In This Issue
Summer Bridge on Issues at the Technology/Policy Interface
July 1, 2016 Volume 46 Issue 2

Charging Mechanisms for Road Use An Interface between Engineering and Public Policy

Wednesday, July 6, 2016

Author: Bismark R. Agbelie, Samuel Labi, and Kumares C. Sinha

Increasing numbers of roads and bridges in unsatisfactory condition, along with shrinking funds for maintenance and repair, are of great national concern. For decades, the motor fuel tax, an indirect excise tax on the sale of fuel, has been the primary source of federal and state highway revenue in the United States. The current federal tax on gasoline and diesel is 18.4 and 24.4 cents per gallon, respectively, while the state fuel tax varies by state, averaging about 30 cents per gallon for gasoline and diesel.

Federal and most state fuel tax rates have not changed for many years, and increasing fuel efficiency has created a serious funding gap that is rapidly increasing (NSTIFC 2009; TRB 2006). The American Society of Civil Engineers (ASCE) estimates that to improve the nation’s highways, $170 billion needs to be invested annually—$79 billion more than the $91 billion that is currently spent. The effect of this shortfall is deferment in highway capital investments, resulting in a cycle of maintenance cutbacks, further deterioration, and increased need for repair. If present trends continue, the gap in highway funding—48 percent of the total need in 2010—can be expected to grow to 54 percent by 2040 (ASCE 2013).

It is important to recognize the significance of the dichotomy between expenditures and needs. An agency can only spend the resources it has; but the actual need often far exceeds what is actually spent.

Why the Fuel Tax Is Inadequate

Although the fuel tax–based funding mechanism worked well for most of the 20th century, it is now anachronistic and even counterproductive for several reasons.

  1. Because the revenue from the tax depends on the amount of fuel consumed and because the federal formula rewards highway agencies for higher miles of travel in their state, this mechanism does not promote travel reduction or fuel conservation. In effect, it contributes to the emission of greenhouse gases and other air pollutants, impacts that are directly related to fuel consumption.
  2. The increasing use of hybrid and electric vehicles makes the concept of fuel tax inconsistent with revenue generation objectives.
  3. The current fuel tax is not equitable across highway user groups (vehicle classes): although higher vehicle classes (trucks) consume more fuel per unit of travel—and thus pay more in fuel taxes—compared to lower classes (automobiles), the damage a truck inflicts on the infrastructure compared to an automobile far exceeds the extra amount of fuel a truck consumes compared to an automobile.

Alternatives

Possible ways to address the inadequacy of the existing pricing mechanism might be to increase the fuel tax rate or index the fuel tax to inflation at the federal and state levels, charge tolls on specific road corridors, increase state vehicle registration fees, adopt other local taxes specifically for transportation, impose a sales tax (at any level of government), or increase the local property tax. These approaches could be used individually or in combination. However, even if they were politically palatable, these approaches do not adequately address the core concerns associated with the existing mechanism of highway financing.

The time has come to transition from the current indirect mechanism of road user charging to a direct mechanism. This need has been recognized for some time but it is only recently that the implementation of a direct mechanism has become technically and economically feasible. With direct user charging (DUC), the cost responsibilities of each vehicle class can be used as a guide to charge individual vehicles. This approach requires a detailed allocation of highway costs, the steps for which are discussed in the next section.

Cost Responsibilities by Road User/Vehicle Class
Road User/Vehicle Classes

The Federal Highway Administration (FHWA) vehicle classification scheme represents the vehicles that operate on highways and categorizes road user groups based on vehicle type, size, and number of axles (figure 1). Heavier vehicles are further classified in terms of their maximum gross weight.

Figure 1

The physical degradation of pavements and bridges is linked directly to vehicle weights and axle distributions, and operational degradation (in terms of safety and mobility) is affected by vehicle size. For example, engineering principles indicate that doubling the traffic load causes an eightfold increase in pavement damage. Similar nonlinearity is evident in the structural damage to bridges when subjected to traffic loading.

