cost-Benefit Analyses. Each analysis has compared the cost of an enforcement strategy (scenario) with the expected benefits, this is visualised in Figure 3, below. The white blocks correspond to the topics on which WP-4 has collected as much research data as possible, costs and benefits, which have then been applied to each scenario shown in chapter 5. After gathering the research data, the Cost-Benefit Analyses have been carried out either as calculations or general discussions.
scenario
efficiency of enforcement
decrease overloaded vehicles
costs
reduction increase damage to road infrastructure safety
reduction unfair competition
cost benefit analysis
costs
benefits Figure 3 – Cost-Benefit Analysis total flowchart
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3.
Boundary conditions
The area of Cost-Benefit Analysis has ‘only’ a supporting role within the REMOVE project, therefore the work for WP-4 has been rather limited. This chapter explicitly states the boundary conditions that have been applied. In addition information is also given on the sources that have been used in the process of collecting research data.
3.1. Research data In this area only existing research data has been used. Some basic figures were collected from EU member states by the project using the Questionnaire this was carried out in WP1, but covers all work packages, However in the main most of the research data has been provided by the members of the REMOVE project themselves. The research that has been used in the project has the following origins: Enforcement costs – The Netherlands and Germany; Effectiveness of enforcement – The Netherlands; Efficiency of enforcement – no figures available; Damage to infrastructure – The Netherlands, USA; Road safety – UK, USA; Unfair competition – no figures available.
3.2. Costs The only costs that have been considered are the direct cost of enforcement: Purchasing cost of measurement equipment (e.g. static scales or weigh in motion); Ongoing maintenance costs of measurement equipment and the measurement site; Supporting equipment (e.g. cars and administrative systems); Depreciation of the measurement equipment and supporting equipment; Cost of man hours (e.g. the time spent by the people carrying out the enforcement strategy); The only depreciation calculated for is that depreciation caused by the limited lifespan of the equipment. Depreciation caused by technical progression leading to cheaper equipment has not been accounted for. This can be justified because of the limited lifespan of measurement equipment (5 to 10 years). The incomes from fines, as well as the cost for the judicial chain are not considered because the main goal of enforcement is to achieve higher compliance to legal load limits, and not to collect fines.
3.3. Benefits A large goods vehicle can be overloaded in different ways: Axle overloading – one or more axles or axle combinations are beyond the legal limit; Total weight overloading – the total weight of the truck is beyond the legal total weight limit; Trailer weight overloading – the weight of the trailer is beyond the legal limit, considering the pulling truck. Overloading of the king pin (i.e. putting too much pressure on the hinge construction between truck and semi-trailer) Overloading results in several negative effects, however by reducing those negative effects, by achieving a decrease in overloading this produces a (relative) benefit. Only the following effects have been considered:
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Road safety – Overloading increases braking distance and manoeuvrability of an LGV, thus posing an additional threat to road safety. Unfair competition – Companies that overload have an economical advantage over companies that obey the rules, which is a form of unfair competition Damage to infrastructure – With increased axle load(s), the damage to infrastructure increases exponentially, in other words overloading directly leads to excessive damage to infrastructure. Overloading comprises two parameters: the overall number of over overweight vehicles/axles and the amount of overloading per vehicle. When referring to the reduction of overloading, a reduction of one or both of these parameters is intended.
3.4. Extrapolation of regional figures The only real European figures that were available for the REMOVE project to consider were the costs of enforcement and the damage to infrastructure from The Netherlands. Within the limitations of the project, the only way to calculate figures on a European scale was by extrapolating these regional figures. Pavement damage caused by overloading depends strongly on the type of road surface, (asphalt v. concrete). Without knowledge of the proportion of asphalt roads and concrete roads within the total road network, it is unwise to extrapolate regional figures using the road network lengths of each member state. Therefore this extrapolation is achieved by comparing the road maintenance budget of all member states. Unfortunately this extrapolation results in some uncertainty within the overall figures, and this uncertainty will be noted in the report. Note: The extrapolation also cannot be done by comparing the LGV fleet of each member state, because the movements of each fleet are not confined to its own country. As an example Austria may have a small vehicle fleet but might have a serious overloading problem. Due to the central location in Europe a lot of potentially overloaded vehicles may cross this country, independent of Austria’s own LGV fleet.
3.5. Additional boundary conditions In order to compare different enforcement scenarios, as far as possible the same circumstances are assumed for each scenario. This means that within the calculations on targeted enforcement scenarios, the scenarios are mapped on the same road with the same supply of overloaded vehicles. All scenarios are considered to be implemented under ‘ideal’ circumstances, e.g. a constant and sufficient supply of overloaded vehicles without the problem of overloaded vehicles avoiding checks after a certain amount of time. How the problem of avoidance is dealt with, is discussed in work package 3. (ref. @ Future Strategy) The time period considered in the Cost-Benefit Analysis is sufficient to write off the purchasing cost of the measurement equipment. Currency inflation is incorporated into the considered research data. All prices are recalculated on price levels within the year 1999, because most of the available data comes from 1999. Currency inflation is neglected in the Cost-Benefit Analysis, i.e. the cost and the benefits increase with the same factor over the considered years.
3.6. Sources of research data Except for the project members, the following sources have been addressed: EU member states by means of the questionnaire in WP-1; FERHL (Forum of European National Highway Research Laboratories, EU) IRU (International Road Transport Union, EU) CORDIS (Community Research & Development Information Service, EU)
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Euro Stat website (EU) ERF (European Union Road Federation, EU) Long-Term Pavement Performance program website (US)
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4.
