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A new approach for allocating pavement damage between heavy goods vehicles for road-user charging
Transport Policy 12 (2005) 419–430 www.elsevier.com/locate/tranpol
A new approach for allocating pavement damage between heavy goods vehicles for road-user charging Nii Amoo Dodoo*, Neil Thorpe School of Civil Engineering and Geosciences, University of Newcastle upon Tyne, NE1 7RU, UK Accepted 24 June 2005
Abstract This paper argues that current Heavy Goods Vechicle (HGV) charging systems do not take into account key factors affecting the extent of pavement damage caused by individual HGVs. Thus, charges are poorly aligned to actual costs which is contrary to the EC’s polluter pays principle. This paper describes the development and on-road trials of a new system, which uses on-board axle weighing and satellite positioning technology to estimate the amount of pavement damage caused on individual road links by an individual HGV. Although the on-road trials of the system were successful and demonstrated how current HGV charging systems can be improved in order to align pavement costs more closely to pavement charges, the paper also notes a number of implementation issues that need to be overcome before widespread implementation of the system is practicable. q 2005 Elsevier Ltd. All rights reserved. Keywords: Pavement damage; Road-user charging; HGV charging systems
1. Introduction This paper describes the design, development and onroad demonstration of a new system for allocating pavement damage between individual Heavy Goods Vehicles (HGVs)1 for road user charging purposes. Ever since the publication of the Smeed Report in the mid-1960s (Ministry of Transport, 1964), the possible implementation of direct forms of road-user charging has attracted considerable interest. This interest stems from the potential contribution that charging could make in managing travel demand and the considerable net revenues that could be generated. As managing increasing traffic congestion is most often cited as the main motivation for considering the case for introducing charging, it is understandable that most attention has focussed on charging private cars. The European Commission’s Green Paper Towards Fair and Efficient Pricing in Transport (1995) discusses in * Corresponding author. E-mail addresses: [email protected] (N.A. Dodoo), neil.thorpe@ ncl.ac.uk (N. Thorpe). 1 Vehicles over 3.5 tonnes gross vehicle weight.
0967-070X/$ - see front matter q 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.tranpol.2005.06.009
depth the costs associated with transport to society, the inefficiencies in the transport market and their combined effect on the environment and socio-economic development of member states. The Green Paper identifies the principles of marginal cost pricing as a key requirement of a fair and efficient transport system, whereby charges paid by users for individual journeys are aligned to the actual (internal and external) costs of the journey. One of these costs is clearly the physical damage caused by vehicles to the road infrastructure. HGVs are responsible for almost all of the structural damage to road pavements which, in the UK, accounts for approximately two thirds of road maintenance expenditure (Department for Transport, 2004). Various mechanisms for internalising these costs are currently used worldwide in the form of annual taxes and user fees. However, the extent to which these taxes and fees are able to reflect the actual cost of damage caused by HGVs to road pavements has come under close scrutiny as part of the move towards fair and efficient pricing in transport. This is to ensure that each particular vehicle’s contribution to pavement damage is estimated accurately and charged for appropriately. If all HGVs caused the same amount of damage per unit distance travelled, irrespective of (for example) their speed and actual gross vehicle weight, then a simple distance-based charging system could be used. In reality however, the relative amount of damage caused by individual
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HGVs varies widely depending on a number of vehicle, pavement and climatic characteristics. We argue therefore, that these various characteristics must be properly taken into account to ensure that individual HGVs pay a fair and efficient charge appropriate to the actual amount of damage they cause. A fundamental problem with most current charging systems lies in the methodologies used, albeit successfully over recent decades, to recover costs from users of transport infrastructure for pavement damage caused. This paper argues that these methods are unable to implement current and emerging charging objectives, which seek to charge users based on the costs of individual journeys. With respect to HGVs and pavement damage, current understanding of the mechanisms relating vehicles with pavement damage gives further impetus to the development of new charging methodologies, which embrace the ideals of a sustainable transport policy. In 1988, the transport economist David Newbery suggested that: “If every link in the road network had a tollgate, then vehicles could be charged at a vehicle and road specific rate (per axle weight-km, at different rates depending on the characteristics of the road, or the road type, measured by the pavement strength, traffic flow, maintenance strategy). In practice, of course, such fine-tuning of the system of road user charges is impractical with current technology” (Newbery, 1988, p. 298). Since then, there have been significant technological advances which now make such a system a far more realistic proposition. The development of such a system is the focus of this paper. The overall aims of this paper are; 1. to identify what characteristics affect the amount of damage caused that should be taken into account when calculating charges (Section 2); 2. to assess how well current HGV charging systems are able to achieve the EC’s goal of fair and efficient pricing (Section 3); 3. to describe the concept, development and field trial of a new system that includes key variables affecting the extent of pavement damage caused to relate charges more closely to pavement damage costs (Sections 4 and 5); and 4. to discuss issues relating to the future implementation of the system (Section 6).
pavements have changed significantly in terms of materials and methods of construction and vehicles today have very different designs and configurations from those in the 1960s (Cebon, 1999). Subsequent research has led to a much clearer understanding of the interaction between vehicles, pavements and the climate and the nature and extent of the factors responsible for road pavement damage. Differences between vehicles in terms of their loading conditions and physical characteristics, such as axle configuration (e.g. number and spacing), tyre type and configuration (e.g. single, dual or wide-base single) and suspension type (e.g. air or steel), can cause the nature and extent of loads and stresses imposed on pavement structures, and hence the amount of pavement damage caused, to vary considerably in time and space. Different pavement types (e.g. flexible and rigid) are susceptible to different forms of pavement damage (e.g. cracking or rutting) while thicker pavement structures possess stronger structural capacities that are able to withstand higher axle loads and stresses and hence sustain less pavement damage from axle loads. Increased surface roughness can also lead to the generation of greater levels of dynamic axle loading and consequently more pavement damage. Finally, variations in climatic conditions (e.g. moisture and temperature) lead to changes in the material properties and structural strength of the pavement and, as a consequence, affect the amount of pavement damage caused by axle loads. The significance and relative importance of these variables and how they affect the nature and extent of pavement damage has been studied widely over the years (see for example Addis and Whitmarsh, 1981; Middleton and Rhodes, 1991; Gillespie et al., 1993; OECD, 1998). For example, Gillespie et al. (1993) report that variations in axle loads and pavement thickness are the two most important factors and can cause pavement damage to vary by a factor of over 20. Tyre type (e.g. wide-base against single dual) can cause pavement damage to increase by a factor of 1.5–4. Similarly, the extent of roughness can affect the amount of pavement damage by between 30–50% (Huhtala et al., 1989; Gillespie et al., 1993; OECD, 1998). Research suggests that all these factors (e.g. gross vehicle weight, tyre type, pavement roughness, suspension type, vehicle speed and pavement temperature) either solely or interacting with each other can lead to significant variations in the amount of pavement damage caused. What is very clear is that the damaging effect of individual HGVs varies over time and space. The following section describes how well these variations are accommodated in current HGV charging systems.
