GAO

United States General Accounting Office

Report to Congressional Committees

June 2000 HIGHWAY

INFRASTRUCTURE

FHWA’s Model for

Estimating Highway

Needs Is Generally

Reasonable, Despite

Limitations

GAO/RCED-00-133

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Contents

Letter 3

Appendixes Appendix I: Scope and Methodology 24

Appendix II: Description of the HERS Model 26

Appendix III: Results of Sensitivity Analyses Using the

HERS Model 36

Appendix IV: GAO Contacts and Staff Acknowledgments 38

Tables Table 1: Development of Highway Investment Requirements

Report and FHWA’s Models 8

Table 2: The HERS Model’s Estimates for Highways 13

Table 3: Percentage Change in HERS Estimates Resulting From

Changes in Input Data 36

Figures Figure 1: FHWA’s Projected Annual Highway and Bridge Investment

Requirements, 1998 through 2017 7

Figure 2: FHWA’s Road Classification System 9

Figure 3: Simplified Representation of the HERS Modeling Process 11

Figure 4: Sensitivity of HERS Estimate to Changes in Certain

Assumptions 20

Figure 5: Schematic of Process Used to Create HERS Data 28

Figure 6: Simplified Representation of the Structure of the HERS

Model 31

Abbreviations

DOT Department of Transportation

EPA Environmental Protection Agency

FHWA Federal Highway Administration

GAO U.S. General Accounting Office

HERS Highway Economic Requirements System

HPMS Highway Performance Monitoring System

IRI International Roughness Index

PSR Present Servicability Rating
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United States General Accounting Office

Washington, D.C. 20548

Resources, Community, and

Economic Development Division

B-284060 Letr

June 5, 2000

The Honorable Bob Smith

Chairman

The Honorable Max S. Baucus

Ranking Minority Member

Committee on Environment and Public Works

United States Senate

The Honorable Bud Shuster

Chairman

The Honorable James L. Oberstar

Ranking Democratic Member

Committee on Transportation and Infrastructure

House of Representatives

Transportation systems play a vital role in the nation’s economy by

facilitating the movement of people and goods. The United States has made

significant investments in its transportation infrastructure. Effective

management of this infrastructure depends in part on reliable methods for

estimating the amount of continuing investment required for maintaining

and improving the transportation system. In this context, the Congress has

required the Department of Transportation (DOT) to report every 2 years

on the nation’s need for investment to maintain and improve the nation’s

highways and bridges.To help estimate these future investment

requirements, the Department’s Federal Highway Administration (FHWA)

uses the Highway Economic Requirements System (HERS) computer

model.

The Transportation Equity Act for the 21st Century (P.L. 105-178) directed

GAO to evaluate and report to the Congress how the Department of

Transportation determines highway investment requirements using the

HERS model. Accordingly, this report describes (1) the methodology the

model uses to generate its estimates of the nation’s highway investment

requirements, (2) the strengths and limitations of the model, and (3) the

usefulness of the HERS estimates for deciding on federal investments in

highway infrastructure. In reporting on investment requirements, DOT

includes estimates for highways, bridges, and transit systems. This report

focuses on highway investment requirements and the HERS model’s

portion of these requirements.We used a draft of DOT’s latest Conditions
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and Performance Report, dated January 10, 2000, as the source of DOT’s

estimated investment requirements for highways. DOT approved this

report for issuance on May 2, 2000, without changes to this material.We

reviewed the model’s documentation and interviewed its developers and

operators, evaluated the model using general economic standards for

models of this type, interviewed experts in transportation modeling to

obtain their views, and interviewed legislative and executive branch

officials who use the model and its results. See appendix I for more

information on the methodology we used and a list of the transportation

modeling experts we contacted.

Results in Brief The HERS computer model estimates investment requirements for the

nation’s highways by adding together the costs of highway improvements

that the model’s benefit-cost analyses indicate are warranted. In making its

estimates, the model relies on extensive data on highway segments

throughout the nation, such as pavement conditions and expected growth

in traffic, which the states primarily collect and update. The model also

uses information, such as vehicle operating costs and emissions, obtained

from other sources. The HERS model uses the data to (1) project the future

condition and performance of the highway system, (2) assess whether any

highway improvements are warranted, and (3) select and implement

appropriate improvements. Such improvements range from resurfacing a

highway to adding lanes and are based on a comparison of the construction

costs and the lifetime benefits of the improvement. Adding a lane to relieve

projected congestion, for example, has benefits because the increased

capacity can reduce travel time and vehicle operating costs. FHWA uses the

HERS model to estimate highway infrastructure improvement costs for

certain highways under several different scenarios. For example, under an

“economic efficiency” scenario, the HERS model estimates that, for these

highways, the cost of constructing improvements for which the estimated

benefits exceed the construction costs would be about $48 billion per year

(1997 dollars) out of FHWA’s overall estimate of $94 billion in investment

requirements for all roads and bridges. Similarly, under a “maintain current

conditions” scenario, the HERS model estimates that for these highways,

the least costly mix of improvements that would maintain the pavement

condition of the highways at current levels (1997) would be about

$29 billion per year, out of FHWA’s overall estimate of $57 billion in

investment requirements for all roads and bridges.

The HERS model has several strengths that make it a unique and

reasonable tool for estimating a general level of national highway
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investment requirements, but it also has some limitations that affect the

precision of its results. A major strength of the model is its ability to assess

the relative benefits and costs associated with alternative options for

improving the nation’s highway infrastructure. This is a significant

improvement over FHWA’s previous method, which used engineering

standards to identify highway deficiencies and estimated the cost of

correcting these deficiencies without regard to economic merit. In June

1999, the HERS model was reviewed by an expert panel, which found that

FHWA has strengthened the model over time. The model has limitations,

however, in that it (1) does not completely account for the effect of

highway improvements on all other highways and modes of transportation;

(2) does not fully account for the uncertainties associated with its methods,

data, and assumptions; (3) relies on a computational “shortcut” to

approximate the future lifetime benefits of an improvement; and (4) uses

data that vary in quality. The overall effect of these limitations on the HERS

estimates cannot be determined; however, they indicate a level of

imprecision with the estimates. Although FHWA plans to improve the

model by addressing the limitations in the computational shortcut and the

data, transportation modeling experts generally agree that a more complete

accounting of the interrelationships between all highways and

transportation modes cannot be done with the current state of the art in

transportation modeling. In addition, changing the model to account for the

uncertainties in its methods, data, and assumptions would be costly.

HERS estimates can be useful as a general guide for the investment

requirements of the nation’s highways included in the model, such as rural

and urban interstates, and for assessing relative investment requirements

over time. Nevertheless, the limitations and inherent uncertainties

associated with making forecasts prevent the estimates from being a

precise forecast of highway investment requirements. FHWA includes the

HERS estimates in its current report on the conditions and performance of

the nation’s highways, bridges, and transit systems. In the report, however,

FHWA does not clearly disclose the level of uncertainties in the HERS

estimates. Furthermore, to derive a total estimate of highway investment

requirements, FHWA combines the HERS estimates with estimates for

other types of highways and investments that are not based on benefit-cost

analyses. As a result, the report’s readers are not likely to be aware of the

imprecision of the HERS estimates and the fact that only part of the total

highway investment requirements is estimated on the basis of an

assessment of the benefits and costs of alternative improvement options.
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This report makes recommendations to improve the model’s

approximation of the future lifetime benefits of highway improvements and

FHWA’s disclosure of some of the uncertainties associated with the model’s

estimates in its report to the Congress. DOT generally agreed with these

recommendations.

Background DOT submits biennial reports to the Congress detailing the state of the

nation’s highways, bridges, and other surface transportation systems. The

Conditions and Performance Report to Congress, known as the C&P

Report, fulfills the mandate1 for a report on future highway investment

requirements that the Congress first established in 1965. The reports

include forecasts of investment requirements for the nation’s highways and

bridges over the following 20 years.