Highway System Use by User/Vehicle Class
Highway system use is generally quantified in terms of vehicle-miles travelled (VMT), and user charging is based on the extent to which each class uses the highway. The national VMT in 2013 was 3.04 trillion (FHWA 2015). The distribution by vehicle class for the state of Indiana is shown in figure 2. Passenger vehicles accounted for the greatest amount of road use (63 percent), followed by vans and pickup trucks (25 percent). Tractor-trailer trucks (classes 8–13) accounted for just 8 percent of highway use, but they cause the greatest damage to pavements and bridges.

Figure 2

Where the costs cannot be attributed to specific vehicle classes and thus are considered common costs across all vehicle classes, equal VMT fees can be applied, and where the costs are allocated differently across vehicle classes due to vehicle weight or size differences, the VMT fees need to be modified to reflect the extra pavement thickness and extra strength of bridge components required to support heavier vehicles or to reflect the extra roadway width needed to accommodate larger vehicles.

Examples of modified vehicle-miles are load-miles or passenger car equivalent miles (PCE-miles). Load-miles, which are consistent with weight-distance fees, may be measured in ton-miles or equivalent single axle load miles (ESAL-miles). The ESAL concept arose from the need to develop a common denominator for measuring traffic load to account for the different damage contributions of each user group. It is derived from the equivalent wheel load factor (Yoder and Witczak 1975) that is defined by the damage per pass caused to a specific pavement by the vehicle in question relative to the damage per pass caused by a reference vehicle (or axle load).

The American Association of State Highway Officials (AASHO) Road Test in Batavia, Illinois, in late 1950s established the reference axle load as 18,000-lb. single axle with dual tires. A higher ESAL value indicates a relatively higher damage contribution. For a given pavement thickness and material type, ESAL values vary significantly according to the vehicle class (and therefore the number of axles and axle configuration) and loading typically carried by that class in a given state. Table 1 presents the ESAL distribution by vehicle class and pavement material type in Indiana, averaged over all thicknesses. For each class of vehicles, the nature of loadings may vary across the two pavement types according to travel patterns and thus affect the relative ESAL values.

Table 1

The current trend in pavement design is toward a mechanistic-empirical approach (AASHTO 2015) that calibrates the physical causes of stresses in pavement structures with performance data from the FHWA Long-Term Pavement Performance (LTPP) program or other sources to determine the damage relationships (AASHTO 2010).

Table 2

The PCE concept is similar to the ESAL. The rationale is that, from an operational viewpoint, the presence of large vehicles in the traffic stream reduces capacity because these vehicles (1) take up more space, (2) have operating characteristics (acceleration/deceleration) that are inferior to those of passenger cars, thus requiring longer headways, and (3) cause drivers of nearby vehicles to keep longer headways from them. From a physical facility viewpoint, the roadway must be wider to accommodate large vehicles, and this impacts the amount of material, labor, and equipment for the construction. Table 2 presents PCE in Indiana by vehicle class and highway class. According to the PCE shown, a bus (Vehicle Class 4) would be operationally equivalent to 2.2 passenger vehicles for use of any road that is not part of the Interstate Highway System.

Allocation of Costs
Pavement Costs

Costs for new pavement construction can be analyzed on a project-by-project basis and separated into two components: those on a base facility (the thinnest pavement adequate to support the lightest class of vehicles), which serves as a platform for building the remaining facility (the additional pavement layers needed to support heavier vehicles). The base facility costs are allocated to vehicle classes based on VMT, with adjustments for vehicle width; the remaining-facility costs are typically allocated based on vehicle weight, specifically, ESAL-miles of travel (FHWA 1997).

Costs for pavement maintenance and rehabilitation are incurred based on (1) load, allocated to the vehicle classes on the basis of their ESAL contributions, and (2) nonload (damage due to the environment), allocated to the vehicle classes based on their VMT contributions.

Bridge Infrastructure Costs
Bridge construction is more costly when heavier vehicles must be accommodated, so costs are allocated proportionally by vehicle class because each class induces different stress levels. New bridge construction costs are typically allocated using factors for design loadings established by AASHTO. These factors are typically developed by statistically correlating critical stress levels caused by AASHTO design vehicles and FHWA operating vehicles.

