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Engineering Economic Analysis Practices for Highway Investment (2012)

Chapter: Chapter Three - Case Examples

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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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Suggested Citation:"Chapter Three - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2012. Engineering Economic Analysis Practices for Highway Investment. Washington, DC: The National Academies Press. doi: 10.17226/22795.
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32 chapter three Case examples ImpaCt of CrItICal Interstate transportatIon faCIlItIes Introduction The Port Authority of New York and New Jersey (PANYNJ) is a regional public authority established by bi-state charter that operates a number of multimodal transportation facili- ties within its defined Port District. It has responsibility for major interstate transportation facilities, including six highway crossings between New York and New Jersey and transporta- tion stations and centers in both states. It operates three major metropolitan airports and two regional airports, several marine facilities, and transit lines with ferry connections to Manhattan. The PANYNJ also oversees reconstruction of the World Trade Center in Lower Manhattan (“The Port Authority . . .” n.d.; “Overview of Facilities and Services” 2010). Despite the signif- icance of its existing transportation infrastructure and resulting impacts to the movement of people and goods throughout the metropolitan region, PANYNJ before 2000 had not attempted to quantify comprehensively the economic benefits conferred by its transportation infrastructure. This case describes the first step in that quantification: the estimation of the economic ben- efits of PANYNJ’s interstate transportation facilities. Although the Port Authority’s own study considered several categories of infrastructure outlined previously, this case example focuses specifically on the six bridges and tunnels between New York and New Jersey; facilities that can be regarded as critical infra- structure in terms of the impact of highway investment on local and regional economic conditions. The data and methodology used in this effort form part of a proposed regional cost–benefit capability described here. The case is unique given the network- level significance and criticality of the transportation facilities involved. Within the framework of this synthesis, it provides an example of planning information developed at a corridor and network level. The documentary source for this critical facilities case is the economic impact study performed for the Port Authority by a consulting firm (The Economic Impact . . . 2000). Other sources relating to a specific issue regarding the Bayonne Bridge will be presented at that point later in the case example. role of economic analysis in Highway Investment Facilities The Port Authority’s transportation facilities are located in the New York–New Jersey metropolitan region as illustrated in Figure 1. The Port Authority Interstate Transportation Facili- ties (PAITF), which is the focus of this case example, is a sub- set of the facilities in Figure 1 comprising the following: • Highway Bridges and Tunnels – George Washington Bridge, Goethals Bridge, Outer- bridge Crossing, Bayonne Bridge – Lincoln Tunnel, Holland Tunnel. • Interstate Transit Links – Port Authority Trans-Hudson (known as PATH) tran- sit service – Coordination of transit service with ferry services to downtown and midtown Manhattan that are provided by other operators. • Transportation Stations and Centers – Port Authority Bus Terminal – George Washington Bridge Bus Station – Journal Square Transportation Center. Daily use of these facilities is shown in Table 7, which orga- nizes the facilities into four major corridors. This traffic repre- sents the major share of commuter and freight flows between New York and New Jersey. The PAITF are critical links within the highway, transit, and rail networks that serve the New York–New Jersey metropolitan region shown in Figure 1. These networks connect New York City, Long Island, the northern suburbs of New York, other points north, other points east of the Hudson River, the northern suburbs of New Jersey, and other points west of the Hudson River. The Midtown Cor- ridor shows substantial road traffic in the Lincoln Tunnel. This tunnel, which provides an exclusive bus lane, is a major transit corridor into midtown Manhattan. The Port Authority’s report includes a separate estimate of the benefits of this bus traffic. In addition to the PAITF, rail and transit services to midtown are provided by Amtrak, New Jersey Transit, the Metro–North Railroad, the Long Island Rail Road, New York City Transit, and private commuter bus and ferry services. Components of the Analysis Three components of economic benefit were considered in the Port Authority study of the PAITF: 1. Transportation benefits, comprising savings in travel time and VOC resulting from the existence of a PAITF facility.

33 FIGURE 1 Locations of PANYNJ transportation facilities. Source: Port Authority of New York and New Jersey, http://www.panynj.gov/about/facilities-services.html. Corridor/Facility Weekday Use Weekend Use Measure of Use Northern Corridor George Washington Bridge 151,700 149,000 Vehicles Midtown Corridor Lincoln Tunnel 62,200 57,400 Vehicles PATH Service to 33rd Street 41,300 21,600 Passenger trips Midtown Ferry Service 11,500 6,100 Passenger trips Downtown Corridor Holland Tunnel 49,700 49,500 Vehicles PATH to World Trade Center 60,400 13,400 Passenger trips Downtown Ferry Service 12,500 1,500 Passenger trips Southern Corridor Goethals Bridge 36,000 38,000 Vehicles Outerbridge Crossing 40,900 45,900 Vehicles Ba yo nne Bridge 9,700 7,000 Vehicles Source: The Economic Impact… (2000). TABLe 7 DAILY USe OF PAITF, 1999

34 2. Operating and capital impacts, the result of expendi- tures on the Interstate Facilities by the Port Authority, its tenants, and other transportation providers. These expenditures purchase goods and services from regional businesses that support the maintenance, operation, and enhancement of the facilities. The result is not only an improved level of transportation service, but also an improved economic welfare of the region resulting from direct purchases and subsequent indirect purchases owing to PAITF expenditures. 3. Competitive impacts, which result from more efficient access to, and movement within, the region served by PAITF. This benefit reflects the improved economic competitiveness and stimulation of growth owing to services provided by the Interstate Facilities in several categories; for example, commuter trips between New Jersey and New York, tourist travel, intra-regional and longer-distance trucking shipments, and direct eco- nomic development occurring around and surrounding PAITF locations. This synthesis focuses on the first of these benefits cate- gories, direct transportation benefits, and on the bridges and tunnels specifically, because these tend to be the most preva- lent for consideration in LCCAs for highway investment. methods and measures Analytic Principle A methodology was needed to address the quantification of benefits resulting from facilities of different modes, character- istics, and usages, located within an extensive metropolitan, multimodal transportation network. The principle that was adopted was that the benefits of an existing facility would be equal to the additional costs to all travelers if that facility were removed from the network. Worded more formally in the Port Authority report: The transportation benefits of a facility are defined in this [Port Authority] study as the value of increased travel costs, consist- ing of travel time and vehicle operating costs, that displaced users would incur if that facility were no longer available, and all other network facilities remained open. Source: The Economic Impact . . . 2000, p. 5. The Port Authority believed that this estimate was con- servative in the following sense: If two or more Interstate Facilities were closed down simultaneously, the overall cost impacts would likely exceed the sum of the costs of individu- ally removing each of these facilities from the network. The Port Authority also realized that highway-user costs would differ among facilities for several reasons, including wide variations in origin–destination points among respective road users, the convenience of the preferred river crossings perceived by users, the convenience and travel cost of avail- able alternate routes, and existing levels of congestion. The Port Authority’s study offered the following examples to illustrate these points. . . . closing the George Washington Bridge imposes a high increase in travel time on its users principally because alterna- tive river crossings (primarily the Holland and Lincoln Tunnels) are relatively distant and the sheer volume of present users at the George Washington Bridge would cause grave congestion prob- lems at these alternative crossings. On the other hand, closing the Holland Tunnel would lead to significantly smaller increases in travel costs because the existing traffic at the Holland Tunnel is much lower . . . and alternative facilities are both relatively near and capable of absorbing the increase in traffic. Similarly, while the Goethals Bridge and Outerbridge Crossing serve over- lapping markets and have similar traffic levels, the analysis mag- nifies the impact of the latter bridge because it does not have as many nearby alternatives as the former. Source: The Economic Impact . . . 2000, p. 5. Methodology With this guiding principle established, the calculation of benefits was organized within a methodology that entailed four basic assumptions governing the determination of needed input values. These assumptions involved value of road users’ time, value of VOC, the degree of diversion to transit, and projection of traffic volumes to year 2000, the base year of the analysis. • Value of road users’ time. Value of time was estimated based on relationship to wage rates and variations based on trip purpose. The assumed values of time were as fol- lows: working time during transportation (e.g., truck and bus drivers) is equal to the gross wage; commuting time is equal to 50% of the gross wage; and leisure time (or personal travel) is equal to 25% of the gross wage. Val- ues of the gross wage were estimated based on the aver- age wage in the vehicles’ destination county in the a.m. travel period (from origin–destination data), because the destination would be an indication of work location for commuters. Destination county was also used to estimate the wages of those in heavy-goods vehicles, factored at 100% of the county’s average wage. The value of travel time associated with each vehicle also accounted for aver- age vehicle occupancy. • Value of VOC. VOC include the costs of fuel, oil, tire wear, and vehicle maintenance, plus an allowance for the capital cost of the vehicle. A literature review was con- ducted to estimate the following composite values for the New York metropolitan area: $0.29 per mile for autos, $1.20 per mile for trucks, and $0.91 per mile for buses. • Diversion to transit. Some of the road users displaced by bridge or tunnel closure were expected to divert to mass transit. An elasticity factor was assumed based on locally available transportation alternatives at each PAITF. This elasticity of transit use to auto travel time was estimated to be 0.15 to 0.3, with the study assump- tions leaning toward the higher end of this range. For example, an elasticity of 0.25 would mean that for every 10% increase in auto travel time, transit use

35 would increase by 2.5%. This range of 0.15 to 0.3 was somewhat lower than values appearing in the literature at the time of the study (extending to 0.8). The lower values were believed to be more realistic for this par- ticular study; however, because other studies had found relatively inelastic behavior of auto travelers on trans- Hudson crossings with respect to diversion to transit. • Projected traffic volume. Available traffic data were projected to the study year (2000) to arrive at 24-hour weekday distributions, which served as a basis for assum- ing traffic volume inputs. Other data were applied to complete the estimate. For example, survey results were available to enable estimates of average vehicle occupancy on certain of these bridges and tunnels, as well as trip purpose. The Interstate Network Analysis (INA) model was used to simulate the closing of individual bridges and tunnels and the resulting “shock” impacts throughout the network. These impacts consisted of rerouting the displaced vehicles to the “best” available alternative based on their origin–destination data, and then rerunning the INA model to compute a new net- work equilibrium. The model did not assume any peak shift- ing as the result of these diversions, regardless of the level of congestion and increased travel time to the road users. More- over, the focus of the calculations was on the change in travel costs to the former users of the closed facility, not to the users of other facilities in the network. (This assumption is another indication that the estimate of transportation benefit conferred by each Interstate Facility was conservative.) The INA model then reported the net increases in travel time and distance for road users, which were converted to costs using the travel time and VOC inputs discussed earlier. The results of this analysis show that the George Washing- ton Bridge has greater benefits than the other crossings, for the reasons cited earlier: heavy travel demand and the lack of alternate crossings nearby. Results for each bridge and tunnel are also available disaggregated into three line items that respond to the imposed closure of a facility: the cost of increased travel time experienced by former users of the facil- ity who must now divert to alternate routes; the increased time for former facility users who are now diverting to transit; and the increased cost of vehicle operation by former users of the closed facility. Decision support Background Information The economic analysis described earlier provides a point of departure for more comprehensive and detailed analyses of the roles that these critical interstate transportation facilities serve at a regional and national level. As an example, the fol- lowing paragraphs frame a transportation issue that PANYNJ is now dealing with that involves significant investment needs as well as significant impacts to regional highway transporta- tion and, potentially, to national and international maritime shipping. The issue is multimodal and multijurisdictional: it involves benefit–cost applications in both a regional and a national context. The issue concerns the Bayonne Bridge, which is shown at the lower-left-hand area of Figure 1. The bridge carries a high- way link between Bayonne, New Jersey and Staten Island, New York. The body of water that it crosses, the Kill Van Kull, is the entrance westward to the Port Authority’s mari- time facilities, also shown in Figure 1. The current height of the bridge over the water (151 ft), referred to as its air draft, is becoming a limiting factor on shipping entering the port because of the increasing size of cargo ships worldwide. This growth in the dimensions of large container ships is expected to increase when the capacity expansion of the Panama Canal is completed by 2015. The Port Authority recognizes a dual set of objectives and needs regarding issues such as this air- draft constraint: to continue providing a world-class port with navigable channels and clearances that can accommodate large cargo vessels and continue to provide the landside infrastruc- ture needed to move cargo (“Next Steps to Address . . .” n.d.). USACE Air Draft Analysis In 2008, the Port Authority commissioned the New York District of the U.S. Army Corps of engineers (USACe) to study “the commercial consequences of and the national economic ben- efits that could be generated by a potential remedy of the Bay- onne Bridge’s air draft restriction” (“Next Steps to Address . . .” n.d.). The USACe approached the problem by addressing when and to what extent the Bayonne Bridge would present an obstacle to larger ships, what are the economic consequences, and would further planning and environmental analyses of pos- sible solutions be warranted. The report was conducted in the nature of a Corps reconnaissance study, rather than a feasibility study, in that it did not recommend a specific project or cost- sharing plan. However, it did provide technical and economic data responsive to the Port Authority’s planning and decision- making needs. The primary findings of this study included the following (Bayonne Bridge Air Draft Analysis Sep. 2009): • The current height of the Bayonne Bridge is and will be an obstruction to larger container vessels within a 50-year analysis horizon. • Based on preliminary estimates addressing a range of engineering solutions to the air-draft problem, all have favorable benefit–cost ratios as summarized in Table 8. • Further planning and environmental analyses by the Port Authority are warranted to identify a preferred solution to the air-draft restriction. The current Bayonne Bridge structure is a steel arch with cables suspended from the arch to support the roadbed. The

