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Case Study: Portland, Oregon


Portland, Oregon Trucks in Congested Traffic

This case study illustrates how regional benefits to freight as well as passenger movement can be estimated. Readily available models are used to assess a range of user, economic, and environmental benefits associated with transportation improvements. The methodology benefits from a rich database on freight movements within the metropolitan region.

Interstate 5 (I-5) is a key north-south route for both freight and passenger movement through the Portland, Oregon - Vancouver, Washington metropolitan region. The freeway, which runs from Canada to Mexico, is an important route for long-distance goods movement. With its connections to local industrial centers and intermodal terminals, the freeway is also crucial to the economy of the Portland-Vancouver region.

Given the high levels of congestion on I-5 and the importance of freight movements in this corridor, the Washington and Oregon Departments of Transportation initiated a study of improvements to facilitate freight movement. The study investigated a number of strategies in the I-5 corridor, including:

  • Fixing hot spots (bottlenecks);
  • Improving the Columbia River crossing;
  • Adding more general-purpose freeway capacity;
  • Adding freight-only freeway capacity; and
  • Adding more capacity on key freight arterials.

To compare the strategies, user and economic benefits were measured using a combination of a travel model post-processor and an economic simulation model. First, the region's travel demand model was applied in conjunction with FHWA's Surface Transportation Efficiency Analysis Model (STEAM) to compute systemwide user benefits including travel time savings, vehicle operating costs, and accident costs. Benefits were calculated for both freight and passenger traffic. The overall economic benefits to the region were then estimated using the REMI model developed by Regional Economic Models, Inc. The output of the REMI model was used to identify overall impacts on employment, output, and personal income in the Portland region.


Regional Setting

The Portland, Oregon - Vancouver, Washington metropolitan region has enjoyed a strong and growing economy over the past decade. Growth in the manufacturing sector, especially high-technology manufacturing, has dramatically shifted the regional economy from one primarily dependent on the natural resources sector to one that is more diverse and robust. Employment has grown consistently over the past eight years at an average rate of 3.3 percent per year. Metropolitan population has also increased proportionately and is currently 1.8 million.

Trade comprises a significant share of the regional economy, and much of the region's growth is due to its strategic location along primary traffic corridors (railway, highway, and waterway) and the availability of deep-water ports. The Portland/Vancouver metropolitan area today plays a leading role among regional distribution and transshipment centers for international commerce. Portland's ratio of wholesale to retail sales is two and one-half times that of the nation as a whole, and the region ranks 13th among U.S. cities based on the value of exports (Parsons Brinckerhoff, 2000). While these facts illustrate the importance of freight traffic to the region, the recent shift towards high-technology goods - which are valuable, light, and time-sensitive - has dramatically increased the importance of air freight and just-in-time delivery. As a result, the effect of traffic congestion on goods movement is of growing concern.

Container Yard

The I-5 Corridor

I-5, the only continuous highway between Mexico and Canada on the West Coast, directly serves regional and state economies in Washington, Oregon, and California. Within the Portland/Vancouver metropolitan area, I-5 is the north-south backbone of regional trade, intersecting with two east-west transcontinental railroads, deep-water shipping and upriver barging, and providing primary access to the region's two ports and regional warehousing and distribution facilities. Figure 1 shows the I-5 study corridor and major transportation facilities.

Figure 1. Portland I-5 Study Corridor

Fig. 1 Portland I-5 Study Corridor thumbnail

Domestically trucks carry 75 percent of the goods shipped to or from other states, and north and south truck movements in and out of the Portland/Vancouver region account for the majority of annual truck freight volumes (Parsons Brinckerhoff, 2000). Yet the ability of I-5 to provide freight mobility within and beyond the region is increasingly threatened by traffic congestion. The Texas Transportation Institute (TTI) currently ranks the Portland/Vancouver metropolitan areas as the 12th most congested in the nation, with I-5 being one of the most congested facilities in the region. In addition, congestion is projected to worsen substantially with rapid population growth and increases in vehicle-miles of travel (VMT) per capita. For example, congestion at the I-5 Columbia River bridge is expected to create six- to seven-mile peak direction queues during the morning and afternoon peak periods in 2020, if no improvements are made.

Study Background

The I-5 corridor freight study was jointly funded by the Oregon and Washington State Departments of Transportation, with additional participation by the Port of Portland, Port of Vancouver, and the Portland and Vancouver MPOs. The study was conducted by Parsons Brinckerhoff and Cambridge Systematics, Inc. It was intended in part to determine eligibility for federal funding from the FHWA Borders and Corridors program in the Transportation Efficiency Act for the 21st Century (TEA-21).

