Using SMITE-ML 2.2 To Evaluate Road Pricing Alternatives

Patrick DeCorla-Souza, AICP

Team Leader

## FEDERAL HIGHWAY ADMINISTRATION

Office of Transportation Policy Studies, HPTS

400 Seventh St. SW, Room 3324

Washington, DC 20590

Tel: (202)-366-4076

Fax: (202)-366-7696

e-mail: <patrick.decorla-souza@fhwa.dot.gov>

1.0 INTRODUCTION

Interest in road pricing as a congestion management and revenue
generating mechanism is increasing in the U.S. Two types of priced
express lanes are under consideration in several metropolitan areas --
HOT lanes and Express Toll lanes. \"HOT" is the acronym for "High
Occupancy/Toll."  On HOT lanes, low occupancy vehicles are charged a
toll, while High-Occupancy Vehicles (HOVs) are allowed free or
discounted use. Generally, an HOV is defined as a vehicle carrying two
or more persons. Tolls vary by time-of-day, either according to a
pre-set schedule or in real time (i.e., "dynamically") in order to
manage traffic demand and ensure free flow of traffic. Tolls are
collected at highway speeds using electronic toll collection technology.
Express Toll (ET) lanes operate in a similar fashion, the only
difference being that HOVs are not exempt from tolls. Both types of
priced lanes may be combined with new express bus services or Bus Rapid
Transit (BRT) operating on the free flowing priced lanes. Public
officials are interested in how these concepts compare with one another
with regard to their congestion mitigation and financial implications.

This study estimates the impacts of ET and HOT concepts with and without
new BRT service in a prototypical suburban transportation corridor in a
major metro area, in order to facilitate an understanding of the
trade-offs between transportation performance and financial feasibility
with regard to such concepts.

### 2.0 PRICING CONCEPTS 

The prototypical corridor is a major heavily congested suburban freeway
travel corridor in a large metropolitan area in the Northeast. The
corridor is 20 miles long, and 40% growth in travel demand is
anticipated over a 20-year period. The existing freeway facility in the
corridor has 8 lanes. Available right-of-way is only sufficient for
expansion of the freeway by one added lane in each direction.

ET and HOT concepts selected for consideration include two priced lanes
in each direction. Thus, they require taking one existing lane in each
direction for use as a priced lane in conjunction with an added lane. ET
and HOT concepts involving a *single* priced lane in each direction were
excluded from consideration, for the following reasons. First, a single
separated lane makes it impossible for a faster vehicle to overtake a
slower vehicle. This can cause back-ups behind a slower vehicle,
reducing the speed and level of service for those vehicles caught behind
the slower vehicle. It may also lead to gaps in front of the slower
vehicle, reducing lane throughput. Secondly, carpooling rates in major
travel corridors in large metro areas are often forecasted to be high in
future -- high enough to fill up and even exceed the capacity of a
single lane during peak periods. Thus, there would not be spare capacity
available to "sell" to low-occupancy toll-paying vehicles. A single HOT
lane would therefore not be feasible, unless vehicle occupancy
requirements were raised above the currently prevailing requirements in
most major metropolitan areas. Finally, in case of accidents and vehicle
breakdowns, it would be easier to move traffic through a two-lane
configuration than through a single lane configuration.

The ET and HOT concepts selected for consideration would divide the new
5-lane configuration in each direction into two sections - three regular
lanes and two priced lanes. Free access would be provided for transit
vehicles. Both concepts would utilize one new lane and take one existing
lane for use as two priced lanes. Some have questioned public
acceptability of such a concept in view of the failure of past attempts
to take general-purpose lanes for restricted use. However, the ET
concept analyzed for this study is quite different with regard to its
effects. Since the freeway will be expanded, congestion will actually be
reduced on the general-purpose (GP) lanes. Vehicle demand per lane will
be lower than prior to expansion (i.e., the No Build case). This is very
different from previous experiences, when more motorists were forced
onto remaining GP lanes, *increasing* the number of vehicles that would
need to be served per GP lane and thus exacerbating congestion.