36 USACe considered the following engineering alternatives to remove the bridge air-draft restriction: • Jack the existing steel arch and roadbed to a new height providing an air draft of 215 ft. • Build a new bridge structure with an air draft of 215 ft. • Bore a tunnel under the Kill Van Kull to replace the existing bridge. • Construct an immersed tunnel under the Kill Van Kull to replace the existing bridge. The benefit–cost results for each of these alternatives are shown in Table 8. Costs were estimated using data provided by PANYNJ’s Tunnels, Bridges & Terminals Department, based on the start of detailed engineering and design in 2010. Facility operation and maintenance (O&M) costs were esti- mated for each alternative, using the 50-year analysis period with O&M costs commencing at the completion of construc- tion. Benefits were estimated according to National economic Development (NeD) guidance, discussed here. Benefits were assumed to commence at the completion of construction of each alternative as shown in Table 8, including removal of the constraining roadbed from the channel. Net present value, benefit–cost ratio, and IRR of the cost and benefit streams were computed using a discount rate of 4.625% over a 50-year analysis period. The USACe also projected 50-year forecasts on the characteristics of shipping to the Port of New York and New Jersey (PONYNJ) in the absence of alteration or replacement of the Bayonne Bridge (i.e., the No-Build option) (Bayonne Bridge Air Draft Analysis Sep. 2009, pp. 32–36, Appendix B). Federal objectives and guidelines regarding studies of water and related land/resources development are spelled out in a document prepared by the U.S. Water Resources Coun- cil (Economic and Environmental Principles . . . Mar. 1983). The federal objective in project planning involving these resources is “to contribute to national economic devel- opment consistent with protecting the Nation’s environ- ment,” and to do so in compliance with relevant federal statutes, executive orders, and other planning requirements (Economic and Environmental Principles . . . Mar. 1983, p. iv). Project plans might address problems and explore opportunities to meet this objective, including identification of project benefits that contribute to NeD. Contributions to NeD are defined as “increases in the net value of the national output of goods and services, expressed in monetary units” (p. iv). Contributions to NeD may occur within the study region, or elsewhere in the nation as the result of the proj- ect. That NeD reflects a net increase in total output implies real gains attributable to the project on a nationwide basis, not simply a transfer of benefits from one region of the country to another. Benefits of the proposed Bayonne Bridge project were analyzed in terms of the reduced costs of maritime shipping owing to economies of scale in using larger vessels. To com- pute this cost reduction, USACe formulated two future pos- sibilities: (1) the Without-Project (or No-Build) condition, in which maritime commerce entering PONYNJ would be car- ried in smaller, less economically efficient vessels that could operate with the restricted air draft of the Bayonne Bridge; and (2) the With-Project condition, in which the existing air- draft constraint is removed by bridge alteration or replacement, allowing larger, taller vessels to be added to New York-bound routes. The USACe analysis forecast the amount of freight commerce through PONYNJ over a 50-year analysis period. It also forecast changes in the worldwide shipping fleet with the addition of the larger container vessels, contrasting the fleets to be used in Conditions 1 and 2. The USACe analysis then in effect “loaded” the two fleets with the projected cargo volumes, estimated the number of trips and container-miles required for the With-Project and Without-Project assumptions, and com- puted the respective vessel operating costs in each case. The difference between these two shipping-cost totals was taken as the NeD benefit attributable to the project (Bayonne Bridge Air Draft Analysis Sep. 2009, pp. 12, 13, 32, 33). USACe dealt with a number of issues in formulating this economic benefits study (Bayonne Bridge Air Draft Analysis Sep. 2009, pp. 13–32): • The trends in several inputs to the benefits computation had to be estimated through the 50-year analysis period. Alternative Year the Im provem ent Is in Place Break-Even Year Benefit– Cost Ratio Internal Rate of Return Net Benefit, $Billions Jack Structure to 215 ft 2019 2033 3.0 10.7% $3.271 New Structure at 215 ft 2022 2039 2.1 8.4% $2.822 Bored Tunnel 2024 2042 1.9 7.7% $2.585 Immersed Tunnel 2024 2051 1.4 6.1% $1.517 Source: Bayonne Bridge Air Draft… Sep. 2009, Tables 4 and 6. TABLe 8 SUMMARY OF BeNeFIT–COST ReSULTS, USACe AIR-DRAFT STUDY

37 These trends included a forecast of commerce through PONYNJ, the characteristics of the future maritime fleet, likely patterns of fleet use on routes bound for U.S. east Coast ports, loading patterns in accommodating cargo on different types of vessels while conforming to the opera- tional needs of regularly scheduled service worldwide (i.e., ships depart ports on a schedule, whether or not fully loaded), how the vessel fleets should be deployed in the analysis to handle growth in cargo volume for the With-Project and Without-Project conditions respec- tively, and estimation of the costs of operating vessels in the With-Project and Without-Project fleets. • USACe also had to address other potential restrictions on shipping that might negate the benefits of the Bayonne Bridge project. For example, if PONYNJ harbor chan- nels were not deep enough to handle large vessels, the prospective benefits of increasing the air draft on the Bayonne Bridge might never be realized. On this par- ticular point, an earlier Harbor Navigation Study (HNS) had been performed in 1999, recommending deepening of several channels in PONYNJ; construction funding for this project was authorized by the U.S. Congress in 2000. For a number of positive reasons, USACe applied the NeD methodology used in the Harbor Navigation Study to its air-draft study. This consistency of method made it possible for the Corps to ensure that the benefits of the air-draft project were separate and distinct from the benefits of the harbor deepening work, avoiding double-counting or overstating of benefits. • Other external factors and constraints could also limit the actual benefits to be realized from the Bayonne Bridge project, along the lines suggested in the preced- ing item. For example, possible limitations in rail and highway capacity, port crane capacity, berthing space, and yard capacity could themselves limit the volume of cargo handled by PONYNJ, apart from restrictions imposed by the bridge air draft. Also note that the Bay- onne Bridge is not an obstacle to port facilities located eastward, so greater use of these port facilities could increase benefits regardless of whether or not the air- draft constraint were removed. (This is not to say that such capacity constraints actually existed. USACe was just pointing out that a valid evaluation of benefits needed to consider these other factors, which was done in a broad context in developing the findings of the air-draft study.) • A similar point related to more global constraints—the USACe further considered whether these might limit the benefits that could be realized by altering or replacing the Bayonne Bridge. A key global constraint was the existence of air-draft restrictions in other parts of the world, which might themselves constrain the heights of future maritime fleet additions. The Corps investi- gated these and found that although certain height lim- its did exist, the air draft of the Bayonne Bridge was the most constraining among those affecting 12 major ports worldwide. USACe further considered other factors that might influ- ence future decisions on the project, and conducted scenario analyses to investigate the effects of differing assumptions underlying the study. • The Corps recognized factors that were outside the scope of its study, but that could inform and affect PANYNJ’s decisions on how to proceed on this project. These included regional and local economic benefits and impacts (as compared with the national benefits com- puted in the air-draft study); the possibility that not all NeD benefits were accounted for in the study (maritime transportation cost savings tend to be used as a NeD benefit measure because they are relatively conserva- tive and easier to compute than other categories of ben- efits); and that although the study referred generally to “the Port of New York and New Jersey,” the Port com- prises a number of stakeholders to whom benefits will accrue; for example, ocean carriers, terminal operators, labor interests, land-side transportation providers, and regional consumers (Bayonne Bridge Air Draft Analysis Sep. 2009, pp. 37–38). • The Corps recognized several areas of potential uncer- tainty in the analysis, and subjected each to scenario testing in which key parameters or assumptions were varied to assess their impact on the economic results. Nine categories of scenario analyses were addressed in all, covering diverse aspects such as the projections of maritime commerce, shifts in the location of man- ufacturing in Asia and their effect on shipping to the east Coast, project cost estimates, different engineer- ing options in the height to which the bridge roadway might be raised, and delays in the start of design and construction, among others. For a given category, the scenarios comprised several repetitions of the analysis, each repetition testing a different parameter value or assumption. Results of each repetition provided infor- mation comparable to that shown in Table 8. Coming PANYNJ Analyses The USACe analysis demonstrated that the Bayonne Bridge project was justified economically from a national perspec- tive. This result opened the door for the Port Authority to con- duct its own technical and economic analyses of the project and how it might proceed. As the contact representative of the PANYNJ has pointed out, the roles of the respective eco- nomic analyses can be understood essentially as follows: the USACe analysis indicated that the project is justified at a national level, whereas the PANYNJ analysis will indicate whether the regional benefits exceed the costs. The coming PANYNJ regional analysis will examine issues not addressed in detail in the national study; for example, a more comprehen- sive assessment of highway-user benefits addressing the land- side facilities of PONYNJ (including traffic over the Bayonne Bridge during and after construction), and changes in maritime

38 air pollution emissions because of the anticipated shift in ves- sel fleet characteristics calling on PONYNJ as the result of the modified air draft. In December 2010, the Port Authority announced that its preferred engineering option for the Bayonne Bridge would be a reconstruction of the main-span roadbed and bridge approaches and ramps, to raise the roadbed as it crosses the channel through its supporting steel arch. As of March 2011, PANYNJ was proceeding to identify and select an engineer- ing consultant to provide design services for this project. resources needed and other Information Resources The PANYNJ’s study of the economic impacts of its trans- portation infrastructure has been accomplished with the assis- tance of a consulting firm working with Port Authority staff. Although USACe personnel performed the cost and benefit analysis for the Bayonne Bridge Air Draft study and developed a portion of the input data, it obtained other data from PANYNJ. Corps personnel also met with PANYNJ consultants who were performing comparable analyses on other studies, to compare trend projections and check their consistency. plannIng anD programmIng: mobIlIty anD safety projeCts Introduction This section presents the methodology now used by WSDOT for highway capital programming, currently being extended to highway system planning. WSDOT’s programming pro- cess has been in place for almost two decades, and has bene- fited from continual updating, improvement, and integration within broader statewide performance-accountability initia- tives. This case example describes work that is comprehen- sive, innovative, and unique in the thorough integration of economic thinking from the top-level guidance of enabling state legislation through detailed analysis of the estimated costs, benefits, and technical performance of project alter- natives. An extensive information infrastructure has been built to support these procedures in headquarters and region (district) offices. WSDOT’s Capital Program Development and Management Office (CPDM) provides overall guidance to this effort in its conception, implementation, and applica- tion. Although WSDOT manages programs across several modes and types of work, the processes and economic analy- ses described here apply only to the highway construction program. It would normally be more natural to explain the planning process first, followed by capital programming. However, given the history of program-development pro- cesses at WSDOT, the following description will reflect the chronological order of their implementation: highway capi- tal programming first, followed by the extension to highway system planning. role of economic analyses in Highway Investment Background In 1990, WSDOT began working on a new, performance- based capital programming process under a project sponsored by the (then Joint) Legislative Transportation Committee. It had become apparent by that time that an emerging set of policy issues at the federal and state levels would confront WSDOT and Washington’s Transportation Commission, and changes to the highway capital construction programming process would be needed. Key objectives to be met included: (1) a strong, clear connection between the programming pro- cess and the emerging policy concerns; (2) a strengthened abil- ity to highlight and evaluate key tradeoffs in funding projects; (3) a more rational, understandable basis for prioritization rooted in economic as well as engineering performance; and (4) incorporation of greater flexibility and accountability in rec- ommending projects. The study was concluded in 1991, and its recommendations were accepted by WSDOT for future imple- mentation. Since that time, the programming process has been continually refined to meet new transportation program needs, accommodate the terms of new legislative requirements and funding sources, update analytic methods and decision criteria, contribute to statewide initiatives in performance-based man- agement and accountability, and incorporate new technology. Statutory Program Guidance The Revised Code of Washington (RCW) compiles all per- manent laws of the state of Washington; Title 47 deals with public highways and transportation. RCW 47.05, Priority Programming for Highway Development, was rewritten in 1993 as the result of the capital programming study men- tioned earlier and enabled WSDOT implementation of the new programming process to be fully implemented. The new statute restructured Washington’s highway investment program, introduced new capital construction programming processes that considered least-cost and benefit–cost evalu- ations of proposed solutions to transportation problems, and responded to new policy initiatives at the state and federal levels. The law has been revised since then to be coordinated with other chapters of Title 47 (e.g., defining legislatively mandated transportation goals) and to fit within an expand- ing application of performance-based management through- out Washington state government. The declaration of purpose of RCW 47.05 is as follows, with specific reference to use of economic methods: The legislature finds that solutions to state highway deficiencies have become increasingly complex . . . Difficult investment trade-offs will be required. It is the intent of the legislature that investment of state trans- portation funds to address deficiencies on the state highway system be based on a policy of priority programming having as its basis the rational selection of projects and services according to factual need and an evaluation of life cycle costs and benefits that are system- atically scheduled to carry out defined objectives within available

