National Academies Press: OpenBook

State Highway Cost Allocation Studies (2008)

Chapter: Chapter Three - State of the Practice

« Previous: Chapter Two - History and Evolution of Highway Cost Allocation Studies
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2008. State Highway Cost Allocation Studies. Washington, DC: The National Academies Press. doi: 10.17226/14178.
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2008. State Highway Cost Allocation Studies. Washington, DC: The National Academies Press. doi: 10.17226/14178.
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2008. State Highway Cost Allocation Studies. Washington, DC: The National Academies Press. doi: 10.17226/14178.
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2008. State Highway Cost Allocation Studies. Washington, DC: The National Academies Press. doi: 10.17226/14178.
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2008. State Highway Cost Allocation Studies. Washington, DC: The National Academies Press. doi: 10.17226/14178.
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2008. State Highway Cost Allocation Studies. Washington, DC: The National Academies Press. doi: 10.17226/14178.
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2008. State Highway Cost Allocation Studies. Washington, DC: The National Academies Press. doi: 10.17226/14178.
×
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2008. State Highway Cost Allocation Studies. Washington, DC: The National Academies Press. doi: 10.17226/14178.
×
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2008. State Highway Cost Allocation Studies. Washington, DC: The National Academies Press. doi: 10.17226/14178.
×
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2008. State Highway Cost Allocation Studies. Washington, DC: The National Academies Press. doi: 10.17226/14178.
×
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2008. State Highway Cost Allocation Studies. Washington, DC: The National Academies Press. doi: 10.17226/14178.
×
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2008. State Highway Cost Allocation Studies. Washington, DC: The National Academies Press. doi: 10.17226/14178.
×
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Suggested Citation:"Chapter Three - State of the Practice." National Academies of Sciences, Engineering, and Medicine. 2008. State Highway Cost Allocation Studies. Washington, DC: The National Academies Press. doi: 10.17226/14178.
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In reflecting on the history of HCASs conducted over the past 70 years, one point comes across most clearly: the motivation behind the HCAS is the achievement of equity. Historically, equity has been one of the most important principles driving tax policy, and has been considered when raising revenues and allocating funds for maintenance, capital improvements, operating programs, and services to the public. HCASs can aid in achieving equity-related objectives. As noted in chapter one, an HCAS survey was distributed to all 50 state DOTs. A general conclusion from the survey responses is that state HCASs have reached a fairly stable condition. That is, there have been no major breakthroughs in research or methodology in recent years. Most states doing these studies are using some variation of the methods devel- oped in the 1982 Federal HCAS, and most have been making gradual evolutionary improvements while achieving better efficiency in performing these studies. RECENT DEVELOPMENTS IN HIGHWAY COST ALLOCATION STUDY METHODS AND SOFTWARE Since the 1997 Federal HCAS, several states have made en- hancements to their own studies based in part on the research and methodological improvements in that study. Although the FHWA commissioned the development of HCAS soft- ware and guidelines for states based on that 1997 HCAS, little has been done to market these products or to encourage states to continue to perform HCASs, and no technical assis- tance has been offered except for volunteer efforts by mem- bers of the team that developed FHWA’s 2002 State HCAS Model. Some states have developed and applied simplified versions of complete studies, and some have conducted simple updates of previously completed studies. Over the last decade since the completion of the 1997 Federal HCAS, few major changes in HCAS practice have occurred. The most significant recent activities have included: • Completion of FHWA’s work on development and re- finement of NAPCOM. • FHWA’s development of NAPCOM into a model that can be relatively easily applied in state HCASs. • FHWA’s development of generalized state HCAS soft- ware building on the results of the 1999 Oregon HCAS and FHWA’s work cited earlier. 10 • As part of FHWA’s software development effort, analy- ses needed for inputs to the software for state HCASs (see chapter five). • Vermont’s successful use of the above software and guidelines with very minimal outside consultant effort (>$10,000). • Oregon’s continued analysis of numerous HCAS sub- jects in the issue papers prepared in its HCASs and its continued exploration of performing a full cost-based allocation study where the external or social costs that are imposed by the system are directly allocated to highway-user classes as opposed to the allocation of just highway expenditures. • FHWA’s continuing refinement of data collection pro- grams by the states as a cooperative effort, resulting in far greater comparability of data among the states. A consultant team working for the FHWA prepared an HCAS software package following completion of the 1997 Federal HCAS and the development of the first operational version of the package for the 1999 Oregon HCAS. The soft- ware consists of an Excel spreadsheet package intended for performing any state’s HCASs. The package contains four spreadsheets—two main spreadsheets containing Visual Basic programs, a special visual analysis spreadsheet and a default data spreadsheet. One of the main spreadsheets contains most of the data and the two programs necessary to perform the allocation of costs. The other main spreadsheet contains the programs that summarize the results of the cost and revenue allocations and produces various summary output tables using user- defined formats. After all required data are entered, each of the programs can be run by clicking on the buttons on the sheets at the locations shown in the tables of contents of each spreadsheet. The third spreadsheet in the package contains a model de- rived from results of running the two main sets of programs. The model is designed to provide equity assessments of any special vehicle, such as a different truck configuration than currently allowed or a truck applying for an overweight per- mit. The fourth spreadsheet provides default data obtained from national sources or estimated from sources for each state. These default data can be used, with due care, to pro- vide roughly half of the data required for application of the software. CHAPTER THREE STATE OF THE PRACTICE