Moreover, even if a freeway were not expanded, the establishment of
*priced* lanes has a different effect than establishment of HOV lanes.
HOV lanes are often underutilized. Priced lanes on the other hand are
fully utilized and actually *increase* freeway vehicle throughput per
lane in peak periods relative to throughput per lane on regular lanes.
This occurs because of the loss of vehicle throughput in GP lanes due to
severely congested conditions ([1]{.underline}). Data from the SR 91
Express Toll Lanes in Orange County, CA indicate that vehicle throughput
per lane on the ET lanes in peak hours in March 2004 was twice that on
the adjacent regular lanes ([2]{.underline}). Further, when taking GP
lanes for use as priced lanes, surplus toll revenue may be generated.
This surplus may be used to enhance transit or carpooling alternatives,
further increasing freeway *person* throughput and reducing vehicular
demand and congestion.

To ensure apples-to-apples comparisons of all pricing concepts, all
alternatives considered in this study involve expansion of the freeway
to 10 lanes. A No Build alternative (8 lanes) and a conventional Build
alternative involving expansion to 10 free lanes (Alternative 1) are
also considered for comparison. The ET alternatives (Alternatives 2 and
3) and HOT alternatives (Alternatives 4 and 5) reserve four of the 10
lanes (i.e., two in each direction) for use as priced lanes. Alternative
6 is a new concept called "Fast and Intertwined Regular" highways or
FAIR highways. The FAIR concept involves pricing *all* freeway lanes
while providing free HOV service, low-income motorist discounts, and
low-fare/ high quality transit service with convenient park-and-ride
access. The ET and HOT concepts are each analyzed in combination with
two alternative transit policy packages, as follows:

-   "*Low transit" policy package* (Alternatives 2 and 4): This policy
    would allow toll-free use of priced lanes by transit vehicles, but
    not provide funding for new express service or BRT service.

-   *"High transit" policy package* (Alternatives 3 and 5): This policy
    would allow toll-free use of priced lanes by transit vehicles;
    provide funding for additional express bus or new BRT service
    sufficient to meet transit demand during peak periods at normal
    fares; and provide new park-and-ride facilities at freeway access
    points in the residential areas of suburbs to further encourage
    transit use.

# 

# 3.0 ANALYSIS PROCEDURES

All models have limitations and their results always contain
uncertainties, no matter how sophisticated they may be. This is
particularly true with regard to modeling of pricing policies. Pricing
policies require extremely complicated modeling procedures. For accurate
representation of travel behavior, they must use *distributions* of the
value of travel time, rather than *average* values, as most four-step
travel demand models do, even those that are highly advanced
([3]{.underline}). The state of the practice with regard to modeling of
pricing policies is in its infant stages. US DOT has only recently begun
efforts to advance the state of the practice and state of the art. These
efforts are not expected to bear fruit for several years. In the
meantime, analysts seeking to evaluate pricing policies may consider
using quick-response "sketch planning" tools such as SMITE-ML
([4]{.underline}) or SPRUCE ([5]{.underline}). Such models are generally
transparent. Analysts can quickly understand how they work and the key
parameters that cause them to produce the results that they do.

An enhanced version of the SMITE-ML model was used for this study. Since
the model was designed for analysis of Managed Lane concepts,
modifications had to be made to the model in order to provide capability
to analyze the conventional Build concept with *no* priced lanes
(Alternative 1) and the FAIR highways concept that involved pricing
*all* lanes (Alternative 6). The enhanced model produces estimates of:

-   *Travel demand impacts* (i.e., changes in modal shares for
    commuters, peak period and daily traffic on highway facilities in
    the travel corridor, HOV and toll-paying vehicle volumes, etc.);

-   *Mobility impacts and toll revenues* (i.e., changes in travel
    delays, vehicle and person throughput, user costs for tolls, annual
    toll revenues, etc.);

-   *Environmental costs* from vehicle operation, including the social
    costs or benefits of any changes in vehicular travel; and

-   *Performance measures*, including measures of financial feasibility
    (e.g., excess of costs above revenues), economic efficiency (e.g.,
    net present value) and cost-effectiveness (e.g., cost per hour of
    delay reduced, transit costs per new transit trip, highway costs per
    new person trip accommodated, etc.).

The enhanced SMITE-ML model used in this analysis may be downloaded from
*http://knowledge.fhwa.dot.gov/* (Click on "Highway Community Exchange"
on the right; then click on "Value Pricing" from the list at the bottom;
then click on "Works in Progress"; then click on SMITE-ML 2.0)

SMITE-ML model inputs for the base case No Build alternative for the
prototypical corridor were based on outputs from a four-step travel
model run for the year 2020 using a model maintained by the Metropolitan
Planning Organization (MPO) for the metro area. For the SMITE-ML model
runs, the 20-mile corridor was divided into three segments based on
differences in traffic volumes from one segment to the next.