Effectiveness and efficiency of enforcement
4.1. Effectiveness of enforcement An estimate of the effect of the enforcement scenarios is a critical element of the benefit branch, of the total Cost-Benefit Analysis, see figure 3. In other words, what effect does enforcement activity have on the issue of overloaded large goods vehicles? Four aspects are important: Factors other than enforcement that influence and determine compliance by transport companies to keep to legal load limits. For instance, during an economic recession extra pressure is placed on the profit margins of transport companies, therefore lower profit margins increase the temptation to overload their vehicles. Such factors should be considered as well, before the effect of a certain enforcement scenario can be concluded. Type of transport that is overloaded – International transport takes place every day of the year, therefore as most of the overloading on a certain road is caused by international transport, an automated enforcement may be very effective. On the other hand when most of the overloading is caused by transport related to a temporary construction site, or seasonal harvest campaigns, an automated enforcement might not be effective at all, given that consideration for its complete lifetime, in this case manual enforcement controls may be more appropriate. Geographical range of a weight check-point – This is the area of a road network where the effects of enforcement activities at a checkpoint can be realised. The geographical range is limited by the possibility to avoid a control location. Foe example on a very dense road network (a main road network with many entrances and exits or an extensive provincial road network) there may be many possible ways for vehicles to avoid overload controls. Where it is easy to avoid the checkpoint, the effect of the enforcing applications will be small. For applications that do not primarily focus on enforcement, such as Company Profiling, avoidance will be less significant because these applications focus on the complete route of the goods vehicle. Motivations for overloading – Different groups of people have different reasons to break the rules. There are three specific groups defined in [kagan&scholz]: Amoral calculators – group of people deliberately offending against the law to gain economical benefits; Political citizen – group of people willing to comply with the law, as long as the law seems reasonable; Organisationally incompetent – group of people who are willing to obey the law, but fail because of the lack of proper knowledge or unsound organisation structure. It becomes obvious that enforcement is most effective when it fits the reasons for overloading, e.g. the amoral calculators are would be most effectively dealt with by repressive enforcement, whereas for the other groups education and problem solving may seem most appropriate. When considering the toolbox analogy within the different available WIM applications, the highest compliance is likely to be achieved by using WIM tools that fit the specific group being targeted.
4.2. Available research It has proved very difficult to find authoritative research data or operational data on the effectiveness of overloading controls within the European Union. There are however two main issues: The loading of the heavy goods vehicles is not monitored in a structured and harmonised way, or not at all. Overloading controls tend to have a very local effect, with the amount of overloaded vehicles on a certain road dropping dramatically during a control. The first point may suggest that member states do not accord enough importance to the issue of overloaded vehicles.
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The second point is vital when trying to derive representative statistical information for a member state. Nevertheless, some general information on the effectiveness of overloading controls is available from the WIM-NL project in the Netherlands. This project started in 1998 and aimed to reduce the numbers of overloaded goods vehicles on the main road network by 75%, although there has been no specific time span set in which to achieve this reduction. A concept evaluation report states that the transport industry has responded to the WIM-NL project with several measures. For example [wim-vid]: Increase in vehicles with integrated axle load measurement devices; Increase in (extra) axles on vehicles; Load limiting measuring equipment, such as a balloon in tankers. Purchase of static weighs bridge by transport companies; General raising in awareness of the issue of overloading; Direct enforcing WIM-systems work 24 hours a day, their effectiveness may be comparable to other enforcement systems that also work 24 hours a day, such as fixed location speed controls that measure the average speed over several kilometres. These speed controls are located on several highways in the Netherlands, and the Agency for Traffic Enforcement of the Public Prosecutor (Bureau Verkeershandhaving Openbaar Ministerie, BVOM) in the Netherlands reports a decrease in speed violations from 10% to below 2% when these speed control systems are applied. Given these facts there is no reason to believe that direct enforcement using WIM-systems would not result in a similar result. There is no reason why the ‘predicted’ figures for direct enforcement using WIM-systems should not have the same magnitude of effect.
4.3. Efficiency of enforcement Due to the fact that the amount of research data or operational data on the effectiveness of enforcement is very limited, an alternative solution has been chosen: this is the calculation of the efficiency of enforcement. The calculation of the efficiency of enforcement enables the comparison to be made between different scenarios however it has two major limitations: There is no direct link between the costs of an enforcement scenario and the benefits achieved from less overloading. This means that there is a ‘gap’ in the benefits branch, of the total cost benefits analysis flow chart, therefore the cost benefit circle cannot be closed, see figure 3 above. Scenarios are compared in terms of “enforcement cost per penalty”, therefore only targeted enforcement scenarios can be compared, i.e. Manual selection, Pre-selection and Direct enforcement. When in addition to the calculation of the efficiency of the enforcement, the costs of overloading in relation to damage to the infrastructure, reduction in traffic safety, and unfair competition can be calculated, the gap can be minimised. In this way an indication can be given of the amount of money that can be earned when overloading is reduced. However it was found that it was impossible to calculate the costs in relation to traffic safety and unfair competition (see chapter 7 and 8).
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5.
Enforcement scenarios
The enforcement scenarios mentioned in this chapter are based on the enforcement applications described in detail in the REMOVE report “Applications Terms Utilized in Vehicle Weighing”. The possible applications/scenarios are: Manual Selection, Planning & Statistics, Pre-selection, Problem Solving, Direct Enforcement and Intelligence. A scenario can be defined as the way an enforcement application is realised in daily practice. The scenarios that are considered by WP-4 are described in paragraph 5.1. For each scenario the enforcement costs and the efficiency of enforcement are given these are shown in paragraph 5.2.
5.1. Considered scenarios Due to the lack of information on the effectiveness of enforcement, only the efficiency of scenarios can be calculated. The efficiency is calculated in terms of cost per screened and checked vehicle. Only targeted scenarios are considered. First of all this is done because for targeted scenarios (a small amount of) research data is available, while for the other scenarios no figures have been found. Second, the targeted scenarios can be easily compared with each other, because they involve the same type of enforcement procedures and the same geographical range. The other scenarios involve different procedures and have different geographical ranges (see paragraph 4.1). Screening of a vehicle is the process of looking for indications that a vehicle might be overloaded. In the case of manual selection screening is carried out by an enforcement officer, based on the experience and skill of that officer when looking at the external characteristics of the vehicle, e.g. the type or actual load or focuses on the tyres and distance between frame and axle. In case of screening by a WIM-system the axle load and vehicle mass measurements are used to determine if the vehicle might be overloaded in the case of pre-selection, or is overloaded, as in direct enforcement. The checking of a vehicle means measuring the axle loads and vehicle mass in a legally accepted way, and performing a comparison of the measurements against the accepted legal limits. The scenarios given in Table 1 are those that were considered: scenario 1
definition Manual Selection, no use of WIM.
2
WIM used for pre-selection controls
3
WIM used for automatic direct enforcement
description Human, static overloading measurements, based on visual pre-selection WIM is used to select the goods vehicles that then need to be measured with the traditional means An automated and certified WIM-system that generates fine notices for overloading directly based on the WIMmeasurement.
Remarks The current/traditional and most common way of overloading enforcement These WIM-systems can also be used for the applications ‘Statistics & Planning’ and ‘Problem Solving’. This way of enforcement is not yet available.