11 The software package is supported by detailed documen- tation and a set of guidelines for preparation of all required inputs to the software (see chapter five). As a result of the recent Vermont HCAS, a few minor problems with this HCAS model have been identified and should be corrected. There is also a growing need to update the default database. Appendix C contains a letter from Bart Selle of VTrans that documents the technical problems with the FHWA State HCAS Model. The Simplified Model for Highway Cost Allocation Studies in Arizona (Arizona SMHCAS) was designed to enable the Arizona DOT to update the state’s HCAS report simply and in a cost effective manner. As noted in its com- pleted survey, Arizona DOT representatives believe that if a state cannot find the budget to complete a comprehensive HCAS on a frequent basis (at least once every five years) it is better to use a simplified methodology rather than not doing a comprehensive study, because older HCASs are often “criticized or dismissed as obsolete given new traffic and new construction programs” (J. Semmens, personal com- munication, Jan. 2007). The Arizona SMHCAS breaks highway expenditures into three categories: capacity-driven expenditures, strength- driven expenditures, and common costs. Both capacity-related and common costs under the Arizona SMHCAS are allocated to vehicle and weight classes based on relative shares of VMT. Capacity-related expenditures, however, are allocated based on urban VMT only, whereas common costs are allo- cated based on total VMT shares. One key element of the Arizona SMHCAS is that it treats urban and rural programs differently, with urban expenditures being allocated based on the view that these expenditures are driven by congestion and, thus, should be allocated based on relative shares of VMT. Expenditures on rural roadways are assumed to be driven by the need to provide pavements that are wide, thick, and strong enough to accommodate heavy-truck traffic. Based on this premise, rural costs are allocated based on vehicle axle loads driven per mile. In 2001, contractors hired by the Oregon Department of Administrative Services converted the state’s HCAS model, which was based on the State HCAS Model developed by FHWA, from an Excel-based spreadsheet model to a data- base model programmed in Access. The Access model was built with a dynamic structure that incorporated feedback loops enabling it to capture the impact that alternative tax rates would have on travel, vehicle ownership, and tax eva- sion (Jack Faucett Associates with ECONorthwest 2001). Although the model was constructed with this capability, evasion rate data along with price elasticity of demand data for vehicle purchases and highway travel were not developed or input into the model. A model as complex as the one deployed in Oregon is not necessary to conduct an HCAS, because the feedback can be applied separately in any case where a study may seriously consider a major change in tax rates that would significantly affect highway use. States considering conducting an HCAS have a range of options, including using existing software such as the State HCAS Model prepared by the FHWA or developing a more simplified model similar to the Arizona SMHCAS. VEHICLE CLASSES AND HOW THEY ARE DIFFERENTIATED One key issue that is addressed in all HCASs is the determi- nation of vehicle classes for the study. Highway cost alloca- tion is strongly influenced by the weight and configuration of a vehicle. Damage caused to road systems is strongly influ- enced by vehicle weights and axle loadings. Ideally, HCASs would be designed to examine an extensive set of vehicle configurations and weight classes. In practice, vehicle cate- gories, axle configurations, and weight classes are limited by data constraints (when selecting vehicle classes for analysis, the examiner must at a minimum acquire data that can effec- tively be used to attribute revenue, to estimate VMT, and to identify gross weights and axle loadings to each vehicle class), research budget limitations, and the inability of many transportation tax structures to effectively implement HCAS findings at a detailed level. It is important to note that unless those performing an HCAS are considering recommendations for making changes in the tax structure, the selection of vehicle classes to be used in the study is often primarily driven by the state’s existing tax structure. For example, the Oregon HCAS uses 2,000-lb gross weight classes primarily because the state’s weight-mile tax rates are graduated in 2,000-lb increments. The availability of data and the state’s tax structure are the two principal criteria used in determining vehicle classes. It is also important to note, however, that HCASs that include more detail in terms of vehicle class differentiation can aid in policy analysis and consideration of future changes to the existing tax structure even if modifications are not currently recommended. After reviewing what various recent HCASs have done in defining vehicle classes, we will conclude this subsection with some additional elaboration of the issues relevant to establishing vehicle classes. The 1997 Federal HCAS examined a broad spectrum of vehicle types and weight classes. Table 3 identifies the 20 ve- hicle types included in the 1997 Federal HCAS. In addition, these vehicle types were further examined according to weight categories in 5,000-lb increments. With the vehicle types and weight classes identified, the Federal HCAS could have examined vehicles in 600 categories or classes; however, there were many categories with no vehicles registered within them. For example, there are no 100,000-lb automo- biles or 20,000-lb combination trucks registered in the United States. Ultimately, the Federal HCAS examined

12 vehicles in 212 vehicle classes. The Federal HCAS could explore vehicle cost responsibility at such depth because the U.S.DOT was completing a comprehensive trucks size and weight study. States have historically examined far fewer vehicle classes than what was considered in the 1997 Federal HCAS. Most but not all state HCASs differentiate vehicle classes based on both weight and configuration. For example, the 2006 Vermont HCAS examined 20 broad vehicle classes without consideration of weight: passenger cars, pickups and vans, 3 single-unit truck configurations, 14 combination- truck configurations, and buses. The 1999 Nevada HCAS classified vehicles only according to broad weight cate- gories: basic vehicles weighing 10,000 lb or less and heavy vehicles weighing in excess of 10,000 lb. Other states have established vehicle classes based on both axle configuration and registered vehicle weight: • The 2007 Oregon HCAS modeled vehicle classes based on vehicle weights and number of axles in 2,000-lb increments. • The 1999 Arizona HCAS considered five broad vehicle types and 23 weight classes. • The 2000 Kentucky HCAS used both vehicle and weight categories to establish 17 vehicle classes: motorcycles, cars, buses, and 14 truck classes differentiated solely by registered or declared weight. • The 2002 Idaho HCAS covered five vehicle types (autos, pickups, buses, single-unit trucks, and combina- tions) spread over 9 weight classes. Studies can also differentiate between vehicle classes based on fuel type (e.g., gasoline, diesel, alternative fuels or hybrids) and on treatment in the tax code (e.g., full-fee pay- ing, partial-fee paying, and exempt). To elaborate and summarize, vehicle classes are generally defined in any HCAS with the following considerations: • From a perspective of distinguishing vehicles by cost responsibility: (1) operating axle weights of vehicles, (2) gross weights of vehicles, (3) miles operated, and (4) differences in the streets and highways on which vehicles operate. • From a perspective of distinguishing vehicles by user payments made: (1) fuel economy, (2) registered weight class and other vehicle class differences, and (3) fee ex- emptions and reduced fee classes of special vehicles, such as publicly owned vehicles, out-of-state-based vehicles, and vehicles used in particular industries or ve- hicles providing special services. • Existing vehicle registration classes. VC Acronym Description 1 Auto Automobiles and motorcycles 2 LT4 Light trucks with 2-axles and 4 tires 3 SU2 Single unit, 2-axle, 6 tire trucks 4 SU3 Single unit, 3-axle trucks 5 SU4+ Single unit trucks with 4 or more axles 6 CS3 Tractor-semitrailer combinations with 3-axles 7 CS4 Tractor-semitrailer combinations with 4-axles 8 CS5T Tractor-semitrailer combinations with 5-axles, two rear tandem axles 9 CS5S Tractor-semitrailer combinations with 5-axles, two split (>8 feet) rear axles 10 CS6 Tractor-semitrailer combinations with 6-axles 11 CS7+ Tractor-semitrailer combinations with 7 or more axles 12 CT34 Truck-trailer combinations with 3 or 4-axles 13 CT5 Truck-trailer combinations with 5-axles 14 CT6+ Truck-trailer combinations with 6 or more axles 15 DS5 Tractor-double semitrailer combinations with 5-axles 16 DS6 Tractor-double semitrailer combinations with 6-axles 17 DS7 Tractor-double semitrailer combinations with 7-axles 18 DS8+ Tractor-double semitrailer combinations with 8 or more axles 19 TRPL Tractor-triple semitrailer or truck-double semitrailer combinations 20 Bus Buses (all types) TABLE 3 1997 FEDERAL HCAS VEHICLE TYPES