### 4.0 travel impacts

SMITE-ML uses a "pivot point" mode choice model ([6]{.underline}) to
estimate impacts of alternatives on peak period mode shares, pivoting
off of estimated No Build mode share estimates. For each alternative,
appropriate inputs were provided, as shown for one segment of the
corridor in Table 1, to reflect differences in in-vehicle travel times,
out-of-vehicle travel times and out-of-pocket costs for each mode
relative to the No Build base case. For pricing alternatives, the
solo-driver and carpool in-vehicle travel time inputs represent the
combined effect of changes in both travel time and toll costs in terms
of travel time. After completion of the SMITE-ML model runs, travel time
outputs were compared with the travel time inputs to ensure that they
were consistent. If inconsistent, adjustments were made to the inputs,
and the model was run iteratively, until consistency was obtained. Table
2 presents the results for one of the three corridor segments, the
southern segment (also identified as Segment 1).

Due to mode shifts to transit and carpooling, pricing alternatives tend
to reduce vehicle demand relative to the base case No Build and
conventional Build alternatives. However, the reduced vehicular demand
and reduced congestion on regular lanes causes diversions of traffic
*to* the freeway from other routes and destinations, and allows
additional development to occur in the region with consequent new trips
in the corridor, also known as "induced" trips. SMITE-ML estimates the
increase in traffic and new person trips that result from mobility
improvements.

Before estimating induced demand, SMITE-ML estimates traffic diverted
from arterials to the expanded freeway by redistributing traffic such
that relative levels of congestion on the freeway and the arterials stay
the same. This technique is based on techniques used by practitioners in
refining traffic forecasts from four-step models for project development
([7]{.underline}). SMITE-ML then uses travel demand elasticities with
respect to travel time, to estimate new travel that may be induced over
and above traffic that is simply rerouted from other highways. This
includes *new* trips generated or attracted to new development, and
*existing* trips diverted from other destinations. (The mode choice
model estimates *existing* trips that may be diverted to autos from
other modes of travel such as transit.)

SMITE uses speed relationships developed by Margiotta *et al*
([8]{.underline}) to estimate the effects of congestion on speeds. The
Average Daily Traffic-to-Hourly Capacity ratio (ADT/HC) is a key
variable used to predict congestion-related delays, where \"HC\" refers
to two-way hourly capacity. Hourly capacities per lane vary based on
number of concurrent flow lanes. Capacities from the Highway Capacity
Manual ([9]{.underline}) were used to calculate hourly capacities on the
GP and priced sections of the freeway. For priced lanes, it is assumed
that variable pricing will dampen peak vehicle demand to maintain
free-flow speeds in the peak periods. Toll rates would be set
dynamically to keep average demand on the priced lanes at 0.75 times
capacity for two priced lanes per direction, and 0.85 times capacity for
five priced lanes per direction (i.e., for the FAIR highways
alternative) due to the greater freedom to switch lanes with five
concurrent lanes.

An elasticity of demand with respect to travel time of --0.2 was
assumed. To test the sensitivity of analysis results to this elasticity
assumption, the model was run with a low-end estimate (50% lower) of
--0.1 and a high-end estimate (50% higher) of --0.3. These demand
elasticities are relatively lower than commonly found in the literature
([10]{.underline}). They reflect the paucity of vacant land available
for increased development in already developed freeway corridors in
major urban areas, the large proportion of relatively short trips, as
well as the fact that mode choice changes which might contribute to
induced travel are already accounted for using pivot point mode choice
analysis.

Induced demand is estimated for the general-purpose lanes only. By
iteratively estimating induced travel demand on GP lanes and the
resulting travel time "price" change, an equilibrium point is found at
which demand and price are in balance, using a series of equations
([11]{.underline}) approximating the equilibration process. With regard
to priced lanes, the mode choice model already estimates induced carpool
usage, and solo-driver demand in peak hours is assumed to fully utilize
the balance of available capacity up to the service volume thresholds
set to ensure free flow of traffic. Peak period HOV use on the HOT lanes
was estimated assuming that 90% of HOV demand estimated by the mode
choice model would use the lanes. Single-occupant vehicle (SOV) volumes
on HOT lanes were estimated to be equal to the spare vehicle capacity
that would be available on the lanes. The diverted and induced traffic
estimates for the alternatives for the southern corridor segment are
presented in Table 3.