FHWA’s estimates of total highway and bridge investment requirements in

the C&P Report combine estimates derived from the HERS model, a bridge

model, and other types of estimates. The HERS model uses benefit-cost

analyses to estimate future highway investment requirements on the basis

of information about existing highways. On the other hand, the bridge

model is based on engineering data and does not currently use benefit-cost

analyses in estimating investment requirements for bridges. In addition,

FHWA supplements these two estimates by including the cost of improving

those highways not modeled in HERS. These costs include estimates for

new highways, highway classes not included in the HERS model, and

highway-related requirements such as safety enhancements, traffic

operation improvements, and environmental improvements. FHWA

estimates these costs by assuming that they represent a fixed percentage of

the combined HERS and bridge models’ estimate of investment

requirements. The percentages are based on data from 1997 highway

expenditures. Of the total highway and bridge average annual investment

requirements identified in the C&P Report ($94 billion), only 51 percent are

derived using the HERS model and its benefit-cost analyses. The remaining

49 percent are derived using either the bridge model or the fixedpercentage procedure. See figure 1.

1 See 23 U.S.C. section 502(g) and 49 U.S.C. section 308(e).
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Figure 1: FHWA’s Projected Annual Highway and Bridge Investment Requirements,

1998 through 2017

Dollars in billions

Source: FHWA 1999 C&P Report.

The methodology FHWA uses to estimate highway investment

requirements has changed since the first “wish list” of estimates was

submitted to the Congress in 1968. The earliest estimates simply collected

and reported investment requirements prepared by the states. In the early

1980s, the agency designed an engineering model that identified highway

deficiencies and estimated the cost to improve them on the basis of

engineering standards such as pavement deterioration and road design.

Recognizing that a benefit-cost approach combined with an engineering

model could yield a more defensible estimate of future investment

requirements, FHWA began developing the HERS model in 1988. However,

the agency used its engineering model exclusively to forecast highway

$47.9 • HERS model estimates

$13.4 •

Highway classes not modeled

in HERS

$14.6 •

New construction not modeled 

in HERS

$7.5

Highway-related needs 

not modeled in HERS

$10.6

Bridge model estimates

•

•
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investment requirements until the 1995 C&P Report. This report

incorporated one estimate based on HERS benefit-cost analyses and a

second estimate based on the engineering model approach. Table 1 outlines

FHWA’s efforts to estimate highway investment requirements. According to

FHWA officials, the HERS benefit-cost approach complies with an

executive order2 that requires federal spending for infrastructure to be

based on a systematic analysis of expected benefits and costs.

The HERS model estimates investment requirements for 9 of FHWA’s

12 classes of roads—those that are included in the agency’s database of

highway conditions. FHWA classifies public roads in the United States into

12 categories. Area categories include rural and urban highways.

Functional categories are arterials, collectors, and local roads. Arterials

allow the highest traffic speeds. They often have multiple lanes and a

degree of access control. Collectors are designed for lower speeds and

shorter trips. They typically are two-lane roads that may extend into

residential neighborhoods. Local roads are any roads below the collector

system. Other categories distinguish roads by significance criteria, for

example, interstate highways or major and minor traffic flows. Figure 2

shows which classes of roads are modeled in HERS.

2 Executive Order 12893, Principles for Federal Infrastructure Investments (1994),

discusses the importance of continuous infrastructure investment to sustained economic

growth. The order directs federal agencies with infrastructure investment responsibilities to

plan for investments using a systematic analysis of expected benefits and costs.

Table 1: Development of Highway Investment Requirements Report and FHWA’s

Models

Year FHWA effort

1968 First FHWA highway investment requirements report (response to

1965 statutory requirement).

Early 1980s FHWA designs model to estimate highway investment requirements

using engineering standards.

1988 to 1994 FHWA develops HERS model, adding economic analyses to

engineering-based estimates.

1995 First C&P Report to include HERS results.

1999 First C&P Report with environmental costs of vehicle emissions

included in HERS results.
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Figure 2: FHWA’s Road Classification System

Source: GAO analysis of FHWA information.

From fiscal years 1995 through 1999, FHWA spent a total of $2.4 million on

HERS support contracts. In 1999, FHWA spent a total of $677,345 on

expenses related to the HERS model. For example, FHWA contracted to

develop revised pavement information at a cost of $150,986. In addition,

FHWA spent $350,000 on HERS support for the 1999 C&P Report, ongoing

maintenance and operation of the model, and a study on the needs of the

interstate highway system.

Rural interstates

Rural other

principal arterials 

Rural minor arterials

Rural major collectors 

Rural minor collectors 

Rural local roads

Urban interstates

Urban freeways and

expressways 

Urban other

principal arterials 

Urban minor arterials 

Urban collectors Urban local roads

Rural roads

Urban roads

Arterials Collectors

Arterials Collectors

Local roads

Local roads

FHWA uses HERS 

to project needs 

for these highways.

FHWA uses non-HERS

methods to project 

needs for these highways. 

KEY
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The HERS Model Uses

Benefit-Cost Analyses

to Estimate Highway

Investment

Requirements

To estimate future investment requirements,3 the HERS model uses an

extensive set of data on segments of highways throughout the nation to

conduct benefit-cost analyses. The HERS model uses these data to forecast

the condition and performance (congestion) of the highway segments over

the following 20 years and to evaluate whether improving the segments is

economically justified. The HERS model evaluates potential improvements

on each segment by comparing their construction costs with their benefits,

including reductions in travel times, vehicle operating costs, and accidents,

to determine whether an improvement is warranted. FHWA uses the HERS

model to estimate highway investment requirements under several

different scenarios.

The HERS Model Relies on

Extensive Data

To estimate investment requirements, the HERS model uses a database of

information about highway conditions and performance submitted by the

states. Using guidance developed by FHWA, each state collects and

annually updates data on a sample of highways representing nine highway

classes. These data include factors like highway capacity, average annual

daily traffic, pavement roughness, and lane width. In total, the states collect

and report to FHWA information on about 125,000 highway segments,

ranging in length from one block to 10 miles. The states also develop

forecasts of traffic growth on each segment. The HERS model uses

“expansion” factors to generalize the estimated improvement costs for

segments to the highway classes they represent.

In addition to the state-collected data, the HERS model uses other

information that FHWA derives from various economic studies. For

example, in estimating the benefits associated with highway

improvements, the HERS model counts as a benefit any reduction in travel

time brought about by the highway improvement. In making this

calculation, FHWA uses hourly compensation data from the Department of

Commerce’s Bureau of Labor Statistics to quantify the dollar value of travel

time saved by travelers on work-related trips. In addition, as currently

modeled in HERS, highway improvements increase net traffic and hence

total vehicle emissions. As a result, the HERS model subtracts the dollar

value of the air pollution damages caused by vehicle emissions from the

3 In using “investment requirements,” we are referring to the HERS model’s estimates of

average annual infrastructure improvement costs for the nine highway classes included in

the model.
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benefits of making an improvement. FHWA obtains emissions data for

several classes of vehicles from the Environmental Protection Agency

(EPA). FHWA also obtains dollar estimates from the economic literature

for the human health and property damages caused by specific pollutants.

The HERS Model Evaluates

the Relative Benefits and

Costs of Alternative

Improvement Options

The HERS model simulates the effects of infrastructure improvements for

the highways it models by comparing the relative benefits and costs

associated with alternative improvement options.4 The HERS model begins

by assessing the current condition of the highway segments in the data

sample. The model then projects the future condition and performance of

the segments, based on expected changes in factors such as traffic,

pavement condition, and average speed. Performance is measured in terms

of highway congestion. The model makes its projections in four 5-year

increments (funding periods), for a total of 20 years.

Figure 3 provides a simplified representation of the modeling process. The

model compares each segment’s future condition with FHWA criteria for

highway deficiencies for factors such as pavement condition, congestion,

and lane width. For each segment identified as deficient (not meeting the

criteria), the model assesses the relative costs and benefits associated with

alternative improvement options to determine whether improving the

segment is economically justified. The options range from resurfacing the

pavement to completely reconstructing the road and adding lanes.

Figure 3: Simplified Representation of the HERS Modeling Process

Source: FHWA.