39 revenue. The state must develop analytic tools to use a common methodology to measure benefits and costs for all modes. The priority programming system must ensure preservation of the existing state highway system, relieve congestion, provide mobility for people and goods, support the state’s economy, and promote environmental protection and energy conservation. . . . The priority programming system for improvements must incorporate a broad range of solutions that are identified in the statewide transportation plan as appropriate to address state highway system deficiencies, including but not limited to high- way expansion, efficiency improvements, nonmotorized trans- portation facilities, high occupancy vehicle facilities, transit facilities and services, rail facilities and services, and transpor- tation demand management programs. Source: http://apps.leg. wa.gov/rcw/default.aspx?cite=47.05.010. Legislatively mandated goals for the transportation pro- gram are as follows (RCW 47.04.280): • Economic vitality: To promote and develop transpor- tation systems that stimulate, support, and enhance the movement of people and goods to ensure a prosperous economy; • Preservation: To maintain, preserve, and extend the life and utility of prior investments in transportation systems and services; • Safety: To provide for and improve the safety and security of transportation customers and the transpor- tation system; • Mobility: To improve the predictable movement of goods and people throughout Washington state; • Environment: To enhance Washington’s quality of life through transportation investments that promote energy conservation, enhance healthy communities, and protect the environment; and • Stewardship: To continuously improve the quality, effectiveness, and efficiency of the transportation system. programming mobility projects WSDOT’s highway capital construction program is divided into two major components, Preservation (P) and Improve- ment (I). Specific types of projects are organized within pro- gram categories under Programs P and I, respectively. Both major programs employ economic analyses to assist in project ranking and selection, program development, and recommen- dation of a biennial budget. The Preservation Program gener- ally considers the criterion of lowest life-cycle cost, whereas the Improvement Program is based typically on benefit– cost considerations. Other, nonmonetary factors are also considered in final decisions on P and I projects. The P and I programs are further subdivided into subprograms that contain specific types of projects. This case example addresses one of the Improvement Program subprograms, Mobility. The Mobility subprogram includes projects addressing urban congestion, rural mobility, urban bicycle connectiv- ity, and high-occupancy vehicle (HOV) lanes. Projects are grouped in this way to enable “peer group” or “apples-to- apples” comparisons among candidates when prioritizing and selecting the best solutions to identified needs or prob- lems. each program receives an investment target from the legislature; this target anticipates monies from a number of state and federal funding sources, each with separate require- ments (“2009–2011 Scoping . . .” Aug. 2007). Recommen- dation of those high-ranking projects to be constructed within the budget target is the task of the programming process. The process encompasses the following steps (MacDonald Feb. 2004; “WSDOT Projects . . . Prioritization” 2008): • To identify a problem or need (typically based on find- ings in the Highway System Plan), based on an identi- fied performance objective or goal. • To explore possible solutions and advance the most cost-effective and least capital-intensive alternative. • To develop a project scope that—in addition to esti- mated effects on transportation system performance— takes into account potential issues in environmental impact, roadway design, and stakeholder reaction, including community acceptance. • To estimate project costs based on information in the scope and develop a basis of estimate to document all assumptions. • To estimate project benefits based on information in the scope. • To compare the benefits and costs of this project with those of its peers to determine project rank and priority. As part of the Highway System Plan updating process, WSDOT uses multiple tools in screening and evaluating proj- ect candidates. CPDM uses the Highway Segment Analysis Program as a screening tool to identify all congested highway segments on the network, complemented by other WSDOT analytic tools (e.g., to identify bottlenecks). Resulting state highway needs are consolidated with road needs identified by MPOs, RTPOs, and tribal nations. Cost-effective solutions are then developed and analyzed using traffic analysis tools to make sure the projects improve performance. Next, the Mobil- ity Project Prioritization Process (MP3) tool is used to analyze the benefits and costs of each Mobility project as affected by its engineering and performance characteristics, to prioritize and rank projects within each subprogram, and to evaluate program tradeoffs in the face of budget constraints. • Screening criteria – Candidate projects that are not listed in the Highway System Plan are ineligible for further consideration. – To meet air quality conformity requirements, candidate projects that would degrade air quality in non attainment areas are ineligible for further consideration. – Given budget limitations, candidate projects might favor near-term to mid-term needs, rather than solely long-term needs, to warrant further consideration. • Evaluation criteria – BCA (discussed in the following section). – environmental impact: wetlands, water quality and permitting, and noise; evaluated on a nonmonetary

40 basis using either responses to yes–no questions (e.g., regarding permitting requirements) or penalty points and risk-factor points for adverse environ- mental consequences. – Stakeholder response: degree of community support, views of other stakeholders, potential disruption of neighborhoods; evaluated on a nonmonetary basis using responses to yes–no questions. – Project design: projected relationship of project to, or expected impact on, matters such as land use, efficient use of existing capacity, network/system connec- tivity, use of alternative modes including bicycling and walking, and modal integration (both inter- modal and packaged multimodal solutions); evalu- ated on a nonmonetary basis using responses to yes–no questions. These criteria are weighted, with the benefit–cost criterion having the heaviest weight. The mathematical prioritization considers both economic and nonmonetary criteria. Projects closer to the ideal-best result are higher in ranking; those closer to the theoretically worst result are lower in ranking. • Analytic tool – The MP3 analytic tool and its results are described in the following section. – To focus the technical discussion of this methodol- ogy, the case example considers a particular group of Mobility projects: those that improve highway capac- ity and operational performance to provide congestion relief. mobility methods and measures Engineering Economic Methodology The BCA of WSDOT Mobility projects is conducted using the Mobility Project Prioritization Process (MPPP or MP3). MP3 is a spreadsheet workbook that evolved from model develop- ment by WSDOT through the 1990s, which was improved with additions and modifications by a consultant team in 2000. The MP3 workbook accepts inputs on the type, location, and engineering characteristics of the project; traffic forecasting data; data to estimate benefits in travel-time reductions and collision reductions; and project cost data. MP3 users may also specify changes in key parameters [e.g., discount rate, project life cycle, benefit-days per year, hourly average annual daily traffic (AADT) distribution curves] and the internal representation of speed-flow curves to allow choice between the WSDOT default speed-flow relationship and that in the Highway Capacity Manual (HCM 2000). In most of the anal- yses, the benefit of travel-time savings is computed based on the difference in vehicle-hours of travel time with and with- out the project. For intersection improvements, the benefit of travel-time savings is based on the change in overall delay comparing the build and no-build options (Dowling Associ- ates, Inc. et al. May 2000, p. 9). eeAs of project benefits are structured individually for each type of Mobility improvement (Dowling Associates, Inc. et al. May 2000, supplemented by review of the current MP3 workbook provided by WSDOT): • Mainline lane addition/access management benefits: addition of general purpose lanes, addition of truck- climbing lanes, addition of a two-way left-turn lane on two-lane highways, and modification of type of median on four- to seven-lane highways. • HOV lane benefits: adding an HOV 2+ lane to an urban multilane highway/freeway, either or both direc- tions; converting a general purpose lane of an urban multilane highway/freeway to an HOV 2+ lane, either or both directions; and conversion of an HOV 2+ lane to an HOV 3+ lane when the HOV-lane volume reaches HOV-lane capacity. • Intersection improvement benefits: originally, improve ment of existing signalized intersections based on intersection control; later allowance for improve- ment of Stop-controlled intersections; later addition of roundabouts as a new type of intersection improvement. • New interchange benefits: new interchange at a new access point. • Park-and-ride lot benefits: road user benefits result- ing from constructing a park-and-ride lot adjacent to a state highway; the workbook provides several options on type and location of the parking lot. • Safety benefits: benefits of expected accident reduc- tions owing to the highway improvement; benefits assigned to collision reductions in five categories: fatal- ity, disabling injury, evident injury, possible injury, and property damage only. Consider the example of the addition of a general purpose lane: • Input data or internal global values on the proposed lane- addition project, traffic volume and composition, traffic growth rate, and 24-hour distribution of daily traffic are used to estimate the effects on speed and travel time under the build and no-build options, in the analysis base year and the analysis future year. Standard engineering cal- culations such as those used with the Highway Capacity Manual are applied to compute volume–capacity ratios, resulting operating speeds, implied travel times, and travel-time savings resulting from the proposed project. • Benefits in each of the 24 daily hours are computed using a number of default values within MP3, which can be changed from time to time with appropriate documen- tation of source and CPDM concurrence. These values include a factor that specifies the number of days per year for which benefits are assumed (i.e., the number of days per year for which the 24-hour distribution of traf- fic applies; e.g., 260 days per year); wage rates appli- cable to drivers of general-purpose vehicles and trucks, respectively; together with a multiplicative factor identi-

41 fying the percentage of wage rate to be used in the ben- efits calculation (e.g., 50% for general vehicles, 100% for trucks), average vehicle occupancy during peak and off-peak periods, and the travel-time savings computed earlier. • Benefits are tallied for each of the 24 daily hours and expanded to annual totals for each year of the analysis period using the specified days-per-year figure discussed earlier (e.g., 260 days per year). The value of the discount rate (an MP3 global variable with default value of 4%; deviation from this figure requires WSDOT approval) is used to compute the present value of the benefits stream. • Project costs are input using data from the project scop- ing estimate or planning-level cost estimate. Construction cost inputs cover preliminary engineering, right-of- way, and construction of structures, drainage, grading, and other items. Total construction costs are reduced by the amount of cost sharing by agencies other than WSDOT. Operation and maintenance costs are input on an annual basis; a workbook calculation applies these to each year of the analysis period, and computes the pres- ent value using the present-value-of-annual-series fac- tor for the specified discount rate and length of analysis period (e.g., 4%, 20 years). The present value of total costs equals the sum of WSDOT construction costs and the present value of operation and maintenance costs. • The workbook computes the net present value (present value of benefits minus present value of costs) and the benefit–cost ratio (present value of benefits divided by present value of costs). Results of Analyses A corresponding approach is used for other types of Mobility projects addressed by the MP3 workbook. A summary of the analytic elements on each workbook tab, including the tabs (or worksheets) for the respective project types, is shown in Table 9. Results for all of these analyses are expressed as net present values and benefit–cost ratios. mobility Decision support The benefit–cost results for Mobility projects, together with results of corresponding economic analyses for other I and P subprograms, provide the economic input to project prioriti- zation that is critical to WSDOT’s development of its capital construction program and biennial budget. The recommended project rankings produced by the analytic programming procedures such as MP3 are helpful in understanding the economic value-to-cost of projects and programs, as well as their relative strengths in other, nonmonetary criteria; how- ever, they do not determine the final budget. Flexibility in the process allows WSDOT to respond to other influences such as community interest and need. Individual projects may be raised in priority and others deferred to compensate within the constrained budget. The legislature may also direct fund- ing to specific projects regardless of their computed priority (“WSDOT Projects . . . Prioritization” 2008). These results of the programming process are reviewed internally by department executives and other senior manag- ers. externally, the resulting program and budget recommen- dations are forwarded to the legislature and communicated to the appropriate executive agencies, other stakeholders, and the public. Budget recommendations are reviewed by the Washington State Legislature, including confirmation of revenue forecasts to fund the transportation programs. Separate reviews and hearings are conducted by the House and the Senate Trans- portation Committees, respectively. either committee may adjust the proposed list of projects or the amount of funding requested in any of the programs. One or both committees may file a budget bill, which proceeds through the legislative process to final passage and submittal to the governor for sig- nature. The governor may sign the bill as is, veto selected line items, or veto the entire bill, returning it to the legislature for further action. After the transportation budget is passed and signed, CPDM works with WSDOT’s Budget Services Office to communicate legislative authorizations and funded items internally to WSDOT regional managers and modal system managers, enabling final adjustments to lists of projects and related tracking-system data. Baselines are established for monitoring subsequent project delivery at the regional and headquarters levels. These baseline data are also incorporated within the legislature’s computerized tracking system and WSDOT’s Transportation executive Information System, enabling the legislature and department executives to moni- tor progress in delivering WSDOT’s transportation programs (“Building the Capital Program” Feb. 2008). programming safety projects In May 2005, AASHTO presented WSDOT with its newly established Safety Leadership Award, recognizing the depart- ment’s “proactive approach to safety”: This approach involved [a] local, corridor, and system-wide perspective. Working with other safety agencies, WSDOT adopted a strategic safety plan, called Target Zero. As an out- come, the state has had a 56% decrease in fatal and disabling crash rates since 1990 even though vehicle miles traveled over that period have increased by 35%. Source: Measures, Markers, and Mileposts: The Gray Notebook, Quarter ending June 30, 2005, p. 52. Washington State has continued to apply its management, planning, engineering, data collection, and analytic resources to identify and apply cost-effective measures that reduce the societal costs of fatal and disabling crashes. The approach is holistic in that a number of Washington’s highway programs and subprograms have measurable safety-related objectives. These objectives consider historical experience; for exam- ple, highway locations/sections that have a serious accident