Table 1 – enforcement scenarios considered for Cost-Benefit Analysis
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Since scenario 1 is the current way of carrying out overload enforcement, it functions as a baseline; the efficiency of enforcement of the other scenarios is compared to this baseline. All scenarios are calculated using the same conditions, this includes: The number of overloaded and non-overloaded vehicles; The distance between the location of the WIM-system, the location where an overloaded vehicle is selected and escorted to the static weighing area and the location for the static weighing itself; The cost of equipment and personnel (e.g. static scales used in different scenario’s have the same cost, officers working in different scenario’s have the same cost). Not included are: The costs for the judicial chain, this is not included as it is seen as equal to all considered enforcement scenarios; The income from fines is not considered because the goal of enforcement is the reduction of overloading and not the collection of fines.
5.2. Costs and efficiency of enforcement In order to compare the cost and the efficiency of the three selected enforcement scenarios, the three scenarios were applied to the same “average” location on the TERN. In Figure 4 the number of overloaded vehicles is given, measured by a WIM site on highway A12, in the Netherlands. The figures are given as such: In the middle of the night, there are about 500 ÷ (7×24) = 3 overloaded vehicles per hour. At noon, the peak corresponds to 3500 ÷ (7×24) = 21 overloaded vehicles per hour. On average, there are about 12 overloaded vehicles per hour or in other words one overloaded vehicle per 5 minutes. In the following paragraphs the average of 12 overloaded vehicles per hour is used. It is interpreted correctly or incorrectly that an officer possibly has to wait 5 minutes to select an overloaded vehicle. The equipment and personnel costs for each scenario are based on an estimate given by the Dutch National Police Agency, the Transport Inspectorate of the Netherlands and the Bundesamt für Güterverkehr of Germany.
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Distrib ution of overload ed vehic les per w eek - Hig hway A12, northern WIM site 5000 4500
wk 31 '03 wk 32 '03
4000
wk 33 '03 wk 34 '03
Numb er of vehicles
3500 3000 2500 2000 1500 1000 50 0 0
0 00 0 0 00 0 00 0 00 0 0 00 0 00 0 00 0 0 0 0 00 00 0 0 0 00 00 : : : : :0 :0 : : :0 : : :0 :0 :0 : : :0 :0 : : :0 :0 : : 17 18 19 2 0 21 12 13 14 15 16 09 10 11 07 08 22 23 00 01 02 0 3 04 05 0 6
Time
Figure 4 – weekly distribution of overloaded vehicles
5.2.1. Manual selection
Manual selection is performed with a team of three officers. Table 2 gives the cost involved in this scenario. One officer drives a car or motorcycle and selects the vehicles to be measured. Selection is based on visible characteristics; therefore the officer needs special skills. The officer needs 5 minutes to monitor the traffic and select a potentially overloaded vehicle. Then it takes 15 minutes to lead the vehicle to the weighing area and again 15 minutes to drive back to the place where the traffic is monitored. These 15 minutes is rather long, this means the selection site is relatively far away from the location for static weighing. For all scenarios this same driving time of 15 minutes is used.
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Figure 5 – weighing with static scales The actual weighing is done by the two other officers using static scales, see Figure 5. These officers don’t have special skills. The weighing equipment is transported with a special weighing bus. entity officers - 1 officer (special skills) - 2 officers (general) - Overhead (30%) static scales - purchase - exploitation 1 weighing bus - purchase - exploitation 1 vehicle for selecting - purchase - exploitation total yearly cost
purchasing cost
depreciation
yearly cost
-
-
€ 35,000 € 2 x 30,000 € 28,500
total € 123,500
€ 12,000 €
30,000 -
in 3 years -
€ €
10,000 2,000
€
50,000 -
in 5 years -
€ €
10,000 3,500
€
40,000 -
in 5 years -
€ €
8,000 3,000
€ 13,500 € 11,000 € 160,000 Table 2 – costs for manual selection
The officer who selects the potentially overloaded vehicles limits the number of vehicles that can be checked. Considering 35 minutes to bring in one vehicle and an effective working day of six hours, every day 10 vehicles are checked. With respect to 220 working days per year, 2200 vehicles are checked yearly.
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The questionnaire shows that manual selection has a hit rate of about 50%. Thus weighing 2200 vehicles per year actually results in 1100 offences established. On the other hand, 1100 vehicles have been stopped (and delayed) despite the fact there were not overloaded at all. This is summarised in Table 3. For comparison reasons, the figures are given per officer as well. Scenario: manual selection Number of vehicles checked
per year 2200
Number of overloaded vehicles Number of wrongly stopped vehicles Enforcement cost Enforcement cost per overloaded vehicle
per year per officer 734
1100 1100 € 160,000 € 145
367 367 € 53,333 € 145
Table 3 – enforcement cost using manual selection 5.2.2. Pre-selection Pre-selection is done with a team of six officers, divided into three pairs. Within a pair, one officer brings in a potentially overloaded vehicle. On average, such an officer has to wait 5 minutes for the WIM system to select a vehicle and 15 minutes to lead the vehicle to the static weighing area. At the location for static weighing, the pair carries out the static weighing. This may take 5 minutes. After the static weighing, the first officer drives back to the place where the traffic is monitored. This takes another 15 minutes, making a total cycle of 40 minutes. In the meantime the other officer goes through the administrative process of the possibly overloaded vehicle.
Figure 6 – pre-selection
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Table 4 gives the cost involved in this scenario. Because the WIM system selects the potentially overloaded vehicles, no special skills are required for the policemen. entity officers - 6 officers (general) - Overhead (30%) WIM system - purchase - maintenance - exploitation static scales - purchase - exploitation 1 weighing bus - purchase - exploitation 3 vehicle for selecting - purchase - exploitation total yearly cost
purchasing cost
depreciation
yearly cost
total
-
-
€ 6 x 30,000 € 54,000
€ 350,000 -
in 5 years -
€ € €
70,000 50,000 10,000
€
30,000 -
in 3 years -
€ €
10,000 2,000
€
50,000 -
in 5 years -
€ €
10,000 3,500
in 5 years -
€ 3 x 8,000 € 3 x 3,000
€ 234,000 € 130,000
€ 12,000 € 13,500 € 33,000 € 3 x 40,000 -
€ 422,500 Table 4 – costs for pre-selection
The officers who bring in the potentially overloaded vehicles limits the number of vehicles that can be checked. The time for selecting a vehicle, driving to the weighing area and back takes on average 40 minutes. Considering an effective working day of six hours, one officer brings in 9 vehicles. With three pairs, per day 27 vehicles are checked. Over the considered 220 working days per year, 5940 vehicles are checked yearly. Manual selection has a hit rate of at most 95%. Thus weighing 5940 vehicles per year actually results in 5643 offences being detected. On the other hand, 297 vehicles have also been stopped (and delayed) although not actually overloaded. This is summarised in Table 5. Note: For comparison reasons, the figures are given per officer as well. Scenario: pre-selection Number of vehicles checked
per year 5,940
Number of overloaded vehicles Number of wrongly stopped vehicles Enforcement cost Enforcement cost per overloaded vehicle
per year per officer 990
5,643
940
297 € 422,500 € 75
50 € 70,417 € 75
Table 5 – enforcement cost for pre-selection
5.2.3. Direct enforcement In the case of direct enforcement, there is no enforcement officers involved in the enforcement cost. Instead there is a system administrator who monitors 10 direct enforcing WIM systems. The cost of a WIM system increases because of extra hardware needed for certifying the system as an autonomous enforcement system. The costs of this scenario are given in Table 6. With direct enforcement, every overloaded vehicle is selected and fined. The system works 24 hours a day and 7 days a week. Due to the fact that there are 12 overloaded vehicles per hour, every day 288 overloading offences will be detected and fined. Per year the total number selected overloaded vehicles becomes 105,120.