Phase 1 of the study, described here, examines how increasing congestion in the I-5 corridor may affect freight movement, business productivity, and the health of the region's economy. Phase 2, to be completed, will expand the scope of the analysis to include other benefits and costs relevant to the proposed projects. These will include, for example, potential land use responses to growing congestion and to proposed transportation improvements.

Benefit-cost analysis was selected as the primary evaluation measure for the proposed I-5 corridor improvements. FHWA requests a benefit-cost analysis for any application for TEA-21 funding for borders and corridors projects and recommends benefit-cost measures and the specific values of critical parameters (e.g., value of travel time or cost per accident). Project sponsors also felt that the complexity and significance of evaluating multi-billion dollar improvements to the I-5 corridor required the systematic enumeration of benefits and costs.


Overall Approach

The procedure employed in this study involves four basic steps: 1) determine the travel impacts of each alternative investment program, using Portland Metro's regional travel demand model; 2) estimate the direct user benefits for each program using STEAM; 3) project the economic benefits that flow from the direct user benefits using the REMI model; and 4) calculate the benefit cost ratio for each alternative. This procedure is illustrated in Figure 2.

Figure 2. Analysis Procedure

Fig. 2 Analysis Procedure

Only the user benefits concerned with freight movement and other business travel were considered to have impacts on the regional economy. These benefits include time, vehicle operating, and accident cost savings for truck traffic and for "on-the-clock" business travel. User benefits to highway automobile passenger travelers were also reported and were included in the benefit-cost analysis but not in the economic impact analysis.

The following additional impacts were not estimated, either because they were assumed to be small or were not viewed as relevant to the study. However, they could be measured with little additional effort:

  • Reductions in emissions and energy use, as well as monetary valuation of these reductions (STEAM calculates these impacts);
  • Project construction expenditures (these were ignored because their impact is short-term rather than permanent); and
  • Impacts on the economy of cost savings to passenger travelers. While cost savings for passenger travel may effect the regional economy, the linkage is less direct than cost savings for business travel. Research is underway for National Cooperative Highway Research Program (NCHRP) Project 2-21, Economic Impacts of Congestion, to investigate the impacts of commuter benefits on business cost savings.

Finally, the following effects were not considered because they were difficult to quantify:

  • Effects of the transportation improvement on attraction of new industries and tourists (according to local sources, these effects are expected to be small).
  • Salvage values of the facilities constructed. A salvage (or residual) value is often calculated in benefit-cost analysis in order to compare with different lifetimes. Calculation of salvage values would have been complex because of the many different types of investments included in the I-5 analysis, and also would rely on uncertain assumptions about project lifespans.
  • Land use impacts (these will be addressed in a future phase of the project).
  • Transit benefits and costs. Some of the options included transit and TDM improvements. The magnitude of transit-related benefits was not estimated, except to the extent to which transit improvements reduced highway traffic volumes and the level of congestion.
  • Congestion caused by accidents. Recent evidence suggests that non-recurring delay resulting from incidents is valued more highly than predictable delay (Small, Noland, Chu, and Lewis, 1999). Truck incidents may also have significantly larger time delay impacts than passenger vehicles. Good analytical procedures and data to measure these impacts, however, do not currently exist for the Portland region.
  • Other truck-related congestion and congestion at interchanges. Traffic delays from truck-related congestion were estimated conservatively using generic "passenger car equivalent" values. Regional travel demand models, such as the Portland Metro model used as the basis for this study, are not sufficient to estimate localized changes in delays from traffic diversions and interchange improvements.

Travel Impacts

Portland Travel Demand Model

Portland Metro's regional travel demand model is among the most advanced trip-based travel models in the U.S. It includes features such as household characteristics modeling; auto ownership modeling; market segmentation of households for trip generation, distribution and mode choice; time-of-day modeling; and feedback from congested traffic assignment to trip distribution and mode choice.. Three peak time periods are used: 7:00 to 9:00 a.m., 2:00 to 3:00 p.m., and 4:00 to 6:00 p.m. The model is run using EMME/2 software. Another noteworthy feature of the model, directly relevant to this analysis, is the inclusion of a relatively sophisticated truck model.

Metro recently undertook a major commodity flow survey (Portland Metro, 1997) to serve as a basis for the truck model. The commodity flow survey utilized public and private data sources on freight flows, in conjunction with external classification counts, to develop tables of movements by mode, commodity type, and direction of flow. Flows were tracked for 16 commodity groups. Commodity-flow ends were distributed to traffic analysis zones (TAZ) based on employment by industry in combination with specific information on flows through ports and airports. Commodity flows were then converted into truck movements through a series of processing steps, and truck volumes were converted into passenger-car equivalents. (Information on the commodities associated with truck movements is retained through this process.) Classification count data were used to split 24-hour demand into the peak periods required in the Metro model. For additional model documentation, see Cambridge Systematics (1998).