42 Worksheet Description Required Inputs/Actions Optional Inputs Notes/Comments Software Notes Provides software’s purpose, structure, color coding scheme. Describes each of the worksheets. None None None Project Description Project description Project description, including route, posted speed, title, beginning and ending mileposts, no build and build num ber of lanes, and terrain None The default population density is taken from the Global Variables worksheet. Posted speeds are rounded to 50, 60, or 70 mp h. Global Variables Benefit–cost analysis assum ptions and default values that are used throughout the workbook. Discount rate ( i ), project life cycle ( n ), benefit days per year, select or define ADT 24- h distribution curve, identify start and end of a.m . and p.m . peak periods, value of tim e and operating costs, population density (urban or rural) Project-specific peak and/or off-peak AVOs. Can provide ratio of benefits to new users (default assumes economic “rule of half”) Defaults should be used unless there is a co mp elling reason to do otherwise. Any m odifications to the default values need to be docum ented. 24-Hour Volume Distribution Chart Graphically displays the selected Year 1 directional and total volume distribution by hour of the day Select or define the ADT 24-h distribution curve in the Global Variables worksheet. The selected curve will automatically be displayed in the 24 Hour Volume Distribution chart None Graph only displays the selected Year 1 curve. Estimate and B-C Ratio Cost estimates for preliminary engineering, environmental retrofit, right-of-way, construction, operation & maintenance. Incorporates present value of user benefits for each particular im provem ent. Estimates the benefit/cost ratio. Quantities needed for cost calculations, non-WSDOT cost share, and operation & maintenance costs, or total WSDOT present value costs (PVc) User has the option of entering general cost per m ile estimates, or a resultant to tal WSDOT present value cost (PVc) estim ated outside of the worksheet. Can use general cost per mile calculations or detailed cost calculations Output from this worksheet is used as inputs to TOPSIS to pr io ritize highway mobility projects. 4-Step M odel Benefits Estim ates annual 24-h user benefits based on output from an accepted 4-step m odel. Model description, truck percent, peak period AVOs, and 24-h vehicle-hours traveled on state facilities 24-h vehicle-hours traveled on entire system , not just state system. Can estim ate user benefits for entire system if data are provided, but only benefits for state system users will be incorporated into overall project B/C rat io. Two-Way Left-Turn Lane (TWLTL) and Multilane Acces s Management Benefits Estim ates annual 24-h user benefits for converting a 2-lane undivided facility to a 3-lane TWLTL facility (Harwood/St. John method), or for median treatm ents and/or access spacing changes for 4–7 lane facilities ( NCHRP 395 method). Peak direction of selected ADT hourly distribution curve, median type, average access spacing, access control class, daily and peak hour traffic data, and truck % Peak and nonpeak turns per access, if evaluating benefits using the NCHRP 395 meth od. Uses ADT hourly distribution curve selected in Global Variables to estimate peak and off-peak percents and to convert working peak hour user benefits to 24-h benefits. General Purpose Lane Benefits Estim ates annual 24-h user benefits for adding a general purpose lane. Facilities that can be analyzed include: a 2- lane highway, an arterial, a rural/sm all urban freeway, or a mu ltilane highway or freeway. No build and build posted speeds, direction(s) of added lane, ADT and K factor or working peak hour volum es, truck percent, grade and length of grade, volume growth rate, and roadway type ADT and K factor or working peak hour volume is required, but either can be input. Can input data for one or two directions. Benefits are estimated by each hour of the day for the selected direction(s) of the facility. Climbing Lane Benefits Estimates the annual 24-h user benefits for adding a truck clim bing lane to a 2-lane highway or to an arterial. Sam e as above Sam e as above This worksheet has not been updated to look up values from the WSDOT speed-flow curve worksheet. WSDOT curves are em bedded in worksheet. TABLe 9 MP3 WORKSHeeT DeSCRIPTIONS

43 role of economic analysis in Highway safety Investment The computation of the societal costs of accidents (or the benefits of avoiding these costs) is based on the following (Median Treatment Study . . . Mar. 2002): • Identification of the societal costs of different severities of accident: cost per fatal collision, cost per disabling (or serious) injury collision, cost per evident injury col- lision, cost per possible injury collision, and cost per property-damage-only collision. • Identification of the frequency of occurrence of each cat- egory of accident severity, before and after a particular history—as well as proactive analyses of highway character- istics and traffic volumes and behaviors that point to a poten- tial for accidents in the future (“Safety Management System” Oct. 2009). WSDOT’s highway system Preservation (P), Improvement (I), and Maintenance (M) programs all play a role in promoting highway safety. However, this case exam- ple will focus specifically on projects included in the Safety improvement (I2) subprogram. Although a number of state DOTs use economic dollar values in analyzing accident costs and conduct safety-related benefit–cost studies, WSDOT’s approach is unique in the way it has organized the leadership of statewide highway safety initiatives, including coordina- tion with other agencies and stakeholders. Worksheet Description Required Inputs/Actions Optional Inputs Notes/Comments Intersection Benefits Estimates the annual 24-h user benefits for improving an existing intersection No build and build total approach volumes, number of lanes, average intersection delays, and in tersectio n v/c ratios, existing approach volum es by hour for 24-h, and build scenari o percent reduction by approach Most recent counts of hourly approach volumes that can be converted to existing hourly approach volumes Benefits are estimated by each hour of the day. Since Year 20 VHT can be higher than Year 1 VHT, there is a potential for negative benefits. When negative benefits are estim ated, they are assum ed to be zero benefits. New Interchange Benefits Estimates the annual 24-h user benefits for adding a new interchange to an existing facility Year 1 and Year 20 working peak hour volumes, distances and speeds or travel tim es for no build and build or ig in– destination (O-D) pa th s Model travel times can be input for specific O-D paths instead of being calculated based on distances and speeds. Working peak hour user benefits are converted to 24-h benefits using ADT hourly distribution curve selected in Global Variables. HOV Lane Benefits Estimates the directional annual 24-h user benefits for addi ng an HOV lane Directional num ber of lanes with and without project, ADT or directional working peak hour volum es, HOV and GP growth rates, truck percentages, and traffic composition Can select the HCM 2000 speed-flow curve instead of using the WSDOT default curves. Can change default GP/HOV capacities per lane, but mu st document. Benefits are estimated by each hour of the day for the selected direction(s) of the facility. Worksheet assu me s that HOV lane can be used by GP traffic outside of the peak period. Park & Ride Lot Benefits Estimates the bi-directional annual 24-h user benefits for constructing a park & ride lot. Nu mb er of parking spaces, percent of lo t capacity used, various destination data, user distribution (t ransit riders/carpoolers), and AVOs None 24-h benefits are assum ed to be equal to working peak hour or peak period benefits. Safety Benefits Estimates the annual 24-h user benefits of im proving the safety of a facility. Selection of safety im provem ents, identification of the num ber of accidents by type of accident None None WSDOT Default Curves Contains WSDOT default speed-flow curves for 50, 60, and 70 mph facilities. Speeds are dependent on v/c ratio and the number of lanes. HOV lane speeds are dependent upon volumes. None None The lowest allowed congested speed for general purpose lane speeds is 15.2 mph (for v/c ± 1.2). Allowable HOV lane speeds are 55 mph at free-flow down to 40 mph at capacity. HOV lane speeds are solely dependent on lane volumes and an assumed capacity HCM 2000 Curves Contains the HCM 2000 speed-flow curves for freeways. Speeds are dependent on free-flow speeds, length of segment, and v/c ratio. Posted speed and length of section must be provided in the Project Description worksheet. These values are used to estimate speed-flow relationship. None Freeway speeds for GP and HOV lanes can range from free-flow speeds down to about 12 mph at a v/c of 2.0. Source: WSDOT MP3 workbook, “Software Notes” tab (2009). TABLe 9 (continued)

44 safety action (e.g., a safety project, enforcement activ- ity, or educational campaign). • Computation of benefits in terms of the reduction in accident societal costs resulting from the safety action (whether a reduction in accident frequency, accident severity, or both), comparing the “before” and “after” cases with the yearly benefits discounted through an analysis period. • Computation of costs of performing the safety action (typically construction plus maintenance) with the annual costs discounted through the analysis period. • Computation of the benefit–cost ratio, using the dis- counted values. Although the B/C ratio is computationally straightforward, predicting accident frequency and severity that result from a safety investment can be difficult. Technical studies such as those described here provide a basis for estimation. Similarly, valuing the societal costs of an accident involves a number of assumptions; cost- and benefit-related issues and a synthesis of state DOT practices are discussed by Hanley (2004). In its safety analyses, WSDOT uses societal costs recommended by FHWA (2007–2026 Highway System Plan . . . Dec. 2007). Legislative Guidance and Agency Goals WSDOT’s highway-safety approach responds to the provi- sions of the federal SAFeTeA-LU legislation (P.L. 109-59, Aug. 10, 2005). SAFeTeA-LU establishes and funds the Highway Safety Improvement Program as a core program, giv- ing states flexibility to address their most critical safety needs with a focus on demonstrating performance. It calls for states to develop Strategic Highway Safety Plans (SHSPs), approved by the governor or a responsible state agency, to identify safety needs and opportunities, propose ways to address them through prioritized actions, and evaluate the quality of data. To conform to the provisions of SAFeTeA-LU, the SHSP is developed in consultation with others involved in high- way safety. It specifies performance-based goals for meet- ing highway safety needs in both the infrastructural and the driver behavioral categories on all public roads, proposes ways to assess resulting improvement in safety performance, and applies these lessons to prioritizing future safety actions (SAFeTeA-LU Aug. 10, 2005). WSDOT’s SHSP is embodied in the Target Zero document mentioned earlier, currently updated to 2010 [(Target Zero) Washington State’s Strategic Highway Safety Plan . . . Aug. 27, 2010]. This strategic safety plan sets the important aspirational goal of zero traffic deaths and serious injuries on Washington State’s roads by 2030. Consultation in developing this SHSP has included a number of state agencies: WSDOT; State Patrol; Departments of Health, Licensing, and Social and Health Services; Washington Traffic Safety Commission; Washington Transportation Commission and a host of others; several federal agencies; tribal nations and organizations; private and nonprofit groups; and community, local, and regional agencies and organizations. The plan encompasses the “four es” commonly associated with highway safety programs: engineering, education, emergency services, and enforcement. Key elements of Target Zero are incorporated within WSDOT’s 20-year Highway System Plan. The SHSP indicates that fatal highway accidents have declined in Washington State from a rate of 4.91 deaths per 100 million vehicle-miles traveled (MVMT) in 1966 to 0.94 per 100 MVMT in 2008, the state’s lowest traffic fatality rate on record and below the 1.27 per 100 MVMT national rate computed by NHTSA (Target Zero, p. 7). Several likely reasons for this decline in fatal crashes are cited, including decreased levels of driving resulting from escalating gaso- line prices and the economic recession in 2008; investments in cost-effective, performance-enhancing safety projects; improvements in roadway engineering, specific roadside safety features (discussed in greater detail later), vehicle design, and safety equipment; and the beneficial effects of safety education, tougher impaired-driver and seat-belt-use laws, faster emergency response, and law enforcement. Not- withstanding these improvements, challenges to meeting the Target Zero goals remain. For example, motorcycle deaths are increasing, countering the otherwise favorable motorist fatality trend. Although impaired-driver-related fatalities are decreasing, they are not dropping fast enough to meet the 2030 zero-level target. WSDOT has adjusted its proposed safety countermeasures to address these issues. Target Zero organizes the factors involved in traffic fatali- ties, related safety analyses, and resulting recommendations within four priority levels. For the 2010 update, these priority levels are based on recorded percentages of total highway fatal- ities during 2006–2008, as follows (Target Zero, pp. 11–14): • Priority One consists of factors implicated in 40% or more of traffic fatalities between 2006 and 2008. It includes accidents involving alcohol- or drug-impaired drivers, speeding, and run-off-the-road crashes. each of these factors was identified as a contributing circum- stance in accidents accounting for 40% or more of total highway fatalities. (Author’s note: in structuring these priority levels, the number of fatalities, not the number of fatal crashes, is used.) • Priority Two consists of factors implicated in 21% to 39% of traffic fatalities in 2006–2008. It includes acci- dents involving young drivers (ages 16–20 and 21–25), unrestrained passenger vehicle occupants, distracted drivers, and accidents at intersections. • Priority Three consists of factors implicated in 11% to 20% of traffic fatalities in 2006–2008. It includes acci- dents involving unlicensed drivers; opposite-direction, multi-vehicle collisions; motorcyclists; pedestrians; and heavy trucks. • Priority Four consists of factors implicated in less than 10% of traffic fatalities in 2006–2008. It includes accidents involving older drivers, drowsy drivers, nonmotorized cyclists, road work zones, wildlife, vehicle–train collisions, school buses, and aggressive drivers.