13 • The possible need to subdivide any vehicle registration classes into two or more subclasses because of any of the aforementioned cost responsibility considerations. • Defining vehicle classes in one way for analysis of cost responsibility and in another way for revenue attri- bution: it is important to have a good way of applying conversions from one class to the other or to summarize categories of vehicle classes for reporting results and estimating equity ratios. FUNCTIONAL CLASSES OF ROAD SYSTEMS EXAMINED IN HIGHWAY COST ALLOCATION STUDIES The determination of the functional classes of road systems examined within an HCAS is important because higher order systems (e.g., Interstates, other freeways and expressways, and other principal arterials) are designed to higher standards to withstand the punishment of heavy axle loadings and high traffic levels. Therefore, the attribution of cost responsibility is inextricably linked to the design standards of the roadway systems where both the miles of travel occur and the con- struction and maintenance expenditures are made. The following is a list of the standard 12 functional classes desig- nated by AASHTO in cooperation with FHWA. • Rural – Interstate – Other Principal Arterials – Minor Arterials – Major Collectors – Minor Collectors – Local • Urban – Interstate – Other Freeways and Expressways – Other Principal Arterials – Minor Arterials – Collectors – Local Historically, these 12 functional classes have served as the standard in terms of the treatment of functional classes of road systems in HCASs. The 12 functional class system was used in the 1997 Federal HCAS, 1999 Arizona HCAS, 2000 Kentucky HCAS, and the 2007 Oregon HCAS, although some other recent HCASs have compressed these functional class road systems into a smaller number of categories for reporting purposes (1999 Oregon HCAS and 1999 Nevada HCAS). The designation of highway functional class between rural and urban is another important distinction. The dis- tinction of rural versus urban has taken on additional signif- icance in recent Arizona HCASs. The Arizona SMHCAS simplifies the cost allocation procedure by assuming that expenditures on urban roads are driven by congestion and should be allocated based on relative shares of VMT, whereas expenditures on rural roadway systems are driven by the strength requirements caused by heavy truck traffic and, there- fore, should be allocated based on vehicle axle loads and mileage. SELECTING APPROPRIATE COST ALLOCATORS Each element of a state HCAS relies on some measure that can be quantified and used to allocate costs to various classes of highway users. Under the Incremental Method, the recog- nition that roads are built wider and thicker to withstand the loading of heavy trucks led to the allocation of a certain por- tion of roadway width and depth solely to heavy trucks. In re- cent years, however, more comprehensive models, including NAPCOM, have been developed to assign cost responsibil- ity to vehicle users based on a more complete understanding of the influence of vehicle traffic, environment, and other factors on pavement deterioration. These models predict the impact that highway use will have on pavement damage based on empirically established relationships between axle weights and pavement damage, and assigns cost responsibil- ity based on these established allocation factors. In the absence of a more comprehensive pavement model, some states have historically used more straightforward mea- sures that are designed to vary in proportion to the damage caused to the roadway system by vehicle classes. These allo- cators include: • Axle Miles of Travel (AMT)—VMT multiplied by the number of axles. Because trucks generally have more axles than cars, sports utility vehicles (SUVs), or pick- ups, their share of the total AMT on any given highway system will be about double their share of the VMT on that system. • Axle Weight or Axle Load—The gross load carried by an axle. • Ton-Miles—VMT multiplied by tonnage. • Equivalent Single-Axle Loads and Equivalent Single- Axle Load Miles—The pavement stress imposed by a single axle with an 18,000-lb axle load is termed one ESAL. ESAL-miles are equivalent single-axle loads times miles traveled. These allocators have been used extensively at the state level to assign specific wear-related costs to highway-user classes. For example, the 2007 Oregon HCAS, while using a comprehensive HCAS model, assigns striping costs based on axle-miles of travel (ECONorthwest 2007). Roadway strip- ing deteriorates as a result of friction of tires wearing away the paint on roadways. Thus, the number of axle-miles is used as a proxy for the number of times contact is made between vehicle tires and roadway striping. The 1999 Arizona HCAS allocates the costs associated with the extra roadway thick- ness required to accommodate heavy-truck traffic based on