To develop forecast year (2020) in addition to base year commodity flows, regional economic forecasts were combined with judgments on shipping trends.

Application of Model

The Metro travel demand model was run for a base case and for each of the alternatives defined by the project team to provide forecasts for the year 2020. The model area was a six-county area covering Portland and surrounding areas in northwest Oregon and southwest Washington. For each alternative, Metro prepared peak passenger-car equivalent trip tables and ran three peak assignments of this table to the regional highway network.

The EMME/2 modeling software permitted Metro to segment the output trip tables into a maximum of 12 categories. The 16 commodity groups available in the Metro model were aggregated into eight categories of commodities moved by heavy truck. With the remaining four categories available, two categories of medium truck and two categories of auto, SOV and HOV, were specified.

Simplified Approach

Most metropolitan areas will have considerably less detailed data on freight movements and will not have a model structure that allows tracking of freight by commodity class. Even without commodity or truck flow data, it is still possible to estimate user and economic benefits to freight traffic, although additional assumptions and approximations are required. Two possible situations include:

Sources of Commodity Flow Data

The Commodity Flow Survey (CFS), conducted by the Bureau of Transportation Statistics (BTS) and the Bureau of the Census, reports freight tonnage by commodity group between 89 National Transportation Analysis Regions. The CFS data are available free of charge from the Bureau of Transportation Statistics or the Census Bureau.

More detailed commodity flow data can be purchased from Reebie's TRANSEARCH database. This database contains commodity flow data between counties (and in some cases, zip codes), and is based on a more extensive sample and additional information sources compared to the CFS.

  1. An MPO has developed a truck model that produces zone-to-zone truck flows, but does not have data on flows by commodity type. In this case, user benefits to truck traffic can still be estimated in the aggregate using STEAM. To develop inputs of user benefits by commodity type to REMI, commodity flow data are analyzed to identify the mix of commodities by tonnage for the region. Then, data from the Census Bureau's Vehicle Inventory and Use Survey (VIUS; formerly the Truck Inventory and Use Survey, or TIUS) are used to identify average freight volumes (in tonnage) per truck. These two sources are combined to estimate the percentage of truck movements by commodity type, and user benefits from STEAM are then allocated proportionally. This approach assumes that the average benefit per truck is the same across all commodity groups. This would not be the case if different commodity groups follow different travel routes.
  2. An MPO has not developed a truck model. In this case, it is not possible to estimate freight user benefits based on network flows with STEAM. Truck benefits would need to be estimated using a project-specific analysis. If truck travel time benefits can be estimated, a sketch-level methodology can then be used to translate these benefits into REMI inputs for the economic analysis. The Freight Transportation Investment Model (FTIM) provides an example of such an approach. FTIM was developed for Columbus, Ohio but could be applied to any metropolitan area.

User Benefits

The STEAM Model

The Surface Transportation Efficiency Analysis Model (STEAM) was developed by FHWA in 1997. Full documentation of the model can be obtained from the FHWA's STEAM web site. The primary objective of STEAM is to provide a framework for estimating the network-wide impacts of multimodal transportation alternatives. STEAM accepts inputs from four-step travel demand models, including trip tables, network and centroid files, and time and cost change files. STEAM then computes the following measures of effectiveness:

  • Benefits and costs to transportation users;
  • Annualized cost to public agencies;
  • Change in criteria pollutant emissions;
  • Change in energy use;
  • Change in noise and other external costs;
  • Change in fatal, injury, and property damage only accidents;
  • Revenue transfers due to toll or fare changes; and
  • Monetary value of user benefits, costs, emissions, noise, and accidents.

STEAM operates in a Windows environment. As shown in Figure 3, STEAM contains four modules:

  1. A User Interface Module, to specify parameters and file names, conduct runs, etc.
  2. A Highway Network Analysis Module, which reads a file containing vehicular traffic volumes, highway segment lengths, highway capacities, and other link data and produces zone-to-zone travel times and distances based on minimum time paths through the network.
  3. A Trip Table Analysis Module, which produces estimates of user benefits based on a comparison of Base Case and Improvement Case conditions. It also produces estimates of emissions, noise costs, accident costs, energy consumption, and other external costs associated with highway use.
  4. An Evaluation Summary Module, which calculates net annual worth and a benefit-cost ratio for the improvement under consideration. It also provides summary information on individual benefit and cost items.