45 Target Zero notes that many fatalities are associated with more than one of these factors. These traffic deaths are there- fore represented more than once in the fatality data associated with the four priority levels. Technical and Organizational Approach WSDOT, like several other state DOTs, has found that a partic- ularly cost-effective approach to reducing fatal and disabling- injury accidents is to invest in low-cost, systematic safety improvements. WSDOT has focused on centerline rumble strips and cable median barriers on its mainline state high- ways as successful ways to manage vehicular departures from the road. Other cost-effective, performance-enhancing safety measures include improvements in (or greater use of) the fol- lowing: pavement markings (including wider markings, chev- rons, and route decals or “horizontal signing”), directional signage, fluorescent yellow sign sheeting (e.g., on curve- warning signs), addition of left-turn lanes, active-warning sys- tems (e.g., for “crossing traffic ahead” and advanced-warning “end-of-green” flashers), roadway lighting, shoulder and edge- line rumble strips, access management (e.g., raised medi- ans), speed-feedback signs, vehicle recovery areas, guardrail end treatments, roadside or guardrail delineators, and features at intersections (e.g., improved vehicular and pedestrian traffic signals, transverse rumble strips, improved signage, and round- abouts). Several state DOT presentations on these types of traf- fic engineering countermeasures were given at a traffic safety summit (“everyOne Counts” Feb. 2009). WSDOT’s organizational approach to highway safety improvement differs from models used in some other DOTs. In lieu of a designated safety office or safety engineer, WSDOT organized a Highway Safety Issues Group (HSIG) in the 1990s. Co-chaired by the heads of traffic operations and highway design, the HSIG core membership consists of representatives of WSDOT planning, program management, traffic operations, WSDOT regional traffic and design engineers, and the FHWA division office. By its nature, it promotes a team approach and brings multidisciplinary expertise to safety issues. The HSIG undertakes a number of activities, among them identifying areas of potential safety improvement and coordinating the development of safety policies and initiatives on behalf of the department. It may undertake studies such as safety BCAs, recommend applications of departmental safety resources, and review proposed actions submitted by WSDOT management. It acts as a champion for safety. It also can interact effectively with outside groups through the Washington Traffic Safety Commission (WTSC) (Mercer Consulting Group June 2007, pp. 6–7; State of Alaska . . . Sep. 2007, p. e-15). safety program methods and measures WSDOT’s assignment of Priority One to run-off-the-road crashes and its emphasis on centerline rumble strips and cable median barriers as technically and economically feasible solutions resulted from nationwide data and analyses that were conducted in the 1990s and early 2000s. A key influ- ence on WSDOT’s thinking was a study by the Insurance Institute for Highway Safety, or IIHS (Persaud et al. 2003). The IIHS report compiled available data and research find- ings from several sources, including FHWA, NHTSA, state DOTs, and academic and consultant researchers, all within the 1990s–early 2000s time frame. These research results collectively indicated the following (Persaud et al. 2003, pp. 1–3): • Although urban areas experience the highest rates of motor vehicle accidents overall, fatal accidents are more likely to occur in rural areas (2.3 fatal crashes per 100 MVMT on rural highways versus 1.0 fatal crash per 100 MVMT on urban highways nationally). • Reasons for the higher average rate of severe accidents on rural roads include generally higher traffic speeds, lower seat belt use, longer response times for emergency medical assistance, and road design characteristics, particularly on rural two-lane roads. • Nationally, rural two-lane roads account for approxi- mately 90% of all fatal crashes on rural highways. The characteristically undivided configuration of two-lane highways, and the absence of wide medians or centerline barriers to physically separate opposing-traffic flows, are factors in vehicles crossing the centerline. • The result of vehicles departing from their correct direc- tional lanes can be head-on collisions or the sideswiping of vehicles traveling in the opposite direction. Although these collisions are not the result of a single cause, fac- tors typically cited by police include failure to keep in the proper lane, driver inattention, driver fatigue, and speeding. • Roadway widening and installation of centerline barri- ers are possible highway engineering solutions to reduce opposing-traffic collisions; however, they are expensive and therefore tend to be limited to specific, high-priority locations. Such spot-location fixes do not solve the more general problem of opposing-traffic collisions that can occur virtually anywhere along the length of a two-lane, undivided highway. • A more economical and practical potential solution is the installation of centerline rumble strips along the length of undivided two-lane highways. By providing an audible vibration under vehicles encroaching on the centerline, rumble strips can alert inattentive, fatigued, distracted, or speeding drivers that they are drifting into the opposite lane. • Rumble strips had already proven themselves on the right-hand shoulders of limited access highways in reducing run-off-the-road-to-the-right incidents, which did not involve collisions with opposing traffic. How- ever, at the time of the IIHS study (2003), there was relatively little research or field experience on how these rumble strips would perform on the centerlines of two-lane rural highways. The limited informa- tion that was available, however, comprising simple before–after comparisons of crash rates in studies

46 by two state DOTs, indicated that centerline rumble strips did reduce the rates of both head-on collisions and opposing-direction sideswipes. • The purpose of the IIHS study was to update these findings on the value of centerline rumble strips in improving rural highway safety. It did this by expand- ing the available data to a larger pool of state DOT experience, and refining the analysis of crash reduc- tions resulting from centerline rumble strips to cor- rect for certain mathematical algorithms and biases in earlier works. • The results of the 2003 IIHS study indicated that center- line rumble strips did indeed result in significant crash reductions on two-lane rural highways. All injury crashes combined (i.e., disabling injury, evident injury, and possible injury) were reduced by an average of 15%, or a range of 5% to 25% at the 95% confidence inter- val. Head-on (frontal) crashes and opposing-direction sideswipe crashes were reduced by an average 25% (5% to 45% at a 95% confidence interval). The study concluded: In light of their effectiveness and relatively low installation costs, consideration should be given to installing centerline rumble strips more widely on rural two-lane roads to reduce the risk of frontal and opposing-direction sideswipe crashes. Source: Persaud et al. 2003. The evaluation of candidate safety project sites entails a technical diagnosis of problems and potential solutions, plus a BCA to assist in prioritization. safety program Decision support Decision-Making Approach The objective of this study is to identify cost-effective solu- tions that yield a high rate of return in terms of reducing fatal and serious (or disabling) injury crashes. For a valid analy- sis, however, the locations, frequencies, and circumstances of fatal and serious-injury accidents must be known. WSDOT relies on a GIS-based safety management reporting system, supported by descriptive accident data provided by the State Patrol, which enables WSDOT managers to identify where serious safety problems exist, what factors are influenc- ing crashes (particularly those of high severity), and what options might provide the best solution. (WSDOT’s Trans- portation Data Office heads a Collision Report Commit- tee that, with the cooperation of the State Patrol, provides for uniform accident reporting across the state.) The GIS- based graphical displays are packed with information that assists highway and traffic engineers in diagnosing crash locations, clusters, and situations. The highway route and the crash-location symbols employ color coding to indi- cate crash severity, density of clustering, and locations of significant Priority One events. each accident indication can be expanded to reveal detailed text descriptions of all crashes that have occurred at that location within the speci- fied time frame (which can be multi-year), based on the aforementioned State Patrol reports. Based on these data, WSDOT can pursue cost-effective solutions that provide the “biggest bang for the buck” in addressing the targeted safety goal. As an illustration for this case example, WSDOT’s analysis shows that many fatal accidents are caused by head-on collisions on undivided highways. The GIS reporting system allows WSDOT to pinpoint those highway locations having the greatest con- centration of these crashes or of vehicles leaving the road after crossing the centerline and opposing lanes. In lieu of relatively expensive centerline barriers, WSDOT has pur- sued more economical centerline rumble strips. The BCA described earlier allows WSDOT to identify high-priority segments where the installation of centerline rumble strips is recommended. It is not unusual for B/C ratios in these seg- ments to exceed 100 to 1. Legislative Review and Approval This methodology is the foundation of WSDOT’s safety pro- gram budget recommendations. The recommendations are submitted to the legislature as part of the transportation bud- get package. The legislature reviews these recommendations and proposed funding levels, and may make adjustments as described earlier in the section on Mobility before sending the approved budget to the governor for signature. Follow-Up Studies WSDOT has followed up on this benefit/cost-based prioriti- zation process to determine whether the safety performance results for centerline rumble strips has been effective. (One could also consider economic performance to be reflected in the before–after analysis of crash statistics, because changes in the frequencies of different accident severities underlay the benefit–cost calculation.) The results of this follow-up study could then inform any updates needed in WSDOT’s highway design guidance for centerline rumble strips. Find- ings and conclusions of this study were as follows (Olson et al. Mar. 2011, pp. ix–x): • The collisions of primary concern when installing cen- terline rumble strips are crashes with opposing traffic, either frontal (head-on) or sideswipes. The observed before–after results were a 44.6% reduction in All Injury Severities and a 48.6% reduction in Fatal & Serious (Disabling) Injury collisions. • In this study, this positive performance result held for all ranges of posted speed limits. No particular speed limit (or range of limits) detracted from the reduction in cross-centerline collisions. • This positive performance result held for all contributing causes to crashes except one: excess speed. An 18.5%

47 increase in Fatal & Serious Injury crashes occurred when speeding was a contributing cause. For all other contrib- uting causes, rates of both Fatal & Serious Injury crashes and All Injury Severities crashes declined following the installation of centerline rumble strips. • With respect to horizontal alignment: Cross-centerline collisions decreased by 59.0% on tangent sections and by 26.8% on curves after installing centerline rumble strips. On the curved sections that were studied, the Fatal & Serious Injury crashes that did occur were pri- marily the result of excess speed or to drivers impaired by alcohol or drugs. Also, there were differences in the resulting accident rates depending on whether the cross-centerline collisions occurred on the inside or the outside of the highway curve. • Centerline rumble strips were not anticipated to reduce the collision rates for run-off-the-road-to-the-right events, but they did: a 6.9% decline in All Injury Sever- ities crashes and a 19.5% reduction in Fatal & Serious Injury crashes. Although the research team found this result interesting, further investigation as to why this result occurred and how to explain it was judged to be beyond the scope of that study. • Conclusions: Centerline rumble strips “are an effective, low-cost, low-maintenance countermeasure that sig- nificantly reduces the frequency of collisions, regard- less of lane/shoulder width, posted speed limit, or any of the other geometric conditions examined.” To fur- ther the applications of this successful countermeasure, WSDOT planned to conduct a further study of noise aspects to determine where centerline rumble strips could be installed acceptably in residential areas. Based on the findings of this study, the research team rec- ommended that (1) WSDOT maintain its current guidance on reducing cross-centerline collisions; (2) WSDOT continue installing centerline rumble strips conforming to this guid- ance; and (3) from the analytic results, future priority might be given to locations with AADT less than 8,000, combined (one-directional) lane plus shoulder widths of 12 to 17 ft, and posted speeds of 45 to 55 mph (Olson et al. 2011). extension to Highway system planning Strategic View Reducing congestion is critical to Washington State’s people, economy, environment, and quality of life. “Moving Wash- ington” has been formulated as a strategic initiative compris- ing actions in three broad areas, all of which are needed to improve mobility in major transportation corridors (“Conges- tion” and “Moving Washington . . .” 2010). WSDOT execu- tives issue guidance to the planning process in terms of these focus areas: • Managing demand entails commuter travel options that promote greater efficiency by reducing the need to drive, particularly to drive alone. There are many possibili- ties, such as access to convenient bus service, carpool- ing and vanpooling, telecommuting, and flextime. Other measures include real-time traffic information displayed on variable message signs, which can influence traffic demand to shift to less congested routes. • Operating the highway system more efficiently by improving the functioning of existing roads. This approach includes measures that smooth traffic flow and remove impediments to flow more efficiently, as in responding to accidents. • Adding capacity strategically through informed invest- ment choices by focusing on the worst bottleneck loca- tions. WSDOT notes that such an approach can improve traffic flow on longer segments of highway while remain- ing within budget constraints. These strategies are part of the process incorporated in the production of the Highway System Plan. Identifying the most cost-effective options within these strategies and pro- ducing a balanced approach to congestion reduction require additional considerations before BCAs are addressed. The WSDOT office of CPDM introduces these additional con- siderations as screening criteria and by structuring a tiered, incremental approach to defining candidate solutions for fur- ther evaluation in the planning process. Screening and Structuring Potential Solutions The screening process recognizes that there is insufficient annual funding to achieve free-flow conditions on highways statewide. The goal is therefore to achieve maximum through- put on congested state highways: approximately 2,000 vehicles per hour, at speeds of 42–51 mph, or about 70% to 85% of the posted speed. At speeds below this threshold, the throughput decreases and the highway no longer operates efficiently. A key screen used by WSDOT for assessing mainline high- way congestion is to identify locations where peak-hour speed is less than 70% of the posted limit. This is the pri- mary criterion; others, related to bottlenecks, chokepoints, and congested corridors, are described in WSDOT’s High- way System Plan (2007–2026 Highway System Plan . . . Dec. 2007). Needs identification is accomplished in coor- dination with the appropriate MPOs or RTPOs. Proposed projects that meet these criteria are advanced to the next step in the planning process. Those that do not yet meet these screening criteria are held in the Highway System Plan database for future consideration should traffic condi- tions change on these segments or locations. Another mechanism used by WSDOT to guide project development toward effective and efficient solutions is to apply a tiered, incremental approach in defining projects. In this way, solutions that do not entail large capital expendi- tures are investigated first; and, new projects build on the improvements accomplished by previous projects, avoiding