Safety, Mobility, and Other Infrastructure Costs
Most costs of safety, mobility, and other related work are analyzed as common costs and allocated to the user classes on the basis of VMT. A few categories of these costs can be attributed to vehicle size differences and therefore are allocated on the basis of their PCE-weighted VMT (i.e., PCE-miles).

Cost Responsibilities by Vehicle Class
Under current indirect charging mechanisms, the unit cost responsibility values are compared with unit revenue contributions in order to identify inequities among vehicle classes and the fee structure is adjusted accordingly. Table 3 shows the unit cost responsibility values from a recent study in Indiana.

Table 3

A unit cost value is a ratio of allocated expenditures and the amount of travel; therefore, it is very sensitive to both values. Class 2 vehicles (automobiles) have relatively high amounts of travel compared to other vehicle classes. However, their very low cost responsibility per VMT (as illustrated in table 3) renders the ratio rather modest.

It is also important to note that a large percentage, as high as 50 percent (Luskin et al. 2002), of costs are common costs allocated on the basis of VMT. Cost responsibility values, therefore, cannot be directly translated to specific road user charges and should be used only as a guide to appropriate rates.

Direct User Charging (DUC) to Finance Highway Infrastructure

For the self-financing of highways, with user-based revenues adequate to cover expenditures associated with highway construction, reconstruction, rehabilitation, maintenance, and operations, a user fee structure can be guided by the cost responsibilities of each user class.

The amounts shown in table 3 for vehicle classes 1–3 (2 cents/mile) would help cover only current expenditures, not funding need. To be feasible, the cost allocation process must start with funding needs by work category (construction, reconstruction, rehabilitation, and maintenance) and the amounts adjusted upward to cover the administrative costs as well as costs for implementing the DUC scheme. The user charge amounts will depend on the cost responsibilities of each user class, which in turn depend on the distribution of expenditure levels across work categories over the cost allocation analysis period; if that period was marked by a significant change in spending in certain categories, then the cost responsibilities of various users will also change. For this reason, periodic updates in cost allocation are essential.

In Oregon’s 2013 road user charge pilot program (Oregon DOT 2014), which involved only automobile users, participants were billed monthly at a rate of 1.56 cents/mile, an amount that approximates the fuel tax paid by a vehicle with fuel efficiency of 20 miles/gallon plus an administrative fee. The values obtained by a study in Minnesota are 1 cent/mile (off-peak period) and 3 cents/mile (peak period) depending on the time of day (Baker 2014).

There are opportunities in direct charging for achieving broad societal goals. DUC not only can recoup agency costs for construction and upkeep of the highway infrastructure; by internalizing costs associated with safety, travel delay, air quality, and other impacts, it can also attain effectiveness, efficiency, and equity in highway taxation. A well-designed DUC mechanism allows variable pricing—by location, time of day, and weight class—to ensure that the charges are appropriate and help generate a stable revenue stream. The scheme can be gradually phased in, starting with a flat fee structure by vehicle class only.

Technology for Implementation

DUC implementation would require deployment of appropriate technologies to monitor road use and to collect fees. To monitor use, an on-board unit (OBU) installed on the vehicle’s windshield would communicate vehicle information to receivers on fixed locations (e.g., gantries) via dedicated short-range communication (DSRC) technology.1 Alternatively, because smartphones are equipped with GPS positioning capability, they could be used instead of OBUs (Bomberg et al. 2009).

Direct user fees could be paid using in-vehicle or out-of-vehicle systems or a combination of the two. For each method, available technologies include electronic payment, optical vehicle recognition, and global positioning systems (GPS), and developments in the smartphone have unleashed a world of opportunities for tracking travel amounts and electronic payment through direct bank transfers.

Under the DUC scheme, road users would periodically receive (by mail, email, or text message) a bill for distance driven, with adjustments for time of day of the travel, location of road class travelled, and other aspects (e.g., operating weight). The user would verify the bill and pay using standard or pay-as-you-go methods (e.g., a smartphone or vehicle dashboard communication console). In certain systems, smart cards store credit that can be used for subsequent payments; these cards can be inserted and read by the OBU and removed as needed. Some technologies available for automated DUC collection are shown in figure 3.