Figure 3. Overview of STEAM

Fig. 3 Overview of STEAM

A noteworthy feature of STEAM is that it post-processes traffic assignment outputs from conventional four-step planning models. This provides more accurate highway travel speeds, especially under congested conditions, compared to many four-step models. The speed models in STEAM are calibrated separately for freeways and signalized arterials, under both peak and off-peak conditions, based on hour-by-hour simulations of traffic volumes and queuing for facilities with different levels of congestion. The speed models account for:

  • Delays due to incidents, using data on the frequency, severity, and duration of incidents;

  • Peak spreading that occurs when facilities become more congested;

  • Day-to-day variations in traffic; and

  • Decreases in highway capacity observed after demand volumes exceed capacity.

As a result, speeds and related values, such as vehicle-hours of travel, are likely to differ compared to those estimated using the regional travel demand model. In cases in which local agencies prefer to use their own estimated speeds, STEAM can still be used to calculate user benefits and other performance indicators.

STEAM includes other useful features to help develop more accurate estimates of user benefits. For example:

  • The model allows consideration of induced demand. This is done using a default or user-specified elasticity of travel with respect to travel time. Benefits to new users as well as to existing users are estimated on each link in the network using the concept of consumer surplus (see the STEAM documentation for details). The consumer surplus concept is also used to estimate changes in benefits for users who shift routes, modes, or origins/destinations.
  • The model can perform risk analysis to clearly describe the level of uncertainty in the results of the analysis. STEAM accomplishes this by allowing ranges (probability distributions) to be attached to the forecasts of each input variable. The risk analysis can help assess which input assumptions have significant impacts on the outputs and which do not. Figure 4 shows sample output for a cost-benefit analysis. The cumulative probability chart in Figure 4 indicates that there is a roughly 70 percent probability (1 - 0.3) that the benefit-cost ratio is greater than one, and a roughly 40 percent probability (1 - 0.6) that the benefit-cost ratio is greater than two.

Figure 4. STEAM Risk Analysis Results: Cumulative Benefit-Cost Ratio

Fig. 4 STEAM Risk Analysis Results: Cumulative Benefit-Cost Ratio

Application of STEAM

In the Portland I-5 freight study, STEAM was used to calculate user benefits based on the difference between the base case and each alternative investment strategy. STEAM was run using inputs provided by the Metro travel model and the default STEAM parameters for value of time, fuel consumption rates, accident rates, etc. Metro also provided local data to override these defaults in some cases.

The STEAM results used in the study included monetary equivalents for the change in four user benefit components: travel time, accidents, non-fuel operating costs, and fuel costs. STEAM generated an estimate for each component for each of the three peak periods and each commodity/vehicle type. These were then converted into 24-hour values to estimate overall benefits.

Some of the specific procedures involved in calculating user benefits include:

In-Vehicle Travel Time Savings. The value of time to vehicle occupants was obtained from the U.S. Department of Transportation guidance (U.S. DOT, 1997). In the Portland study, the value of time was expanded to include value per vehicle and value of inventory. The values of travel time used in the Portland study are summarized in Table 1.

Table 1. Value of One Hour of Travel Time (1995 Dollars)
$7.16 $6.41 $6.16      
Value of Inventory1 - - - $0.60 $0.60
Personal Travel
In-Vehicle Value per Person $8.50 - - - -
Avg. Vehicle Occupancy 1.67 - - - -
Avg. Value per Vehicle $10.17 $19.98 $23.66 $25.49 $25.24
Avg. Value per Person2 $8.50 $19.02 $23.66 $22.76 $22.54

To compute the inventory costs for five-axle combination trucks, an hourly discount rate was computed and multiplied by the value of a composite average shipment. The discount rate selected was 9.8 percent, equal to the average prime bank lending rate in 1995 plus one percent. Dividing this rate by the number of hours in a year produces an hourly discount rate is 0.0033 percent. The average payload of a five-axle combination is about 35,000 pounds. In 1993, the average value of commodities shipped by truck was $1.35 (on a ton-mile weighted basis). (Source: U.S. Bureau of the Census, 1992 Census of Transportation, 1993 Commodity Flow Survey, U.S. Government Printing Office, Washington, D.C., 1996. Values from Table 6 data on value, tons and ton-miles by distance shipped.) Inflating to 1995 dollars using the GDP deflator and multiplying by the average payload produces an average payload value of roughly $50,000. The resulting time value of the average payload is approximately $0.60 per hour (ignoring any costs for spoilage and depreciation over time). Payload for four-axle combination trucks is lower than for five-axle combination trucks, but the value of the cargo probably is higher. Consequently, the value per shipment was assumed to be the same for both types of trucks.