48 wasted effort. The project tiers are at three levels (2007–2026 Highway System Plan . . . Dec. 2007, p. 70): • Tier I—low-cost projects with high return on capital investment and short delivery schedules; for example, incident management, ITS, access management, ramp modifications, turn lanes, and intersection improvements. • Tier II—moderate- to higher-cost improvements that reduce congestion on both highways and affected local roads; for example, improvements to parallel corri- dors (including local roads), auxiliary lanes, and direct- access ramps. • Tier III—highest-cost projects that yield corridor-wide benefits; for example, commuter rail, HOV/HOT lanes, additional general-purpose lanes, and interchange modifications. The incremental aspect of WSDOT’s planning process means that proposed mobility solutions in Tier I must be evaluated (unless they already exist on the highway segment under study) before Tier II solutions can be recommended. Proposed mobility solutions in Tier I and Tier II must be eval- uated (unless they already exist on the highway segment under study) before Tier III solutions can be recommended. evalua- tion of tiered solutions at this step entails an analysis of traffic impacts and performance improvement over 10 or 20 years. Further Evaluations for Inclusion in System Plan Once solutions at the appropriate tiers have been identified as candidates they are subjected to a BCA using the MP3 tool. Solutions with favorable benefit–cost results receive further review under additional criteria; for example, impact on cur- rent and future needs projections, the degree of improvement in traffic throughput, and the estimated number of years that the solution will last (in terms of throughput speed meet- ing or exceeding 70% of posted speed). Proposed solutions, refinements of concepts, and the BCA are conducted in coop- eration with cognizant MPOs and RTPOs. Those projects judged most favorable are entered in the Highway System Plan database and forwarded to headquarters executives for review and approval. Projects that are judged as not yet meet- ing criteria for selection are held in the Highway System Plan database for further future analysis (“2011–2030 Highway System Plan . . .” n.d.). Analytic Tools The MP3 workbook that was described for project program- ming is also used to evaluate Mobility solution benefits at the planning stage. Because projects have not yet been scoped, however, prepared cost estimates are not available. WSDOT has therefore developed a Planning Level Cost estimation tool to estimate costs for projects still at a conceptual level of development. It is based on historical unit price data for key highway construction cost factors, accounting for regional variations and differences in land use and development den- sity within a region. Input data describe the project in terms of characteristics and features of its right-of-way, mainline roadway, intersections and interchanges, crossroads, bridges, retaining walls, noise walls, wetlands, ITS features, and other items. Unit prices are applied to the quantity estimates for these items; assigned prices also account for regional location (Central Puget Sound, Vancouver, Spokane, other parts of the state) and density of local development (rural, suburban, urban, dense urban). Adjustments can be included for preliminary engineering, mobilization, construction engi- neering, traffic control, and other implementation items, as well as a separate adjustment for uncertainty (Murshed and McCorkhill 2008). resources needed and other Information The MP3 workbook and the Planning Level Cost estima- tion tool are the primary analytic tools for the BCA at the planning stage. The MP3 workbook and project scoping estimates provide benefit–cost data for project programming. IDAS (ITS Deployment Analysis System) software is used for ITS cost and benefit estimates. WSDOT also applies a number of other software packages for different types of traf- fic analyses depending on the complexity of the proposed solution (“Requirements for Proposed . . .” n.d.). WSDOT staff is conversant with economic methods, and apply the information and tools discussed throughout this summary for long-range and biennial planning updates, capi- tal programming, and budget development. The department makes use of academic and consulting experts for tasks such as research, business-process renewal, model/system devel- opment, and implementation assistance. For the most part, however, the department assumes responsibility for using these products once completed. brIDge projeCt programmIng anD permIttIng Introduction This case describes the methodology applied by Caltrans for bridge project programming, with significant influence on deci- sions exerted by permitting requirements. Caltrans applies the Pontis™ bridge management system (BMS) for conventional analyses of bridge preservation and mobility improvement, and for decision support in project prioritization. However, a number of critical, risk-related bridge needs are not addressed by a BMS and must be analyzed separately. Moreover, bridge projects in California are potentially subject to permitting requirements or right-of-way negotiations that, experience has shown, can extend several years beyond the time needed for project plan development. The Caltrans Bridge Manage- ment Office has therefore developed a unique and innovative

49 approach to evaluating bridge projects for inclusion in its State Highway Operation and Protection Program (SHOPP). This procedure entails the use of utility theory to capture the benefits of reducing risks of degraded bridge performance regarding scour, seismic events, and bridge-railing safety, in addition to benefits associated with meeting the preserva- tion and mobility needs. This computed value of utility is applied as the measure of benefit in a “benefit–cost analysis” (or, perhaps more accurately, a cost-effectiveness analysis structured as a B/C ratio). Cost-effectiveness is not, how- ever, the only decision variable to be considered. The time to obtain permit approval for these bridge projects, particu- larly in coastal regions and certain other situations, means that the programming decision must consider those projects that realistically can be expected to be ready for construction within a manageable time period. The following descriptions describe Caltrans’ analytic procedures for programming of bridge needs, and use of these results in decisions on bridge project recommendations. role of economic analysis in Highway Investment Background With an inventory of just under 13,000 state highway bridges and with bridge needs exceeding annual funding, Caltrans looks to make informed decisions in selecting the “best” projects for its bridge program. The California SHOPP identifies bridge preservation needs in five areas: (1) reha- bilitation and replacement owing to deterioration of bridge elements, (2) scour risk reduction, (3) seismic risk reduction, (4) bridge rail upgrade (a safety matter), and (5) mobility upgrades (raising and strengthening structures to accom- modate updated traffic volumes and vehicle characteristics). SHOPP lists funding commitments to selected projects through a 4-year programming period. California state law also requires a 10-year SHOPP plan that identifies uncon- strained needs across all transportation assets. Although BMS analyses, which include economic as well as technical modeling, can address needs for preservation (rehabilitation or replacement) owing to condition-based deterioration of bridge elements and for mobility upgrades, they do not deal effectively with risk-related problems: seismic, scour, and bridge-rail safety. These risk-based needs, which account for about 40% of the total SHOPP bridge-related amount, require different analytic procedures. Caltrans has turned to multi-objective utility theory to represent the benefits of addressing the five categories of bridge needs, with initial application of the procedure to the 2008 SHOPP develop- ment (Johnson 2008). Multi-Objective Utility Model A dimensionless, multi-objective, zero-to-one utility func- tion represents the contributions of several factors relevant to programming decisions. Moreover, the factors can be weighted to reflect their relative importance. The general utility relationship is given in eq. 1 (Johnson 2008). U a b X a b X a b X a b X a b X a b t i i i= = + + + + Σ 1 1 1 2 2 2 3 3 3 4 4 4 5 5X5 1( ) where: Ut = total project utility, zero to one; S = sum for all i = 1 to 5; ai = indicator that attribute i is addressed (1 = yes, 0 = no), i = 1 to 5 denoting each category of bridge needs; bi = weighting factor for attribute i; sum of all weighting factors = 1.0; Xi = value function of attribute i contributing to the utility function, where: X1 = value function for bridge rehabilitation or replacement; X2 = value function for scour risk mitigation; X3 = value function for bridge rail upgrade; X4 = value function for seismic risk mitigation; and X5 = value function for bridge mobility improve- ment (strengthening and raising clearances). Example for Scour The individual value functions Xi are themselves relation- ships containing dependent and independent variables, coef- ficients, and functions. For example, in terms of the National Bridge Inventory (NBI) rating items, the scour-related con- tribution to utility (i.e., the value function X2) is formulated using the NBI scour item (Item 113), the average daily traffic (ADT, Item 029), and detour length (DL, Item 019) (Record- ing and Coding Guide . . . Dec. 1995). Ratings of condition within the NBI are assigned on a 0 to 9 scale, where 9 denotes “undamaged” or “not subject to risk,” 3 denotes “critical,” and 0 denotes “bridge failed, out of service.” As an example, consider the scour value function X2, with a form expressed in eq. 2. This function is graphed in Figure 2 versus the NBI scour rating code SC, with values of traffic ADT and detour length DL held constant. The value-function results are inter- preted as follows (Johnson 2008, pp. 191–192): • When SC = 8, the bridge foundation is “stable” and the scour risk is essentially zero. A project that addresses scour would therefore provide no real benefit in terms of scour risk mitigation. (An NBI rating of 9 for this item would denote a bridge foundation on dry land, well above flood water elevation, and is not represented in the value function.) • As the scour risk increases (i.e., as SC moves toward the “critical” threshold where the scour rating would equal 3), the scour value function likewise increases and at SC = 3 it exceeds 0.75. Projects that mitigate scour risk now are in a range to contribute substantial potential benefit to the utility function.

50 X SC ADT DL 2 1 1 4 8 0 000001 = + − − + −( ) + ∗ ∗    exp .     ( )2 where: X2 = the value function for scour risk mitigation; SC = the NBI scour rating code, Item 113, for a bridge; ADT = the average daily traffic, NBI rating Item 029; and DL = the detour length around the bridge, miles, rating Item 019. Generalized Value Functions for Bridges To generalize the scour example to the other utility attributes (i.e., the other categories of bridge needs), all of the value functions are expressed as a logit, or “S-shaped,” function given in general form in eq. 3 (Robert and Vlahos 2007, cited by Johnson 2008, p. 191). The specific relationships governing the value functions of all categories of bridge needs are shown in Table 10, together with explanations of parameters and the values of assigned weights. In developing these relationships and weights, Caltrans bridge engineers 0 0.2 0.4 0.6 0.8 1 0 1 2 3 4 5 6 7 8 9 NBI Scour Code Va lu e: D eg re e o f S co ur R is k M iti ga tio n FIGURE 2 Example value function for scour risk mitigation, X2. Attribute = Category of Bridge Need Key Para me ters Expression for C ( i ) in Eq. 3 Assigned Weight i = 1: Rehabilitation and replacem ent needs BHI Bridge Health Index BHI Change in BHI Due to Project TEV Total Element Value in Bridge ADT Average Daily Traffic DL Detour Length Around Bridge RU Repair Urgency 2.5 + 0.000001[(100 BHI BHI ) * TE V ]/100 + 0.00000001 * AD T * DL + 0.5 * (10 RU) 25% i = 2: Scour needs SC NBI Scour Code ADT Average Daily Traffic DL Detour Length Around Bridge 4 + (8 SC ) + 0.000001 * ADT * DL 20% i = 3: Bridge-rail upgrade needs RS Caltrans Bridge–Rail Upgrade Score 2 + RS 10% i = 4: Seismic retrofit needs Sv Caltrans Seismic Priority ADT Average Daily Traffic DL Detour Length Around Bridge 1.5 + Sv + 0.000001 * ADT * DL 25% i = 5: Mobility needs (raising/ strengthening) PIB Pontis Improvement Benefit 4.5 + 0.00015 * PIB 20% Source: Johnson (2008), Tables 1 and 2. Note: Author has changed some variable names slightly to increase comprehension. TABLe 10 CALTRANS VALUe-FUNCTION eLeMeNTS FOR FIVe CATeGORIeS OF BRIDGe NeeDS