4 FHWA documented the model’s specifications in its draft report entitled Highway

Economics Requirements System Technical Report (U.S. Department of Transportation,

Federal Highway Administration, 1999).

Identify

deficient

segments

Assemble 

highway 

data (traffic 

forecasts,

highway 

conditions, etc.)

Forecast 

future 

condition and 

performance 

of segments

Identify 

economically 

justified 

improvements 

for deficient 

segments

Select and 

implement 

segment 

improvements 

Extrapolate 

segment

improvement

costs to

develop 

investment 

requirements
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The HERS model calculates costs as the capital expenditures required to

construct the improvement and calculates the benefits as reductions in

factors like travel time, vehicle operating costs, and accidents over the

lifetime of the improvement. For example, adding lanes in congested areas

can be beneficial because the increased capacity can reduce travel times,

and operating costs.5 Future benefits are discounted to the present.6 The

HERS model selects for implementation those improvements that are

economically justified, including those improvements for which the

estimated benefits exceed the cost of constructing the improvement

(positive net benefits). To estimate the investment requirements for the

highways it models, the HERS model uses “expansion” factors to generalize

segment improvement costs to the nine highway classes included in the

model. The expansion factors enable the HERS model to relate information

about the sampled segments to the highway classes they represent.

Investment requirements for the combined highway classes are obtained by

adding together the estimates for the nine different classes. Appendix II

describes the structure of the HERS model.

The HERS Model Estimates

Highway Investment

Requirements for Several

Different Scenarios

FHWA uses the HERS model to forecast the investment requirements for

the highways represented in the model on the basis of several different

scenarios. For example, under the “economic efficiency” scenario, the

HERS model selects for implementation those improvements that have

positive net benefits (benefits minus costs). The investment requirements

under this scenario are about $48 billion per year from 1998 through 2017.

Similarly, under the cost to “maintain current (pavement) conditions”

scenario, the HERS model selects for implementation the least costly mix

of improvements that would maintain average pavement conditions at 1997

levels over the forecast period. Under this scenario, the investment

requirements are about $29 billion per year. In addition to these scenarios,

FHWA estimates the investment requirements for maintaining current

5 The HERS model also uses “price elasticity” to assess the behavioral response of drivers to

changes in the cost of traveling on the highway. Price elasticity mitigates to some extent the

beneficial aspect of making highway improvements. For example, because improving a

segment lowers travel costs, some drivers may respond by driving more frequently. As a

result, traffic on the improved segment may increase more quickly than anticipated,

reducing the future benefits of the improvement.

6 Discounting accounts for the fact that, in general, one dollar today is worth more than one

dollar a year from now.
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(1997) levels of travel time and vehicle user costs. See table 2 for the HERS

estimates representing the different scenarios.

Table 2: The HERS Model’s Estimates for Highways

Note: Dollars are 1997 dollars. These estimates reflect only the HERS portion of FHWA’s estimates of

highway investment requirements.

Source: FHWA’s 1999 C&P Report.

The HERS Model Has

Strengths and

Limitations

The HERS model has several strengths that make it a unique and

reasonable tool for estimating a general level of the nation’s highway

infrastructure requirements. A major strength of the model is its ability to

assess the relative benefits and costs associated with alternative options

for making improvements on the nation’s highways. We found no other

transportation model that could assess benefits and costs of alternative

improvement options at the national level. In addition, FHWA has convened

expert panels to assess the reasonableness of the HERS methodology and

has made some changes to the model in response to recommendations

from the panels. The model also has several limitations. First, it does not

completely account for the interrelationships between all highways and

different transportation modes, such as how traffic is redistributed as

improvements are made. Second, it does not fully account for the

uncertainties associated with its methods, data, and assumptions. Third, it

relies on a computational “shortcut” to approximate the future lifetime

benefits of an improvement, even though this is no longer necessary.

Finally, it uses data that vary in quality. Although the net effect of the

limitations on the HERS estimates cannot be determined, FHWA is taking

steps to mitigate some of these limitations.

Dollars in billions

Scenario

HERS forecast of

annual costs

Economic efficiency $47.9

Maintain current travel times 39.1

Maintain current vehicle user costs 31.1

Maintain current pavement conditions 29.4
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The HERS Model’s Major

Strength Is Its Application

of Benefit-Cost Analyses in

Assessing Highway

Investments

The HERS model’s major strength is its ability to assess the relative

benefits and costs associated with potential improvements in the nation’s

highways. This is a significant improvement over FHWA’s previous

methods, which used engineering standards to identify deficiencies and

select improvements without regard to economic merit. By contrast, the

HERS model selects for implementation only those improvements that are

economically justified. We found no model other than HERS that is capable

of applying benefit-cost analyses in estimating investment requirements at

a national level. For example, theWorld Bank’s Highway Design and

Maintenance Standards model is designed to be used at the project level. In

addition, a model known as StratBENCOST uses benefit-cost analyses to

evaluate state and local highway projects.7

Another strength of the HERS model is that FHWA has consulted with

experts in order to assess the model’s reasonableness and improve it. For

example, in June 1999, FHWA convened an expert panel consisting of

economists and engineers from the public and private sectors. This panel

found that FHWA has strengthened the model over time and that the recent

refinements have increased its applicability and credibility.

FHWA has also instituted several procedures to make the state-provided

data for the HERS model as reasonable as possible. For example, FHWA

periodically conducts workshops to inform state transportation officials

about changes to the database used by the HERS model, and FHWA staff

are available to conduct additional training at the states’ request. In

addition, FHWA recently completed reassessing its database needs to

eliminate unnecessary data items and reduce the states’ data collection

burden. Changes as a result of this reassessment became effective in 1999,

and the states will submit data reflecting these changes to FHWA in June

2000. As a result of the reassessment, FHWA identified the potential for

reducing the number of sampled segments in the database to 80,000 from

its current level of about 125,000.

The HERS Model Has Some

Limitations

Although the HERS model is a reasonable tool, we noted that it has several

limitations. First, because the model analyzes each highway segment

independently rather than the entire transportation system (collectively

7 StratBENCOST was developed by HLB Decision Economics, Inc. for the National

Cooperative Highway Research Program.
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referred to as a network), it cannot completely reflect changes occurring

among all highways and modes in the transportation network at the same

time. For example, the HERS model does not capture the effect on traffic

levels of improving one highway segment while leaving neighboring

segments unimproved. The HERS model incorporates information on how

changes in costs to users of vehicles affect the demand for travel (via “price

elasticity”). As a result, FHWA officials assume that the HERS model

captures the net effect of all changes in the transportation network as well

as the overall economy. However, we did not find consensus among the

transportation modeling experts we interviewed that the HERS model

completely captures the net effect of all changes in the network. The

implication of this limitation is unclear—it may over- or under-estimate the

effect of changes in traffic resulting from a highway improvement.

Nonetheless, transportation modeling experts we talked to generally agree

that explicitly modeling the entire transportation network is not possible

with the current state of the art in modeling or available data.

Second, because the HERS model is not designed to completely quantify

the uncertainties associated with its methods, assumptions, and data, the

model cannot estimate the full range of uncertainties within which its

estimates vary. As a result, the precision of the model’s estimates is

unknown. In making its estimates, the HERS model relies on a variety of

estimating techniques and hundreds of variables, all of which are subject to

some uncertainties. Executive Order 12893 states that federal agencies, in

evaluating infrastructure investments, should address uncertainty when

the amount and timing of important benefits and costs are uncertain. For

its C&P Report, FHWA accounted for some uncertainties by conducting

“sensitivity analyses” to measure how much the HERS estimates change

when the value of certain key inputs or assumptions used in the model are

changed. Nevertheless, the sensitivity analyses do not account for all the

uncertainties in the model. We discussed this issue with one of the HERS

model’s developers, who indicated that, according to his understanding of

the model, the uncertainty associated with the “single point” estimates

could range up to plus or minus 30 percent. However, changing the model

to fully account for uncertainties in its factors is not likely to be costeffective because it could require extensive and expensive reprogramming.