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entity
purchasing cost
depreciation
-
-
-
-
€ 700,000 -
in 5 years -
personnel - 1/10 system administrator - Overhead (30%) WIM system - purchase - maintenance - exploitation total yearly cost
yearly cost € 1/10 x 55,000 € 1,650
total €
7,150
€ 315,000 € € €
140,000 150,000 25,000 € 322,150
Table 6 – costs for direct enforcement Scenario: direct enforcement Number of vehicles checked
per year all passing vehicles
Number of overloaded vehicles
105,120
Number of wrongly fined vehicles Enforcement cost Enforcement cost per overloaded vehicle
0 € 322,150 €3
Table 7 – enforcement cost for direct enforcement Two comments should be noted here: 1. A starting point of the above mentioned enforcement cost per vehicle is that the number of overloaded vehicles remains the same despite the hit rate of the enforcement scenario. The higher the hit rate, the less this assumption will be true in real life. It would be better to compare the different scenarios by estimating the effect on overloading behaviour for each scenario, for instance by estimating the number of overloaded vehicles passing after applying a certain enforcement scenario. As discussed in chapter 4 there is not enough research data available to estimate efficiency, therefore an indication of effectiveness can only be given by estimating the enforcement cost per overloaded vehicle. 2. Applying a WIM system for direct enforcement places higher demands on that WIM system than pre-selection. A pre-selecting WIM system can be allowed to make a certain number of wrong selections, as during as the static weighing process will show that the vehicle is not overloaded, the driver will not then be fined. A direct enforcement WIM system cannot be allowed to select vehicles that are not overloaded. Technically this is solved by not giving a penalty to vehicles in the lowest part of the overloading spectrum. In this case a vehicle that is not overloaded, but falls within the lower part is not automatically fined. At this time it is estimated that future WIM-systems will need 10% tolerance set within the overloading spectrum to be sure that a vehicle is not wrongly fined. This will correspond to about 25% of the total number of overloaded vehicles checked. The number of overloaded vehicles in Table 7 is reduced to about 79,000 which correspond to an enforcement cost of € 4 per overloaded vehicle.
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6.
Damage to infrastructure
Traffic that uses the roads infrastructure unavoidably causes wear and tear of that infrastructure. However, it is important to realise that with increasing axle load(s) on goods vehicles the damage to the infrastructure increases exponentially by at least a factor of 4. Large goods vehicles are known to cause the most of the damage to the road infrastructure, and it is believed that overloaded goods vehicles take an even greater share in causing this damage. In relation to this topic again there is a limited amount of research is available, mostly from the Netherlands. It is this research that forms the basis of this chapter. In the UK currently there is also some research being is carried out on road and pavement damage, but at this time there is no available written data, on this research able to be used in this report. This chapter can only give an estimate of the damage to infrastructure caused by overloaded goods vehicles. It is only possible to show the costs for road maintenance and the corresponding cost of traffic delays as a result of the maintenance. Any damage to bridges has not been considered.
6.1. Damage to road pavement There are several available studies which conclude that with increasing axle load(s) the damage to the road infrastructure increases exponentially. This damage has been shown to be caused by overloaded vehicle axles rather than vehicles which are overloaded on the gross weight. When considering the load on the axle, within an axle combination, several parameters are important. In a study, COST 334 [COST334] the following parameters are mentioned: • Tyre configuration – damage depends for instance on the tyre type (single, wide base or dual), inflation pressure and tyre diameter; • Axle combination configuration – a load on a tandem axle or tri-axle configuration causes less damage than the same load on a single axis would do. In [GROENENDIJK] it is given that the impact of a single axle load is 0.6 times less when a tandem axle would have been used and 0.45 times less in the case that a tri-axle combination would have been used ; • Suspension configuration – damage is different for every suspension type; The amount of damage also depends on the pavement type. For instance, asphalt is rather soft and therefore suffers easily from rutting. With increased axle loading, the amount of damage increases with a power of 2 to 4. On the other hand, concrete is really stiff, and as long as it can withstand the axle load, the damage is considerably small. However as soon as increased loads cause the concrete to cracks, the damage is enormous. In this case, with increased axle loading the damage increases by a magnitude of 10.
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Figure 7 – damage to road pavement (rutting) 6.1.1. European research There was some extensive research carried out in the Netherlands on the topic of damage to road pavement in 2001 [GROENENDIJK]. In summary it showed that in the Netherlands a yearly bill of € 12.0 million up to € 22.0 million is spent on national roads for repairing damage caused by overloaded vehicles. The costs for repairing secondary roads are € 5.1 million up to € 18.8 million yearly (price level 2001). The repairs also relate with traffic delays, and show a social cost of € 1.6 million up to € 3.0 million per year (price level 1997) [ROZEMEIJER]. The abovementioned values are summarised in Table 8. Prices are corrected to price level 1999 because in the extrapolation hereafter the data from other member states are also given for 1999. Cost € 11.6 million - € 21.2 million
Damage to road pavement on national roads Damage to road pavement on secondary roads Social cost of related traffic jams Total cost of damage to road pavement
€ 4.9 million - € 18.1 million € 1.6 million - € 3.0 million € 18.1 million - € 42.3 million
Table 8 – Road damage cost caused by overloaded vehicles in the Netherlands In [TTI] a rough indication of the damage to road pavement is given for the UK, namely €100 million per year. Because the origin and scope of this figure is unclear, this figure hasn't been used for drawing conclusions. Nevertheless it indicates that the order of magnitude of the numbers used throughout the report is correct. 6.1.2. US research Other extensive research has been found that was carried out in the United States, namely USA Special Report 225. This study estimates that in the US every year $ 160 million up to $ 670 million is spent on repairing road damage caused by overloaded goods vehicle axles (price level 1988, Bearing in mind the fact that the USA has a national road network length of 1.7 times longer than the national road length of all 15 EU combined together, this study
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would suggest that European expenditure figures might be in the region of $94 and up to $394 million per year for repairs to damage caused by overloaded vehicle axles. This figure then only takes account of the EU national road network.