51 sought to incorporate the set of key decision variables, draw on readily available bridge condition and rating information, and predict individual bridge-needs benefit values (Xi) and overall project utility (Ut) that would reflect the judgments of experienced bridge engineers. Trial use of the methodology and sensitivity analyses confirmed that individual value func- tions and total improvements in utility correlated highly with project priorities that would have been assigned by experi- enced bridge engineers. The utility approach that is based on eq. 1 has enabled Caltrans to analyze the programming of bridge projects across the diverse categories of bridge needs simultaneously, and to reflect the overall benefit of a project within a single utility value Ut (Johnson 2008, pp. 191–194). X C ii = + − ( )( ) 1 1 3exp ( ) where: Xi = the value function for attribute i, i = 1 to 5: that is, the value function for each category of bridge needs (refer to eq. 1); exp = the exponential function; C(i) = exponent for each attribute i, given in Table 10 (note that the negative of this value must be used in eq. 3). Values of these parameters are obtained from one of the following sources: NBI bridge ratings conducted by Caltrans according to the NBI Coding Guide (Recording and Coding Guide . . . Dec. 1995); departmental calculations of factors such as the BHI (Shepard and Johnson 2001), seismic retrofit priority Sv, and bridge rail upgrade score RS; the improvement- related benefit of projects, Pontis Improvement Benefit, as analyzed by the Pontis BMS used by Caltrans (technical refer- ence: Cambridge Systematics, Inc. 2005); and the Total ele- ment Value (TeV) of a bridge as defined in Caltrans’ bridge health index (BHI) formulas (Shepard and Johnson 2001), computed by Pontis as documented in its technical reference (Cambridge Systematics, Inc. 2005). An additional use of the TeV is explained in the following section. methods and measures Adjustment for Project Scale In applying the utility concept as a generalized measure of benefit for comparison to cost Caltrans realized one other adjustment was needed. The cost of a bridge project is influ- enced by many factors, but an important one is the scale or magnitude of the project, which is related to the size or value of the existing bridge. Given this dependence of cost on bridge scale, it was necessary to compensate on the ben- efit side to provide a fair assessment of benefit (or utility) to cost, bearing in mind that the utility is a dimensionless, zero-to-one number that does not retain any information on project scale. (This discussion applies to risk mitigation, but not necessarily to bridge rehabilitation work. Although risk mitigation is blind to bridge size, bridge rehabilitation considerations by Caltrans make use of a BHI, which does account for the relative size of the structure.) Among sev- eral possibilities for accounting for bridge scale, Caltrans selected the TeV parameter described in Table 10. The final measure of “benefit–cost,” or measure of cost-effectiveness structured such as a benefit–cost ratio, is given in eq. 4. Project Utility B C ratio Project_Cost= ∗U TEVt ( )4 where all benefits variables are as defined earlier, and Project_ Cost is the cost of the proposed project developed by Caltrans’ Office of Specialty Investigations & Bridge Management as part of its SHOPP program building. Illustration of Utility as a Benefit Measure for Bridges A simple arithmetic example illustrates how the Ut benefit measure operates to distinguish relative benefits of proj- ects on different bridges, a key step in project programming (Johnson 2008, p. 193). The example includes both a condi- tion-related need (rehabilitation and replacement) and a risk- related need (mitigation of scour-related risk); a combination that Caltrans believes demonstrates the power of the util- ity concept. Consider two bridges with similar structures but with different combinations of condition and scour needs, as shown in Table 11. Assume two projects for bridges A and B, respectively that address both condition and scour needs. • Bridge A has ratings that indicate a condition-related value (X1) of 0.20. Its NBI scour rating is 8, which denotes no scour (X2 = 0; refer to Figure 2). The con- tribution of these values to the project utility computed for Bridge A is shown in the last column of Table 11 to be 0.05, using the weights for condition and scour in Table 10. Structure Condition Value, X 1 NBI Rating of Scour Risk (Item 113) Scour Value, X 2 Contribution to Utility U t (weighted sum of X 1 and X 2 ) Bridge A 0.20 8: no scour 0.0 0.25 * 0.20 + 0.20 * 0.0 = 0.05 Bridge B 0.20 3: scour is critical 0.75 0.25 * 0.20 + 0.20 * 0.75 = 0.20 TABLe 11 exAMPLe OF THe UTILITY CONCePT APPLIeD TO TWO BRIDGeS

52 • Bridge B also has ratings that indicate a condition value X1 = 0.20. Its NBI scour rating however is 3 (critical), which corresponds to a scour value X2 of 0.75 (Fig- ure 2). The contribution of these values to the utility of the project for Bridge B is 0.20, or four times the benefit value for Bridge A. The Caltrans Bridge Management Office has applied the set of value functions and weights to every state-owned bridge in the BMS, together with estimated project costs. Those bridges with the highest utility–cost ratios (eq. 4) were evaluated for possible inclusion in the SHOPP program. This exercise showed that the approach can be used successfully for an inventory of bridges of different size, material, and composition. Possible Future Modifications Caltrans noted a simplifying assumption in this initial develop- ment of a utility approach. It was assumed that the post-project condition and risk value functions would all be restored to an undamaged (“like new”) or no-risk state. This assumption was justified partly by a tenet of the SHOPP program: all needs should be addressed when a SHOPP project is undertaken. A possible future refinement is to reflect the relative effectiveness of different bridge treatments, in which the post-project value functions do not automatically assume complete correction of damage or complete removal of risk. (Although not discussed in the Caltrans paper, this refinement could also be a first step to representing a time dimension more explicitly within the total utility result.) Decision support A multi-step process is used to evaluate candidate bridge projects for SHOPP and to build a prioritized program, a process comprising the following steps: • A bridge inspection or an analysis of the bridge identi- fies bridge needs. • For bridge replacement needs or for needs that exceed a certain cost threshold, a peer review is required by internal Caltrans policy. The peer review, conducted by Structure Maintenance & Investigations personnel, documents the following: current issues with the bridge structure and materials performance, alternatives con- sidered for solving the problems, LCCAs that have been performed to compare these alternatives, and notes of remaining concerns. • The result of the peer review is a recommended strategy to deal with the identified problems on the bridge, orga- nized within a project. • A utility function is developed for each competing bridge need or proposed project, formulated as described in the previous section. A utility–cost ratio is computed (eq. 4). • The utility–cost ratios are used to create an initial order- ing of bridge priorities for purposes of planning. • More complete project data are developed in project study reports. These data are evaluated to further assess the project’s priority and its likelihood of being deliv- ered on schedule. • Depending on the result of this assessment, funds may be allocated to the project. Alternately, the project may be developed further without additional funding alloca- tion, until its likelihood of timely delivery improves. This issue of project delivery is a significant one for Cal- trans regarding bridge projects generally, and especially those projects in coastal zones or sensitive environmental areas, and those projects involving historic bridges. Internal Caltrans reviews have shown that (1) bridge projects are much more likely to require substantial environmental study than are highway projects generally; (2) the time needed to complete an environmental review for bridge projects averages 4 years for a Finding of No Significant Impact, and 8 years for an environmental Impact Study—both of which exceed the 4-year time frame of a given SHOPP pro- gram document; (3) the time needed to complete an envi- ronmental review for bridge projects is longest for bridges requiring Coastal Zone Conservation clearances, regardless of the type of environmental document required; for exam- ple, the average time to complete an environment Impact Study in this case is almost 11 years; and (4) the type of bridge work and its setting (e.g., whether over water) also affect the environmental clearance time—bridge widen- ing and bridge replacement projects are typically the most problematic. resources required and other Information Resources • Application of the utility-based approach to program- ming is performed by Caltrans staff. • Consultants assisted in developing the initial concepts and models. • The analytic tools needed are relatively simple; value- function calculations and their contributions to total utility can be handled in spreadsheet workbooks. • Data of the required currency, accuracy, and timeliness are generated through the federally mandated biennial bridge inspection program, the peer reviews that are conducted for certain bridge projects, and routine activi- ties performed as part of the programming process, such as preparation of cost estimates. • Caltrans has been a leader in promoting eeA within a wide range of departmental activities and analyses. Members of the department’s bridge unit served on the state-user advisory panel that assisted in the original development of the Pontis BMS. The agency has also developed detailed BCA products, the Cal-B/C series, for use at a project, corridor, or network level. Cal-B/C is applied in a later case example on Value Analysis (Caltrans’ implementation of Ve).

53 • Caltrans has an extensive organizational commitment and website resources dedicated to a wide range of top- ics in eeA. Among these topics are LCCA and BCA, supported by drill-down details on individual website pages to address each step of an analytic procedure and to explain the application of the correct method to par- ticular cases or situations. There is strong integration of economic concepts and methods within a number of Caltrans business processes, buttressed by comprehen- sive and detailed documentation. eConomICs-baseD traDeoff analysIs Introduction In its consideration of asset management systems for trans- portation infrastructure, the New York State DOT (NYSDOT) has sought to articulate the distinctive aspects of an “asset management approach” as compared with that of traditional infrastructure management systems. Several precepts that distinguish asset management have been identified to guide system design and development. A core capability in this approach is the conduct of tradeoff analyses among four major departmental programs or “goal areas”: pavements, bridges, safety, and mobility. To address a well-known stumbling block in analyzing such tradeoffs—the need for a common measure of benefit across different programs or projects—NYSDOT has looked to an economics-based measure, excess road user costs. Based on this concept, a prototype tradeoff analysis has been developed. Although this experimental procedure has not yet been implemented on an operational basis, it has been included in these case examples to illustrate a unique and inno- vative application of eeA. Within the framework established for this synthesis, this case example addresses programming or resource allocation at the highway corridor and network levels, affecting investments across multiple programs. role of economic analysis in Highway Investment This case example of a tradeoff analysis prototype is drawn from materials prepared by NYSDOT asset management staff: a paper published through TRB (Shufon and Adams 2003) and a slide presentation at the Fifth National Transportation Asset Management Workshop (Adams 2003). Summary informa- tion on this presentation in the context of other workshop dis- cussions is given in the workshop proceedings (Wittwer et al. 2004). Further background information on the NYSDOT trad- eoff analysis concept has been compiled by FHWA in its asset management case study series (“economics in Asset Manage- ment: The New York experience” 2003). Asset Management Framework In their consideration of the distinguishing features of asset management that could provide value-added information and insights, NYSDOT managers realized the following (Shufon and Adams 2003): • Traditional management approaches were organized vertically within each program or goal area (pavement management, bridge management, safety management, mobility or congestion management). These vertical per- spectives, often referred to as “stovepipes” or “silos,” enabled basic infrastructure data (e.g., inventory, cur- rent and historical condition, and performance) to be transformed into information useful to various business processes at different organizational levels: identification of investment needs, planning, programming, budget- ing, and so forth. • To provide additional benefits, an asset management system needed to go beyond these capabilities of exist- ing or legacy management systems; for example, an updated system architecture, advances in data collec- tion techniques, improved database design, or other advances that enabled better decisions based on bet- ter information. Lacking any beneficial contribution, “asset management systems” would simply represent the “buzzwords du jour.” • Although a vertical perspective on infrastructure man- agement processes was still needed, asset management also called for a horizontal consideration across programs or goal areas. This view would enable managers to con- sider multiple assets and the tradeoffs inherent in balanc- ing investment choices among them. A tradeoff analysis would integrate highway infrastructure decisions and provide a greater benefit to users. (Multimodal tradeoffs have also been addressed in the asset management litera- ture, but are not the focus of this synthesis.) These perspectives led NYSDOT managers to articulate the contributions of an asset management system within the following four precepts: [1] Asset management systems are decision support systems. They do not make decisions; people make decisions. The busi- ness foundation must be in place to support decision making. [2] It would be virtually impossible to cover all assets owned or administered by a transportation agency. Assets should be covered only by the umbrella asset management system in which trade-offs make sense. For example, it makes little sense to develop procedures for trade-off analysis between investment in pavement preventive maintenance and investment in specialized transit services for the handicapped. In addition, the individual or “silo” management system should be already operational for the asset to be covered by the umbrella system. Otherwise, costs for the inventory, condition assessment, and so forth, would be prohibitive. [3] Trade-off analysis can be conducted only if a common technical measure can be used to quantify benefits of diverse proj- ects: for example, a pavement project versus a mobility project. [4] Generally, these analysis methods involve an economic analysis of competing alternatives. Source: Shufon and Adams 2003, p. 38. Common Measures for Diverse Projects: Excess Road User Costs The third and fourth precepts underlay the application of eeA to tradeoff analyses. The commensurate measures selected by