2. The factors affecting the extent of pavement damage caused by HGVs 3. Road cost allocation and HGV charging systems Since the American Association of State Highway Officials’ (AASHO) road tests in the 1960s, which resulted in the ‘fourth power law’ to assist in designing pavements and allocating highway costs between different user classes,
The OECD (1998) estimates that construction and maintenance of road networks consume between 0.2–1.9% of a country’s GNP. Pavement designers attribute all
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pavement damage to HGVs with pavement maintenance activities resulting from HGV loading forming a significant proportion of total road budgets in most countries and accounting for up to 75% of total road infrastructure investment (Gwilliam and Shalizi, 1999). The ‘Cost Occasioned Approach’ which is applied in road track cost allocation methods is the most commonly used method for determining taxes and charges to raise funds for road construction and maintenance (Federal Highway Administration, 1997). It is based on the principle that each user of the road pays for the costs they incur on it. Pavement costs (e.g. maintenance and reconstruction) are allocated to different vehicle classes based on their collective responsibility for different components of these costs using a variety of measures (e.g. vehicle-kms travelled, standard-axle-kms and PCU-kms) assumed to relate vehicle use to road costs. Link et al. (1999) review the application of this method in a number of European countries. Despite worldwide usage, the implementation of the road cost allocation and charging mechanism described above suffers from important weaknesses undermining their ability to apply the ‘polluter pays’ principle. First, data used in road track cost allocation methods are at best crude averages of road usage for individual HGVs in which the relationship between costs and charges is weak. For example, in the UK, Dodgson et al. (2000) proposed an improved method for allocating road track costs which included more refined categories for HGV class, vehicle characteristics (e.g. tyre and suspension types) and road type. Second, the use of fuel tax as the principal mechanism for recovering charges is debatable as fuel consumption is a poor proxy for pavement damage costs. A further issue of concern here is the recovery of costs caused by ‘foreign’ vehicles on a nation’s roads. Thus, the main shortcoming with these traditional applications stems from their inability to capture fully the principle on which it is based (the polluter pays)–that is, different vehicles within each class pay equal amounts in terms of indirect charges irrespective of their individual contribution to road costs. Furthermore, traditional forms of direct charges, which are based on distance travelled, are poor proxies for the extent of pavement damage caused. A number of countries (e.g. Switzerland, Austria and Germany) have tried to correct these inconsistencies through new cost recovery schemes that attempt to recover the true costs of pavement damage from the actual vehicles that are causing the damage. In the Swiss system, the distances travelled by each HGV on all public roads in the country are measured using the tachograph. A microwave-based On Board Unit (OBU) using Dedicated Short Range Communications (DSRC) technology installed in each HGV then records these distances. Data are downloaded from the OBU to a chipcard each month for billing purposes by the Swiss Customs Authority. Distance measurement is switched off when an HGV leaves the country at the border and on again when it returns. Charges are calculated based on the distance
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travelled, maximum permissible vehicle weight and emission class of the HGV (Krebs and Balmer, 2002). In contrast, the Austrian HGV charging system applies only to the motorway network. This network has been divided into 800 separate sections using microwave based, multi-lane toll gantries that allow tolls to be collected automatically from HGVs (over 3.5 tonnes GVW) at normal traffic speeds when passing under a toll gantry (Eberstaller, 2003). Similarly, the German system operates only on the autobahn network but applies only to HGVs over 12 tonnes (GVW). Unlike the Swiss and Austrian charging systems that use microwave technology, the German system uses onboard satellite, digital map and GSM communication technologies. The position of an HGV on the road network obtained from GPS satellites is compared continuously to a digital map of toll roads as the vehicle travels around the network. An HGV is charged when the OBU identifies that the HGV is travelling on a tolled road. Distance travelled is obtained from the digital road map. The charge rate depends on the number of axles, maximum permissible vehicle weight and emission class of the HGV (Charpentier and Fremont, 2003). Drawing upon available literature, Table 1 presents a summary of these and other HGV charging systems world-wide (Starkie, 1988; Volpe, 1994; Kageson, 2000; HM Treasury et al., 2004, 2005). Table 2 then summarises for each system which of the key factors that affect the amount of damage caused are actually taken into account when calculating the appropriate charge per vehicle. In practice, these variables that all affect the amount of pavement damage caused can vary frequently during a journey for individual vehicles as they travel around at different speeds, on different types of pavements carrying loads that can increase and decrease as goods are collected and delivered. Referring to Table 2, none of these systems take into account pavement characteristics (e.g. type and roughness) or prevailing climatic conditions when estimating the extent of pavement damage caused. Three of the systems (The Eurovignette, the Swiss HVF and the system in Germany) do differentiate charges on the basis of emission class in attempt to internalise some of the costs associated with atmospheric pollution. This leaves vehicle characteristics as the sole determinants of the level of charge payable. Axle loads are the most important factor determining the extent of pavement damage caused (Section 2) and the seven charging systems account for this in three ways. The first approach, as employed in the Eurovignette system, is not to include any representation of axle loads at all. Thus, all HGVs are charged the same per unit distance travelled irrespective of their actual weight. We estimate, using simple load equivalency factor calculations, that a 44-tonne 6 axle HGV causes approximately 75 times more damage when fully laden compared to when empty. Apart from the system in Switzerland, the rest differentiate charges by number of axles (e.g. 2, 3, 4C) but again this leads to
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Table 1 Summary table of key features of current and proposed HGV charging systems Country of operation
Implementation date
Charging parameters
System description
Network coverage
Vehicles charged
Payment Method
New Zealand
1st April 1978
Hubodometer measures distance travelled. Distance licence purchased
All public roads
All HGVs O 3.5 tonnes GVW
Pre-payment at post offices. licences bought in multiples of 1000 km
Germany, Netherlands, Belgium, Luxembourg, DenmarkCSweden ‘The Eurovignette’
1st January 1995
Distance travelled, number and spacing of axles, number of tyres, maximum permissible gross vehicle weight Number of axles, emission class
Motorways only
HGVs O 12 tonnes
Pre-payment
USA HELP programme
October 1993
Distance travelled
Designated sections of highways in 24 states
Participating HGVs
Post payment by invoicing operators
Switzerland
1st January 2001
All public roads
HGVs O 3.5 tonnes
Vehicle journey data downloaded via chip card or modem to billing centre
Austria
1st January 2004
Distance travelled, max. permissible gross vehicle weight, emission class Distance travelled, number of axles (2, 3 and 4C)
Motorways and expressways
All HGVs O 3.5 tonnes
Post payment by bill and pre-payment with on-board account
Germany
1st January 2005
Paper-disc (weekly, monthly or annually) giving access to motorway network in participating countries Automatic vehicle identification and classification system allows vehicles to by-pass toll stations. Vehicles weighed by weigh-in-motion systems. GPS and DSRC; distance travelled measured using tachograph complemented by GPS DSRC based system. Tolls collected separately on each of the 800 sections of the network GPS/GSM based system with onboard digital map of tolled roads. DSRC for enforcement
Motorways only
HGVs O 12 tonnes
Post and pre payment options available
UK
2007/ 2008
All public roads
HGVs O3.5 tonnes
Not known but probably pre and post payment options
Distance travelled, number of axles, max. permissible gross vehicle weight, emission class Distance travelled, road class, number of axles (2, 3, 4C), emission class
Not yet known but probably GPS based
certain anomalies because of the number of axle categories used. For example, a five axle truck weighing 40 tonnes causes approximately twice the amount of damage per unit distance than a six axle truck with the same weight.
However, the axle categories defined (for example in the Austrian system) result in both trucks paying the same charge. The second axle load proxy is to vary charges depending on a vehicle’s maximum permissible gross
Table 2 Pavement damage factors and their inclusion in HGV charging systems Country
Dynamic axle loads
Number of axles
Type of axle
Tyre type
Pavement type
Pavement thickness
Temperature and moisture
Distance travelled
New Zealand Eurovignette HELP (US) Switzerland Austria Germany UK
No No (Noa) No No No No
Yes Yes Yes No Yes Yes Yes
No No No No No No No
No No No No No No No
No No No No No No No
No No No No No No No
No No No No No No No
Yes No Yes Yes Yes Yes Yes
a
Weigh-In-Motion used for enforcement of axle and gross weight limits only.
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Fig. 1. Overview of pavement damage allocation system (Dodoo and Thorpe, 2004).
vehicle weight (e.g. in New Zealand, Switzerland, Germany and the UK). Again, all trucks are assumed to cause the same amount of damage whatever their actual weight (for example when running full or empty). Load equivalency factor estimates suggest that vehicles with the same gross vehicle weight can cause different amounts of damage depending on the number of axles used to distribute loads. The German system accounts for number of axles and gross vehicle weight while the system in New Zealand goes further to include the spacing of axles and number of tyres in the charging structure. Finally, the US HELP programme measures static axle weights at strategic points around the network, but this is only used for enforcing axle load limits. If these weights were used to estimate charges, this could have the distinct advantage of capturing some of the variation in actual axle weights that occurs as loads are delivered and collected at different locations. However, the principal disadvantages of this include the cost of installing and maintaining the roadside equipment necessary for static load measurement and the considerable errors in estimating damage estimates from static load measurements (see for example Cebon, 1999). 4. Development of a new pavement damage allocation system The concept behind our new system for allocating damage between individual HGVs evolves from the way HGVs cause road pavement damage as they travel around the road network. Fig. 1 presents an overview of the system. In light of the discussions in Sections 2 and 3, the key functional requirements for the new allocation system were identified as follows:
1. to estimate a vehicle’s position on the network with sufficient accuracy to determine the individual road links that have been traversed; 2. to measure vehicle speed and distance travelled on road links between any specified data polling interval; 3. to measure continuously the axle loads of a vehicle during a journey; 4. to store data measured during a journey for processing; 5. to provide a means of retrieving data recorded on the vehicle to the back office for processing; 6. to identify relevant pavement characteristics for all road links used by an individual HGV from a pavement database; and 7. to estimate the relative pavement damage caused by individual vehicles over a given distance or during a given period of time. The components of the system were therefore selected to meet these requirements. These components are; † an automatic vehicle positioning system to provide continuous data on vehicle position, speed and distance travelled; † a device capable of measuring continuously dynamic wheel loads; † an on-board system for processing and storing data; † a device for two-way vehicle/roadside data communication; † a digital road map database, which combines with the positioning system to provide vehicle route information; † a pavement database to provide information on pavement characteristics; and † a model to estimate pavement damage.