6.2. Damage to bridges The damage caused to bridges due to vehicle overloading is an even more complex matter, here not only is the pavement on the bridge damaged, but also (parts of) the construction of the bridge may be damaged. The sensitivity to overloading depends on things like construction, materials and age; additionally the sensitivity to overloading varies with each type of bridge or even with each individual bridge. In general when considering the damage to bridges the gross vehicle weight is more relevant than the increased individual axle loads. The calculation of the total amount of damage to bridges caused by overloading would require extensive research, and therefore lies outside the scope and resources of work package 4 of the REMOVE project. The cost benefit calculation for the damage caused to bridges is therefore not included.
6.3. Damage to road pavement on a European level As previously discussed, within Europe research into road pavement damage caused by overloaded vehicles has only been thoroughly investigated in the Netherlands. Since there are no other figures available, this is the only data that can be used to estimate the damage to infrastructure on a European scale. The extrapolation that is carried out in this paragraph is very sensitive to changes in the maintenance budget of The Netherlands, which varies from year to year. The maintenance budget used in the calculation is above average, thus the estimated percentage is relatively low. This result in a conservative estimation of the amount of road damage on a European level. Paragraph 3.4 gives the motivation of using this particular type of extrapolation. In order to extrapolate the data from the Netherlands, it has been assumed that each European country spends the same percentage of their road maintenance budget on repairing the damage caused by overloaded vehicles. The budgets from 11 of the 15 EU countries have been supplied by [ERF] and represented in Figure 8. The budget of the four missing countries is estimated on basis of their road network length compared to the total road network length of the 11 countries; these estimated values are shown in orange. In Figure 8 it is shown that the budget for road maintenance in the Netherlands is around € 800 million. Therefore the road pavement damage caused by overloaded vehicles amounts to 2.3% - 5.3% of the budget. The total road maintenance budget of the 15 EU countries given in Figure 8 is around € 10,500 million. Assuming the same percentages for the 15 EU countries, is the same as the Netherlands then € 239 million to € 557 million is being spent yearly on repairing road damage caused by overloaded vehicles. If only the national road network is considered then the figures are likely to be €153 millions to €227 millions being spent each year, which fits the same scale of spending, as previously shown at paragraph 6.1.2.
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2500
EUR million
2000
1500
1000
Blue: 500
0 B
DK
D
EL
E
F
IRL
I
L
NL
A
P
FIN
S
UK
investment given by [ERF] Orange: investment estimated using road network length and total EU-investment
Figure 8 – investment in road maintenance for EU-15 countries in 1999 The estimated costs presented which relate to the damage of road pavement on a European scale should be treated with some care. These figures are only a rough extrapolation, and for instances do not take into account the following: • • •
Different member states have different weight limits, therefore they build roads with different maximum load limits; Different member states have different road traffic densities, these relate to differing LGV fleet, and the location of the member state within the TERN. Bridges are not considered;
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7.
Road safety
When considering the effects on road or traffic safety in relation to overloaded LGV’s several aspects are important, within this chapter three important issues are discussed. First of all, overloaded or wrongly loaded goods vehicles have decreased vehicle handling characteristics, increasing the possibility for accidents. Secondly, overloading may also give an indication that other safety regulations may being disregarded as well. Thirdly, as argued in the previous chapter overloading does cause pavement damage and this may directly lead to dangerous driving conditions caused by that road pavement damage.
7.1. Reduced traffic safety because of overloading When large goods vehicles are overloaded, the vehicle handling characteristics deteriorate, this increases the chance of being involved in, or causing an accident. The following aspects are involved: 1. Overloading of the gross vehicle weight increases the braking capabilities and therefore the braking distance of the vehicle. Increased braking distances potentially mean that more accidents are likely to occur that otherwise could have been avoided. 2. In the case where an accident could not be avoided (overloaded or not), a large goods vehicle will have a higher impact than a vehicle that is not heavily loaded. This leads to more severe accidents. 3. Overloading of axles can lead to a decrease in steering capability/manoeuvrability and lessens overall control of the vehicle (see Figure 9). For example an overloaded vehicle has a decreased chance of avoiding a collision, and/or an increased chance of toppling over when trying to avoid a collision. Accidents are more likely to occur that otherwise could have been avoided, and leads to more accidents. 4. Vehicles that are overloaded beyond their technical specification limits, display increased wear and tear of vehicle parts, e.g. tyres and suspension. When additional vehicle maintenance is not carried out, parts of the vehicle may break down more readily, causing additional accidents. 5. On secondary roads, particularly in mountainous areas, goods vehicles that are extremely overloaded (and therefore slow) often urge drivers of cars to make dangerous overtaking manoeuvres. This can lead to more accidents. 6. However overloading a vehicle mass may also relate to less overall vehicle movements, less vehicles on the roads may potentially mean a reduction in the chance of an accident. When considering from this aspect, overloading could be seen as reducing the pressure on road traffic safety.