Third, the HERS model uses a computational shortcut to approximate the

lifetime benefits associated with an improvement. Benefits and costs

should be measured over each improvement’s full lifetime, 20 years or

more. However, in its initial evaluation of whether to improve a highway

segment, the HERS model calculates benefits, such as reductions in travel
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time, only during the first 5-year period. To account for the benefits

accruing after the first 5 years, FHWA developed a shortcut that essentially

uses an estimate of the improvement’s construction cost as a proxy for the

improvement’s remaining future benefits.8 FHWA developed the shortcut

several years ago, when limitations in computer processing power

necessitated simplifying some of the calculations. Several of the

transportation modeling experts we talked to question whether these costs

are a reasonable approximation of future benefits. Ideally, the model

should estimate the benefits associated with an improvement over its full

lifetime, discounted to the present. FHWA officials acknowledged that the

shortcut is a limitation that is no longer necessary given recent

improvements in computer processing power.

Fourth, although FHWA has taken steps to ensure that the data used in the

HERS model are reasonable, some of these data vary in quality. For

example, the HERS model relies on emissions data that some members of

FHWA’s 1999 expert panel consider unrepresentative of actual conditions.

To estimate the emissions associated with traffic on a given segment, the

model uses information from EPA on emissions rates per vehicle type and

speed. Vehicle emissions, however, may depend more on how the vehicle is

driven than on the total miles driven. FHWA officials told us they recognize

that the emissions data may not reflect actual conditions but included the

data to approximate the environmental effect of highway travel. EPA is

currently revising these emissions data.

In addition, we reported earlier that the pavement roughness data reported

by the states to FHWA are not comparable, partly because the states use

different devices to measure roughness.9 The HERS model uses the

roughness data in projecting the pavement condition of each segment.

Moreover, some of the information used in the model is dated. For

example, the pavement resurfacing costs used in the HERS model are

based on 1988 data (adjusted for inflation from 1988 to 1997).

Finally, to project the future condition of the pavement, the HERS model

uses information that does not fully capture the range of environmental

8 With this shortcut, the HERS model assumes that the remaining future benefits of an

improvement can be approximated by the costs that would be avoided by making the

improvement in the current 5-year period. See appendix II for more information.

9 Transportation Infrastructure: Better Data Needed to Rate the Nation’s Highway

Conditions, (GAO/RCED-99-264, September 27, 1999).
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conditions affecting the nation’s highways.10 To account for the effect of

climate on pavement condition, for instance, the model assumes all

segments face freezing and thawing conditions. However, segments in

warm and drier areas of the country rarely face freezing or thawing

conditions, and FHWA officials acknowledged that the pavement

information does not completely account for these conditions. Although

the effect of the variability in the quality of the data has not been

determined, it reduces confidence in the overall precision of the HERS

estimates.

FHWA Plans to Improve the

HERS Model

FHWA recognizes that the HERS model has some limitations and is taking

steps to improve it. For example, FHWA officials said they plan to revise

the emissions data used in the HERS model as soon as EPA finishes

revising its emissions model. In addition, FHWA plans to update the

pavement resurfacing costs, currently based on 1988 data, to represent

1998 or 1999 costs. FHWA also has contracted with one of the model’s

developers to incorporate varied pavement performance information based

on different climate zones throughout the country instead of assuming one

climate as is now done. FHWA officials also expressed interest in revising

the model to eliminate the computational shortcut used to approximate

benefits. They said that as of March 2000, FHWA has not yet contracted to

make this improvement. Furthermore, beginning this fiscal year, they plan

to modify the HERS model to incorporate the effects of user fees, such as

motor fuel taxes, into the model’s assessment of the benefits and costs of

alternative highway improvements.

In addition, FHWA is currently developing a state-level “prototype” of the

HERS model in order to provide the states with the ability to forecast statelevel highway investment requirements. FHWA is incorporating into the

model selected features from customized versions of the HERS model

developed for transportation officials in Indiana and Oregon by a private

contractor. After the development of the state-level prototype is complete,

FHWA will provide the model to a limited number of states as part of a pilot

program to determine the usefulness of the model for state-level highway

planning.

10 HERS uses a pavement deterioration “submodel” to forecast pavement condition. See

appendix II.
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HERS Estimates Can

Be a Useful Tool to Aid

Decisionmaking but

Have Limits

HERS estimates are useful as a general guide for the investment

requirements of the nine highway classes represented in the model. In

addition, the HERS estimates developed for the “economic efficiency”

scenario can be useful for assessing the relative requirements of the

highway classes over time. Congressional and federal agency officials told

us they use the estimates as an overall indicator of highway needs.

However, the limitations and inherent uncertainties associated with

making forecasts prevent these estimates from being a precise forecast of

investment requirements. In addition, because the current version of the

HERS model was designed to estimate investment requirements at the

national level, the estimates derived from this model should not be used to

project investment needs for particular highway projects. Finally, as

presented in the 1999 C&P Report, the uncertainties associated with the

HERS estimates are not highlighted, and the HERS estimates are combined

with other estimates that are not based on an assessment of the relative

benefits and costs of alternative improvement options.

HERS Estimates Are Useful

as a General Guide for

Investment Requirements

In general, the HERS estimates provide legislative and executive branch

officials one source of information to use for decisionmaking. Legislative

and executive branch officials told us that they use the estimates in the

C&P Report to obtain general information on the nation’s need for

infrastructure investments. Legislative branch officials told us that HERS

estimates are more useful than previous estimates that were based on

engineering analyses alone. Furthermore, different groups may use the

HERS estimates in funding debates. For example, according to an FHWA

official, construction industry interests could use the higher investment

scenario estimate to show legislators a need for a higher level of highway

funding.

In addition to serving as a general guide, the HERS estimates for the

economic efficiency scenario can be useful in assessing the relative

investment requirements over time for the nine highway classes

represented in the model. Adjusting for inflation and changes in the model’s

formulas, assumptions, and data between reports, the HERS estimates

from different reports can be compared to assess whether investment

requirements are increasing, decreasing, or remaining the same. For

example, using data developed for the 1995 C&P Report and the current

C&P Report, FHWA found that the average annual highway investment

requirements increased slightly, from $46.1 billion to $47.9 billion (1997

dollars).
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Page 19 GAO/RCED-00-133 FWHA’s HERS Model

Although the HERS model provides a general estimate of the highway

investment requirements, in our view it is important that the model not be

used for other than its intended purpose. First, while some federal officials

have expressed an interest in using the HERS model to determine which

highway projects should receive funding, the current version of the HERS

model was developed to estimate investment requirements nationwide. As

a result, the estimated investment requirements generated by the HERS

model should not be used for project-level estimates.

Second, federal decisionmakers we spoke with expressed an interest in

retrospectively comparing actual highway investments by the states with

those forecast by the HERS model. This comparison could be misleading

because states may base their highway improvement decisions on criteria

other than those used in the HERS model. For example, under the

economic efficiency scenario, the model implements only those

improvements that are economically justified (that have positive net

benefits). However, some states may fund highway improvements that

would not pass the same economic test. For example, states may improve a

highway in an economically disadvantaged area in an attempt to foster

economic development.

Third, although comparing the HERS estimates developed for the

economic efficiency scenario in successive C&P Reports can be useful,

making the same comparison using the HERS estimates for the maintain

current conditions scenario could be misleading. Currently, the data used

by the HERS model to establish the current condition of the highway

system are updated every year. Because the HERS model uses the current

condition of the highway system as a “baseline” in projecting future

investment requirements, the HERS estimates for the maintain current

conditions scenario can be influenced by the prior level of state spending.