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The on-board system consists of a 12-channel GPS unit with an integrated internal antenna, a GSM unit and 1MB of data storage memory. A standard RS232 serial interface allows for integration with other devices, in this case the axle load measuring device. The 1MB data memory allows for a maximum storage of approximately 12,000 lines of ‘events’ representing almost 33 h of recording time at 10 s intervals before data must be uploaded. Once data are uploaded, the data storage memory is cleared to enable new data to be stored. A number of systems are available for on-board dynamic wheel load measurement for HGVs. Instrumented axles with strain gauges and accelerometers is considered the only practical way to measure accurately wheel forces generated by all axles of a vehicle (Cebon, 1999). However, as this method is considerably expensive this study adopted a low cost alternative comprising axle weight sensors (strain gauges) and a multiplexer. Sensors are embedded in each axle to measure the shear forces (as a voltage), which is converted by a microprocessor unit into an axle load in tonnes. Tests carried out on the system suggest that measured axle loads are accurate to 150 kg for a rear axle and 400 kg for a front axle (Phillips and Simmons, 1996). Predicting the performance of road pavements subjected to vehicle loads and climatic conditions remains an area fraught with numerous difficulties and uncertainties because of the complex interactions between vehicles, roads and the climate (Cebon, 1999). Analytical models are available (e.g. single-vehicle pass calculation and whole-life pavement models) to assess the relative impact of vehicle, pavement and climatic factors on the amount of pavement damage caused by HGVs (Cebon, 1999). The model developed in this study is based on these analytical methods and consists of two key components; a matrix of pavement damage variables and a table of pavement damage tariffs. The matrix of pavement damage is essentially a two-dimensional table Table 3 Example of variable matrix for pavement damage estimation
consisting of key vehicle, pavement and climatic variables necessary to estimate pavement damage caused by an HGV, and categories for each of these variables (Table 3). The pavement damage tariffs represent the relative amount of pavement damage caused for each combination of the pavement damage variables (e.g. the shaded cells in Table 3). Other variables required to estimate pavement damage but are relatively constant over time and space (e.g. vehicle suspension and axle properties) are taken into account using a pavement damage simulation model in the development of the pavement damage tariffs. The combination of variables shown by the shaded cells in Table 3 is used to determine the ‘damage tariff’ (of say 0.5 units of damage per unit distance travelled) from the damage tariff table generated using the Mathematical Model of Pavement Performance software (Ullidtz and Larsen, 1983; Hildebrand et al., 2003). This is an analytical model that simulates pavement damage in flexible pavements due to dynamic loads and climatic effects over time and predicts cracking, rutting and roughness damage. The tariff value remains constant whilst there is no change in the categories for the vehicle or pavement variables. However, if there is a change which results in a change in category (e.g. the vehicle turns from a flexible onto a rigid pavement), then the new value of ‘damage tariff’ corresponding to the new combination of circumstances is applied. Pavement damage is then calculated by multiplying the ‘damage tariff’ per unit distance travelled with the total distance travelled at that tariff value (Dodoo and Thorpe, 2004a,b). Fig. 2 shows an example of rutting damage caused in two different scenarios. A comparison of the rutting damage caused shows that, on average, approximately five times more rutting damage is caused for Case 2 compared to Case 1. Using this approach, pavement damage tariffs were developed for all possible combinations of vehicle,
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1.2 Case 1
Case 2
Rut Depth (mm)
1
0.8 Axle Load = 8t, Speed = 80kph, Pavement Type = Flexible Pavement Thickness = Thin, Pavement Roughness = Smooth, Season = Summer
0.6
0.4
0.2 Axle Load = 4t, Speed = 30kph, Pavement Type = Flexible Pavement Thickness = Thick, Pavement Roughness = Medium, Season = Spring
0 0
1
2
3
4
5
6
7
8
9
10
Years Fig. 2. Comparison of rutting damage caused for two scenarios.
pavement and seasonal factors (Table 3). An example of the tariffs for rutting damage is shown in the Appendix. Data on the properties of road links were required as an input to estimating pavement damage caused by the HGV. These data were to be obtained by linking road link pavement data (e.g. pavement type, thickness, rutting, cracking) available from the UK Highways Agency to road links of the OS MasterMap Integrated Transport Network (ITN) digital road map. However, synthetic pavement data (for pavement type, thickness and roughness) had to be generated as realistically as possible for road links in the OS MasterMap Integrated Transport Network (ITN) digital road map due to their current incompatibility with those in the Highways Agency’s pavement database (Dodoo and Thorpe, 2004). A Pentium III desktop computer running Microsoft Windows XP operates as the back-office system and manages remotely the upload of data from the vehicle onboard system via wireless data transfer (GSM). The backoffice system holds the OS MasterMap ITN layer, the synthetic pavement database for all road links, a mapmatching tool and the pavement damage estimation model (see Fig. 1).
unit and data storage memory) was installed in the driver’s cab connected to two front axle weighing sensors. Data were recorded approximately every 10 seconds by the system while the vehicle performed its normal day-today activities over a 60-day period. The system performed without malfunctioning and recorded data during journeys made by the HGV. Data were uploaded remotely from the on-board unit to the back-office system via the GSM link. Table 4 shows sample data obtained from the HGV. The processing of the uploaded data involves the following steps: 5.1. STEP 1.Identifying vehicle routes Vehicle position coordinates (shown in Table 4) are plotted onto the OS MasterMap ITN digital road map using ESRI ArcGIS software (Fig. 4). A map-matching tool developed in the project automatically identifies the road links used by the HGV. The map-matching algorithm used is a simplified version of the approach described by Quddus
5. Field trial of HGV pavement damage allocation system For the on-road demonstration of the new system, the front axle of an 18-tonne 2-axled HGV was instrumented (see Fig. 3). The front axle has single tyres at each wheel while the rear axle has a dual tyre arrangement. The HGV is fitted with parabolic leaf spring suspensions on both axles. The on-board unit (with the integrated GPS receiver, GSM
Fig. 3. Axle weight sensor embedded at one end of front axle.
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Table 4 Example of data uploaded to the HGV Event time
Position coordinates
13.09.2004 09:47:44 13.09.2004 09:47:34 13.09.2004 09:47:24
427,054 427,054 426,995
577,201 577,101 576,965
et al. (2003), due to an absence of road link connectivity data in the digital road maps available for this research. A list of road links and their properties corresponding to the route driven by the HGV is then generated by the mapmatching tool (Table 5). For each vehicle position associated with a road link, the exact location of the vehicle (Table 5 column 5) is calculated. This is a variable required to retrieve relevant pavement data over that particular section of the road link from the database. The distance travelled over each 10-s interval is also calculated. 5.2. Step 2.Establishing road link properties from the pavement database The next step is to determine the pavement properties of the road links identified in Step 1 from the road pavement database (Table 6). Using the unique road link identifier (LinkID) and the exact vehicle position on that link (Chainage on Link) the pavement type, category corresponding to the thickness of the wear course and level of pavement roughness are retrieved from the pavement database.
Av. speed (kph)
Heading (deg)
Axle Load (tonnes)
38.7 41.3 58.7
183.2 186.9 239.5
8.76 8.76 8.76
5.3. Step 3.Pavement damage estimation model This involves assembling the processed data from Steps 1 and 2 for all of the input variables in the matrix of the pavement damage model. These data are the axle weights, average speed and distance travelled between each data poll, pavement type, thickness and roughness (Table 7). From this, the appropriate damage tariffs are obtained from the ‘lookup’ table of predefined damage tariffs. The damage tariffs are (dimensionless) ratios of how much damage is caused by an HGV under a set of conditions defined in the pavement damage matrix (Table 3). Each damage tariff is then normalised for the distance travelled within that interval to obtain an estimate of damage caused over the distance travelled before the next poll event. By summing the estimates of damage calculated between poll events, an estimate of the total damage caused may be obtained for a whole journey. An analysis of different journeys undertaken by the instrumented HGV along the same route (i.e. set of road links) suggests that the amount of pavement damage caused varied by up to 40% for a 50 km journey.
Fig. 4. Vehicle positions plotted on the OS MasterMap ITN digital road map.