5.0 TOLL REVENUES AND OPERATION COSTS

The average toll rate per mile was estimated based on average time saved
per mile by vehicles in the priced lanes relative to GP lanes. Time
saved is converted into a monetary value, using the "minimum" value of
time of toll-payers. This value is equivalent to the toll that the
"marginal" solo-driving motorist who chooses the priced lanes (and
values his or her time the least among all priced lane users) would be
willing to pay. For example, commuters in the toll lanes in the median
of SR 91 in Orange County, CA value their time at a minimum of \$13 to
\$16 per hour ([12]{.underline}). The analysis assumed a value of \$14
per hour for the two HOT alternatives and \$13 per hour for the two ET
alternatives. Since more toll-paying motorists will use ET lanes than
HOT lanes, the minimum value of time of such motorists will be lower
than that for the HOT alternatives. For the FAIR alternative, all
motorists using the freeway other than HOVs will pay the toll.
Therefore, the minimum value of time of toll-paying motorists was
assumed to be \$3 per hour, i.e., about 50% of the minimum wage rate.

These assumed values are critical in estimating toll revenues for
financial analysis. It is therefore essential that they be verified
through stated preference surveys or other means to ensure greater
accuracy. To test the sensitivity of the model's estimates to these
assumptions, the model was run with low-end estimates (50% lower) of
\$7, \$6.50 and \$1.50 per person hour respectively, and high-end
estimates (50% higher) of \$21, \$19.50 and \$4.50 respectively.

Annual revenues are estimated based on tolls charged on 250 working
weekdays a year, supplemented by week-end and holiday revenues amounting
to an additional 10 percent. For the FAIR alternative, a 10 percent
reduction in revenue was assumed in order to account for low-income
motorist discounts.

The SMITE-ML model estimates costs for toll operations, based on an
electronic toll collection cost of 10 cents per trip and an average
priced trip distance of 5 miles on tolled segments. The model also
estimates new transit subsidies that would be needed to support
additional transit service above the No Build case. BRT subsidies were
estimated at 50 cents per passenger mile, based on nationwide subsidies
of \$23.5 billion supporting 50 billion passenger miles annually
([13]{.underline}). Results from the model showing highway and transit
impacts for the southern corridor segment are presented in Tables 4 and
5.

### 6.0 SOCIETAL COSTS AND BENEFITS 

A major portion of traveler benefits is the reduction in travel time.
The value of travel time savings is estimated for both "previous"
travelers as well as diverted or "induced" travelers. For "induced"
trips, the rule of half is used to estimate consumer surplus. The
conversion of time savings to a monetary value is based on an *average*
value of time of \$9.00 per person hour based on estimates by US DOT
([14]{.underline}). The parameter is critical in estimating traveler
benefits for economic analysis. Sensitivity of model results to this
critical value of time assumption was tested using a low-end estimate
(50% lower) of \$4.50 per person hour and a high-end estimate (50%
higher) of \$13.50 per person hour.

In addition to the value of travel time saved by reduced delays,
motorists save fuel as a result of reduced accelerations and
decelerations. FHWA's Highway Economic Requirements System (HERS) model
([15]{.underline}) estimates fuel consumption in relation to speeds.
Based on the HERS model equations, ECONorthwest ([16]{.underline})
calculated excess fuel consumed per minute of delay. On a facility with
a free-flow speed of 60 mph, excess fuel consumed ranges from 0.037
gallons per minute of delay for a small car to 0.073 gallons per minute
of delay for a sports utility vehicle (SUV). This equates to an added
fuel cost (inclusive of fuel taxes) of about 10 cents per minute of
delay assuming about \$2.00 per gallon at the pump. Since fuel taxes are
a transfer, savings to motorists are losses to government agencies, and
there is no net change in societal benefit from gas tax savings.
Therefore, in computing societal benefits for the alternatives, changes
in fuel taxes are ignored. After subtracting State and Federal fuel
taxes, fuel costs amount to 8 cents per minute of delay, or \$4.80 per
vehicle hour of delay. Assuming average vehicle occupancy of 1.33,
travel time delay costs amount to \$12.00 per vehicle hour (i.e., \$9.00
per person hour X \$1.33). Thus, fuel consumption costs from delay
amount to about 40% of travel time delay costs.