For example, if state spending on highway improvements declines relative

to estimated investment requirements, the condition of the highway system

might also decline. The subsequent HERS projection would be based on a

new baseline, reflecting a decline in the condition of the highway system

from the previous period. Moreover, the estimated investment

requirements required to maintain the new current condition into the

future would also decline since less investment would be required to

maintain a more deteriorated condition. Such a decline in estimated

investment requirements over time, however, might be misconstrued to

indicate that the condition of the highway infrastructure is improving,

when in fact it would indicate a decline in the baseline condition.
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Page 20 GAO/RCED-00-133 FWHA’s HERS Model

HERS Estimates Could be

More Clearly Presented

As we discussed, the HERS model has several limitations that affect its

ability to precisely estimate investment requirements. Furthermore,

forecasting highway investments using computer models is by its nature an

inexact science, and a model cannot capture all the complexities of

transportation systems. Although FHWA conducted sensitivity analyses to

quantify some of the uncertainties associated with the HERS estimates

developed for its 1999 C&P Report, the report does not highlight the results

of these analyses. For example, FHWA found that increasing its traffic

growth assumption by 31.5 percent increased the HERS estimate by about

17 percent, from $47.9 billion to $56.1 billion (see fig. 4). The change in the

assumption represented actual average annual growth from 1977 to 1997.

However, because the C&P Report presents the HERS estimates as singlepoint estimates and the results from the sensitivity analyses are presented

in a separate chapter later in the report, the range of uncertainties

disclosed by the sensitivity analyses may not be evident to the reader. See

appendix III for additional results from sensitivity analyses.

Figure 4: Sensitivity of HERS Estimate to Changes in Certain Assumptions

Source: FHWA.

Note: Dollars are 1997 dollars. Results are for the economic efficiency scenario, and represent the

effect of changes in certain assumptions used in the HERS model. For example, the overall average

annual growth in traffic in terms of vehicle miles traveled was increased by 31.5 percent, the discount

1997 dollars in billions

0

10

20

30

40

50

60

47.9

56.1

50.6

43.0

HERS

estimate

Overall

traffic

Discount 

rate

Urban

traffic
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Page 21 GAO/RCED-00-133 FWHA’s HERS Model

rate was lowered from 7 to 4 percent, and the average annual growth in traffic in the largest urbanized

areas was decreased by 100 percent (to no growth). In terms of the latter assumption, about

29 percent of the estimate represents highway improvements in the largest urbanized areas.

In addition, when reporting on investment requirements for highways and

bridges, the C&P Report did not clearly disclose that its estimates are only

partially modeled using benefit-cost analyses. Specifically, only 51 percent

of the reported investment requirement is based on the HERS model and its

benefit-cost analyses. The other 49 percent, which consists of bridges and

non-modeled factors such as the construction of new highways, is not

based on the same methodology and thus has not been proven to be

economically justified. As a result, the estimates are technically not

comparable. In addition, FHWA views the highway investment

requirements estimated outside the HERS model as less reliable. Although

the C&P Report presents the estimates relating to highways and bridges

separately, it combines the HERS-modeled estimates with the non-modeled

estimates. Thus, as currently presented, it may not be evident to the reader

that only a portion of the total highway investment requirements is based

on benefit-cost analyses and as a result is economically justified. (See fig. 1

for an analysis of these estimates.)

Conclusions In developing the HERS model to forecast the investment requirements for

the nation’s highways, FHWA has taken steps to enhance the model’s

integrity and rigor. Furthermore, because the model incorporates benefitcost analyses in selecting potential highway improvement projects for

inclusion in its estimates, it is a significant improvement over previous

methods, which used engineering standards to identify highway

deficiencies and estimated the cost of correcting these deficiencies without

regard to economic merit. The HERS model selects those improvements

that are economically justified and as a result provides the Congress with a

more useful and realistic estimate. Although FHWA significantly improved

upon the analytical rigor of previous methods by incorporating benefit-cost

analyses, the HERS model has some limitations that affect the precision of

its estimates.

While not all the limitations in the HERS model can be addressed because

of the inherent complexities of modeling, FHWA is taking steps to improve

the model. FHWA has expressed interest in changing the model to

eliminate the shortcut for calculating an improvement’s lifetime benefits

but has not established a timeframe for this change. It is also planning to

improve the model’s information on pavement performance and cost.

FHWA could present the model’s estimates more effectively in its C&P
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Page 22 GAO/RCED-00-133 FWHA’s HERS Model

Report to help the report’s readers be aware of the full extent of the caveats

and uncertainties associated with the estimates. In particular, FHWA could

highlight the uncertainties associated with the HERS estimates as indicated

by its sensitivity analyses so that readers of the report do not believe the

estimates are more precise than they actually are. Finally, FHWA’s C&P

Report generally presents an overall estimate of all highway investment

requirements—combining the HERS estimates with other estimates that

are developed using less rigorous methods. The report could highlight the

difference between these estimates and note that FHWA has more

confidence in the HERS-generated estimates.

Recommendations In order to ensure that the HERS model achieves its objectives and that the

limits of its estimates and the estimates presented in future conditions and

performance reports are disclosed, we recommend that the Secretary of

Transportation direct the Administrator of FHWA to

• establish a timeframe for revising the HERS model in order to account

for the expected lifetime benefits that are associated with alternative

highway improvement options;

• clarify, when presenting the HERS estimates, that there are

uncertainties associated with the estimates and refer readers to the

sensitivity analyses performed on the HERS model that illustrate these

uncertainties; and

• explain in the report that one portion of the estimate for highway

investment requirements is from the HERS model and is based on

benefit-cost analyses and that the other portion was calculated using

less reliable methods, as well as the percentage that each of these

portions constitutes of the overall estimate.

Agency Comments and

Our Evaluation

We provided a draft of this report to the Department of Transportation for

review and comment. We met with Department officials, including the

Team Leader for Highway Needs and Investment Planning in the Federal

Highway Administration. These officials generally agreed with the findings

and recommendations in this report. With regard to the recommendation to

establish a timeframe for accounting in the model for the expected lifetime

benefits of highway improvements, the Department plans to eliminate the

computational shortcut it uses to approximate future lifetime benefits in

time to prepare estimates for the C&P Report it will issue in 2003. In

response to the recommendation to clarify the uncertainties associated
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Page 23 GAO/RCED-00-133 FWHA’s HERS Model

with HERS estimates, the Department plans to expand its use of

uncertainty analysis beyond the analysis in the 1999 report for the C&P

Report for 2001 in order to provide a more complete discussion of this

issue. Finally, in response to the recommendation to distinguish between

HERS model estimates and other less reliable estimates, the Department

plans to clarify and enhance its discussion of these differences in the C&P

Report for 2001, including a figure similar to our figure 1. In addition, the

Department will work to expand the scope of HERS to consider more types

of highway deficiencies and solutions to address them in order to reduce

the percentage of estimates using these less reliable methods. The

Department also provided technical and clarifying comments, which we

incorporated into the report as appropriate.

We conducted our review from September 1999 through April 2000 in

accordance with generally accepted government auditing standards.

We will send copies of this report to cognizant congressional committees;

the Honorable Rodney E. Slater, Secretary of Transportation; and the

Honorable Kenneth R. Wykle, Administrator, Federal Highway

Administration.

If you or your staff have any questions about this report, please contact me

at (202) 512-2834. Appendix IV lists key contacts and contributors to this

report.

John H. Anderson, Jr.

Director, Transportation Issues
Page 24 GAO/RCED-00-133 FWHA’s HERS Model

Appendix I

Scope and Methodology AAppenednxidxeIis

To assess the reasonableness of the Highway Economic Requirements

Systems (HERS) model’s assumptions and data, and the usefulness of the

model’s results, we reviewed the Principles for Federal Infrastructure

Investments (Executive Order 12893), the Federal Highway

Administration’s (FHWA) June 1999 expert panel’s comments on the HERS

model, and several FHWA reports and documents on the HERS model from

1994 through 1999.

In addition, we discussed the HERS methodology with FHWA economists

and engineers and two of the FHWA contractors that helped develop the

model. Moreover, we interviewed users of the HERS’ results, including

legislative and executive-branch officials, several members of the June

1999 HERS expert panel, and other transportation modeling experts (see

list of names below). We attended the June 1999 expert panel meeting as

well as an FHWA-sponsored outreach meeting on the Conditions and

Performance Report (C&P Report) in November 1998. We used standard

economic principles to evaluate the model’s application of benefit-cost

analyses and the key economic assumptions used in the model, and we

asked FHWA to provide us with results for sensitivity analyses conducted

using alternative values for price elasticity and the discount rate. In

addition, we reviewed the methods used by other transportation models to

assess highway investments.