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Table 5 Results from map-matching for selected vehicle positions onto road links Link ID
Road number
Road name
Road class
Chainage on link (m)
Distance travelled (m)
74239 74550 74565 73179 73179 71861 71861 94432 94387
– B1326 B1326 A19 A19 A19 A19 A1058 A1058
N’BRIAN ROAD N’BRIAN ROAD N’BRIAN ROAD – – – – COAST ROAD COAST ROAD
Minor Road B Road B Road A Road A Road A Road A Road A Road A Road
321.7 0.0 118.1 63.2 275.0 120.3 519.6 175.6 7.4
107.5 111.1 114.7 163.1 154.4 243.6 282.2 220.1 191.1
6. Discussion From the results of the trial, there is every indication that the operation of an HGV charging system along the lines of that described above is certainly possible. However, a number of implementation issues need to be addressed. The first concerns the availability of on-board axle load sensors on HGVs, a cornerstone to achieving the polluter pays principle in HGV charging for pavement damage. In the UK, the Armitage Report (1980) recommended on-board axle weighing systems on HGVs primarily for enforcing axle overloading although there has been very little followup interest. This issue will need addressing to refine HGV charging systems to the level described here and could include technical and regulatory mechanisms involving national governments, vehicle manufacturers and HGV operators. The second issue concerns the availability of relevant data relating to the pavement properties of road links of the network. Pavement data is only currently available for the UK motorway and trunk road network, which accounts for approximately 4% of the total length of the network. However, there are plans in place to broaden the coverage of pavement data. This is expected to happen in the short to medium term as and when the programme of Traffic Speed Condition Surveys (TRACS) currently used on motorways and trunk roads is rolled out across the rest of the network (Ekins and Hawker, 2003; ODPM, 2003). Converting pavement damage into a road-use charge is also an important consideration. Charging HGVs for pavement damage involves a two stage process where damage is allocated to HGVs in proportion to the amount they are deemed to have caused (i.e. the allocation stage) and a costing stage where charge tariffs are then assigned to
the allocated pavement damage. The research described here focuses on the allocation stage of an HGV charging system, although it is also useful to identify a number of possible ways of setting charge tariffs for pavement damage. Figure 5 shows a road link initially at a given level of pavement serviceability A at time T0. As a result of pavement damage, there is a gradual (non-linear) decrease in serviceability to a level B. The road link can be restored to its initial serviceability A1 at time T1after rehabilitation at a cost of VX. Ideally, VX should be charged to all HGVs who have used this road link between T0 and T1 in proportion to the amount of damage each vehicle is estimated to have caused. In theory, it is possible to achieve this with the HGV charging system presented here although, in practice, several potential difficulties would need to be overcome. For example, charges can only be calculated when the road link is rehabilitated (thus revealing VX). Typically, this happens on average once every 10–20 years for most road links which seems incompatible with the need to generate sufficient income on a frequent basis to maintain the network. For the current stock of road links already in use it is not possible to apply this mechanism retrospectively as there are no data available on how much damage has already been caused and by whom. A more practical approach to determining pavement damage charges would be to use prevailing (annual) funding budgets for road infrastructure maintenance. In this approach, total annual maintenance costs resulting from HGV axle loadings (i.e. structural pavement damage) would be divided by the sum of all pavement damage accruing from HGVs to derive the charge per unit of pavement damage caused by each HGV. A similar principle was used to calculate the charge rate in the distance-based HGV
Table 6 Pavement properties of map-matched links Link ID
Road number
Chainage on link
Pavement type
Wear course thickness
Pavement roughness
74239 74550 74565 73179 73179 94432
– B1326 B1326 A19 A19 A1058
321.7 0.0 118.1 63.2 275.0 175.6
Flexible Flexible Flexible Flexible Flexible Flexible
Thin Thin Thin Thick Thick Thick
Medium Medium Medium Smooth Smooth Smooth
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Table 7 Sample calculation of pavement damage caused Link ID
Axle Load (tonnes)
Average speed (kph)
Pavement type
Wear course thickness
Pavement roughness
Season
Damage tariff (/m)
Distance travelled
Damage caused
74239 74550 74565 73179 73179 94432
8.76 8.76 8.76 8.76 8.76 8.76
38.7 40.0 41.3 58.7 55.6 79.5
Flexible Flexible Flexible Flexible Flexible Flexible
Thin Thin Thin Thick Thick Thick
Medium Medium Medium Smooth Smooth Smooth
Summer Summer Summer Summer Summer Summer
0.25 0.25 0.25 0.15 0.15 0.10
107.5 111.1 114.7 163.1 154.4 220.1
26.9 27.8 28.7 24.5 23.2 22.0
charging system in Switzerland (Balmer, 2003). Here, the tonne–kilometre rate was fixed by dividing the total transport costs not recovered through existing charges and taxes by the total annual tonne–kilometres travelled by domestic HGVs. The potential impacts of this new system relate mainly to HGV operation with charges being affected not only by the amount of load carried but also by factors such as the route taken, average speed or season of operation. Thus, the introduction of this damage-based charging system could encourage changes in fleet composition (e.g. to HGVs with higher numbers of axles), and route re-selection (e.g. to more durable pavements). In practice, many factors will influence the response of HGV operators. For example, Small et al. (1989) analysed the effect of charging HGVs per standard axle passage per mile in the US. They report that a freight operator seeking to switch to HGVs with more axles in order to reduce charges will have to consider capital and running costs of acquiring and using larger HGVs as well as the effect on fleet size, dispatch schedules and load sizes on the efficiency of freight operations. Changes in route (e.g. from a thin to a thick pavement) will depend on factors such as congestion levels, travel time and the location of distribution terminals. A further issue to be resolved is how to reconcile the objective of encouraging higher vehicle load factors to reduce traffic and emission levels by charging HGVs based on their maximum carrying capacities (e.g. in the Swiss and German systems), and encouraging lower axles loads to reduce pavement damage. These two objectives could be reconciled by using
A1
Serviceability
A
B
T0
T1
Time (years)
Fig. 5. Life cycle of road link serviceability.
appropriate vehicle configurations (i.e. size and number of axles) that will provide high vehicle load factors but also lead to reduced individual axle loads. Finally, the potential benefits of the widespread implementation of the pavement damage-based HGV charging system described in this paper include; † an improved system for the recovery of pavement damage costs from individual HGVs which encompasses more fully the EU’s policy of fair and efficient pricing; † improved knowledge on where and how much pavement damage is occurring around the network to inform maintenance activities and targeting of resources; and † improving loading practices such as reduced axle and vehicle over-loading.
7. Conclusions This paper describes the design, development and onroad demonstration of a prototype system for charging heavy goods vehicles for pavement damage caused. Research evidence suggests that the extent of pavement damage caused by HGVs is determined by a number of factors including; † dynamic axle loads; † axle and tyre characteristics; and † road pavement properties. Thus any system that attempts to charge individual HGVs fairly and efficiently should take these factors into account. A review of current HGV charging systems reveals that there is in general movement in the right direction towards fulfilling the objectives set out in the 1995 EC Green Paper by way of electronic distance-based charging systems for HGVs. However, these systems omit key factors such as axle loads and pavement properties, which are believed to be the most important factors in estimating pavement damage caused by HGVs. This leads to certain inconsistencies with the polluter pays principle, some of which have been discussed here. A new system which includes the key factors that determine the amount of pavement damage caused by
N.A. Dodoo, N. Thorpe / Transport Policy 12 (2005) 419–430
429
220 200
Rutting Damage Tariffs
180 160 140 120 100 80 60 40 20
100kph 60kph 40kph 30kph ) ph (k 20kph d ee 10kph Sp
0 6T
5T
4T
3T
Axle Load (t)
2T
1T
Fig. A1. Variation in rutting damage tariffs for axle load and speed.
individual HGVs has been developed and demonstrated in on-road trials. The trials have been successful in terms of the operation of the system and estimating the amount of pavement damage caused by an HGV by using a pavement damage model and data recorded by the prototype system. The methodology presented could help inform the process of developing and implementing fairer and more efficient systems for determining the amount of pavement damage caused by HGVs for charging purposes. Clearly, there are a number of implementation issues to be overcome particularly in terms of equipping vehicles with axle load sensors and the availability of pavement data. However, it is hoped that this research will inform the development and design of future systems for recovering the costs of pavement damage from HGVs.
† † † †
Cambridgeshire County Council, UK MAN Depot, UK Mr Walter Howe, UK. Dr Christian Busch, COWI A/S, Denmark.
Appendix Figs. A1 and A2.
250
Acknowledgements The authors wish to acknowledge the following for their support and help in this project; † † † † † † † †
Department for Transport, UK University of Newcastle upon Tyne, UK FELA Management AG, Switzerland COLAS Ltd, UK Roger West Ltd, UK Ordnance Survey, UK Highways Agency, UK Dotted Eyes, UK
Damage Tariffs
200
150
100
50 6T 5T
0 4T Summer Spring Autumn Season Winter
3T 2T 1T
(t) ad Lo e l Ax
Fig. A2. Variation in rutting damage tariffs for axle load and season.
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References Addis, R.R., Whitmarsh, R.A., 1981. Relative damaging power of wheel loads in mixed traffic, Laboratory Report LR 979. Transport and Road Research Laboratory, Crowthorne, Berkshire. Armitage, A., 1980. Inquiry on Lorries, People and the Environment. Department of Transport, London. Balmer, U., 2003. Practice and experience with implementing transport pricing reform in heavy goods transport in Switzerland, IMPRINTEUROPE Thematic Network—Implementing Pricing Policies in Transport: Phasing and Packaging, Brussels. Cebon, D., 1999. Handbook of Vehicle–Road Interaction. Swets and Zeitlinger, Lisse. Charpentier, G., Fremont, G., 2003. The ETC system for HGV on highways in Germany—First lessons after system opening, 10th World Congress and Exhibition on Intelligent Transport Systems and Services, Madrid. Department for Transport, 2004. National Road Condition Survey: 2003. Department for Transport, Transport Statistics, London. Dodgson, J., Buckland, M., Begg, M., Watkiss, P., Davison, P., Forster, D., Murrells, T., Walker, C., Ramdas, V., 2000. Lorry Track and Enviromnental Costs. Department for the Environment, Transport and the Regions, London. Dodoo, N.A., Thorpe, N., 2004a. The development of a GPS-based HGV charging system, 10th World Conference on Transport Research, Istanbul, Turkey. Dodoo, N.A., Thorpe, N., 2004b. Towards fair and efficient charging for heavy goods vehicles, 12th IEE International Conference on Road Transport Information and Control, RTIC 2004. Institution of Electrical Engineers, London, pp. 231–236. Eberstaller, B., 2003. The Austrian truck tolling system—system design, 10th World Congress and Exhibition on Intelligent Transport Systems and Services, Madrid, Spain. Ekins, J.D.K., Hawker, L.G., 2003. TRACS Type Surveys for Local Roads, Scoping Study. Highways Agency, UK. European Commission, 1995. Towards Fair and Efficient Pricing in Transport. European Commission, Directorate General for Transport, Brussels. Federal Highway Administration, 1997. Highway Cost Allocation Study. US Department of Transportation, Washington, DC. Gillespie, T.D., Karamihas, S.D., Sayers, M.W., Nasim, M.A., Hansen, W., Ehsan, N., 1993. NCHRP Report 353, Effects of Heavy-Vehicle Characteristics on Pavement Response and Performance. National Cooperative Highway Research Program, Transportation Research Board, Washington, DC. Gwilliam, K., Shalizi, Z., 1999. Road funds, user charges and taxes. The World Bank Research Observer 14 (2), 159–185. Hildebrand, G., Busch, C., Gleerup, S., Kristiansen, J., Mølga˚rd, K., Nielsen, E., Ullidtz, P., 2003. MMOPP4 [Program]. 2.2.1: Vejteknisk Institut.