14 axle loadings (1999 Update of the Arizona Highway Cost Allocation Study 1999). Bridge costs have historically been allocated to highway- user classes based on the size and weight of the vehicles crossing the structures. When assigning these costs, two key issues are: 1. The definition of increments used in the incremental analysis of bridge cost responsibility and the methods used to assign vehicles to those increments. 2. The methods used to allocate costs among increments, including the determination of load and non-load por- tions of bridge costs. Bridge costs are often stratified into three categories: new bridges, bridge replacements, and bridge rehabilitation. The costs associated with new and replacement bridges have historically been allocated in many studies based on an in- cremental analysis of the costs of constructing bridges using different design loadings. This approach was used in the last two federal HCASs and several state HCASs. These loadings are based on hypothetical vehicles for which stresses in the load-bearing members of bridges are calculated and com- pared with permissible stress levels. As loadings become heavier, the size of bridge members, and consequently bridge costs, must be increased to remain within permissible stress levels. When allocating bridge rehabilitation costs, load- and non-load-shares are determined. Bridge rehabilitation ad- dresses the needs to both improve its structural and func- tional condition. The non-load share of bridge rehabilitation costs is largely allocated to all vehicles based on relative shares of VMT. This allocation procedure is based on the principle that vehicle wear drives rehabilitation costs. The load share of rehabilitation costs is often allocated to heavy- truck classes based on some measure that accounts for the additional stress placed on bridges by heavy vehicles, such as ESAL-miles or heavy-truck VMT (Stowers et al. 1998). Issues relating to the allocation of pavement and bridge costs are examined in more detail in chapter five. Historically, the costs associated with new roadways were allocated based on an incremental analysis of the additional thickness and depth required to sustain heavy trucks. In recent years, however, the costs of constructing new roads in urban areas have been treated as investment decisions relating to the tradeoffs between congestion and roadway expenditures. Thus, new facilities in urban areas are often viewed as designed to re- lieve congestion levels on existing facilities. With this view in mind, state HCASs are increasingly allocating capital costs in urban areas based on the contribution of each highway-user class to congestion. From an empirical standpoint, the ideal state would exist if state HCASs examined the costs associated with congestion (including wasted time and fuel, emissions, and noise), states implemented highway-user tax structures that taxed on a marginal cost rather than average cost basis, and those fee structures could be used to address cost responsibility. The economic principles involved have been addressed in the 1997 Federal HCAS and recent Oregon studies. In the absence of this preferred set of circumstances, most states have found proxy allocators used to attribute most cap- ital costs largely based on some measure of travel. In the 1999 Arizona HCAS, an additional distinction was made in the simplified model between urban and rural capital costs with urban costs assumed to have been driven by congestion and allocated based on relative shares of VMT. The base Arizona HCAS model in the 1999 Arizona HCAS used axle loadings to assign cost responsibility for the additional pave- ment thickness required to accommodate heavy-truck traffic. The 2007 Oregon HCAS assigned responsibility for the base increment cost based on a measure of the space that vehicle classes take up on roadway systems during congested peri- ods. This allocator is referred to in the Oregon studies as con- gested PCE VMT. The PCE factor is an appropriate allocator because congestion is driven by the space that vehicles oc- cupy on the road system, not simply the number of vehicles or the total number of miles traveled. Heavy trucks are larger and require more braking and acceleration distances to oper- ate safely on road systems and, therefore, have a greater PCE factor than lighter, smaller vehicles. There are elements of any transportation agency budget that have no clear relationship to specific vehicle characteris- tics. These costs include planning and administrative over- head costs. These costs are generally allocated based on either an assignment of responsibility to a specific highway-user class or some general measure of VMT. When considering the allocation of costs to a specific user class, an appropriate example would be the allocation of expenses tied to motor carrier enforcement. These costs would not be incurred in the absence of heavy-truck traffic. Therefore, costs associated with motor carrier enforcement are generally allocated to heavy-truck classes based on the relative shares of VMT for each class of heavy trucks. COST ALLOCATION IN A MULTIMODAL ENVIRONMENT Recent developments in federal policy have served to in- crease the flexibility in the application of federal-aid funds and encourage intermodalism. The Intermodal Surface Transportation Efficiency Act of 1991 (ISTEA) encouraged the development of a broad multimodal system through in- corporating modes into a National Intermodal Transportation System. In turn, some have argued for a broader consideration of modes in the cost allocation process. To proponents of intermodalism, the exclusion of other modes serves to pro- mote an incomplete understanding of equity. One study examined the policy implication of applying cost allocation across all modes, examined the pros and cons

15 of a multimodal approach, and presented recommendations related to the treatment of alternative modes in transportation cost allocation (Wheeler 1996). The arguments in favor of a multimodel approach to cost allocation identified in the study included: • An application of transportation cost allocation in a multimodal environment would encourage the emer- gence of a broader view of the transportation system. • Multimodal cost allocation would enhance uniformity and coordination when spending decisions are made. • Highway users generate external costs (air pollution, congestion, noise) that are typically not addressed in HCASs, but impact society and other modes of transportation. • Highway users benefit from the multimodal transporta- tion systems that support the road network. Arguments against the multimodal approach cited by the author were tied to the uncertainty associated with the multi- modal approach and its inability to be used to directly set highway-user charges. The author also noted the complica- tions associated with the inability of most other modes (e.g., rail and public transit systems) to recover operating costs through user charges. The author concluded that there is a need to move toward a broader application of transportation cost allocation; how- ever, more research is needed to implement such a strategy. Required research proposed by the author included: • A detailed review of multimodal economics; • The development of a mode-by-mode approach to transportation cost allocation; and • Examination of the feasibility of extending transporta- tion cost allocation to all levels of government, including federal, state, and local government. METHODOLOGIES FOR REVENUE ATTRIBUTION The process of attributing revenues to highway-user classes is an essential step in any HCAS. The equity ratios created for each vehicle class serve as the principal findings of state HCASs. Although most attention in the literature focuses on cost allocation, revenue attribution has an equal weight in de- termining the outcome of an HCAS. Revenue attribution results in producing the numerator over the cost allocation denominator in any equity ratio. Guidelines for performing revenue attribution are contained in a section of chapter five. States have historically focused on state revenue sources. Reasons cited for focusing on state revenue sources include the historic inflexibility with respect to how federal funds could be used and the inability of states to make adjustments to the federal tax structure. However, because of the flexibility built into the federal-aid program in recent years, many recent studies have included federal, state, and local revenues in the attribution process (Arizona, California, Idaho, and Nevada), and others have included state and federal revenues in the at- tribution process (Delaware, Kentucky, Vermont, Virginia, and Wisconsin). Maryland attributes state and local revenues to highway-user classes. Oregon has established a unique ap- proach. In recent Oregon studies, the numerator of the equity ratios has included only state revenues, but the denominator has included both state and federal expenditures. The result- ing imbalance is corrected by converting the equity ratios to adjusted equity ratios by expressing the ratio as shares of total revenue divided by shares of total expenditures, as is commonly done in state HCASs (see further discussion in the levels of government section of chapter five). The 1997 Federal HCAS and virtually all state HCASs allocate expenditures and attribute revenues to the various user classes for a future time period based on adopted pro- grams and short-term program and revenue forecasts. Most states focus on programmed state transportation improve- ment program (STIP) expenditures projected over a future time period. Traffic and other data are also projected forward for the same future years. The logic behind this approach is that forecast data pro- vide a more accurate description of the changing characteris- tics of demand for travel and expenditures based on changing conditions. For example, constrained budgets and the normal deterioration of a state’s roads and bridges could signal a shift in public investment from capacity expansion to opera- tion and maintenance of existing highways. Historical data would not adequately reflect this trend. To get a better picture of expenditures, a state may choose to consider past expen- ditures (e.g., 2 to 4 years) as well as future program costs, while being cautious in the treatment of one-time large expenditures. The time periods considered in a number of recent studies are presented in Table 4. Similar to the 1997 Federal HCAS, state HCASs gener- ally attribute motor fuel tax revenues based on estimates of travel in the state being examined and motor fuel economy. Study Study Time Period Arizona (1999) 1999–2003 Idaho (2002) 2001–2005 Federal (1997) 2000 Nevada (1999) 1998–1999, program expenditures based on 1999–2008 STIP Oregon (1999) SFY 2000—SFY 2001 Oregon (2007) SFY 2008—SFY 2009 Vermont (2005) 2005 TABLE 4 RECENT HCAS STUDY TIME PERIODS