Motorists may have fewer accidents when congestion delay is reduced. For
example, experience with the toll lanes on SR 91 suggests that there has
been a reduction in accidents on the entire facility as a result of
pricing ([12]{.underline}). However, other research suggests that the
likelihood of fatalities increases with higher highway speeds. Due to
lack of definitive data, possible changes in crash costs have been
ignored for this analysis.

Travelers will be subjected to extra delays during project construction.
The model estimates excess delay due to construction activities. It
assumes that delays would increase by 100%, over a period of 250
construction days ([4]{.underline}). The change in external costs
(including air pollution, noise and crashes) due to changes in traffic
relative to the No Build alternative were estimated using an average
cost of 6 cents per vehicle mile. This cost per vehicle mile was
calculated based on the low-range nationwide estimates of these costs,
amounting to \$153.7 billion, and nationwide vehicle miles of travel
amounting to 2.7 trillion in the year 2000 ([17]{.underline}).

The estimated excess travel delay costs during project construction and
changes in external costs relative to the No Build alternative were
combined with estimates of user benefits (i.e., time and fuel savings)
to get net annual benefits. The present value of benefits over a 30-year
period was estimated assuming a 7% discount rate ([18]{.underline}).
Results from the model showing estimates of societal benefits and costs
for the southern segment of the corridor are presented in Tables 6 and
7.

### 7.0 PERFORMANCE AND FINANCIAL IMPLICATIONS

Tables 8 and 9 present key model outputs for the six alternatives. The
Tables summarize all three corridor segments combined. Table 10 presents
the results of the various sensitivity tests for the effects of demand
elasticity and value of time assumptions.

The results shown in Table 8 suggest that FAIR and HOT alternatives that
include BRT may be superior to ET lane alternatives (with or without
BRT) from a *mobility* standpoint. They reduce delay more effectively,
as may be seen by the estimates of the number of person hours of delay
reduced daily (bottom line). Table 9 suggests that encouraging competing
modes such as HOV and transit on priced lanes can negatively impact the
magnitude of toll revenues. There are far fewer toll-paying vehicles if
HOVs are not required to pay a toll. Also, because congestion is reduced
on general-purpose lanes as drivers shift to alternative modes, this
reduces the magnitude of the toll rates that the remaining low-occupancy
vehicle drivers are willing to pay for use of the priced lanes. For the
FAIR alternative, toll rates are lowest due to the much larger "supply"
of priced road space (i.e., five lanes vs. two for the priced
alternatives). Discounts for low-income motorists require a further
adjustment of toll revenue estimates. However, three more lanes are
tolled, and congestion is relatively higher on alternative free routes
(i.e., the arterials) increasing willingness to pay. Consequently
revenues still exceed those for ET and HOT alternatives.

Highway cost estimates shown in Table 9 are based on FHWA construction
cost data ([15]{.underline}) and data from planning studies and actual
costs from projects implemented under FHWA's Value Pricing Pilot
Program. The following cost parameters were derived:

-   \$10 million per lane mile for added lanes

-   \$2 million per mile of lane separation with priced lanes, including
    extra pavement width

-   Interchange modification costs at an average of \$20 million per
    freeway mile

-   Direct connector ramp costs at \$10 million per freeway mile,
    assuming ramps are needed every two or three miles, for priced lane
    alternatives only

-   Toll collection equipment costs (including vehicle transponder
    costs) averaging \$1 million per mile for ET and HOT alternatives,
    and \$2 million per mile for the FAIR alternative

-   Freeway added maintenance costs of \$50,000 per added lane mile per
    year.

-   HOV enforcement costs of \$100,000 per mile per year for HOT and
    FAIR alternatives.

Note that annual toll collection operation costs are calculated based on
number of tolled trips, as discussed in Section 5. Interestingly, the
added HOV enforcement costs for HOT lanes (i.e., \$2 million per year
for 20 miles) are comparable to the additional annual toll collection
costs for ET lanes of about \$1.6 million due to more toll-paying
vehicles on ET lanes. The results in Table 9 suggest that all pricing
alternatives are more financially feasible than the conventional Build
alternative, due to the additional revenues generated from tolls. ET and
FAIR alternatives are superior to HOT alternatives from the standpoint
of *financial feasibility*. An ET or HOT alternative that is combined
with BRT has the ability to support higher levels of mobility and larger
numbers of person trips, thus generating greater *economic* benefits.
However, the "downside" is that priced lanes with BRT are less
financially feasible because of the high costs for new transit service.
Also, when trips are shifted to transit higher levels of mobility exist
in the "free" lanes, reducing the price that motorists are willing to
pay for premium service and therefore toll revenue.