HM Treasury, HM Customs and Excise and Department for Transport, 2004. Modernising the Taxation of the Haulage Industry: Lorry RoadUser Charge, Progress report three. HM Treasury, London. HM Treasury, HM Customs and Excise and Department for Transport, 2005. Modernising the Taxation of the Haulage Industry: Lorry RoadUser Charge, A discussion paper. HM Treasury, London. Huhtala, M., Pihlajamaki, J., Pienimaki, M., 1989. Effects of tires and tire pressures on road pavements. Transportation Research Record 1227, 107–114. Kageson, P., 2000. Bringing the Eurovignette to the Electronic Age: The Need to Change Directive 1999/62/EC to Allow Kilometre Charging for Heavy Goods Vehicles. European Federation for Transport and Environment, Brussels. Krebs, P. Balmer, U., 2002. Fair and efficient: the distance-related heavy vehicle fee (HVF) in Switzerland, Federal Department of the Environment, Transport, Energy and Communications. Link, H., Dodgson, J.S., Maibach, M., Herry, M., 1999. The Costs of Road Infrastructure and Congestion in Europe. Physica, New York, NY. Middleton, J., Rhodes, A.H., 1991. TORG Research Report No. 80, The Dynamic Loading of Road Pavements: A Study of the Relationships between Road-Profiles and Pavement Wear. Transport Operation Research Group, University of Newcastle. Ministry of Transport, 1964. Road Pricing: The Economic and Technical Possibilities. Ministry of Transport, London. Newbery, D.M., 1988. Road damage externalities and road user charges. Econometrica: Journal of the Econometric Society 56 (2), 295–316. ODPM, 2003. Guidance On Best Value Indicators, viewed 13 April 2004 http://www.odpm.gov.uk/stellent/groups/odpm_localgov/documents/ page/odpm_locgov_609123-10.hcsp. OECD, 1998. Dynamic Interaction between Vehicles and Infrastructure Experiment: Technical Report. OECD Road Transport Research, Brussels. Phillips, S.D., Simmons, I.C.P., 1996. An Evaluation of the Axload Heavy Goods Vehicle Axle Weighing System. Transport Research Laboratory, Crowthorne, Berkshire. Quddus, M.A., Ochieng, W.O., Zhao, L., Noland, R.B., 2003. A General map matching algorithm for transport telematics applications. GPS Solutions Journal 7 (3), 157–167. Small, K.A., Winston, C., Evans, C.A., 1989. Road Work: A New Highway Pricing and Investment Policy. Brookings Institution, Washington, DC. Starkie, D., 1988. The New Zealand road charging system. Journal of Transport Economics and Policy 22 (2), 239–245. Ullidtz, P., Larsen, B.K., 1983. Mathematical model for predicting pavement performance, Transportation Research Record No. 949, pp. 45–55. Volpe, J.A., 1994. IVHS Institutional Issues and Case Studies, HELP/ CRESENT Case Study. US Department of Transportation, Cambridge, Massachusetts.
A new approach for allocating pavement damage between heavy goods vehicles for road-user charging Nii Amoo Dodoo*, Neil Thorpe School of Civil Engineering and Geosciences, University of Newcastle upon Tyne, NE1 7RU, UK Accepted 24 June 2005
Abstract This paper argues that current Heavy Goods Vechicle (HGV) charging systems do not take into account key factors affecting the extent of pavement damage caused by individual HGVs. Thus, charges are poorly aligned to actual costs which is contrary to the EC’s polluter pays principle. This paper describes the development and on-road trials of a new system, which uses on-board axle weighing and satellite positioning technology to estimate the amount of pavement damage caused on individual road links by an individual HGV. Although the on-road trials of the system were successful and demonstrated how current HGV charging systems can be improved in order to align pavement costs more closely to pavement charges, the paper also notes a number of implementation issues that need to be overcome before widespread implementation of the system is practicable. q 2005 Elsevier Ltd. All rights reserved. Keywords: Pavement damage; Road-user charging; HGV charging systems
1. Introduction This paper describes the design, development and onroad demonstration of a new system for allocating pavement damage between individual Heavy Goods Vehicles (HGVs)1 for road user charging purposes. Ever since the publication of the Smeed Report in the mid-1960s (Ministry of Transport, 1964), the possible implementation of direct forms of road-user charging has attracted considerable interest. This interest stems from the potential contribution that charging could make in managing travel demand and the considerable net revenues that could be generated. As managing increasing traffic congestion is most often cited as the main motivation for considering the case for introducing charging, it is understandable that most attention has focussed on charging private cars. The European Commission’s Green Paper Towards Fair and Efficient Pricing in Transport (1995) discusses in * Corresponding author. E-mail addresses: [email protected] (N.A. Dodoo), neil.thorpe@ ncl.ac.uk (N. Thorpe). 1 Vehicles over 3.5 tonnes gross vehicle weight.
0967-070X/$ - see front matter q 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.tranpol.2005.06.009
depth the costs associated with transport to society, the inefficiencies in the transport market and their combined effect on the environment and socio-economic development of member states. The Green Paper identifies the principles of marginal cost pricing as a key requirement of a fair and efficient transport system, whereby charges paid by users for individual journeys are aligned to the actual (internal and external) costs of the journey. One of these costs is clearly the physical damage caused by vehicles to the road infrastructure. HGVs are responsible for almost all of the structural damage to road pavements which, in the UK, accounts for approximately two thirds of road maintenance expenditure (Department for Transport, 2004). Various mechanisms for internalising these costs are currently used worldwide in the form of annual taxes and user fees. However, the extent to which these taxes and fees are able to reflect the actual cost of damage caused by HGVs to road pavements has come under close scrutiny as part of the move towards fair and efficient pricing in transport. This is to ensure that each particular vehicle’s contribution to pavement damage is estimated accurately and charged for appropriately. If all HGVs caused the same amount of damage per unit distance travelled, irrespective of (for example) their speed and actual gross vehicle weight, then a simple distance-based charging system could be used. In reality however, the relative amount of damage caused by individual
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HGVs varies widely depending on a number of vehicle, pavement and climatic characteristics. We argue therefore, that these various characteristics must be properly taken into account to ensure that individual HGVs pay a fair and efficient charge appropriate to the actual amount of damage they cause. A fundamental problem with most current charging systems lies in the methodologies used, albeit successfully over recent decades, to recover costs from users of transport infrastructure for pavement damage caused. This paper argues that these methods are unable to implement current and emerging charging objectives, which seek to charge users based on the costs of individual journeys. With respect to HGVs and pavement damage, current understanding of the mechanisms relating vehicles with pavement damage gives further impetus to the development of new charging methodologies, which embrace the ideals of a sustainable transport policy. In 1988, the transport economist David Newbery suggested that: “If every link in the road network had a tollgate, then vehicles could be charged at a vehicle and road specific rate (per axle weight-km, at different rates depending on the characteristics of the road, or the road type, measured by the pavement strength, traffic flow, maintenance strategy). In practice, of course, such fine-tuning of the system of road user charges is impractical with current technology” (Newbery, 1988, p. 298). Since then, there have been significant technological advances which now make such a system a far more realistic proposition. The development of such a system is the focus of this paper. The overall aims of this paper are; 1. to identify what characteristics affect the amount of damage caused that should be taken into account when calculating charges (Section 2); 2. to assess how well current HGV charging systems are able to achieve the EC’s goal of fair and efficient pricing (Section 3); 3. to describe the concept, development and field trial of a new system that includes key variables affecting the extent of pavement damage caused to relate charges more closely to pavement damage costs (Sections 4 and 5); and 4. to discuss issues relating to the future implementation of the system (Section 6).
pavements have changed significantly in terms of materials and methods of construction and vehicles today have very different designs and configurations from those in the 1960s (Cebon, 1999). Subsequent research has led to a much clearer understanding of the interaction between vehicles, pavements and the climate and the nature and extent of the factors responsible for road pavement damage. Differences between vehicles in terms of their loading conditions and physical characteristics, such as axle configuration (e.g. number and spacing), tyre type and configuration (e.g. single, dual or wide-base single) and suspension type (e.g. air or steel), can cause the nature and extent of loads and stresses imposed on pavement structures, and hence the amount of pavement damage caused, to vary considerably in time and space. Different pavement types (e.g. flexible and rigid) are susceptible to different forms of pavement damage (e.g. cracking or rutting) while thicker pavement structures possess stronger structural capacities that are able to withstand higher axle loads and stresses and hence sustain less pavement damage from axle loads. Increased surface roughness can also lead to the generation of greater levels of dynamic axle loading and consequently more pavement damage. Finally, variations in climatic conditions (e.g. moisture and temperature) lead to changes in the material properties and structural strength of the pavement and, as a consequence, affect the amount of pavement damage caused by axle loads. The significance and relative importance of these variables and how they affect the nature and extent of pavement damage has been studied widely over the years (see for example Addis and Whitmarsh, 1981; Middleton and Rhodes, 1991; Gillespie et al., 1993; OECD, 1998). For example, Gillespie et al. (1993) report that variations in axle loads and pavement thickness are the two most important factors and can cause pavement damage to vary by a factor of over 20. Tyre type (e.g. wide-base against single dual) can cause pavement damage to increase by a factor of 1.5–4. Similarly, the extent of roughness can affect the amount of pavement damage by between 30–50% (Huhtala et al., 1989; Gillespie et al., 1993; OECD, 1998). Research suggests that all these factors (e.g. gross vehicle weight, tyre type, pavement roughness, suspension type, vehicle speed and pavement temperature) either solely or interacting with each other can lead to significant variations in the amount of pavement damage caused. What is very clear is that the damaging effect of individual HGVs varies over time and space. The following section describes how well these variations are accommodated in current HGV charging systems.