To compute average value per person, the sum of value per vehicle and value of inventory is divided by the average vehicle occupancy and added to the in-vehicle value per person.

Source: Cambridge Systematics, Inc., U.S. Department of Transportation, and Highway Economic Requirements System (HERS).

STEAM calculates the change in vehicle travel time by running trips from Metro's trip tables through the EMME/2 networks, comparing the base network results to those of each alternative network. Total travel time is based on the speed and distance traveled by each trip through the EMME/2 network, summed for all trips. Congested speeds and link distances come directly from EMME/2, and STEAM determines the minimum time path.

An important assumption built into the Metro projections of on-the-clock travel, which in this study consisted of only heavy and medium truck trips, is the absence of additional truck trips caused by induced travel. Unlike commute or other trip purposes, Metro assumes that businesses produce the amount of on-the-clock trips necessary to operate efficiently and do not consider the amount of congestion, delay, accidents or other per vehicle-mile costs as a constraint to their trip-making.

Vehicle Operating Costs. Vehicle operating costs in STEAM are a combination of two components: fuel costs and non-fuel costs. Fuel costs depend on both speed and VMT. STEAM uses a series of fuel consumption rates at different speeds in addition to average fuel cost as key inputs to this calculation. For each trip, STEAM sums the cost of fuel used on each and every link of the trip, based on the distance of each link and the congested speed on that link. Non-fuel costs are VMT-dependent costs associated with operating a vehicle. These account for oil consumption and maintenance costs. STEAM simply multiplies a cost factor by the VMT of each trip, summing all trips for total non-fuel costs.

Accident Costs. STEAM determines accident costs based on VMT and the facility-based accident rate. For each trip, the product of the length, accident rate, and accident cost on each link is added up for all links on a trip and for all trips. Costs per accident are provided for fatal, injury, and property damage only accidents.

  Auto 6-Tire Truck 3-4 Axle Truck 4-Axle Comb. 5-Axle Comb.
Business Travel
In-Vehicle Value per Person N/A $16.50 $16.50 $16.50 $16.50
Avg. Vehicle Occupancy N/A 1.05 1.0 1.12 1.12
Value per Vehicle N/A $2.65      

Economic Impacts

The REMI Model

The REMI modeling system, developed by Regional Economic Models, Inc., is an economic simulation and forecasting system designed for project and policy impact analysis within the U.S. The model is custom calibrated for regions consisting of one or more counties. The model predicts the impact of a proposed project on employment and business output for each of 53 industry categories and 94 detailed occupational categories. The model also predicts other variables such as changes in personal income, population, business competitiveness, wage rates, and value added at a similar detailed level. The model is dynamic, meaning that changes to the economy and adjustments to these changes are predicted on a year-to-year basis.

REMI was used in this study to translate transportation user benefits accruing to businesses within the region (freight and on-the-clock travel) into economic benefits for the region as a whole. The procedure for converting user benefits from STEAM into the appropriate REMI inputs is described below.

In addition to considering user benefits, it is also possible to use REMI to measure the impacts of expenditures and funding sources for construction and operation of transportation facilities. (In the I-5 study, construction impacts were viewed as a short-term impact and were therefore not measured in computing overall regional benefits.) Construction expenditures could be entered over the appropriate period of project construction. This is easy to do, since REMI contains "policy variables" that map overall dollar amounts for factors such as highway construction into increases in sales in the appropriate industries.

The flip side of the expenditure analysis is that any local (within-region) sources of funding for the project should be entered into REMI as well. The mechanism for entering local costs depends on the assumed source of funding for the project. A sales tax increase, for example, could be entered as a reduction in consumer spending. Utilization of general government funds could be entered as a reduction in general government expenditures.

Preparing REMI Inputs

In order to model the impacts of the project alternatives on the regional economy, user benefits from STEAM must be converted into appropriate values to be input into the REMI model. The general approach to this process is shown in Figure 5 and described below.

Figure 5. Analysis Procedure

Fig 5 Analysis Procedure

  1. Determine Local User Benefits. The direct economic benefits of each alternative are the share of the user benefits that increase the flow of money due to reduced costs (or increased sales) for businesses. For the most part, this would represent benefits accruing to trucks operated either by for-hire motor carriers or as part of private fleets. The direct user benefits for commuters (i.e., SOV and HOV home-based work trips) are not included in the estimation of economic benefits in this study.