16 Miles-per-gallon estimates are generally obtained through industry surveys, including the Vehicle Inventory and Use Survey (VIUS), or through the default values contained in the State HCAS Model prepared for the U.S.DOT. For states with weight-distance taxes (Kentucky, New Mexico, New York, and Oregon), the revenue attribution process is more transparent as distance-based taxes are graduated to reflect the declared vehicle weights typically examined in state HCASs. Attribution of registration fees, particularly those of In- ternational Registration Plan apportioned vehicles, can be extremely complicated at the state level, depending on the quality of the state’s registration fee and related database. The principal issue that must be addressed is how to convert payments by user classes that are defined by registration fee schedules to user classes examined in the HCAS. For exam- ple, the revenue attribution process may require conversion of registration fees based on registered gross weight to data based on vehicle body type and axle configuration. Some states have constructed complex matrices to perform this conversion. For example, a matrix prepared for the state of Pennsylvania relied on data provided through VIUS, the In- ternational Registration Plan, and special studies conducted at the state level (Jacoby 1990). Table 5 presents guidelines used to conduct a detailed rev- enue attribution process in Kentucky (Osborne et al. 2000). In Element Basis Fuel Tax Heavy vehicle surtax Revenue estimates from VMT, rates of fuel consumption, and tax rates Carrier surtax See above Normal use See above Federal Excise Tax See above Vehicle Registration & License Cars 100% Buses 100% Motorcycles 100% Trucks Revenue estimates from number of registered trucks and registration fees (with adjustments for farm, exempt, and 6,000-lb trucks) Apportioned trucks Number of ID cards Truck ID cards Number of ID cards Truck permits Number of ID cards Other Vehicle-miles Miscellaneous Vehicle-miles Operatorís License Vehicle-miles Commercial Driver’s License Vehicle-miles Usage Tax Buses 100% Other vehicles All excluding buses As reported Federal trucks and trailers Vehicle-miles Road Tolls Toll collection receipts Other Motor Carrier Taxes Weight distance Vehicle-miles Extended weight 100% Federal use Vehicle-miles Other Federal Taxes Vehicle Class Trucks over 59,999 lb Trucks over 26,000 lb All All Cars Buses Motorcycles Trucks Trucks Trucks Trucks All All All Trucks over 22,000 lb Buses Trucks over 33,000 lb All Trucks over 59,999 lb 80,000-lb trucks Trucks over 54,999 lb All Vehicle-miles TABLE 5 GUIDELINES FOR THE ALLOCATION OF HIGHWAY-USER REVENUE TO VEHICLE CLASSES IN KENTUCKY

17 Kentucky, the primary sources of revenue include fuel taxes, registration and license fees, usage taxes, road tools, other motor carrier taxes, federal taxes, and miscellaneous taxes and fees. This table demonstrates how highway-user fees are attributed to each vehicle class. For example, the Kentucky weight distance tax is allocated to trucks weighing in excess of 59,999 lb based on VMT. The regular Kentucky motor fuels tax is allocated to all highway-user classes based on a revenue analysis that considers VMT, rates of fuel consump- tion, and tax rates. TREATMENT OF DIVERSIONS OF HIGHWAY-USER REVENUES TO OTHER USES States have varied in their treatment of diversions of highway- user revenues to other uses. Some HCASs have identified the diversion of highway-user revenues to other uses but have eliminated them from consideration, whereas others have at- tempted to judge each diversion based on its relative merit. For example, most but not all states consider the highway patrol as an essential element of the highway program and allocate these costs accordingly (Idaho Department of Transportation 2002). The 1997 Federal HCAS allocated expenditures of high- way-user revenues on mass transit. The principle underlying this approach was that expenditures on mass transit facilities represent a form of congestion management and, therefore, should be allocated to highway users. Thus, mass transit expenditures were allocated to automobiles, pickups, and vans in proportion to VMT on higher-order urban highways. It is worth noting that practitioners interviewed for this study indi- cated that because heavy-vehicle classes also benefit from congestion-relieving transit investment, it would be more ap- propriate to allocate these costs according to congested PCE. It is also worth noting that not all forms of transit investment ease congestion. For example, although the Central Phoenix/ East Valley Light Rail Project is expected to reduce VMT by four-hundredths of one percent in the region, vehicle speeds are expected to drop by one-tenth of a mile per hour in the re- gion and one-fifth of a mile per hour in the corridor served by light rail (Final Environmental Impact Statement . . . 2002). This counterintuitive result is expected to occur because the light rail will be constructed in an existing roadway (thus re- ducing roadway capacity), trains will be given signal pre- emption rights that will disrupt signal synchronization with vehicular traffic, and train tracks are expected to block direct access to many driveways and side streets along the route. Other HCASs exclude these diverted revenues. For example, the 1999 Nevada HCAS identifies the total value of diverted higher-user funds at the federal, state, and local levels in Nevada but does not allocate them noting: “Since the purpose of highway cost allocation is to identify whether different vehicle classes are contributing in propor- tion to their cost responsibility, only the taxes that come from highway users and are used for highways are included in our study” (1999 Highway Cost Allocation Study 1999). The 2005 Vermont HCAS also focuses exclusively on state expenditures to build and maintain roads (Selle 2006). Oregon has avoided this issue entirely by virtue of its con- stitutional requirement that all highway-user revenue be used for the construction, rehabilitation, and maintenance of roads in the state. The 1994 Texas HCAS excluded the impacts of state highway-user taxes that had been used to fund education programs in the state and federal funds used on mass transit projects (Euriat 1994). In 2000, however, a study sponsored by the Texas DOT recommended exploring scenarios in the next Texas HCAS that would allocate all revenues regardless of their use (Luskin et al. 2001). EXPERIENCE IN SELECTED STATES Brief highlights of HCAS work by 11 selected states are summarized in this section. These states have been selected either because (1) they have been leaders in the field, (2) the amount of work they have done, or (3) they have performed work that may be of significant interest to other states that may want to borrow from what they have learned or use the results of their work directly or indirectly. Arizona Arizona is one of four states that had conducted five or more HCASs and responded to the survey. Each HCAS was com- pleted within the last 14 years, with the last being completed in 2005. It completed a comprehensive study in 1992 to 1993 that included all of the currently recommended analyses and methods, with the exception of some refinements based on the 1997 Federal HCAS. In 1999, Arizona developed and applied a simplified method based on the 1993 study and then applied it again twice over the next two years. The amount of effort involved was reduced by an order-of-magnitude. The output of both the simplified and traditional Arizona HCAS model is pre- sented in Table 6. As shown, the results are consistent between the two models for the auto and bus classes. How- ever, the simplified model generated results that varied sig- nificantly from the Arizona HCAS model for pickups and SUVs (20.7% difference), single-unit truck class (56.7% dif- ference), and combination trucks (14.8% difference). When studying broader vehicle classes (e.g., basic vehicles versus heavy trucks), the results are fairly consistent. See the last section of chapter five dealing with simplified models for fur- ther discussion of the implications of these observations and how improved models of this type might be developed. California California has conducted only two HCASs (1984 to 1987 and 1995 to 2000), but both made important contributions—the first primarily in terms of principles and methodology and the