To assess the reasonableness of the data used in the HERS model, we

reviewed technical documents supporting the primary source of data—the

Highway Performance Monitoring System (HPMS) database. In addition,

we discussed the reliability of the HPMS data with FHWA officials,

including the Chief of Highway Systems Performance. Because FHWA uses

a “preprocessor” to convert the HPMS data into a HERS input data file, we

reviewed the actions performed by the preprocessor to assess whether the

values of the data elements in HPMS are consistent with those in the HERS

input data file. To do this, we asked FHWA to provide us with basic

statistics and frequencies for several key data elements in the HPMS

database, both before and after the data were converted by the

preprocessor. The data included average annual daily traffic,

surface/pavement type, weighted design speed, peak and off-peak percent

of vehicles with greater than four tires, speed limit, and widening

feasibility. For most of the data items, the actions of the preprocessor

produced at most minor changes in a very small percentage of the data

elements. For the data items for which the actions of the preprocessor

affected a larger percentage of the data elements, we asked FHWA to

conduct a sensitivity analysis in order to assess the effect of changes in the
Appendix I

Scope and Methodology

Page 25 GAO/RCED-00-133 FWHA’s HERS Model

data items on the HERS estimates, using the maximum economic efficiency

scenario. We found that changes in these data items did not markedly

change the HERS estimates. See appendix III for the results of these

sensitivity analyses.

In August 1987, we reported on our review of FHWA’s HPMS sampling

plan.1 We found it to be statistically reasonable for selecting highway

sections nationally. For our current effort, we reviewed FHWA’s current

guidance, which the states use to sample segments, and found it consistent

with the guidance we reviewed in 1987.

The individuals we contacted include the following experts.

• Adjo Amekudzi, Assistant Professor of Civil and Environmental

Engineering, Georgia Institute of Technology

• Kenneth D. Boyer, Professor of Economics, Department of Economics,

Michigan State University

• Gregorio Camus, Programmer, Battelle Memorial Institute

• David J. Forkenbrock, Professor of Civil and Environmental

Engineering and Chair, Public Policy Center, University of Iowa

• David Greene, Economist, Oak Ridge National Laboratory

• Chris Hoban, Principal Highway Engineer, The World Bank

• Douglass Lee, Principal Investigator, Volpe National Transportation

Center

• Sue McNeil, Professor of Civil and Environmental Engineering, Carnegie

Mellon University

• Mike Markow, Cambridge Systematics

• Michael Meyer, Professor and Chair, School of Civil and Environmental

Engineering, Georgia Institute of Technology

• Carl L. Monismith, Robert Horonjeff Professor of Civil and

Environmental Engineering and Professor in the Graduate School,

University of California at Berkeley

• Arlee Reno, Engineer, Cambridge Systematics

• Herb Weinblatt, Principal, Cambridge Systematics

1 Highway Needs: An Evaluation of DOT’s Process for Assessing the Nation’s Highway

Needs (GAO/RCED-87-136).
Page 26 GAO/RCED-00-133 FWHA’s HERS Model

Appendix II

Description of the HERS Model ApendxiI

This appendix describes the basic structure of the HERS computer model.

The HERS model simulates infrastructure improvement decisions for the

highways it models by comparing the relative benefits and costs associated

with alternative improvement options. In conducting its analysis, HERS

uses an extensive set of data that are primarily collected and updated by

the states and maintained by FHWA in the HPMS database. In addition, the

HERS model consists of several submodels representing specific highway

processes, including traffic growth, pavement wear, vehicle speed,

accidents, and highway improvement costs. The analysis, which is based

on the current condition of the highway system, is conducted over four 5-

year periods, for a total of 20 years. Information from the submodels is

used to identify deficient segments, evaluate alternative improvement

options, and select and implement improvements. HERS uses benefit-cost

ratios (benefits divided by costs) to evaluate and select improvements

under several investment scenarios. The costs are the capital expenditures

necessary to construct the improvement, and the benefits include

reductions in users’ operating costs, agency maintenance costs, and the

“residual value” of an improvement. Residual value represents the benefits

expected to accrue over the future life of an improvement beyond the

analysis period used in the model. HERS uses a computational shortcut to

estimate residual value.
Appendix II

Description of the HERS Model

Page 27 GAO/RCED-00-133 FWHA’s HERS Model

HERS Uses an

Extensive Data Set

HERS uses input data that are created from the HPMS database and several

parameter and control files. HPMS consists of all the data collected and

updated by the states on about 125,000 randomly selected highway

segments across the United States, ranging in length from one block to 10

miles. The parameter and control files include information such as

deficiency and design standards and basic instructions for the model.

These data are converted to a HERS input file by a separate model called

the “preprocessor,” which aggregates all the data and performs various

data manipulations. For example, the preprocessor assigns a speed limit of

75 mph to segments with no legally mandated maximum speed limit, and it

converts the International Roughness Index data developed by the states to

a “modified” Present Serviceability Rating (PSR) index.1 See figure 5 for a

representation of the process used to create the HERS input data.

1 The HERS pavement deterioration submodel was not designed to use the International

Roughness Index (IRI) so the preprocessor converts the IRI data to a “modified” PSR. The

conversion is based on formulas developed by Al-Omari and Darter in Relationships

Between IRI and PSR, Department of Civil Engineering, University of Illinois, 1992. Both IRI

and PSR are measures of pavement condition, but IRI strictly measures surface roughness

while PSR incorporates other types of pavement distress and may be based on professional

judgement. IRI is measured by a moving vehicle using non-contact sensors such as lasers.
Appendix II

Description of the HERS Model

Page 28 GAO/RCED-00-133 FWHA’s HERS Model

Figure 5: Schematic of Process Used to Create HERS Data

Source: FHWA data.

Developed in 1978 as a national highway transportation system database,

HPMS is a nationwide inventory system that includes limited data on all

public roads and more detailed data for a sample of highway segments

representing nine different highway classes. The sampled data include

information on highway capacity, average annual daily traffic, pavement

roughness, and lane width. In addition to the sample data, the states are

required to report certain basic inventory information for all public roads

that are open to traffic, including an inventory of roads by highway class.

The states also develop traffic forecasts for each segment. In addition, the

HERS model uses “expansion” factors to extrapolate the cost estimates to

the highway classes represented by the segments. The expansion factors

are calculated by the HMPS software the states use to submit the data to

FHWA.

Overall, the HPMS database includes nearly 100 variables. According to

FHWA’s Chief of Highway Systems Performance, the most accurate data in

the HPMS database are variables that are directly measurable, such as the

length of the highway section, number of lanes in the section, and speed

limit. By contrast, the least accurate data are variables that are open to

interpretation by state personnel, such as whether it is feasible to widen a

HERS preprocessor

HPMS

data file

HERS 

input data file

HERS model 

Other data 

(parameter and 

control files) 

Other data 

(parameter and 

control files) 
Appendix II

Description of the HERS Model

Page 29 GAO/RCED-00-133 FWHA’s HERS Model

segment and the estimated percent of trucks traveling in peak and off-peak

periods. For example, in assessing whether a segment can be widened, one

state may view the potential high costs of widening as a detriment while

another state may not. In addition, the states generally estimate the percent

of trucks traveling during peak and off-peak periods from classification

counts taken in a limited number of locations and of varying times and

durations.

FHWA developed an HPMS field manual for the states to use in sampling

highway segments and identifying which data items to collect and how to

measure them. The sampling plan requires the states to select stratified

random samples, where the strata represent different volume groups for

different highway classes in the rural, small urban, and urbanized areas of

each state. Estimates of average annual daily traffic are based on volume

counts on each segment. Since each state selects its own sample,

implementation of the sampling plan may vary.