    In this analysis, only economic benefits to the six-county Portland region are measured. In order to calculate the regional extent of economic gain, the proportion of user benefits that will be realized as monetary gains by regional businesses must be determined. The approach to separating these regional benefits from the total trucking benefits is as follows:
    1. Exclude all through (external to external) trips, based on the truck trip tables provided by Metro.
    2. Exclude a portion of the internal-to-external and external-to-internal truck trips, recognizing that some of these benefits will be gained by businesses based in other regions. The factor used to scale these benefits was arrived at by determining the percentage of trips to and from external zones in the model.
    3. Include all internal-to-internal truck trips.
  2. Map Commodity Groups into Industry Groups. The truck-related user benefits, which were defined by the 10 commodity groups produced by Metro (eight heavy truck and two medium truck), were then mapped into the 53 industries defined in the REMI model. This was done in three steps:
    1. The benefits for medium trucks (non-freight) were allocated among service and trade industries as a function of the following:
      1. Real output per industry, which is derived from the REMI control forecast;
      2. Percent of business activity by industry spent on vehicle-related costs, which are defined as expenses for the purchase, maintenance, and fuel of company-owned vehicles (from the BEA's input-output technological matrix) and labor costs for company-employed drivers and mechanics (from the Census' industry-occupation matrix); and
      3. Percent of total highway travel by the group benefiting from the highway improvement, which is obtained from any available business shipping surveys. The default assumption is to assume that this value does not vary across industries.
    2. The benefits for medium trucks (freight) were allocated among all industries, including for-hire trucking and manufacturing, as a function of the same factors as the non-freight medium trucks.
    3. The benefits for the eight heavy truck commodity groups were allocated in two steps:
      1. The Bureau of Transportation Statistics' Transportation Satellite Accounts (TSA) were used to allocate benefits for each commodity group among for-hire trucking and private fleets.
      2. The benefits experienced among private fleets were allocated from commodity group to industry groups as a function of a) real output by industry in the region; and b) production of each commodity by that industry, as determined by the national input/output technological matrix.
  3. Estimate Intermediate Versus Value-Added Benefits. These benefits were then distributed between intermediate inputs and value-added. Industry output is a combination of intermediate inputs (i.e., purchase of commodities or services) and value-added (labor, taxes, and profits). The benefits were totaled by industry and distributed between intermediate inputs and value added based on the national input/output technological matrix.
  4. Enter Benefits into REMI Model. The benefits related to intermediate inputs were then entered into the REMI model as a reduction in operating costs, while the benefits related to value-added were entered as an increase in total factor productivity.

REMI Outputs

The REMI model was then run for each alternative and the simulation results were compared to the baseline to determine the employment, output, and income changes associated with each alternative. Figure 6 provides sample output produced by the REMI model.

Figure 6. Sample REMI Output

Fig 6 Sample REMI Output

Benefit-Cost Analysis

A benefit-cost ratio for each alternative can be computed by dividing the present (discounted) value of total user benefits obtained from STEAM by the present value of total capital costs. Alternatively, the benefit measure can be taken to be the gain in total personal income, as determined from the REMI model.Total user benefits from STEAM should not be added to total benefits from REMI, since this would double-count some benefits.

Personal income is broader than user benefits in that it includes benefits to non-users of the transportation system. However, it can be a conservative measure of the true income impact, insofar as there is also some net business income (profit) generated, which is not counted in the measure. Some of that profit may be paid out as dividends to local business owners or else reinvested locally in buildings, equipment, or labor - thus further improving the economic base of the region.

Also, the change in personal income does not measure the benefits to traffic that does not have an origin or destination in the region. In addition, in this analysis, only work-travel user benefits were included in the economic model, so the income benefits shown by REMI do not include the full range of user benefits. For a more complete benefit-cost accounting, the user benefits from STEAM not included in the REMI model (i.e., non-work-travel benefits) could be added to the gain in personal income measured by REMI to obtain a measure of total benefits.

The project may result in other types of benefits and costs that were not included in this analysis. Income created by project construction may be considered as a type of benefit; however, it also has an offsetting opportunity cost (i.e., the benefits foregone from spending the money in alternative ways). Externalities and other benefits and costs that are difficult to quantify (i.e., emissions, community impacts, land use shifts) were not considered in this analysis.

Level of Effort

The analysis described here took roughly 12 person-weeks including the STEAM analysis, REMI analysis, and intermediate data conversion procedures. This assumes that the necessary travel demand model output and freight data have been acquired.