18 Equity Ratios Vehicle Class Simplified Model Arizona HCAS Model Autos 1.33 1.30 Pickups/SUVs 1.45 1.74 Buses 0.93 0.90 Single-Unit Trucks 1.41 0.90 Combination Trucks 0.81 0.93 Total 1.20 1.20 Source: 1999 Update of the Arizona Highway Cost Allocation Study (1999). TABLE 6 EQUITY RATIOS AND COMPARISON OF SIMPLIFIED MODEL TO ARIZONA HCAS RESULTS second in terms of demonstrating the value of organizing an HCAS so that it can be open to rapidly changing circumstances. The 1984 to 1987 study was one of the first to be initiated after publication of the 1982 Federal HCAS report and the subsequent national dialog about the impact of that bench- mark study. In performing that study the California DOT made a major commitment to doing the study in a manner that was fully responsive to the 1982 federal study in terms of both economic concepts and the logic behind each of the technical advancements of the 1982 study. Some of the contributions of the 1984 to 1987 study went beyond the federal study in defining economic principles in operational terms and implementing them: • Highway-user payments should be defined to include all types of payments that are unique to the use of highways, regardless of where or how those revenues are spent. • Highway expenditures and future costs should be de- fined to include all expenditures regardless of the source of funds for the expenditures and regardless of which agency is responsible, and all costs that are pub- lic responsibility regardless of whether they have yet been formally adopted or budgeted. • Expenditures for other modes of transportation (pri- marily transit) should be included if they are publicly recognized as being of substantial benefit to highway users, either in terms of congestion reduction or conser- vation of highway capacity for future growth. • Each level of government should be analyzed sepa- rately so that results can be presented in the most flexi- ble manner, either separately or in any combination. • Careful attention should be given to defining what expen- ditures are properly considered part of the analyses for each level of government. For example, state aid to local governments is part of state programs and federal aid to state or local governments is part of the federal program. • A credible HCAS cannot be done for any state’s local governments without use of a specially designed sur- vey of local governments. Such surveys should be built around existing data recently reported by local governments. Other technical contributions of the 1984 to 1987 Califor- nia HCAS included: • Complete adaptation of the 1982 Federal HCAS methods for application at the state level, reflecting the differences in available databases and differences in a variety of technical methods used in pavement and bridge design. • Development of new operational procedures for cross- walks between (1) expenditure databases and new data developed for expenditures for cost allocation categories such as new pavements, pavement rehabilitation, pave- ment maintenance, similar breakdowns for bridge work, grading and drainage, etc. (see Table 11 in the guidelines section of chapter five), and (2) registered weights and operating weights. A significant aspect of these efforts in- volved analyses of detailed data from project files, weigh- in-motion (WIM) data, and data from weigh stations. • Development of well-defined criteria for defining vehi- cle classes. • Development of procedures for distinguishing full-fee paying vehicles and exempt, partially exempt, or spe- cial-fee-paying vehicles for each vehicle class. • Development of procedures for revenue attribution that provide reliable estimates of total taxes and fees paid for each vehicle class for both full-fee-paying vehicles and others. In developing these procedures, California was able to avoid having to deal with various complex issues that are not important in terms of basic cost allocation principles or equity concerns. These include issues that some states have struggled with, such as the amount of evasion there is for var- ious taxes and fees and how to deal with tax subsidies that all legislatures have created for various categories of vehicles. The improvements made in the 1984 to 1987 California HCAS have been used and improved on in subsequent HCASs in California, Vermont, Arizona, Idaho, Minnesota, and Oregon, and in the State HCAS Model developed for FHWA. The 1995 to 2000 California HCAS built on and refined the work of the earlier study, and was noteworthy not for the types of improvement advances described earlier, but for two unique aspects that differentiated it from all other state HCASs. The first is how the study dealt with a complex set of im- pacts that were central to the purpose of that study. Because of recent changes in federal law, California had to make basic changes in how weight fees were being collected on both power units and trailers or risk a loss of more than $100 mil- lion per year. The challenge California faced was how to make

19 these changes and eliminate most trailer fees for commercial vehicles so that (1) fees would bear the closest possible match with cost responsibility of vehicles owned and operated by the many different classes of industry in the states, and (2) how to best select from a wide range of options available for achiev- ing this in a way that did not unduly burden any segment of the trucking industry or the general public. To meet this challenge, a very user-friendly spreadsheet was developed for California (similar in concept to the one described in the weight fee subsection of the guidelines in chapter five) that permitted the project team, California DOT staff, and any interested participant from industry to easily develop and evaluate proposed alternatives. This facilitated more than a year’s worth of technical work and dialog among all interested parties before the HCAS report and recommen- dations were prepared in 1999. The other unique aspect of the 1995 to 2000 California HCAS was a completely unanticipated legislative action that fundamentally changed California’s highway-user tax struc- ture. The legislature decided to phase out and totally elimi- nate the state’s $1.5 billion per year vehicle license fees (an ad valorem annual fee on all vehicles including trailers). California decided to have its HCAS consultant work with the department of motor vehicles (DMV) to develop and eval- uate alternatives for increasing other fees on a schedule that would create revenue neutrality at each step in the phase-out pe- riod for the vehicle license fees. The project team had to adopt the findings, database, and methods developed for that HCAS to develop and evaluate alternative fee schedules for these phases based on HCAS principles, the revenue neutrality re- quirements, and a requirement that this revenue neutrality be maintained for each agency that received a formula share of all highway-user revenues. The required set of fee increases was developed in consultation with the concerned agencies and was submitted to the legislature in 2000 (Sydec Inc., et al. 1999). Idaho Idaho has conducted two relatively recent HCASs—in 1994 and 2002—and several years ago made an attempt to apply FHWA’s State HCAS Model but found that it required greater information technology (IT) expertise than was available at the time. Based on that experience, the Idaho Transportation Department recently undertook a third HCAS using FHWA’s State HCAS Model with the assistance of two Washington State Economists. Although this study was effectively com- pleted in 2007, the results have not been published. Idaho is an appropriate state in which to conduct a second low-cost test of FHWA’s State HCAS Model, because it has the following advantages: • An interest in periodic performance of HCASs; • Good databases for most of the inputs required; • A fairly small central office staff used to working to- gether cooperatively without the need to create special task forces with formally delegated powers; and • Recent experience in conducting two HCASs. Indiana Indiana is one of three states known to have experience with HCASs that did not respond to the survey. Our only source of information about this experience is from the website of the Joint Transportation Research Program of Purdue University and the Indiana DOT and publications by the Director of the Joint Transportation Research Program, Professor Kumares Sinha and others. The 1988 HCAS used the incremental approach, employed extensive data sets, and used numerous allocators, including ESALs, to apportion costs among attributable and non-attributable classes of costs (Sinha et al. 1989). Kentucky Kentucky is the second of the four states responding to the survey that had conducted five or more HCASs, and like Arizona had conducted all of them in recent years (every two years from 1992 through 2000). The studies were done as an initiative of the Kentucky Transportation Cabinet (KTC), and had been effective in calling attention to the inequities of the tax structure. According to the KTC’s survey responses, recent HCASs were criticized for their treatment of a small number of method- ological issues. The principal issue revolved around the low tax rate for the weight-distance tax relative to heavy-truck cost re- sponsibility. The explanation for the decision by KTC to stop conducting HCASs on a regular basis is not that the tax burden would be too much with an increase in weight-distance tax rates, but that “the evasion was too high.” Evidence to support this conclusion came from an analysis of evasion that compared actual tax collections with an estimate of tax liability based on VMT estimates for vehicles weighing in excess of 59,999 lb. Based on the outcome of this analysis, weight-distance tax lia- bility was estimated at $86.6 million as compared with actual tax receipts of $70.2 million (Osborne et al. 2000). The argu- ment behind this decision is that although an increase in weight-mile tax rates would bring about equitable payments from heavy-truck classes as a whole, tax payments would ex- ceed the cost responsibility calculated for the majority of the motor carriers who comply with current tax systems. Further, the argument was advanced that if the KTC reduced evasion associates with weight-mile taxation, heavy-truck payments would equal cost responsibility under the current system and no adjustments to tax rates would be necessary. This decision is one that might have benefited from the findings of the Oregon Weight-Mile Tax Study. The same tax evasion issues had been raised, and Oregon DOT’s response