The section on "performance measures" in Table 9 organizes the key
benefit-cost information relevant to the investment and policy
decisions. It shows estimates of the present value of a stream of
aggregate social benefits and a stream of public infrastructure and
operation costs (for both highways and transit) for a 30-year period.
The present value of public costs is subtracted from the present value
of benefits to get net present value (NPV).

All alternatives demonstrate significant positive NPVs, even under
extreme assumptions of elasticity and value of time, as shown in Table
10. While the ET alternative without BRT generates significant positive
NPVs under all assumptions, these values are generally somewhat lower
than the comparable HOT alternative with the same transit policy
package, even when assumed values of time are extremely low. When BRT is
added to the ET and HOT alternatives, their NPVs increase relative to
the same alternatives without BRT. The FAIR alternative generates the
highest NPV. For decision-making, these benefit-cost analysis results
must, of course, be augmented with consideration of other factors, like
public concerns and the equitable distribution of benefits.

Table 9 also presents effectiveness and cost-effectiveness with regard
to congestion mitigation. The HOT alternatives are more effective than
ET alternatives with a comparable transit policy with regard congestion
mitigation (see person hours of delay reduced). Despite the higher
annual costs for HOV enforcement, HOT cost-effectiveness (i.e., costs
per hour of delay reduced) is also higher when alternatives with similar
transit policies are compared. The last measure of effectiveness, "new
person trips accommodated" attempts to measure the effectiveness of the
alternatives with regard to generating new development. Those
alternatives that allow more person trips to be served (e.g., the
conventional Build alternative) fare better according to this measure.
This suggests that road pricing may be beneficial to commuters and other
travelers, but may adversely affect development interests.

The sensitivity analysis results (Table 10) suggest that extreme demand
elasticity assumptions can cause as much as a 100 percent difference in
the number of induced highway trips. However, the effects of these
differences on the economic efficiency indicator (i.e., NPV) are small
for the pricing alternatives, although they are significant for the
conventional Build alternative. With fewer induced trips (i.e., lower
demand elasticity), higher NPV is attained, due to reduced congestion.
Higher congestion levels on GP lanes caused by more induced trips also
result in higher toll rates on priced lanes, and therefore additional
toll revenue, with about a 5 to 10 percent difference in revenue for a
100 percent difference in the number of induced highway trips.

Value of time assumptions can have significant effects on both toll
revenue estimates as well as NPV estimates. Because time savings are
such a large part of economic benefits (about 70 percent), there are
very large variations in resulting NPV estimates. There is a one-to-one
relationship between *toll-paying* motorists' minimum value of time and
toll revenues, with a 50 percent difference in assumed value producing a
50 percent difference in toll revenue.

The analysis suggests that FAIR highways may be the best choice from the
point of view of congestion mitigation, economic efficiency, and
financial feasibility. However, since public acceptance will be a major
hurdle, the second best choices, from the point of view of congestion
mitigation and economic efficiency, are HOT lanes with BRT. If HOV
enforcement is an issue, ET lanes with BRT may be the next best choice.
If public tax support cannot be obtained for new BRT service and revenue
uncertainty is an issue, ET lanes without BRT would be the next best
choice. These conclusions must, of course, be augmented with
consideration of factors in the decision-making process, such as other
local community objectives, public concerns and the equitable
distribution of benefits.

### 8.0 CONCLUSIONS 

The analysis has demonstrated that, in a typical case, a HOT alternative
may mitigate congestion more cost-effectively than an ET alternative.
Combining BRT with ET may make this alternative much more effective, and
may make it more effective than a HOT alternative with no BRT. BRT
increases benefits and net present value of both ET and HOT
alternatives, but reduces financial feasibility due to the need for
public tax support for transit. The ET alternatives tend to be more
financially feasible than HOT alternatives primarily due to the
additional revenues generated from tolls since HOVs are not exempt. The
conclusions appear to hold up under extreme assumptions with regard to
demand elasticity and value of time. However, travel demand
characteristics vary significantly from one large metro to another, and
from one travel corridor to another. Therefore, it is necessary to
re-run the SMITE-ML model with data from a specific corridor before
definitive conclusions can be drawn about the impacts of pricing
solutions in a specific corridor.