FHWA has instituted some measures to improve the reasonableness of the

HPMS data. FHWA provided the states with software they can use to

assemble, edit, and submit their HPMS data. This software automatically

performs checks for basic validity and missing data. Once the states edit

their data, they run an expansion subroutine that places an expansion

factor in each sample segment’s record that is used to expand sample data

to the full functional system. Once FHWA receives the data from the states,

the data are passed through a software program that conducts basic logic

checks, searches for anomalies, and reviews the distributions of samplerelated items. FHWA staff review all items flagged during this check. FHWA

works closely with the states to obtain answers to its questions concerning

the HPMS data. Nonetheless, the potential for some variability in HPMS

data remains because of potential differences in data collection techniques

among the states.

In addition, from December 1996 through December 1998, FHWA

reassessed its database needs in an effort to eliminate unnecessary data

items and reduce the states’ data collection burden.2 As part of this effort,

FHWA conducted public meetings with state officials to obtain their views

on a future focus for the HPMS database. As a result of the reassessment,

FHWA will make significant changes to the HPMS database. FHWA

2 Highway Performance Monitoring System Reassessment, Final Report, Revised April 1999,

FHWA-PL-99-001.
Appendix II

Description of the HERS Model

Page 30 GAO/RCED-00-133 FWHA’s HERS Model

changed the HPMS field manual and software to guide the states in making

needed changes. For example, FHWA decided to delete some data that the

states have collected in the past but that it determined are no longer

needed, such as the number of interchanges on segments. In addition,

FHWA “collapsed” some data items into fewer categories to reduce state

officials’ time spent in collecting data. For example, the variable describing

the surface or pavement type was reported in 15 categories, many of which

were of little use, so these were reduced to 6 categories. In addition to

these changes, the FHWA reassessment identified the potential for

reducing the HPMS sample from over 125,000 segments to 80,000 segments

to help reduce the states’ data collection burden. The states began

implementing the changes during their data collection efforts in 1999 and

will report the revised data to FHWA by June 2000.

The HERS input data and additional parameter and control data are used

by the HERS model to assess the relative benefits and costs of making

highway improvements. The post-preprocessor parameter and control data

include information that is independent of specific segments, such as

travel-time costs, widening feasibility criteria, and the discount rate.

HERS’ Submodels

Represent Different

Highway Processes

The HERS model consists of several submodels representing specific

highway processes, such as traffic growth, pavement wear, operating costs,

emissions costs, and highway improvement costs. The submodels are used

to project the future condition and performance of the highway system

with and without improvements (for example, the baseline) for each

funding period and each segment.3 In addition, the benefits associated with

making highway improvements are estimated using several submodels

linked together. Benefits are defined as reductions in user costs (travel

time, safety, vehicle operating costs) and agency maintenance costs. In

addition, the “residual value” of an improvement is considered to be a

benefit. The implementation costs associated with making improvements

are estimated using an improvement cost submodel. The information from

the submodels is used to evaluate the benefits and costs of alternative

improvement options, and select for implementation improvements that

are economically justified. See figure 6 for a simplified representation of

the structure of the HERS model.

3 In some analyses, the baseline is a less “aggressive” improvement rather than no

improvement at all.
Appendix II

Description of the HERS Model

Page 31 GAO/RCED-00-133 FWHA’s HERS Model

Figure 6: Simplified Representation of the Structure of the HERS Model

Source: FHWA data.

Travel 

forecast 

Forecast 

pavement 

condition 

Forecast 

vehicle 

speed 

Estimate 

improvement 

costs 

Estimate costs 

(travel time, 

operating, safety, 

emissions, etc.)

Evaluate 

and select 

improvements for 

implementation 
Appendix II

Description of the HERS Model

Page 32 GAO/RCED-00-133 FWHA’s HERS Model

The travel forecast submodel projects traffic growth on each segment,

taking into account the price elasticity of travel demand. For each segment,

the submodel uses information on the amount of current traffic (average

annual daily traffic); initial price of travel (user costs, including operating,

and travel time and safety costs); the state’s traffic growth projection; and

price elasticity to project future traffic volume in each funding period.

Price elasticity measures the effect of changes in travel costs on travel

demand.4 Because there are no empirical estimates of elasticity with

respect to total travel demand, FHWA uses a range of information on

elasticities for the components that constitute total travel demand,

including the price of fuel, vehicle wear, tolls, parking, and travel time.

FHWA constructs a total demand elasticity, taking into account these

effects as well as the share of each component in the total price of travel.

For the 1999 C&P Report, the HERS model uses a price elasticity of −1.0 for

the short run (over one funding period) and −1.6 for the long run (see app.

III for sensitivity analysis results using −1.5 and −2.0 for the short- and longrun values, respectively). The output of the travel forecast submodel—

adjusted traffic growth—serves as an input in the pavement deterioration,

speed, and accident submodels. For example, increases in traffic growth

can cause additional pavement wear and reduce average vehicle speed.

The pavement deterioration submodel is used to measure the effect of

traffic and the environment on the future condition of the pavement. In

general, this submodel uses adjusted traffic growth to project the effect of

traffic on a segment’s future pavement condition, in terms of its PSR. PSR is

a measure of pavement condition, ranging from 0 (very poor or extremely

deteriorated pavement) to 5.0 (very good or smooth pavement). In

estimating future PSR, the submodel relies on equations that were derived

in one climate zone (“wet/freeze”).5 To account for the effect of

environment on pavement wear, the submodel assumes a minimum

deterioration rate. In general, the minimum rate is a function of the time the

pavement was last improved and its maximum life span (from 25 to 40

years, depending on the type of pavement). Output from the pavement

4 More specifically, the price elasticity of demand is a measure of the percentage change in

quantity demanded resulting from a percentage change in price. For example, suppose the

price elasticity of demand for travel were estimated to be -0.8. Thus, if the price of travel

increases by 1 percent, travel demand would be expected to fall by 0.8 percent.

5 HERS uses road test equations developed by the American Association of State Highway

Officials at a test site in Ottawa, Illinois. Because this site is located in a wet/freeze climate

zone, the equations reflect the effect of only this one climate zone. The equations are being

updated to incorporate the effect of more environmental factors.
Appendix II

Description of the HERS Model

Page 33 GAO/RCED-00-133 FWHA’s HERS Model

deterioration submodel is used in the speed, user operating costs, and

agency maintenance costs submodels. For example, increases in traffic

growth can cause the pavement to deteriorate, further increasing vehicle

operating costs. Moreover, worn pavement can reduce vehicle speeds, slow

travel time, and increase a vehicle’s fuel and maintenance costs.

The user costs submodel is used to assess the effect of future pavement

condition and vehicle speed on travel-time costs, vehicle operating costs,

and safety costs. Reductions in these costs brought about by highway

improvements are considered “benefits.” In measuring travel-time costs,

the submodel considers both the time spent traveling by drivers for work

purposes as well as by drivers for commuting, leisure, and other nonwork

purposes. In the case of work-related trips, the submodel estimates travel

time costs primarily on the basis of hourly compensation for each vehicle

occupant. For the value of nonwork trips, the submodel uses 60 percent of

each occupant’s hourly compensation, excluding fringe benefits.

Vehicle operating costs are measured as a function of several factors,

including pavement condition, highway grades and curves, and speed

change cycles (for example, frequency of stopping). The submodel

assesses the effect of these factors on various components of operating

costs, including fuel and oil consumption, tire wear, vehicle maintenance,

and vehicle depreciation. For example, tire wear and vehicle maintenance

needs can increase as pavement condition worsens. In addition, steep

grades and more frequent stopping can increase a vehicle’s fuel and oil

consumption.