2. The factors affecting the extent of pavement damage caused by HGVs 3. Road cost allocation and HGV charging systems Since the American Association of State Highway Officials’ (AASHO) road tests in the 1960s, which resulted in the ‘fourth power law’ to assist in designing pavements and allocating highway costs between different user classes,
The OECD (1998) estimates that construction and maintenance of road networks consume between 0.2–1.9% of a country’s GNP. Pavement designers attribute all
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pavement damage to HGVs with pavement maintenance activities resulting from HGV loading forming a significant proportion of total road budgets in most countries and accounting for up to 75% of total road infrastructure investment (Gwilliam and Shalizi, 1999). The ‘Cost Occasioned Approach’ which is applied in road track cost allocation methods is the most commonly used method for determining taxes and charges to raise funds for road construction and maintenance (Federal Highway Administration, 1997). It is based on the principle that each user of the road pays for the costs they incur on it. Pavement costs (e.g. maintenance and reconstruction) are allocated to different vehicle classes based on their collective responsibility for different components of these costs using a variety of measures (e.g. vehicle-kms travelled, standard-axle-kms and PCU-kms) assumed to relate vehicle use to road costs. Link et al. (1999) review the application of this method in a number of European countries. Despite worldwide usage, the implementation of the road cost allocation and charging mechanism described above suffers from important weaknesses undermining their ability to apply the ‘polluter pays’ principle. First, data used in road track cost allocation methods are at best crude averages of road usage for individual HGVs in which the relationship between costs and charges is weak. For example, in the UK, Dodgson et al. (2000) proposed an improved method for allocating road track costs which included more refined categories for HGV class, vehicle characteristics (e.g. tyre and suspension types) and road type. Second, the use of fuel tax as the principal mechanism for recovering charges is debatable as fuel consumption is a poor proxy for pavement damage costs. A further issue of concern here is the recovery of costs caused by ‘foreign’ vehicles on a nation’s roads. Thus, the main shortcoming with these traditional applications stems from their inability to capture fully the principle on which it is based (the polluter pays)–that is, different vehicles within each class pay equal amounts in terms of indirect charges irrespective of their individual contribution to road costs. Furthermore, traditional forms of direct charges, which are based on distance travelled, are poor proxies for the extent of pavement damage caused. A number of countries (e.g. Switzerland, Austria and Germany) have tried to correct these inconsistencies through new cost recovery schemes that attempt to recover the true costs of pavement damage from the actual vehicles that are causing the damage. In the Swiss system, the distances travelled by each HGV on all public roads in the country are measured using the tachograph. A microwave-based On Board Unit (OBU) using Dedicated Short Range Communications (DSRC) technology installed in each HGV then records these distances. Data are downloaded from the OBU to a chipcard each month for billing purposes by the Swiss Customs Authority. Distance measurement is switched off when an HGV leaves the country at the border and on again when it returns. Charges are calculated based on the distance
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travelled, maximum permissible vehicle weight and emission class of the HGV (Krebs and Balmer, 2002). In contrast, the Austrian HGV charging system applies only to the motorway network. This network has been divided into 800 separate sections using microwave based, multi-lane toll gantries that allow tolls to be collected automatically from HGVs (over 3.5 tonnes GVW) at normal traffic speeds when passing under a toll gantry (Eberstaller, 2003). Similarly, the German system operates only on the autobahn network but applies only to HGVs over 12 tonnes (GVW). Unlike the Swiss and Austrian charging systems that use microwave technology, the German system uses onboard satellite, digital map and GSM communication technologies. The position of an HGV on the road network obtained from GPS satellites is compared continuously to a digital map of toll roads as the vehicle travels around the network. An HGV is charged when the OBU identifies that the HGV is travelling on a tolled road. Distance travelled is obtained from the digital road map. The charge rate depends on the number of axles, maximum permissible vehicle weight and emission class of the HGV (Charpentier and Fremont, 2003). Drawing upon available literature, Table 1 presents a summary of these and other HGV charging systems world-wide (Starkie, 1988; Volpe, 1994; Kageson, 2000; HM Treasury et al., 2004, 2005). Table 2 then summarises for each system which of the key factors that affect the amount of damage caused are actually taken into account when calculating the appropriate charge per vehicle. In practice, these variables that all affect the amount of pavement damage caused can vary frequently during a journey for individual vehicles as they travel around at different speeds, on different types of pavements carrying loads that can increase and decrease as goods are collected and delivered. Referring to Table 2, none of these systems take into account pavement characteristics (e.g. type and roughness) or prevailing climatic conditions when estimating the extent of pavement damage caused. Three of the systems (The Eurovignette, the Swiss HVF and the system in Germany) do differentiate charges on the basis of emission class in attempt to internalise some of the costs associated with atmospheric pollution. This leaves vehicle characteristics as the sole determinants of the level of charge payable. Axle loads are the most important factor determining the extent of pavement damage caused (Section 2) and the seven charging systems account for this in three ways. The first approach, as employed in the Eurovignette system, is not to include any representation of axle loads at all. Thus, all HGVs are charged the same per unit distance travelled irrespective of their actual weight. We estimate, using simple load equivalency factor calculations, that a 44-tonne 6 axle HGV causes approximately 75 times more damage when fully laden compared to when empty. Apart from the system in Switzerland, the rest differentiate charges by number of axles (e.g. 2, 3, 4C) but again this leads to
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Table 1 Summary table of key features of current and proposed HGV charging systems Country of operation
Implementation date
Charging parameters
System description
Network coverage
Vehicles charged
Payment Method
New Zealand
1st April 1978
Hubodometer measures distance travelled. Distance licence purchased
All public roads
All HGVs O 3.5 tonnes GVW
Pre-payment at post offices. licences bought in multiples of 1000 km
Germany, Netherlands, Belgium, Luxembourg, DenmarkCSweden ‘The Eurovignette’
1st January 1995
Distance travelled, number and spacing of axles, number of tyres, maximum permissible gross vehicle weight Number of axles, emission class
Motorways only
HGVs O 12 tonnes
Pre-payment
USA HELP programme
October 1993
Distance travelled
Designated sections of highways in 24 states
Participating HGVs
Post payment by invoicing operators
Switzerland
1st January 2001
All public roads
HGVs O 3.5 tonnes
Vehicle journey data downloaded via chip card or modem to billing centre
Austria
1st January 2004
Distance travelled, max. permissible gross vehicle weight, emission class Distance travelled, number of axles (2, 3 and 4C)
Motorways and expressways
All HGVs O 3.5 tonnes
Post payment by bill and pre-payment with on-board account
Germany
1st January 2005
Paper-disc (weekly, monthly or annually) giving access to motorway network in participating countries Automatic vehicle identification and classification system allows vehicles to by-pass toll stations. Vehicles weighed by weigh-in-motion systems. GPS and DSRC; distance travelled measured using tachograph complemented by GPS DSRC based system. Tolls collected separately on each of the 800 sections of the network GPS/GSM based system with onboard digital map of tolled roads. DSRC for enforcement
Motorways only
HGVs O 12 tonnes
Post and pre payment options available
UK
2007/ 2008
All public roads
HGVs O3.5 tonnes
Not known but probably pre and post payment options
Distance travelled, number of axles, max. permissible gross vehicle weight, emission class Distance travelled, road class, number of axles (2, 3, 4C), emission class
Not yet known but probably GPS based
certain anomalies because of the number of axle categories used. For example, a five axle truck weighing 40 tonnes causes approximately twice the amount of damage per unit distance than a six axle truck with the same weight.
However, the axle categories defined (for example in the Austrian system) result in both trucks paying the same charge. The second axle load proxy is to vary charges depending on a vehicle’s maximum permissible gross
Table 2 Pavement damage factors and their inclusion in HGV charging systems Country
Dynamic axle loads
Number of axles
Type of axle
Tyre type
Pavement type
Pavement thickness
Temperature and moisture
Distance travelled
New Zealand Eurovignette HELP (US) Switzerland Austria Germany UK
No No (Noa) No No No No
Yes Yes Yes No Yes Yes Yes
No No No No No No No
No No No No No No No
No No No No No No No
No No No No No No No
No No No No No No No
Yes No Yes Yes Yes Yes Yes
a
Weigh-In-Motion used for enforcement of axle and gross weight limits only.