For the individual analysis components, STEAM requires roughly two to three person days to analyze an alternative of two networks and eight to 12 trip tables. This estimate includes one day for setting up input files and one day of computer time for doing actual runs. The analysis time would be considerably shorter if the network was not run, but instead only the post-processing of user benefits was performed. Roughly two person-weeks are required to convert outputs from STEAM into inputs for REMI, run REMI, and process the outputs for a set of alternatives. This assumes that some type of model (such as a spreadsheet) is set up to do the required data conversions. REMI itself is quite easy to use. It operates in a Windows environment, and inputs and outputs can be cut and pasted from a spreadsheet application. Run time is minimal.

The STEAM software is available free from FHWA. The cost of the REMI model varies depending upon the rental period and the size of the area being modeled. Contact REMI for quotes on specific areas.


User Benefits

The results in Table 2 show the aggregate direct user benefits in 2020 for each alternative.

An example for one commodity group, wood products, and one alternative, "Hot Spots," illustrates the component parts of the benefits. Truck operators carrying wood products in the Hot Spots alternative experience over 58 percent ($617 thousand) of the total user benefit for all eight categories of heavy truck user benefits; 41 percent of all truck (heavy and medium) benefits; and two percent of total benefits (including HOV and SOV). Of the total annual user benefits of $617 thousand, in-vehicle travel time savings of $505 thousand account for 82 percent.

Overall user benefits to truck traffic in this analysis were on the order of 10 percent of user benefits to automobile traffic. In this corridor, therefore, freight benefits make up a minor but still significant portion of total benefits. The proportion of benefits accruing to freight traffic will vary significantly among corridors or regions, depending upon the amount of truck traffic locally.

Table 2.
Annual Auto & Truck User Benefits 1 for Each Alternative in 2020
(Thousands of 1995 Dollars)
Commodity/Vehicle Category Hot Spots2 CRC3 Freeway Capacity4 Freight Freeway5 Freight Arterial6
H1: Farm products $114 $271 $560 $349 $318
H2: Minerals $28 $61 $118 $85 $112
H3: Stone and waste products $131 $286 $569 $374 $388
H4: Wood products $617 $1,731 $4,150 $2,305 $1,869
H5: Metal products $22 $63 $147 $84 $72
H6: Machinery & elect. equip. $9 $54 $134 $74 $69
H7: Transportation equipment $27 $67 $151 $89 $81
H8: Chemicals and petroleum $102 $267 $603 $365 $372
Medium truck, non-freight $141 $385 $871 $496 $403
Medium truck, freight $308 $620 $1,347 $778 $584
HOV $5,058 $8,085 $14,605 $9,765 $8,679
SOV $23,455 $28,881 $56,534 $48,184 $26,210
Total benefits $30,011 $40,770 $79,790 $62,949 $39,157
Truck subtotal7 $1,498 $3,805 $8,650 $5,000 $4,268
Heavy truck subtotal8 $1,050 $2,799 $6,433 $3,726 $3,281
Auto subtotal (SOV + HOV) $28,513 $36,966 $71,139 $57,949 $34,889
1 Benefits here connote the difference between each alternative and the Base Case (No-Build) Alternative. All alternatives include a set of about 40 planned, but not funded, regional transportation improvements.
2 "Hot Spots" includes capacity expansion at I-5 bottlenecks, an LRT extension, and interchange improvements .
3 Hot Spots + additional Columbia River Crossing (CRC) lanes.
4 Hot Spots + CRC + reversible express lanes on CRC + additional lanes on I-5 + LRT to Vancouver .
5 Hot Spots + CRC + new truck-only ramps.
6 Hot Spots + new freight bridge (port-to-port) .
7 Includes all eight categories of heavy trucks and the two categories of medium trucks.
8 Includes only the eight categories of heavy trucks.

Source: Cambridge Systematics, Inc.

Regional Economic Benefits

Table 3 shows the cumulative economic benefits accruing to the Portland region for each alternative, between 2000 and 2020. These benefits are the sum of the difference in annual benefits between each alternative and the base case for each year, discounted to 1992 dollars.

The economic indicators provide different estimates of the impacts of improved trucking operations on the six-county economy, and each tells a slightly different story. For example, a change in output indicates the amount of additional goods and services produced by businesses located in the six-county area, regardless of whether the business is owned by a Portland-based firm.1 Profits earned on output produced in the six-county area by a firm headquartered in a county outside the area, in another state, or in another country would be exported outside the region. Thus, changes in output overstate the regional economic impact of an alternative. As a more accurate - albeit conservative - estimate of economic impacts, changes in real disposable personal income are used to assess the real benefits retained within the regional economy.