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Figure 9 – reduced manoeuvrability In order to provide an illustration of the abovementioned direct aspects of overloading, the REMOVE project has looked for research that would link the number of overloaded vehicles directly to a number of accidents, and the severity expressed as a ‘social cost’. Only rough estimates can be found, an example came from the US Special Report 225, which indicates that due to increases in truck weights, the involvement rate of these heavy goods vehicles in accidents is also increased, particularly crashes that are roll-over or ramp related. It is also relevant in rearward amplification related crashes that involve multiple trailer combinations. When this happens, small steering movements of the pulling truck lead to great swerves of the trailers, in fact, the system of pulling truck and multiple trailers generally forms an unstable system. The sideways movements of the truck can cause large sideways movements of the trailers. In addition an attempt has been made to provide an illustration, by examining general accident statistics, as shown in [BAST-I] and [BAST-II]. Unfortunately these statistics do not explicitly focus on overloading, which has resulted in data that is not accurate and complete enough to describe road safety in a quantitative way: 1. First, this is caused by the fact that generally an accident is a result of an unlucky combination of events. Often it is difficult to determine all causes of an accident and only the most obvious ones are reported and included in the statistics, for instance excessive speed. 2. Second, the experience and personal ‘preferences’ of the person reporting the accident tend to determine which cause will be chosen. As knowledge about overloading is less widespread than other possible causes like speeding, overloading may often be overlooked as a cause for an accident. 3. Thirdly there is a drawback of using general accident statistics in that there is only a general category called “load”. Even when the statistics show the main cause is ascribed to load, it might mean that the truck was overloaded, but equally it may relate to instances of in secure loads being the cause. In Germany only 2% of accidents involving heavy goods vehicles (>12 tons) are attributed to the “load” as a cause. [BAST-I]. A possible set of causes for an accident where a truck was unable to stop in sufficient time, could be ; excess speed, following too close resulting in a short braking distance between the
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vehicle in front, lack of attention by the driver and overloading of total mass of the vehicle. Generally the lack of braking distance in combination with speeding is the chosen cause because this is relatively easy to determine and it is conclusive enough to define who is responsible for the accident. E.g. Vehicle (A) hits another vehicle (B) from behind, as per definition the first vehicle (A) did not maintain enough (braking) distance; otherwise it would not have hit the second vehicle (B).
7.2. Reduced traffic safety because of other safety deficiencies A recent study in the UK has shown that persons who commit certain traffic infringements also tend to be offenders in other areas [OFFENDER-SELF-SELECTION]. The study itself focuses on illegal parking in disabled bays. The study shows that illegally parked cars are more likely to have a history of other traffic violations than a nearby legally parked car. The same has been shown to go for the registered keeper, in that keepers of illegally parked cars are significantly more likely to have a criminal record than keepers of legally parked cars. A general conclusion can be drawn from this study in that person or companies that violate one rule are also more likely to violate other related rules. When considering this in terms of traffic safety, it may very well be possible that persons, or transport companies that overload LGV’s will also tend to break other safety regulations as well. A similar conclusion is drawn within an article published in the US. [TAYLOR]. Based on an US study [WISCONSIN] it is also argued that overloaded trucks are three times more likely to be in violation of safety regulations when compared to general goods vehicle traffic. Given the conclusions drawn from both the above studies it is concluded, that when governments succeed in successfully decreasing the number of overloaded vehicles, the amount of, and number of other safety violations may also decrease simultaneously.
7.3. Reduced traffic safety due to road damage As previously described overloaded vehicles do indirectly impose a threat to road safety. In chapter 6, overloaded vehicles were shown to cause considerable damage to infrastructure that results in additional unsafe road traffic conditions, the negative effects are described below: 1. The damage itself means a decrease of road safety, the rutting in the pavement surface caused by goods vehicles has a direct effect on safety. It not only creates manoeuvring difficulties for vehicles that enter them, it also causes dangerous situations for cars (trucks and motorbikes), especially in rainy weather conditions when there is the possibility of aqua planning, and decreased visibility caused by splash and spray. 2. The road maintenance works that are necessary for repairing this extra damage also have an additional negative effect on traffic safety. The road work sites involve road narrowing, creating possible traffic jams and subsequent delays etc. There is also an increased safety risk for road workers involved in the maintenance operations. When considering the transport of dangerous goods on the road network the negative effects of overloading in relation to road and traffic safety, increase even more. The transport of dangerous or hazardous goods also has serious potential effects to general public safety and the environment, and in this respect the negative effects of overloading are very pertinent.
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8.
Unfair competition
As previously mentioned and documented overloaded goods vehicles cause problems in the fields of safety, mobility and road maintenance costs. At the same time the practice of overloading large goods vehicles undermines the system of fair competition in the EU. It creates an illegal and unfair advantage for some operators allowing them to charge lower prices for the same journey, thus having a negative effect on price levels. The phenomenon of unfair competition then causes non-compliance in other areas of the transport business, bona fide transport companies cannot compete against companies that operate illegally on lower price levels, by overloading their vehicles. Specific data on the effect that overloading of vehicles has on fair competition is very limited, and exact figures on the amount of financial damage caused by companies that operate by overloading against those companies that do not overload are nonexistent at this time. Even the IRU has no clear view or figures on how big the problem really is the number of companies involved and the unfair profits that are gained. As there is an absence of concrete figures the topic of unfair competition can only be restricted to a general discussion of the principles as currently perceived. This does not mean that the problem should be neglected; on the contrary, more research is definitely required to get a clearer picture on the scale of the problem. The following paragraph describes two types of unfair competition which can be related to overloading: 1) Overloading of the gross vehicle weight, and 2) Overloading of individual axles.
8.1. Gross vehicle loading In instances where the overloading of the gross vehicle weight occurs, i.e. transporting more goods than is allowed, this creates the most direct and significant form of unfair competition. The basic principle is that a company that allows its vehicles to operate whilst overloaded needs fewer trips to transport the same amount (weight) of goods. This principle is explained in the following examples. Example 1, Two companies have to transport a total load of 500 tonnes. Each company uses a 15 tonne truck with a legal limit for the gross vehicle weight of 40 tonne. Company 1 loads its truck with a load of 31 tonne resulting in 16% overloading of the gross vehicle weight. Company 2 loads its truck with 25 tonne resulting in no overloading of the gross vehicle weight. The unfair advantage of company 1 means that it requires only 16 trips to move the total load, instead of the 20 trips it takes company 2. This means an unfair advantage of 20% less costs (less fuel and less driving hours). So company 1 can offer to transport the total load for 15% less and still have a larger profit than company 2. Example 2, Again two companies have to transport a total load of 500 tonnes. This time company 1 uses a 10 tonne truck with a legal limit for the gross vehicle weight of 30 tonne. Company 2 uses a 15 tonne truck with a legal limit for the gross vehicle weight of 40 tonne. Both companies load their trucks with 25 tonne per trip, so both need 20 trips to transport the total load. For company 1 it results in 17% overloading of the gross vehicle weight, whereas company 2 again has no overloading of the gross vehicle weight. The unfair advantage for company 1 is that it uses a lighter and thus cheaper vehicle. It is cheaper because a lighter vehicle is normally cheaper to build and the road tax/toll is normally lower. The exact amount of the unfair advantage depends on the prices of the vehicles and the road toll/tax. It should be noted that the Toll-Collect scheme in Germany has slightly different approach; here the toll is based on the number of axles. This approach however may cause some companies to be tempted to transport a load in a vehicle with fewer axles, therefore increasing the load on the remaining axles.