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Fig. 1. Overview of pavement damage allocation system (Dodoo and Thorpe, 2004).
vehicle weight (e.g. in New Zealand, Switzerland, Germany and the UK). Again, all trucks are assumed to cause the same amount of damage whatever their actual weight (for example when running full or empty). Load equivalency factor estimates suggest that vehicles with the same gross vehicle weight can cause different amounts of damage depending on the number of axles used to distribute loads. The German system accounts for number of axles and gross vehicle weight while the system in New Zealand goes further to include the spacing of axles and number of tyres in the charging structure. Finally, the US HELP programme measures static axle weights at strategic points around the network, but this is only used for enforcing axle load limits. If these weights were used to estimate charges, this could have the distinct advantage of capturing some of the variation in actual axle weights that occurs as loads are delivered and collected at different locations. However, the principal disadvantages of this include the cost of installing and maintaining the roadside equipment necessary for static load measurement and the considerable errors in estimating damage estimates from static load measurements (see for example Cebon, 1999). 4. Development of a new pavement damage allocation system The concept behind our new system for allocating damage between individual HGVs evolves from the way HGVs cause road pavement damage as they travel around the road network. Fig. 1 presents an overview of the system. In light of the discussions in Sections 2 and 3, the key functional requirements for the new allocation system were identified as follows:
1. to estimate a vehicle’s position on the network with sufficient accuracy to determine the individual road links that have been traversed; 2. to measure vehicle speed and distance travelled on road links between any specified data polling interval; 3. to measure continuously the axle loads of a vehicle during a journey; 4. to store data measured during a journey for processing; 5. to provide a means of retrieving data recorded on the vehicle to the back office for processing; 6. to identify relevant pavement characteristics for all road links used by an individual HGV from a pavement database; and 7. to estimate the relative pavement damage caused by individual vehicles over a given distance or during a given period of time. The components of the system were therefore selected to meet these requirements. These components are; † an automatic vehicle positioning system to provide continuous data on vehicle position, speed and distance travelled; † a device capable of measuring continuously dynamic wheel loads; † an on-board system for processing and storing data; † a device for two-way vehicle/roadside data communication; † a digital road map database, which combines with the positioning system to provide vehicle route information; † a pavement database to provide information on pavement characteristics; and † a model to estimate pavement damage.
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The on-board system consists of a 12-channel GPS unit with an integrated internal antenna, a GSM unit and 1MB of data storage memory. A standard RS232 serial interface allows for integration with other devices, in this case the axle load measuring device. The 1MB data memory allows for a maximum storage of approximately 12,000 lines of ‘events’ representing almost 33 h of recording time at 10 s intervals before data must be uploaded. Once data are uploaded, the data storage memory is cleared to enable new data to be stored. A number of systems are available for on-board dynamic wheel load measurement for HGVs. Instrumented axles with strain gauges and accelerometers is considered the only practical way to measure accurately wheel forces generated by all axles of a vehicle (Cebon, 1999). However, as this method is considerably expensive this study adopted a low cost alternative comprising axle weight sensors (strain gauges) and a multiplexer. Sensors are embedded in each axle to measure the shear forces (as a voltage), which is converted by a microprocessor unit into an axle load in tonnes. Tests carried out on the system suggest that measured axle loads are accurate to 150 kg for a rear axle and 400 kg for a front axle (Phillips and Simmons, 1996). Predicting the performance of road pavements subjected to vehicle loads and climatic conditions remains an area fraught with numerous difficulties and uncertainties because of the complex interactions between vehicles, roads and the climate (Cebon, 1999). Analytical models are available (e.g. single-vehicle pass calculation and whole-life pavement models) to assess the relative impact of vehicle, pavement and climatic factors on the amount of pavement damage caused by HGVs (Cebon, 1999). The model developed in this study is based on these analytical methods and consists of two key components; a matrix of pavement damage variables and a table of pavement damage tariffs. The matrix of pavement damage is essentially a two-dimensional table Table 3 Example of variable matrix for pavement damage estimation
consisting of key vehicle, pavement and climatic variables necessary to estimate pavement damage caused by an HGV, and categories for each of these variables (Table 3). The pavement damage tariffs represent the relative amount of pavement damage caused for each combination of the pavement damage variables (e.g. the shaded cells in Table 3). Other variables required to estimate pavement damage but are relatively constant over time and space (e.g. vehicle suspension and axle properties) are taken into account using a pavement damage simulation model in the development of the pavement damage tariffs. The combination of variables shown by the shaded cells in Table 3 is used to determine the ‘damage tariff’ (of say 0.5 units of damage per unit distance travelled) from the damage tariff table generated using the Mathematical Model of Pavement Performance software (Ullidtz and Larsen, 1983; Hildebrand et al., 2003). This is an analytical model that simulates pavement damage in flexible pavements due to dynamic loads and climatic effects over time and predicts cracking, rutting and roughness damage. The tariff value remains constant whilst there is no change in the categories for the vehicle or pavement variables. However, if there is a change which results in a change in category (e.g. the vehicle turns from a flexible onto a rigid pavement), then the new value of ‘damage tariff’ corresponding to the new combination of circumstances is applied. Pavement damage is then calculated by multiplying the ‘damage tariff’ per unit distance travelled with the total distance travelled at that tariff value (Dodoo and Thorpe, 2004a,b). Fig. 2 shows an example of rutting damage caused in two different scenarios. A comparison of the rutting damage caused shows that, on average, approximately five times more rutting damage is caused for Case 2 compared to Case 1. Using this approach, pavement damage tariffs were developed for all possible combinations of vehicle,
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1.2 Case 1
Case 2
Rut Depth (mm)
1
0.8 Axle Load = 8t, Speed = 80kph, Pavement Type = Flexible Pavement Thickness = Thin, Pavement Roughness = Smooth, Season = Summer
0.6
0.4
0.2 Axle Load = 4t, Speed = 30kph, Pavement Type = Flexible Pavement Thickness = Thick, Pavement Roughness = Medium, Season = Spring
0 0
1
2
3
4
5
6
7
8
9
10
Years Fig. 2. Comparison of rutting damage caused for two scenarios.
pavement and seasonal factors (Table 3). An example of the tariffs for rutting damage is shown in the Appendix. Data on the properties of road links were required as an input to estimating pavement damage caused by the HGV. These data were to be obtained by linking road link pavement data (e.g. pavement type, thickness, rutting, cracking) available from the UK Highways Agency to road links of the OS MasterMap Integrated Transport Network (ITN) digital road map. However, synthetic pavement data (for pavement type, thickness and roughness) had to be generated as realistically as possible for road links in the OS MasterMap Integrated Transport Network (ITN) digital road map due to their current incompatibility with those in the Highways Agency’s pavement database (Dodoo and Thorpe, 2004). A Pentium III desktop computer running Microsoft Windows XP operates as the back-office system and manages remotely the upload of data from the vehicle onboard system via wireless data transfer (GSM). The backoffice system holds the OS MasterMap ITN layer, the synthetic pavement database for all road links, a mapmatching tool and the pavement damage estimation model (see Fig. 1).
unit and data storage memory) was installed in the driver’s cab connected to two front axle weighing sensors. Data were recorded approximately every 10 seconds by the system while the vehicle performed its normal day-today activities over a 60-day period. The system performed without malfunctioning and recorded data during journeys made by the HGV. Data were uploaded remotely from the on-board unit to the back-office system via the GSM link. Table 4 shows sample data obtained from the HGV. The processing of the uploaded data involves the following steps: 5.1. STEP 1.Identifying vehicle routes Vehicle position coordinates (shown in Table 4) are plotted onto the OS MasterMap ITN digital road map using ESRI ArcGIS software (Fig. 4). A map-matching tool developed in the project automatically identifies the road links used by the HGV. The map-matching algorithm used is a simplified version of the approach described by Quddus
5. Field trial of HGV pavement damage allocation system For the on-road demonstration of the new system, the front axle of an 18-tonne 2-axled HGV was instrumented (see Fig. 3). The front axle has single tyres at each wheel while the rear axle has a dual tyre arrangement. The HGV is fitted with parabolic leaf spring suspensions on both axles. The on-board unit (with the integrated GPS receiver, GSM
Fig. 3. Axle weight sensor embedded at one end of front axle.
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Table 4 Example of data uploaded to the HGV Event time
Position coordinates
13.09.2004 09:47:44 13.09.2004 09:47:34 13.09.2004 09:47:24
427,054 427,054 426,995
577,201 577,101 576,965
et al. (2003), due to an absence of road link connectivity data in the digital road maps available for this research. A list of road links and their properties corresponding to the route driven by the HGV is then generated by the mapmatching tool (Table 5). For each vehicle position associated with a road link, the exact location of the vehicle (Table 5 column 5) is calculated. This is a variable required to retrieve relevant pavement data over that particular section of the road link from the database. The distance travelled over each 10-s interval is also calculated. 5.2. Step 2.Establishing road link properties from the pavement database The next step is to determine the pavement properties of the road links identified in Step 1 from the road pavement database (Table 6). Using the unique road link identifier (LinkID) and the exact vehicle position on that link (Chainage on Link) the pavement type, category corresponding to the thickness of the wear course and level of pavement roughness are retrieved from the pavement database.
Av. speed (kph)
Heading (deg)
Axle Load (tonnes)
38.7 41.3 58.7
183.2 186.9 239.5
8.76 8.76 8.76
5.3. Step 3.Pavement damage estimation model This involves assembling the processed data from Steps 1 and 2 for all of the input variables in the matrix of the pavement damage model. These data are the axle weights, average speed and distance travelled between each data poll, pavement type, thickness and roughness (Table 7). From this, the appropriate damage tariffs are obtained from the ‘lookup’ table of predefined damage tariffs. The damage tariffs are (dimensionless) ratios of how much damage is caused by an HGV under a set of conditions defined in the pavement damage matrix (Table 3). Each damage tariff is then normalised for the distance travelled within that interval to obtain an estimate of damage caused over the distance travelled before the next poll event. By summing the estimates of damage calculated between poll events, an estimate of the total damage caused may be obtained for a whole journey. An analysis of different journeys undertaken by the instrumented HGV along the same route (i.e. set of road links) suggests that the amount of pavement damage caused varied by up to 40% for a 50 km journey.