Figure 3

Technologies for travel monitoring and user payment continue to evolve rapidly, and it is quite possible that when direct charging is finally implemented, the technologies used will be much more advanced than those of the current era.

Oregon’s 2013 pilot study established some conditions that need to be fulfilled by DUC technology (Oregon DOT 2014):

  • The DUC system must operate as specified.
  • It should be reliable—that is, the mileage-reporting devices and account management system must not fail.
  • It must be secure, to protect the software from potential cyberattacks.
  • It must be highly scalable and flexible enough to accommodate input from any vendor of mileage reporting hardware.
  • The mileage reporting devices must not drain the vehicle battery or cause an increase in fuel consumption.

Overcoming Implementation Barriers
Implementation Costs

Direct user charging has fairly high startup costs for administration and operation, with an agency cost component and a user cost component. The agency costs include infrastructure and equipment capital costs, labor, future technological upgrades and maintenance, and administrative costs. The Oregon Department of Transportation estimated that implementation of its road user charging program would cost 10 percent of revenue raised ($4 million) for 100,000 users, and <5 percent of revenue raised (<$2 million) for 1,000,000 users (Oregon DOT 2014). These estimates were based on the technology available in 2013.

For the user, besides the fees for miles travelled, there are equipment costs. The Oregon DOT (2014) reported an estimated $50–$80 cost per user for the purchase of an external mileage reporting device, but with technological advances this cost is expected to fall significantly. Users may also incur indirect or intangible “costs” such as frustration and inconvenience during the initial period of implementation (Oh and Sinha 2010).

User Perceptions
To foster public acceptance of direct user charging, public outreach and communication initiatives must be pursued so that the public can fully comprehend and agree to the long-term user benefits of this highway revenue generation mechanism. Equity and privacy concerns must be addressed. Based on international experience (Sinha et al. 2011; NCHRP 2015), this can be done through balanced fee structures established from periodic cost allocation studies, exemptions, appropriate use of revenue generated by the DUC scheme, technology, and business rules.

Other Potential Challenges
The DUC mechanism should be financially efficient; that is, it must be capable of generating adequate revenues not only to replace the fuel tax structure but also to address the funding deficit, ensure revenue self-sufficiency, and pursue broad societal goals. It should be equitable: the user charges must be a good reflection of each user group’s assessed “wear and tear” of the highway infrastructure as well as other impacts of road use. The program should be implementable in a way that ensures fairness to all users, in order to win public trust and acceptance.

Concluding Remarks
If properly implemented, direct charging will enable flexibility for agencies to pursue public policy objectives related to congestion, emissions, travel demand management, environmental protection, and equity associated with road use. For example, direct charging may cause traffic shifts to other routes, times of day, or modes depending on policy objectives.

Finally, an analysis of the financial sustainability of highway funding will not be complete without consideration of emerging trends in vehicle technologies. The trend toward driverless vehicles is evolutionary and incremental. Most vehicles already incorporate some advanced features that are part of this trend; over the next decade, it is likely that driving functions will become even more automated and that driverless operations on limited-access highways will be permitted for some vehicles with such automated functions. In fact, according to a USDOT report, fully automated driving (i.e., a driver is no longer needed to steer or adjust speed) could be commercially available within 20 years (USDOT 2014). The widespread use of this new technology will have impacts on both highway revenues and needs.

Direct charging is well suited for synchronous implementation with autonomous and connected vehicle technology. Future research will be necessary to identify the issues associated with the interfaces of these initiatives and to facilitate their deployment.

References

AASHTO [American Association of State Highway and Transportation Officials]. 2010. Guide for the Local Calibration of the Mechanistic-Empirical Pavement Design Guide. Washington.

AASHTO. 2015. Mechanistic-Empirical Pavement Design Guide: A Manual of Practice, 2nd ed. Washington.

Ahmed A, Van Boxel D, Volovski M, Labi S, Sinha KC. 2011. Truck Travel Characteristics as an Indicator of System Condition and Performance. FHWA/IN/JTRP-2011/07. Joint Transportation Research Program, Indiana Department of Transportation and Purdue University, West Lafayette.