Results from the sensitivity analysis suggest that demand elasticity
assumptions do not have a major effect on the magnitude of economic
benefits for pricing alternatives, although effects on toll revenue may
be significant due to higher toll rates resulting from the congestion
effects of induced traffic on toll-free lanes. Value of time assumptions
do have significant impacts on estimates of both economic benefits and
toll revenues. For toll revenue estimates, there is a one-to-one
correspondence, suggesting that, to be credible, any financial analysis
will need to pay close attention to obtaining precise estimates of this
parameter.

### DISCLAIMER: The views expressed are those of the author and not necessarily those of the U.S. DOT or the FHWA. 

### REFERENCES

1.  Chen, Chao and Varaiya, Pravin. The Freeway-Congestion Paradox.
    *Access*. Number 20, Spring 2002.

2.  US DOT. *Report to Congress on the Value Pricing Pilot Program*.
    Draft. June 2004.

3.  US DOT. *Participant Notebook for NHI Course No. 15260, Advanced
    Travel Demand Forecasting Course.* Publication No. FHWA-HI-99-003.
    Washington, DC, December 1999.

4.  DeCorla-Souza, Patrick. Evaluation of Toll Options with
    Quick-Response Analysis Tools. *Transportation Research Record
    1839.* Paper No.03-2946. Transportation Research Board. 2003

5.  DeCorla-Souza, Patrick. An Evaluation of "High Occupancy Toll" and
    "Fast and Intertwined Regular" Networks. Paper No.04-4000. Presented
    at the Annual Meeting of the TRB in January 2004.

6.  Sierra Research, Inc. and J. Richard Kuzmyak. *COMMUTER Model User
    Manual for Analysis of Voluntary Mobile Source Emission Reduction
    and Commuter Choice Incentive Programs*. U.S. EPA. September 1999.

7.  Pedersen N. J. and D. R. Samdahl. *Highway Traffic Data for
    Urbanized Area Project Planning and Design*. NCHRP Report No. 255.
    TRB. 1982.

8.  Margiotta, Richard et al. Improved Speed Estimation Procedures for
    Use in STEAM and in Air Quality Planning, *Economic Implications of
    Transportation Investments and Land Development Patterns .*
    Metropolitan Planning Technical Report No. 11. FHWA. June 1998.

9.  Transportation Research Board. *Highway Capacity Manual 2000.* 2000.

10. Cohen, Harry S. Appendix B of *Expanding Metropolitan Highways:
    Implications for Air Quality and Energy Use*. TRB Committee for
    Study of Impacts of Highway Capacity Improvements on Air Quality and
    Energy Consumption. TRB Special Report 245. 1995.

11. DeCorla-Souza, Patrick and Harry Cohen. Estimating Induced Travel
    for Evaluation of Metropolitan Highway Expansion. *Transportation.*
    Kluwer Academic Publishers. Volume 26, No.3. August 1999.

12. Sullivan, Edward. *Continuation Study to Evaluate the Impacts of the
    SR 91 Value-Priced Express Lanes.* Final Report. State of California
    Department of Transportation. December 2000.

13. Taylor, Jerry and Peter VanDoren. Pricing the Fast Lane. *Washington
    Post,* July 12, 2002, page A21.

14. US DOT. *Memorandum on Departmental Guidance for Valuation of Travel
    Time in Economic Analysis.* Washington, DC. April 9, 1997.

15. FHWA. *Highway Economic Requirements System*. Volume IV: Technical
    Report. Publication No. DOT-VNTSC-FHWA-99-6. December 2000.

16. ECONorthwest. *User Benefits Analysis for Highways.* NCHRP Project
    02-23. AASHTO. Washington, DC. 2003.

17. FHWA. *Addendum to the 1997 Federal Highway Cost Allocation Study*.
    FHWA, May 2000. FHWA-PL-00-021.

18. OMB. *Benefit-Cost Analysis of Federal Programs: Guidelines and
    Discounts.* Circular A-94 revised. Federal Register, November
    10, 1992. Washington, DC.

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