Fig. 4. Vehicle positions plotted on the OS MasterMap ITN digital road map.
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Table 5 Results from map-matching for selected vehicle positions onto road links Link ID
Road number
Road name
Road class
Chainage on link (m)
Distance travelled (m)
74239 74550 74565 73179 73179 71861 71861 94432 94387
– B1326 B1326 A19 A19 A19 A19 A1058 A1058
N’BRIAN ROAD N’BRIAN ROAD N’BRIAN ROAD – – – – COAST ROAD COAST ROAD
Minor Road B Road B Road A Road A Road A Road A Road A Road A Road
321.7 0.0 118.1 63.2 275.0 120.3 519.6 175.6 7.4
107.5 111.1 114.7 163.1 154.4 243.6 282.2 220.1 191.1
6. Discussion From the results of the trial, there is every indication that the operation of an HGV charging system along the lines of that described above is certainly possible. However, a number of implementation issues need to be addressed. The first concerns the availability of on-board axle load sensors on HGVs, a cornerstone to achieving the polluter pays principle in HGV charging for pavement damage. In the UK, the Armitage Report (1980) recommended on-board axle weighing systems on HGVs primarily for enforcing axle overloading although there has been very little followup interest. This issue will need addressing to refine HGV charging systems to the level described here and could include technical and regulatory mechanisms involving national governments, vehicle manufacturers and HGV operators. The second issue concerns the availability of relevant data relating to the pavement properties of road links of the network. Pavement data is only currently available for the UK motorway and trunk road network, which accounts for approximately 4% of the total length of the network. However, there are plans in place to broaden the coverage of pavement data. This is expected to happen in the short to medium term as and when the programme of Traffic Speed Condition Surveys (TRACS) currently used on motorways and trunk roads is rolled out across the rest of the network (Ekins and Hawker, 2003; ODPM, 2003). Converting pavement damage into a road-use charge is also an important consideration. Charging HGVs for pavement damage involves a two stage process where damage is allocated to HGVs in proportion to the amount they are deemed to have caused (i.e. the allocation stage) and a costing stage where charge tariffs are then assigned to
the allocated pavement damage. The research described here focuses on the allocation stage of an HGV charging system, although it is also useful to identify a number of possible ways of setting charge tariffs for pavement damage. Figure 5 shows a road link initially at a given level of pavement serviceability A at time T0. As a result of pavement damage, there is a gradual (non-linear) decrease in serviceability to a level B. The road link can be restored to its initial serviceability A1 at time T1after rehabilitation at a cost of VX. Ideally, VX should be charged to all HGVs who have used this road link between T0 and T1 in proportion to the amount of damage each vehicle is estimated to have caused. In theory, it is possible to achieve this with the HGV charging system presented here although, in practice, several potential difficulties would need to be overcome. For example, charges can only be calculated when the road link is rehabilitated (thus revealing VX). Typically, this happens on average once every 10–20 years for most road links which seems incompatible with the need to generate sufficient income on a frequent basis to maintain the network. For the current stock of road links already in use it is not possible to apply this mechanism retrospectively as there are no data available on how much damage has already been caused and by whom. A more practical approach to determining pavement damage charges would be to use prevailing (annual) funding budgets for road infrastructure maintenance. In this approach, total annual maintenance costs resulting from HGV axle loadings (i.e. structural pavement damage) would be divided by the sum of all pavement damage accruing from HGVs to derive the charge per unit of pavement damage caused by each HGV. A similar principle was used to calculate the charge rate in the distance-based HGV
Table 6 Pavement properties of map-matched links Link ID
Road number
Chainage on link
Pavement type
Wear course thickness
Pavement roughness
74239 74550 74565 73179 73179 94432
– B1326 B1326 A19 A19 A1058
321.7 0.0 118.1 63.2 275.0 175.6
Flexible Flexible Flexible Flexible Flexible Flexible
Thin Thin Thin Thick Thick Thick
Medium Medium Medium Smooth Smooth Smooth
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Table 7 Sample calculation of pavement damage caused Link ID
Axle Load (tonnes)
Average speed (kph)
Pavement type
Wear course thickness
Pavement roughness
Season
Damage tariff (/m)
Distance travelled
Damage caused
74239 74550 74565 73179 73179 94432
8.76 8.76 8.76 8.76 8.76 8.76
38.7 40.0 41.3 58.7 55.6 79.5
Flexible Flexible Flexible Flexible Flexible Flexible
Thin Thin Thin Thick Thick Thick
Medium Medium Medium Smooth Smooth Smooth
Summer Summer Summer Summer Summer Summer
0.25 0.25 0.25 0.15 0.15 0.10
107.5 111.1 114.7 163.1 154.4 220.1
26.9 27.8 28.7 24.5 23.2 22.0
charging system in Switzerland (Balmer, 2003). Here, the tonne–kilometre rate was fixed by dividing the total transport costs not recovered through existing charges and taxes by the total annual tonne–kilometres travelled by domestic HGVs. The potential impacts of this new system relate mainly to HGV operation with charges being affected not only by the amount of load carried but also by factors such as the route taken, average speed or season of operation. Thus, the introduction of this damage-based charging system could encourage changes in fleet composition (e.g. to HGVs with higher numbers of axles), and route re-selection (e.g. to more durable pavements). In practice, many factors will influence the response of HGV operators. For example, Small et al. (1989) analysed the effect of charging HGVs per standard axle passage per mile in the US. They report that a freight operator seeking to switch to HGVs with more axles in order to reduce charges will have to consider capital and running costs of acquiring and using larger HGVs as well as the effect on fleet size, dispatch schedules and load sizes on the efficiency of freight operations. Changes in route (e.g. from a thin to a thick pavement) will depend on factors such as congestion levels, travel time and the location of distribution terminals. A further issue to be resolved is how to reconcile the objective of encouraging higher vehicle load factors to reduce traffic and emission levels by charging HGVs based on their maximum carrying capacities (e.g. in the Swiss and German systems), and encouraging lower axles loads to reduce pavement damage. These two objectives could be reconciled by using
A1
Serviceability
A
B
T0
T1
Time (years)
Fig. 5. Life cycle of road link serviceability.
appropriate vehicle configurations (i.e. size and number of axles) that will provide high vehicle load factors but also lead to reduced individual axle loads. Finally, the potential benefits of the widespread implementation of the pavement damage-based HGV charging system described in this paper include; † an improved system for the recovery of pavement damage costs from individual HGVs which encompasses more fully the EU’s policy of fair and efficient pricing; † improved knowledge on where and how much pavement damage is occurring around the network to inform maintenance activities and targeting of resources; and † improving loading practices such as reduced axle and vehicle over-loading.
7. Conclusions This paper describes the design, development and onroad demonstration of a prototype system for charging heavy goods vehicles for pavement damage caused. Research evidence suggests that the extent of pavement damage caused by HGVs is determined by a number of factors including; † dynamic axle loads; † axle and tyre characteristics; and † road pavement properties. Thus any system that attempts to charge individual HGVs fairly and efficiently should take these factors into account. A review of current HGV charging systems reveals that there is in general movement in the right direction towards fulfilling the objectives set out in the 1995 EC Green Paper by way of electronic distance-based charging systems for HGVs. However, these systems omit key factors such as axle loads and pavement properties, which are believed to be the most important factors in estimating pavement damage caused by HGVs. This leads to certain inconsistencies with the polluter pays principle, some of which have been discussed here. A new system which includes the key factors that determine the amount of pavement damage caused by
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220 200
Rutting Damage Tariffs
180 160 140 120 100 80 60 40 20
100kph 60kph 40kph 30kph ) ph (k 20kph d ee 10kph Sp
0 6T
5T
4T
3T
Axle Load (t)
2T
1T
Fig. A1. Variation in rutting damage tariffs for axle load and speed.
individual HGVs has been developed and demonstrated in on-road trials. The trials have been successful in terms of the operation of the system and estimating the amount of pavement damage caused by an HGV by using a pavement damage model and data recorded by the prototype system. The methodology presented could help inform the process of developing and implementing fairer and more efficient systems for determining the amount of pavement damage caused by HGVs for charging purposes. Clearly, there are a number of implementation issues to be overcome particularly in terms of equipping vehicles with axle load sensors and the availability of pavement data. However, it is hoped that this research will inform the development and design of future systems for recovering the costs of pavement damage from HGVs.
† † † †
Cambridgeshire County Council, UK MAN Depot, UK Mr Walter Howe, UK. Dr Christian Busch, COWI A/S, Denmark.
Appendix Figs. A1 and A2.
250
Acknowledgements The authors wish to acknowledge the following for their support and help in this project; † † † † † † † †
Department for Transport, UK University of Newcastle upon Tyne, UK FELA Management AG, Switzerland COLAS Ltd, UK Roger West Ltd, UK Ordnance Survey, UK Highways Agency, UK Dotted Eyes, UK
Damage Tariffs
200
150
100
50 6T 5T
0 4T Summer Spring Autumn Season Winter
3T 2T 1T
(t) ad Lo e l Ax
Fig. A2. Variation in rutting damage tariffs for axle load and season.
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