ASCE [American Society of Civil Engineers]. 2013. Report Card for America’s Infrastructure. Reston, VA.

Baker R. 2014. Vehicle Miles Traveled Fees. Technical Report PRC 14-02-P. College Station: Texas A&M Transportation Institute.

Bomberg M, Baker R, Goodin G. 2009. Mileage-based user fees: Defining a path toward implementation, Phase 2: An assessment of technology issues. Final Report, UTCM Project #09-39-07. University Transportation Center for Mobility, Texas Transportation Institute. College Station: Texas A&M University.

FHWA [Federal Highway Administration]. 1997. Final Report on the 1997 Federal Highway Cost Allocation Study. Washington: US Department of Transportation.

FHWA. 2015. Highway Statistics Table VM-2 Functional System Travel 2014 (Annual Vehicle Miles). Office of Highway Policy Information. Washington. Available at https://www.fhwa.dot.gov/policyinformation/statistics/ 2014/vm2.cfm.

Gulen S, Nagle J, Weaver J, Gallivan V. 2000. Determination of Practical ESALs per Truck Values on Indiana Roads. Technical Report FHWA/IN/JTRP-2000/23. Joint Transportation Research Program. West Lafayette, IN: Purdue University.

Klatko T, Agbelie B, Labi S, Fricker J, Sinha K. 2015. Framework for VMT Estimation. Joint Transportation Research Program. West Lafayette, IN: Purdue University.

Luskin D, Garcia-Diaz A, Lee D, Walton M, Zhang Z. 2002. Texas Highway Cost Allocation Study, Research Report 0-1810-2. Prepared for the Texas Department of Transportation, Austin.

NCHRP [National Cooperative Highway Research Program]. 2015. Public Perception of Mileage-Based User Fees: A Synthesis of Highway Practice. NCHRP Synthesis 487. Washington. Available at http://onlinepubs.trb.org/onlinepubs/nchrp/nchrp_syn_487. pdf.

NSTIFC [National Surface Transportation Infrastructure Financing Commission]. 2009. Paying Our Way: A New Framework for Transportation Finance. Washington. Available at http://financecommission.dot.gov/Documents/NSTIF_Commission_ Final_Report_Advance%20Copy_Feb09.pdf.

Oh J, Sinha KC. 2010. Self-financing and distance-based highway pricing scheme: State highway system perspective. Journal of Infrastructure Systems 17(3):95–106.

Oregon DOT. 2014. Road Usage Charge Pilot Program & Per-Mile Charge Policy in Oregon. Salem.

Randall J. 2012. Traffic Recorder Instruction Manual. Austin: Texas Department of Transportation.

Sinha KC, Labi S, Arman M. 2011. Lessons from International Experience: Direct Charging Mechanisms for Highway Use. Prepared for the National Transport Development Policy Committee, Planning Commission of the Government of India (in cooperation with Harral, Winner, Thompson, Sharp, Klein, Inc.).

TRB [Transportation Research Board]. 2006. The Fuel Tax and Alternatives for Transportation Funding. Special Report 285. Washington: National Academies Press.

USDOT [US Department of Transportation]. 2014. Beyond Traffic 2045: Trends and Choices. Washington.

Volovski M, Bardaka E, Zhang Z, Agbelie B, Labi S, Sinha KC. 2016. Indiana state highway cost allocation and revenue attribution study and estimation of travel by out-of-state vehicles on Indiana highways. Joint Transportation Research Program. West Lafayette, IN: Purdue University. 

Yoder EJ, Witczak MW. 1975. Principles of Pavement Design, 2nd ed. Hoboken, NJ: John Wiley & Sons.

FOOTNOTES

1  An OBU is a device with memory storage, computing capability, and an interface for communicating with DSRC, cellular networks, or GPS.

About the Author:Bismark R. Agbelie is a postdoctoral research fellow, Samuel Labi is an associate professor of civil engineering, and Kumares C. Sinha (NAE) is Edgar B. and Hedwig M. Olson Distinguished Professor of Civil Engineering, all at Purdue University.