20 was to investigate the reality of the claim. The study found that evasion of the weight-mile tax was not excessive in compari- son with evasion rates for other taxes and fees. The study also examined the trade-off between the weight-mile tax evasion rate and the level of enforcement and concluded that, although the level of enforcement was somewhat below the optimal level (i.e., the enforcement level of effort that would result in the lowest sum of enforcement costs and revenue lost as a re- sult of evasion), the level of evasion was within an acceptable range at 3% to 7% (Cambridge Systematics et al. 1996). The authors of the report recommended a detailed program of increased enforcement that would both reduce evasion and in- crease the cost-effectiveness of the enforcement program. Maine Maine DOT has completed at least four HCASs—in 1956, 1961, 1982, and 1989 (Maine Highway Cost Allocation Study . . . 1989). Maine’s work in at least the last of these studies is of interest because the authors of this work devel- oped original approaches, while generally following the best thinking regarding basic principles of cost allocation. The 1989 Maine HCAS was required by legislation designed to improve equity in the state. The 1989 study examined a small number of expenditure categories: highway construction, maintenance, bridge con- struction, local assistance, and other outlays. The 1989 Maine HCAS used standard approaches for overall study design (e.g., cost-occasioned approach and allocating actual ex- penditures as opposed to costs). It did, however, use some unusual allocators and approaches for attributing costs, in- cluding VMT, ESALs, PCEs, truck miles traveled, standard vehicle equivalent, the Delphi method, overhead, and other allocators. The Delphi method, as applied in the Maine HCAS, allocated some expenditures based on the judgment of maintenance experts. The study also used miscellaneous allocators such as fuel consumption and the number of regis- trations by vehicle class. Minnesota The Minnesota DOT is believed to have conducted only one HCAS (1989 to 1990) using an improved version of the interlinked set of spreadsheets developed and applied for Vermont. When compared with the earlier Vermont study, the Minnesota study incorporated more detailed analysis of revenues, expenditures, pavement designs and types; more detailed program categories and classes of highways; and more detailed analysis of expenditures by local governments. The study finished with two sets of analysis requested by legislative staff: 1. An evaluation of specific alternative changes in tax structure. 2. Analyses of special classes of vehicles that have, or potentially might have, reduced tax rates based on rev- enue contributions beyond their cost responsibility (Result of the Minnesota . . . 1990). Nevada Nevada has completed six HCASs and is the third of the four states that completed five or more HCASs and responded to the survey. Nevada HCASs were conducted in 1984, 1988, 1990, 1992, 1994, and 1999. An outside audit was conducted in 1995 in response to questions and comments by stakeholders and the legislature. The audit included a thorough review and assessment of the procedures and analyses used by the Nevada DOT in the first four Nevada studies, resulting in recommendations for refinements that were incorporated in the 1999 study proce- dures (Sydec 1994). Oregon Oregon is the fourth of the four states that completed five or more HCASs. It conducted the first HCAS (called “cost re- sponsibility” studies in that state until recently) in 1937 and has conducted studies fairly routinely ever since, having completed its fifteenth in 2007—more than twice as many as any other state. Oregon has been the developer of most of the basic prin- ciples that have come to be widely accepted in this field. It has been among the first to adopt the results of research per- formed by the FHWA and others and adopt new national HCAS methods for use at the state level. The 1999 Oregon HCAS was the first state study to adopt FHWA’s new NAPCOM for allocation of pavement costs and was the first to make use of the results of other research and methodology from the 1997 Federal HCAS. The soft- ware developed for the 1999 Oregon study was the first to use Excel’s new Visual Basic programming language, and it formed the basis for FHWA’s subsequent development of the generalized HCAS model developed for use by other states, as described previously. Recent Oregon studies have also included a rather com- prehensive set of issue papers covering most of the common choices facing complex state HCASs. The 1999 Oregon HCAS issue papers included: • Pavement issues – Alternative methods for allocating pavement cost responsibility, – Load and non-load-related damage shares for pave- ment costs,

