Highway Infrastructure: FHWA's Model for Estimating Highway Needs Is
Generally Reasonable, Despite Limitations (Letter Report, 06/05/2000,
GAO/RCED-00-133).
Pursuant to a legislative requirement, GAO provided information on how
the Federal Highway Administration (FHwA) determines highway investment
requirements, focusing on the: (1) methodology the Highway Economic
Requirements System (HERS) computer model uses to generate its estimates
of the nation's highway investment requirements; (2) strengths and
limitations of the model; and (3) usefulness of the HERS estimates for
deciding on federal investments in highway infrastructure.
GAO noted that: (1) 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; (2) 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; (3) the model also uses
information, such as vehicle operating costs and emissions' obtained
from other sources; (4) the HERS model uses the data to: (a) project the
future condition and performance of the highway system; (b) assess
whether any highway improvements are warranted; and (c) select and
implement appropriate improvements; (5) 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; (6)
a major strength of the model is its ability to assess the relative
benefits and costs associated with alternative options; (7) the model
has limitations, however, in that it: (a) does not completely account
for the effect of highway improvements on all other highways and modes
of transportation; (b) does not fully account for the uncertainties
associated with its methods, data, and assumptions; (c) relies on a
computational shortcut to approximate the future lifetime benefits of an
improvement; and (d) uses data that vary in quality; (8) HERS estimates
can be useful as a general guide for the investment requirements of the
nation's highways included in the model, and for assessing relative
investment requirements over time; (9) nevertheless, limitations and
uncertainties associated with making forecasts prevent the estimates
from being a precise forecast of highway investment requirements; (10)
FHwA includes the HERS estimates in its current report on the conditions
and performance of the nation's highways, bridges, and transit systems;
(11) in the report, however, FHwA does not clearly disclose the level of
uncertainties in the HERS estimates; (12) 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; and (13) 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.
--------------------------- Indexing Terms -----------------------------
REPORTNUM: RCED-00-133
TITLE: Highway Infrastructure: FHWA's Model for Estimating
Highway Needs Is Generally Reasonable, Despite Limitations
DATE: 06/05/2000
SUBJECT: Highway research
Highway planning
Data integrity
Public roads or highways
Management information systems
Cost effectiveness analysis
Computer modeling
Life cycle costs
Highway engineering
Federal aid for highways
IDENTIFIER: DOT Highway Economic Requirements System
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GAO/RCED-00-133
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
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
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
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
Resources, Community, and
Economic Development Division
B-284060
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 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.
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 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.
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.
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 fixed-percentage procedure. See figure 1.
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 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.
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.
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.
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.
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.
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 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.
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.
Source: FHWA.
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.
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 (1997) levels of travel time
and vehicle user costs. See table 2 for the HERS estimates representing the
different scenarios.
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
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 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.
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, the World 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.
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
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
cost-effective 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 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
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 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
state-level 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.
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.
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).
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.
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 single-point
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.
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
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.)
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 benefit-cost 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 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.
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.
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 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
Scope and Methodology
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 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.11 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
Description of the HERS Model
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.
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.12 See figure 5 for a
representation of the process used to create the HERS input 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
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 sample-related 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.13 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 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.
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.14 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.
Source: FHWA data.
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.15 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 long-run 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").16 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 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.
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.
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 indicated that
computational time is no longer an issue because of the improvement in
processing speeds.
Results of Sensitivity Analyses Using the HERS Model
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.
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
9.2 3.1 5.5
−1.5 for short run and from
−1.6 to −2.0 for long run
Changing "Discount Rate" from 7 percent to
4 percent 5.4 5.8 5.6
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 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.
b Percent 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.
GAO Contacts and Staff Acknowledgments
John H. Anderson, Jr. (202) 512-2834
Katherine Siggerud (202) 512-2834
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.
(348194)
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
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
1. See 23 U.S.C. section 502(g) and 49 U.S.C. section 308(e).
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.
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.
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).
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.
7. StratBENCOST was developed by HLB Decision Economics, Inc. for the
National Cooperative Highway Research Program.
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).
10. HERS uses a pavement deterioration "submodel" to forecast pavement
condition. See appendix II.
11. Highway Needs: An Evaluation of DOT's Process for Assessing the Nation's
Highway Needs (GAO/RCED-87-136 ).
12. 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.
13. Highway Performance Monitoring System Reassessment, Final Report,
Revised April 1999, FHWA-PL-99-001.
14. In some analyses, the baseline is a less "aggressive" improvement rather
than no improvement at all.
15. 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.
16. 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.
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