The improvement cost submodel uses information on improvement type,

highway class, and terrain type (flat, rolling, and mountainous) to project

the capital costs required to construct an improvement. The capital costs

represent the initial costs of constructing an improvement and depend on

the type of improvement. In the case of improvements involving

resurfacing or reconstructing pavement and widening lanes, improvement

costs represent initial construction costs and expenditures required to

obtain rights of way. For improvements that also involve an alignment, the

HERS model estimates an additional cost that represents the cost required

to improve a segment’s substandard curves and grades. In addition to these

improvements, the model estimates the cost of improving substandard

conditions on urban freeways requiring reconstruction in certain

circumstances (for example, when shoulders are unfinished). The

improvements’ costs are used in evaluating the benefits and costs of

alternative improvement options.
Appendix II

Description of the HERS Model

Page 34 GAO/RCED-00-133 FWHA’s HERS Model

The HERS model uses information from the submodels to identify deficient

segments, evaluate the benefits and costs of alternative improvement

options, and select and implement improvements. The model calculates

benefit-cost ratios (total benefits divided by capital costs) to evaluate

alternative improvement options for deficient segments. Improvements

that meet specific investment criteria are selected and implemented. For

example, under the economic efficiency scenario, the HERS model

implements for each deficient segment the most “aggressive” improvement

with a benefit-cost ratio greater than 1. In so doing, the model maximizes

net benefits and, as a result, generates an economically efficient solution.

“Aggressive” refers to the type of improvement that the model considers.

For example, both the resurfacing and pavement reconstruction

improvement types might improve the condition of a segment, but

pavement reconstruction would be the more aggressive option because it

requires more extensive construction. The HERS model extrapolates

improvement costs using expansion factors in the HPMS database. The

model combines the expanded improvement costs for all segments, and

summarizes them by highway functional class.

HERS Uses Computational

Shortcut to Estimate

Lifetime Benefits of an

Improvement

For certain portions of the analysis, the HERS model uses a “shortcut” to

approximate the benefits that would accrue over the lifetime of an

improvement. For example, for deficient segments, the model begins by

conducting an analysis for one funding-period (5 years) to assess whether

the segment should be improved in the current funding period or in some

later period. A “no improvement” baseline is used to evaluate the timing of

this investment decision. Because an improvement will continue to provide

annual benefits after the first funding period is over, the model

approximates these future benefits using information on the improvement’s

cost. More specifically, these future benefits are approximated by the

improvement’s construction cost minus the depreciation in the

improvement after the first funding period, plus the cost savings from not

having to maintain an unimproved segment in later funding periods. The

total amount is referred to as the “residual value” of the improvement and

is added to the other benefits associated with making an improvement.

Ideally, in evaluating alternative improvement options, the HERS model

should compare estimated implementation costs with the present value of

benefits expected to occur in each future funding period. According to one

of the model’s developers, limitations in computer processing power when

the HERS model was first developed prevented them from accounting for

the full life cycle of benefits. As a result, they developed a computationally

simpler algorithm to evaluate and select improvements. The developer also
Appendix II

Description of the HERS Model

Page 35 GAO/RCED-00-133 FWHA’s HERS Model

indicated that computational time is no longer an issue because of the

improvement in processing speeds.
Page 36 GAO/RCED-00-133 FWHA’s HERS Model

Appendix III

Results of Sensitivity Analyses Using the

HERS Model ApendxIi

Table 3 summarizes the results of sensitivity analyses FHWA performed on

the HERS model. FHWA changed the value of one of the variables used in

the HERS model by the amount indicated in the first column. The results of

these changes on the HERS estimate are shown in columns 2 through 4.

Table 3: Percentage Change in HERS Estimates Resulting From Changes in Input Data

Note: Sensitivity analyses based on HERS version 3.26D, used in developing the 1999 C&P Report.

For all variables except price elasticity and discount rate, changes were made in the HERS

preprocessor output data file. For price elasticity and discount rate, changes were made in the HERS

parameter file.

a Variables are defined as follows:

D is the thickness (or depth) of rigid pavement on sampled roadway segments and SN is the structural

number for flexible pavement on sampled roadway segments. HPMS contains the actual value when it

is known. Otherwise, HPMS contains a typical value for the functional system and pavement type

based on historical data or state practice. The HERS preprocessor assigns either slab thickness (D) or

structural number (SN) to all paved sections for which SN or D was not supplied in the HPMS

database. Depending on the information available, the assignment process may reference the

section’s surface type; pavement section (if heavy, medium, or light); or traffic volume data.

Peak Percent Trucks and Off-Peak Percent Trucks is an estimate of trucks as a percentage of all traffic

during peak or off-peak travel times. States generally estimate using a small number of classification

count stations, comparing the sample section to similar segments elsewhere, and using local

knowledge of travel patterns.

Weighted Design Speed is the speed for which the highway is designed, weighted by the length of the

horizontal curves and tangents in a sample section. The HPMS database requires weighted design

speed only for rural major collectors. For rural sections and some urban sections (interstates and other

Percent change in HERS estimateb

Changes in variablea Rural Urban Overall

Decreasing “D” by 1.4 (equivalent to 10 percent of its range from 0 to 14) 0.3 0.7 0.5

Increasing “D” by 1.4 (equivalent to 10 percent of its range from 0 to 14) -0.1 -0.4 -0.3

Decreasing “SN” by 0.5 (equivalent to 10 percent of its range from 1 to 6) 6.6 4.4 5.2

Increasing “SN” by 0.5 (equivalent to 10 percent of its range from 1 to 6) -1.5 -0.8 -1.1

Decreasing “Off-Peak Percent Trucks” by 20 percent -1.2 -0.8 -0.9

Increasing “Off-Peak Percent Trucks” by 20 percent 1.1 0.4 0.7

Decreasing “Peak Percent Trucks” by 20 percent -0.9 -0.4 -0.6

Increasing “Peak Percent Trucks” by 20 percent 0.9 0.3 0.6

Decreasing “Weighted Design Speed” by 10 percent 0.9 1.7 1.4

Increasing “Weighted Design Speed” by 10 percent -0.6 -0.7 -0.6

Decreasing “Modified PSR” by 10 percent 6.8 10.4 9.0

Increasing “Modified PSR” by 10 percent -4.8 -7.1 -6.2

Changing “Price Elasticity” from −1.0 to

−1.5 for short run and from −1.6 to −2.0 for long run

9.2 3.1 5.5

Changing “Discount Rate” from 7 percent to 4 percent 5.4 5.8 5.6
Appendix III

Results of Sensitivity Analyses Using the

HERS Model

Page 37 GAO/RCED-00-133 FWHA’s HERS Model

freeways and expressways) without reported curves, the HERS preprocessor reads the weighted

design speed from a lookup table (Appendix M in the HPMS Field Manual).

Modified PSR (Present Serviceability Rating) is a measure of the pavement condition of a sample

section. For PSR, states assign values to the pavement condition of a segment using a scale from 0.0

(extremely deteriorated pavement) to 5.0 (new, or nearly new, superior pavement). Most states also

provide information on pavement roughness in terms of the International Roughness Index (IRI). The

HPMS database reports pavement condition in terms of the IRI for 70.5 percent of the segments and

PSR for 84.7 percent of the segments. However, because HERS was not designed to use IRI data, the

HERS preprocessor converts all IRI measurements to a “modified” PSR value. In cases where both IRI

and PSR values are reported for a segment, the IRI value is converted to a “modified” PSR value,

which replaces the original PSR value.

bPercent changes are based on HERS estimates of about $18.8 billion for Rural, $29.1 billion for

Urban, and $47.9 billion for Overall (1997 dollars) calculated for the economic efficiency scenario.

Rural is the total annual average improvement cost for rural interstates, other principal arterials, minor

arterials, and major collectors. Urban is the total annual average improvement cost for urban

interstates, other freeways and expressways, other principal arterials, minor arterials, and collectors.

Overall is combined Rural and Urban.

Source: FHWA’s Highway Economic Requirements System.
Page 38 GAO/RCED-00-133 FWHA’s HERS Model

Appendix IV

GAO Contacts and Staff Acknowledgments ApendxIVi

GAO Contacts John H. Anderson, Jr. (202) 512-2834

Katherine Siggerud (202) 512-2834

Staff

Acknowledgments

In addition to those named above, Richard Calhoon, Catherine Colwell,

Timothy J. Guinane, Mehrzad Nadji, Judy K. Pagano, Raymond Sendejas,

and Phyllis F. Scheinberg made key contributions to this report.

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