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The examples above are very basic, and do not for instance take into account the benefit of overloading on business processes or the extra cost of overloading on wear and tear of the vehicle fleet. More generally it can be stated that, because the profit margins of transport companies are low (below 3%) a small amount of overloading can already be very profitable for a transport company. This conclusion can also be drawn from a calculation of the French ministry of transport [SES144]. This calculation shows that companies with a large vehicle fleet can save 21% of their turnover by permanently overloading their trucks by 20%. The calculation is based on a company which transports 1,000,000 tons yearly and drives 14 tons trucks with a permissible GVW of 40 tons. When the trucks are structurally loaded with 48 tons, the transport company saves money by cutting down the number of trips and by cutting down the vehicle fleet they require to perform the task. The only drawback is a 3% increase of maintenance cost and a 3% increase on fuel consumption, which is incorporated in the calculation as well.
8.2. Axle loading The overloading of individual axles in general is not considered an issue of direct unfair competition. The problems with overloaded axles often originate from the transport of separated loads for different destinations using a tractor-trailer combination. The problem occurs when a vehicle that is fully loaded, and is within the legal limits for the axle loads and gross vehicle weight, however when part of the load is removed by unloading from the vehicle trailer, the driven axle(s) of the tractor may become overloaded. Described below are three possible solutions to this problem: 1. Move the remaining load each time the driven axle becomes overloaded. This causes a problem for the transport companies as moving the remaining load takes time, and thus costs money. In any cases sometimes the construction of the vehicle and/or safety regulations do not allow any load to be moved within the vehicle; 2. Investments are made by the transport companies in special adaptations or equipment for the vehicle which allow the remaining load to be moved easily and safely within the vehicle; 3. Logistical adaptations are made so that transport routes are changed to avoid the problem from occurring. All three solutions have one thing in common; they all cost money and are not always possible in reality. This is discussed in more detail in work package 1 of the REMOVE project. However when a transport company accepts one or more of the solutions it is possible that the companies not willing to make that investment continue driving with overloaded axles, will therefore gain an unfair advantage over companies that do make that investment.
8.3. General effects of enforcement When there is enforcement action taken against overloaded vehicles this can have several effects on overloading behaviour depending on how a company is able to solve their overloading problem: 1. Certain companies use overloaded vehicles with low technical and legal load capacity. For instance, they use a vehicle suitable to carry 20 tons with a load of 30 tons. Overloading enforcement may motivate these companies to buy vehicles with a higher technical and legal load capacity. For example, overloading enforcement may motivate the company to buy a vehicle which is actually suitable to carry 30 tons, to carry their load of 30 tons. 2. Other companies may use overloaded vehicles which already have high technical and legal load capacity. For instance, they use a vehicle suitable to carry 40 tons with a load
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of 50 tons. Overloading enforcement may motivate these companies to stop overloading. This creates a dilemma, in order to ship the same load, more vehicle movements are necessary, the effects on road safety should then be noted. The vehicle is not overloaded anymore which increases road safety, but the increased number of vehicle decreases road safety again. As there is a lack of research in this area it is not possible to determine which aspect would be the most important for road safety. It should be noted that companies willing to overload because of a competition benefit, might also commit other offences to gain competition benefits.
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9.
Cost-Benefit Analysis
All the previous chapters describe the elements of the Cost-Benefit Analysis, which was shown originally in Figure 3. This basis of figure 3 has been repeated in Figure 10. Within the limited time reserved for this work package, all but one element of the CostBenefit Analysis could be considered. Unfortunately, as discussed in chapter 4, there is no research data readily available on the effectiveness of different enforcement scenarios, therefore the work package was not capable of linking enforcement scenarios to an actual change in overloading behaviour, expressed as a decrease in overloaded vehicles. This missing link breaks the chain that would lead to a real Cost-Benefit Analysis, indicated by the cross in Figure 10. Nevertheless the objective of this work package, namely making a case for using WIMsystems for overloading enforcement, can be fully met, and this has been achieved by considering the costs and benefits on a more abstract level.
scenario
efficiency of enforcement
decrease overloaded vehicles
costs
reduction increase damage to road infrastructure safety
reduction unfair competition
cost benefit analysis
costs
benefits
Figure 10 – Cost-Benefit Analysis total flowchart (repeated)
9.1. Benefits of overloading enforcement Chapters 6 to 8 have explained that by reducing the amount of overloaded vehicles in general terms there are decreases in damage to infrastructure, increases road safety and support for fair competition between transport companies. The greater part of these benefits has only been outlined in general terms, but in the case of road surface damage a rough estimate was given. By mapping the pavement damage caused by overloaded vehicles in the Netherlands against the other 15 EU nations, it has been found that on a European scale overloaded large goods vehicles might cause pavement damage to national and secondary roads of between € 239 million and € 557 million, a year. Although this figure is only a rough estimate, it clearly supports the need for efficient and effective overloading enforcement.
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9.2. Costs of overloading enforcement Chapter 5 indicates the enforcement cost for the three enforcement scenarios, applied on the same road with the same amount of overloaded vehicles: • Manual selection; • Pre-selection using WIM; • Direct enforcement using WIM. The equipment and personnel costs for the manual selection scenario are equal to € 53,333 per year per officer. This is lower than in the case of the pre-selection scenario at € 70,417 per year per officer, because with manual selection no WIM system is needed. On the other hand, when using a WIM system for pre-selection, the hit rate increases significantly. Therefore the amount of fines using manual selection (367 fines per year per officer) is almost a third of the case using pre-selection (940 fines per year per officer). Considering the cost per fine, manual selection costs € 154 per fine whereas pre-selection costs € 75 per fine. Finally, because of the higher hit rate using WIM considerably fewer vehicles are incorrectly stopped and delayed when not overloaded. By examining this example closely it is shown that pre-selection is more beneficial in situations where there is a moderate supply of overloaded vehicles. Whereas manual selection is more beneficial when applied in situations with low or seasonable supply of overloaded vehicles. Direct enforcement is not currently available, but when it becomes available it is believed that it will be even cheaper than using pre-selection, this is because direct enforcement fines are levied at every overloaded vehicle 24 hours a day and 7 days a week. The direct enforcement system relates to a very low cost per fine (€ 3 to € 4 per fine). In the examples, for comparison reasons the amount of overloaded vehicles is kept constant, whereas in every day life road users adapt their overloading behaviour, leading to a reduction of overloaded vehicles on the given road. By using a direct enforcing WIM system this reduction will be achieved with considerably less cost, compared to the cost of achieving the same reduction with manual or pre-selection. This shows that direct enforcement (when available) would be most beneficial when applied on roads with a high supply of overloaded vehicles.