Table 3. Aggregate Economic Benefits1 for Each Alternative from 2000 to 2020

Economic Indicators Hot Spots2 >CRC3 Freeway Capacity4 Freight Freeway5 Freight Arterial6
Employment (total jobs) 500 1,100 2,500 1,500 1,300
Gross Regional Product $1 $29 $66 $39 $34
Real Disposable Personal Income $ $23 $51 $30 $27
Output $20 $52 $117 $67 $61
Exports to U.S. and World $5 $13 $30 $18 $15

1 In Millions of 1992 Dollars, discounted at seven percent.
2 "Hot Spots" includes capacity expansion at I-5 bottlenecks, an LRT extension, and interchange improvements.
3 Hot Spots + additional Columbia River Crossing (CRC) lanes.
4 Hot Spots + CRC + reversible express lanes on CRC + additional lanes on I-5 + LRT to Vancouver.
5 Hot Spots + CRC + new truck-only ramps.
6 Hot Spots + new freight bridge (port-to-port).

Source: Cambridge Systematics, Inc.

Initial cost-benefit estimates showed mixed results in terms of the overall benefits of the various alternatives. Final results from this study were not available at the time of this writing.



This case study demonstrates the use of a new modeling tool, STEAM, to calculate user benefits, as well as an established economic modeling tool, REMI, to translate these benefits into economic impacts. Variations on this modeling approach can be used, depending upon available data and resources. Specifically:

  • STEAM can be used independently of REMI to estimate total user benefits of alternative network improvements and derive a benefit-cost ratio or other measure of net benefit. This approach provides a different benefits accounting system, since benefits to all users (not just those accruing to regional businesses) are included. On the other hand, the indirect and induced economic benefits of the various user benefits cannot be estimated using STEAM alone.
  • The approach of tracking freight user benefits by commodity type provides a more accurate accounting from which to estimate economic impacts. Not all urban areas, however, will have readily available data on traffic patterns by commodity type. If these data cannot be obtained, origin-destination commodity flows can be estimated from available national commodity flow data combined with local traffic and land use data. The new Transportation Satellite Accounts (TSA) produced by the Bureau of Transportation Statistics can assist in determining freight transportation inputs by industry.

Limitations and Development

An acknowledged limitation of this study is that it did not consider reductions in incidents or incident-related delay. While new research is available to assist in valuing unpredicted delay (Small, Noland, Chu, and Lewis 1999), further research and analysis would be required to estimate the incident reduction impacts of the specific freight improvements studied.

The economic benefits in this case were found to be relatively small compared to the direct user benefits. For example, the aggregate increase in personal income over the period of 2000 to 2020 ranged from $9 million to $51 million, compared to annual user benefits of $30 million and $80 million for the same alternatives. Note, however, that user benefits aside from on-the-clock business travel were assumed not to provide any regional economic benefits. Considering commuter time savings as an economic benefit to businesses has been found in other studies using REMI to have significant effects on the overall economic benefits. Ongoing research in this area should help clarify the extent to which benefits to commuter or other personal travel should be considered in estimating regional economic impacts.

While final benefit-cost results were not available at the time of this writing, project sponsors still viewed this analysis as a useful tool as well as one with limitations that must be recognized. Some of the ways in which the benefit-cost analysis proved useful include:

  • Making order-of-magnitude comparisons of benefits and costs;
  • Identifying which strategies are most cost-effective; and
  • Identifying the most important benefit areas (e.g., automobile versus truck travel time savings, accident costs, and economic benefits.)

Portland - Train


Published References

Cambridge Systematics, Inc. (1998). "Collection and Analysis of Commodity Flow Information in the Portland Metropolitan Area: Compendium of Technical Memoranda and Other Key Documents." Prepared for Portland Metro and the Port of Portland with ICF Kaiser Consulting Group and Nelson\Nygaard Consulting Associates.

Parsons Brinckerhoff and Cambridge Systematics, Inc. (2000). "Economic Evaluation of Alternative Scenarios: Final Report." Prepared for Oregon Department of Transportation and Washington State Department of Transportation, February 2000.

Portland Metro (1997). "The Collection and Analysis of Commodity Flow Information for Metro and the Port of Portland."


Organization Person Phone
Cambridge Systematics, Inc. Chris Wornum 510-873-8700
Oregon Department of Transportation Project Manager Dan Laden 503-731-8200
Parsons Brinckerhoff John Boroski 503-417-1363
Portland Metro (Commodity Flow Survey) Jean Alleman 503-797-1768

1 The technical definition is the amount of production in dollars, including all intermediate goods purchased as well as value-added (compensation and profit). Output can also be thought of as sales. Output = self-supply + exports + intra-regional trade + exogenous production.

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