21 – Allocation of load-related portion of pavement and shoulder costs, – Use of AMT as an allocator for selected costs, – Reliability of data supporting pavement damage relationships, and – Appropriate environmental factors for allocation of pavement costs. • Bridge issues – Definition of increments, – Cost allocation methods, – New bridges and bridge replacement, – Bridge rehabilitation costs, and – Bridge maintenance. • Width-related cost issues • Other attributable cost issues – Allocation of costs of capacity improvement projects, – Allocation of right-of-way costs, – Allocation of climbing lane costs, and – Allocation of rest area costs. • Common and residual cost issues • Other cost elements and time frame issues – Exclude or include congestion and other external costs, – Use of expenditure versus cost-based approach, – Use of historical versus forecast data, and – Treatment of federal and local revenues and expen- ditures. Since the 1999 Oregon study, there has been a shift in em- phasis in cost allocation procedures from use of engineering and axle weight allocators toward vehicle use allocators. Achieving an appropriate balance between the engineer’s and the economist’s perspective has, in effect, become a new HCAS policy issue as a result of Oregon’s recent experience. Texas The Texas HCASs have employed innovative techniques to conduct highway cost allocation. For example, the 2002 Texas HCAS examined the climatic factors that affect the durability of highways. The study used numerous climatic factors to differentiate local climates, and based on a statisti- cal analysis, found the following factors could be used to establish the relationship between climate and pavement de- terioration: Thornthwaite Index (index of moisture), average winter temperature, total freeze-thaw cycles in one year, and total precipitation or rainfall. This analysis was used to es- tablish five relatively homogeneous climatic regions within the state. Establishing these regions affected how costs asso- ciated with the deterioration of pavement were allocated among highway-user classes. Four major cost components were considered for alloca- tion in the 2002 Texas HCAS: 1. Pavement construction costs (including reconstruction), 2. Pavement rehabilitation and maintenance costs, 3. Bridge costs, and 4. Common costs. The 2002 Texas HCAS allocates bridge costs based on the modified incremental approach. It allocates common costs proportionally based on VMT. To allocate flexible and rigid pavement construction, rehabilitation, and maintenance costs, the study uses five allocation methods: 1. Generalized method—Allocates costs based on a hypothetical facility specially designed for groups of vehicle classes, with costs for the base facility allocated based on VMT and the load-related costs allocated to vehicle classes based on the optimal de- sign for each combination of vehicle classes, highway type, and climatic region. 2. Proportional based on ESALs. 3. Modified incremental analysis—Allocates costs incre- mentally, with some cost elements allocated to specific vehicle classes and others allocated to multiple vehicle classes. 4. Variable lanes approach that allocates costs based on the lanes required for different classes of vehicles—that is, automobiles require more lanes than heavy trucks. 5. FHWA State HCAS Model. Each allocation method was used to determine total cost responsibility and assign equity ratios to each vehicle class examined in the study. Vermont Vermont has conducted four HCASs—in 1982, 1990, 1993, and 2005. The first was reportedly a comprehensive one. Then in 1989 and 1990 Vermont performed an extensive HCAS using an interlinked set of spreadsheets before the de- velopment of Excel’s Visual Basic software that was devel- oped and used in later HCASs. The 1990 Vermont study was unusual in that it was conducted by Vermont’s Legislative Council, with substantial assistance from VTrans. In 1993, an in-house update of the 1990 study was performed. In 2005, VTrans, using the expertise of an IT professional with substantial private sector experience, was the first known transportation department to complete an in-house HCAS using FHWA’s State HCAS software after it was developed for Oregon and later generalized for all states. The 2005 HCAS was requested by the legislature to evaluate proposed changes to DMV fees. VTrans examined actual expenditures and revenue for the previous fiscal year. VTrans then ran dif- ferent DMV revenue scenarios to calculate new equity ratios. Although the truck/auto equity ratios moved one percentage point closer to equity, that was by coincidence. Comparison with neighboring states was a more important consideration. VTrans’ only outside assistance in this effort was a review by the manager of the consultant team that developed the model for FHWA, for a cost of less than $10,000 (Selle 2006).

22 Most Helpful Responses Copies of Previous State HCASs 18 Improved HCAS Guidelines 14 HCAS Software 15 Conferences, Networking, and/or Federal Workshops 14 Other 11 Total 72 TABLE 8 WHAT STATES INDICATED WOULD MOST SUPPORT HCAS EFFORTS STATE HIGHWAY COST ALLOCATION STUDY SELF-ASSESSMENTS AND ADDITIONAL GUIDANCE AND ASSISTANCE DESIRED BY STATES Ten respondents prepared self-evaluations of the HCASs conducted in their state. In some cases, the state transporta- tion officials were grading the performance of a contractor, whereas in others they were grading their own agency’s abil- ity to conduct the study, or some combination of the two. The self-evaluation covered the following elements: • Technical issues relating to methods used and data collected; • Accuracy of the methods; • Credibility of the work among stakeholders; • Coverage of vehicle classes; • Coverage of all relevant funding sources, fees, and taxes; and • Handling of special revenue factors. The technical methods and data used in these studies were generally well reviewed, with seven of ten states rating these elements as good or excellent. The credibility of the work among the stakeholders was cited as a problem in some states, as was the limited coverage of vehicle classes. The ability of these HCASs to handle special revenue factors, such as public-private partnerships (PPPs) and tolls, was viewed as average or weak in four of the ten surveyed states (see Table 7). These issues were explored in greater detail earlier in this chapter and are studied in chapter five as well. In terms of what would be most helpful to states consider- ing conducting HCASs, a total of 72 individual responses were offered by 29 of the 33 states that returned a survey. Respondents were encouraged to select more than one re- sponse as appropriate. The 72 responses are broken down as follows: 18 states selected “copies of previous HCAS reports from other states,” 14 selected “improved HCAS guidelines,” 15 selected “software,” 14 selected “conferences, networking, and/or federal workshops” and 11 selected “other.” These re- sults are presented in Table 8. As noted in Table 8, ten respondents selected “other.” Other responses included the following • The California respondent indicated that AASHTO should consider recommendations to guide states con- sidering future HCAS and related studies. • The Michigan respondent indicated that engineering knowledge about the effect of trucks with Michigan’s weight limits would be useful. • The Nevada respondent argued for legislative action consistent with the study results to motivate the state to conduct additional studies. • The Ohio respondent noted that Ohio would just refer to national studies or studies from other states. • The Wyoming respondent requested improved docu- mentation from the FHWA for the FHWA State HCAS Model and also noted the need for more extensive vehi- cle class data for the entire highway system (detailed documentation for FHWA’s 2001 State HCAS Model is available on the FHWA’s website at http://www. fhwa.dot.gov/policy/otps/costallocation.htm. Elements Poor Technical—Methods and Data Accuracy of the Methods Credibility of Work Among Stakeholders Coverage of Vehicle Classes Coverage of all Relevant Funding Sources, Fees, and Taxes Handling of Special Revenue Factors Total Excellent 1 2 2 2 3 1 11 Good 6 5 4 4 4 4 27 Average 2 2 1 2 2 3 12 Weak 2 1 1 4 0 TABLE 7 STATE SELF-EVALUATION OF HCASs

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TRB’s National Cooperative Highway Research Program (NCHRP) Synthesis 378: State Highway Cost Allocation Studies examines the history and evolution of highway cost allocation study practice and explores the current state of the practice.

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