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10. Conclusions and recommendations 10.1. Conclusions Overall despite the limited amount of research data, the subjects that have been addressed in the Cost Benefit Analysis show that a lot can be gained by achieving a higher compliance to loading regulations: •
Road safety – Decreasing the amount of overloading results in a better traffic safety. Most obvious is that when the amount of overloaded large goods vehicles decreases, there are fewer vehicles on the road that are potentially dangerous to other road users. Also when overloading decreases the extent of road damage also decreases, this leads to a decline of dangerous situations caused by for instance rutting or the road works necessary for repairing the road damage. Finally, overloaded vehicles are more likely to violate other safety regulations, compliance with these other safety regulations may be increased also by targeting overloading violations.
•
Unfair competition – When the compliance with loading regulations increases, it means that more transport companies stay within legal load limits, this is favourable in terms of fair competition. The use of advanced WIM-systems for pre-selection or automatic direct enforcement, means only the overloaded vehicles are targeted and delayed, those that obey the rules are not delayed and therefore achieve a benefit.
•
Damage to infrastructure – Overloaded large goods vehicles cause damage to road pavement and bridges. Given the viewpoint that the relationship between axle load and pavement damage is mathematically exponential, it is obviously beneficial to reduce overloading by large goods vehicles as much as possible. A rough estimate based on figures from the Netherlands shows that in Europe € 239 million to € 557 millions may be spent yearly on pavement repairs because of vehicles with overloaded axles, on highways and secondary roads.
The abovementioned benefits illustrate the need to achieve higher compliance with loading regulations. It is recognised that this can be achieved by using traditional means of enforcement, however within the REMOVE project it is argued that the most cost efficient approach is achieved by using all possible WIM applications defined in the WIM toolbox. Again it should be noted that due to the limited level of resources allocated to the Cost Benefit work package, this work package only has focused on the three targeting WIM applications: •
Manual selection – This traditional way of enforcement is relatively inefficient. However, because it does not need an investment in a WIM-system, this method of enforcement is very much suited to flexible checks. Therefore this enforcement scenario can best be used on the secondary road network, or at construction sites or during the harvest season.
•
Pre-selection – Pre-selection using Weigh in Motion is a more efficient tool than manual selection and has the advantage that the number of non-overloaded vehicles stopped is reduced dramatically. WIM-systems for pre-selection can also be used for the Statistics & Planning and Problem Solving applications; this makes the investment more cost effective.
•
Automatic direct enforcement – This enforcement tool is by far the most efficient enforcement method. However, because it requires a considerable investment at the outset, it is best suited for very busy highways such as the TERN, and at locations were avoiding passing the check point is difficult, e.g. at river bridges or mountain passes
10.2. Recommendations The following recommendations are made:
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• Intelligent Enforcement Mix The Cost-Benefit Analysis shows that every application defined within the IM toolbox has an optimal field of application. It is therefore necessary to recommend the introduction of an Intelligent Enforcement Mix, which is capable of utilising all the applications of the WIM toolbox. It is advisable to make use of the same WIM systems for a number of applications, which ill be achieved by choosing appropriate locations in which to operate. It is obvious that the introduction of WIM systems contribute to the level of enforcement available, at the same costs. For the most effective use of WM systems it is necessary to combine the use of this technology with a good public education and communication strategy. for dissemination to the public. This will particularly useful for example in informing companies that are found to unintentionally overload their vehicle fleet, which’s likely to become evident as a result of the use of the company profiling aspect of WiM systems. • Research on a European Scale The Cost-Benefit Analysis carried out within the REMOVE project is based on very limited research data, basically because there has only been limited research completed regarding the topic of overloading. In order to approach this topic in more detail, the following research can be considered: • • •
Research on damage to road infrastructure by overloaded vehicles on a European scale; Generation of more statistics on road safety, i.e. when an accident is reported, the officer should be advised to report more than one reason for the accident, including the possibility of overloading; Research on the effect of unfair competition caused by overloading.
Bibliography [BAST-I]
Unfallgeschehen mit schweren Lkw über 12 t. Referat Öffentlichkeitarbeit, Heft M 156, Januar 2004.
[BAST-II]
Volkswirtschaftliche Kosten der Sachschäden im Straßenverkehr. Referat Öffentlichkeitarbeit, Heft M 119, Juli 2000.
[COST334]
COST 334, Effects of Wide Single tyres and dual Tyres. Chairman R.R. Addis, june 2000.
[ERF]
European road statistics 2004. European Union Road Federation, June 2004.
[GROENENDIJK]
Groenendijk, dr.ir. J., Onderzoek naar de jaarlijkse onderhoudskosten aan het wegennet, veroorzaakt door overbelading van vrachtauto’s in Nederland. Final version, November 19th, 2001.
[KAGAN&SCHOLZ]
Kagan, R. A. and J. T. Scholz, The "Criminology of the Corporation" and Regulatory Enforcement Strategies. Kluwer-Nijhof, 1984, pages 67-95.
[OFFENDER-SELF-SELECTION]
Sylvia Chenery, Chris Henshaw, Ken Pease, Illegal parking in disabled bays: a means of offender targeting. Policing & Reducing Crime Briefing Note 1/99, May 1999.
[ROZEMEIJER]
Rozemeijer, Sjors, Maatschappelijke kosten van overbelading – Kwantificering van de filekosten op het Hoofdwegennet in Nederland door overbelading in het vrachtverkeer. Adviesdienst Verkeer en Vervoer, April 2002.
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[SES144]
Alain Priol, Isabelle Leroy-Duthilleul, Alain Sauvant et Radouane Sidky, Infractions et distorsions de concurrence. Ministère des Transports / Direction des Affaires économiques et internationales / Service des Études et Statistiques. Published in Les études du SES, n°144, April 2003.
[SPECIALREPORT225]
Special Report 225, Truck Weight Limits: Issues and Options. Transportation Research Board, National Research Council, Washington, D.C., 1990.
[TAYLOR]
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[TTI]
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[WIM-VID]
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[WISCONSIN] Cambridge Systematics Inc., Wisconsin Safety and Weight Policy Study. Prepared for the Wisconsin Department of Transportation Office of State Patrol, 1994.
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