54 NYSDOT managers were the excess road user costs associ- ated, respectively, with each of the department’s goal areas (or programs). These excess costs were defined as “incremental costs incurred by [highway] users . . . attributed to less than ideal operating conditions” (Shufon and Adams 2003, p. 40). excess user costs comprised three components: the cost of delays to travelers and freight, accident or crash costs, and VOC. examples of excess road user costs resulting from less than ideal conditions are the cost of additional tire wear because of rough pavement, the additional trip length (affect- ing both travel-time cost and vehicle operating expenses) imposed on truck travel owing to a posted bridge, and the cost of an accident that might have been prevented with an improved highway feature. Another way to view these costs is to regard them as “avoidable” costs, which provides the basis for treating them as the benefits of pavement, bridge, or safety-related road improvement projects. The treatment of excess user costs in each goal area is as follows (Shufon and Adams 2003, p. 40). Pavement-Related Excess User Costs Pavement-related road user costs are related by NYSDOT to the International Roughness Index (IRI). A threshold value of acceptable IRI can be established; the additional road user costs incident to higher IRI values would constitute excess user costs. The department had engaged Cornell University researchers to advise on specific analytic relationships; their recommen- dation was to adapt pavement management models that had been developed by Saskatchewan. NYSDOT’s application of these models quantified the pavement roughness effects on various components of road user costs: fuel, tire, and vehicle parts consumption; labor cost for vehicle repair; delays and diversion of traffic; and damage to cargo. Of these, NYSDOT found that the roughness-related excess user costs for fuel consumption, cargo damage, and delays or diversion were negligible and safely ignored in network analyses of the state-maintained highways. It was recognized that these results might not hold for local roads or other nonstate networks, where IRI values might be higher than on state highways. Bridge-Related Excess User Costs excess user costs related to bridges include detour costs (entailing travel time and vehicle operation) borne by truck traffic resulting from inadequate bridge and approach clearances and load postings, and acci- dent costs resulting from deficient bridge and approach geo- metry. NYSDOT staff identified sources of information on these relationships; for example, PONTIS (a software app- lication developed to assist in managing highway bridges and other structures) and research by Florida DOT (FDOT). The department adapted the FDOT models for its bridge-related excess user cost calculation. Safety-Related Excess User Costs excess user costs result- ing from accidents are derived from concentrations of crash locations, to which roadway characteristics can be a contri- buting cause. NYSDOT’s system for tracking accidents can identify High Accident Locations (HALs), which com- prise Priority Investigation Locations and Safety-Deficient Locations. • Priority Investigation Locations are highway locations at which the accident rate is more than three standard deviations higher than the mean rate for the comparable class of highway. • Safety-Deficient Locations are highway locations at which the accident rate is one to three standard deviations higher than the comparable mean rate. The excess user cost associated with HALs is computed as the product of the difference between the accident rate at each high-accident location and the comparable mean rate, and the average cost per accident obtained from NYSDOT accident data tables. Mobility-Related Excess User Costs excess user costs related to mobility—that is, congestion costs—arise from both recurring congestion problems and from individual high- way incidents. New York State defines congestion as “delay to persons and goods beyond a limit that can be tolerated”— quantitatively, the boundary between Levels of Service D and e. NYSDOT’s Congestion Needs Assessment Model can identify congested locations and calculate excess user costs as a function of vehicle hours of delay for both auto passengers and freight. However, NYSDOT has for the time being focused the tradeoff exercise on only the freight portion of these costs. (Computation of passenger values of time is beset by several analytic issues and motorist behavioral assumptions. Delays to freight are currently believed to be more clearly defined and supported analytically, and are more consistent with NYSDOT’s current priorities and decision- making practices.) methods and measures Highway System Levels for Computing Excess User Costs For each goal area of pavement, bridge, safety, and mobility, NYSDOT computes and assembles the measures of excess road user cost at three highway-system levels: 1. Individual asset: pavement segment, bridge structure, safety-deficient location, and mobility location. 2. Analysis link: length of highway between major inter- sections, comprising some portion of the individual assets discussed earlier. 3. Corridor: a highway route within a county, comprising some portion of the analysis links discussed earlier. New York State’s highway system consists of a total of 15,000 centerline-miles or 40,000 lane-miles. This system contains approximately 7,000 analysis links and 1,500 corridors.

55 Tradeoff Measures Measures used in the tradeoff analysis are structured as a benefit–cost ratio. • Benefits are defined as reductions in excess road user costs that are attributable to a corrective project. They are excess user costs that are now avoided. These ben- efits are computed as an annual figure. • Costs are agency expenditures for the project. To con- vert costs to an annual basis, the project expenditures are multiplied by a capital recovery factor as a function of the service life of the project and the current depart- mental discount rate. • The benefit–cost ratio is computed using the annual benefit divided by the annualized cost. This computa- tion is performed at the asset, link, and corridor levels described in the previous section. prototyping Decision support Because the NYSDOT research was confined to a prototyp- ing stage, examples of actual decision support are not avail- able. However, departmental staff developed reports that illustrate the type of information that could be made avail- able to decision makers needing a better understanding of investment tradeoffs. Two example reports for a hypothetical highway corridor are shown in Tables 12 and 13: • Table 12 displays information on excess user costs esti- mated for each goal area by link in the corridor. In addi- tion to total excess user costs among all goal areas, it includes an estimate of “base” user costs; that is, costs that are not considered “excess.” The ratio of excess to base user costs in the rightmost column is an indication of the excess-user-cost “tax” borne by each motorist because of deficiencies in key highway assets in this corridor. • Table 13 displays the corridor benefit–cost information that would be computed as described in the previous sec- tion. The benefit–cost ratios are viewed by NYSDOT as indicators suggesting potential candidates for program investments, warranting further investigation and analy- sis. It is also the view of NYSDOT staff that “the power of the [benefit–cost] approach is the capability to assess the investment potential for groups of diverse assets taken together, such as links and corridors” (Shufon and Adams 2003, p. 44). Tables 12 and 13 can be analyzed vertically or horizon- tally. Vertical comparisons consider potential investments within a program; horizontal comparisons, among programs. NYSDOT personnel also envisioned that results shown in these two tables could be displayed not only by the aggre- gations of assets shown (individual asset, link, and cor- ridor), but also by other delineations; for example, route, county, functional classification, traffic-volume groupings, or other available parameters. economic and demographic data would also accompany these analyses, allowing sum- maries to be prepared, for example, for areas suffering low economic growth, where reduction of excess transportation user costs could be targeted to improve the local economy. resources required and other Information Implementation Issues and Challenges Given its status as a prototyping exercise, this case example has not yet developed a track record of resources to be applied in conducting actual tradeoff analyses. Suffice it to say that the proposed analysis, intended as part of NYSDOT’s asset management system for its transportation infrastructure, is Analy sis Link EU C Pavement EU C Bridge EU C Safety EU C Mobility Total EUC for Link Est. Base User Cost Excess/Base User Cost L1 50 — 100 — 150 7,000 2.1% L2 40 40 — — 80 6,000 1.3% L3 — 30 — 20 50 3,000 1.7% L4 — 80 40 30 150 10,000 1.5% L5 120 100 50 100 370 10,000 3.7% L6 90 — 60 110 260 10,000 2.6% Corridor Totals 300 250 250 260 1,060 46,000 2.3% Source: Shufon and Adams (2003), Figure 6, p. 42. Notes: EUC = Excess [Highway] User Costs. — = no excess user costs assumed to occur. TABLe 12 exAMPLe exCeSS-USeR-COST OUTPUT FOR A CORRIDOR ($000S)

Pavement Bridge Safety Mobility Link Totals Analysis Link Annual EUC Avoided Annual- ized Project Cost Bene- fit– Cost Ratio Annual EUC Avoided Annual- ized Project Cost Bene- fit– Cost Ratio Annual EUC Avoided Annual- ized Project Cost Bene- fit– Cost Ratio Annual EUC Avoided Annual- ized Project Cost Bene- fit– Cost Ratio Annual EUC Avoided Annual- ized Project Cost Bene- fit– Cost Ratio L1 50 40 1.2 — — — 100 50 2.0 — — — 150 90 1.7 L2 40 60 0.7 40 20 2.0 — — — — — — 80 80 1.0 L3 — — — 30 50 0.6 — — — 20 100 0.2 50 150 0.3 L4 — — — 80 60 1.3 40 40 1.0 30 20 1.5 150 120 1.3 L5 120 200 0.6 100 80 1.3 50 50 1.0 100 200 0.5 370 530 0.7 L6 90 50 1.8 — — — 60 110 0.5 110 100 1.1 260 260 1.0 Corridor Totals 300 350 0.8 250 210 1.2 250 250 1.0 260 420 0.6 1,060 1,230 0.9 Source: Shufon and Adams (2003), Figure 7, p. 43. Notes: EUC = Excess [Highway] User Costs. — = no excess user costs assumed to occur. TABLe 13 SAMPLe BeNeFIT–COST OUTPUT FOR A CORRIDOR (COSTS ANNUALLY IN $000S)

57 supported by a number of individual management systems and data collection, processing, and analysis activities. The analysis has been conceived by NYSDOT asset manage- ment personnel, with the support of university and industry research in the development of component models of asset performance. The NYSDOT researchers did, however, identify issues that they perceived would be challenges in bringing the tradeoff analysis to actual practice (Shufon and Adams 2003, p. 44): • The first issue is the availability of realistic agency costs to reduce or eliminate excess road user costs. Pavement and bridge costs are available from pavement manage- ment and bridge management systems, respectively. These systems include decision-support algorithms that seek to identify the preferred treatment to address defi- cient conditions and performance. However, the same is not true for safety and mobility. There is a range of safety and mobility actions to address highway sections exhibiting similar performance (e.g., numbers of HALs or vehicle hours of delay). Specifying preferred treat- ments within an investment tradeoff analysis, prior to detailed studies of specific site conditions and factors, is complicated. NYSDOT is studying the issue to see if average costs of safety and mobility actions can be estimated for use in the denominator of the B/C calculation. • The second issue concerns the use of avoided excess highway-user costs as the measure of benefits to com- pare the worth of projects across diverse programs. “Base costs” and “excess costs” imply a threshold value dividing the two categories; this threshold must be chosen with care. For example, too low a value for a particular program would encourage overinvestment in that program. To counter this tendency, the NYSDOT researchers recommended that the asset management sys- tem recommendations, including the tradeoff results, be reviewed by, and calibrated to, “the professional experience of a panel of experts who are responsible for regional program development.” These results would then be “presented to NYSDOT executive management for policy guidance.” • The third issue deals with the scope of the proposed analysis, which is at a highway system or network level, and is based on relative performance (avoided excess user costs) rather than asset condition specifically (e.g., pavement, bridge, safety, or operations needs or deficiencies). The implication is that there is still an important need for management systems that address individual assets; for example, pavement management and bridge management systems. The tradeoff analy- sis relies on these systems for recommended treatment actions and costs, as discussed earlier. Furthermore, these individual asset systems analyze options that are not considered in the tradeoff approach proposed earlier. – For example, the tradeoff analysis does not consider preventive maintenance policies that could lengthen life expectancy of pavements now in smooth con- dition (and which therefore have not yet triggered excess user costs). – Nor does the tradeoff analysis consider the penal- ties of deferred maintenance in terms of the addi- tional future agency cost that will be incurred, for example, by delaying correction of bridge structural deficiencies. Notwithstanding these limitations, the tradeoff analysis is viewed realistically as an additional decision-support tool that provides comparative information horizontally across highway investment programs as well as vertically within them. As a component of an asset management system, it complements, but does not replace, information available from current systems that manage individual assets. pavement type seleCtIon Introduction The use of LCCA for pavement type selection appears to be one of the more widespread uses of engineering economic methods in the United States, as shown by surveys (including the results obtained for this synthesis) that are presented in chapter two. A case example of this application of economic methods thus helps to identify the characteristics of LCCA use across the United State. Results from recent surveys at a broad level will be used to illustrate nationwide patterns as well as the diversity in selection of key parameters such as discount rate. Discussions will then focus on two particular state DOTs to identify specific policies, methods, and other characteristics of LCCA use. Within the framework of this synthesis, these LCCA applications relate to project-level design and development. role of economic analysis in Highway Investment Pavement-Oriented Federal Guidance The FHWA has issued several guidance documents on the use of LCCA in pavement design and type selection, invest- ment analyses of investments at other stages of the pavement life cycle, and for related purposes such as alternate bidding. For purposes of this case example, the relevant guidance is included in the FHWA’s Final Policy Statement (“LCCA Final Policy Statement” Aug. 29, 1996). Information on the engineering aspects of pavement design and performance and how they can be incorporated within life-cycle analyses is given in the FHWA’s Technical Bulletin on the subject (Life Cycle Cost Analysis . . . Sep. 1998). Through its Final Policy Statement, FHWA supports and encourages the use of LCCA to analyze investment alternatives for pavement design, and outlines principles of good practice that might

58 be followed regardless of the methodology used. Among these principles are the following (“LCCA Final Policy Statement” Aug. 29, 1996): • Life-cycle costs should be considered in all phases of a pavement’s life cycle: construction, maintenance, reha- bilitation, and operation. • Analysis periods should be long enough to capture long-term differences in discounted costs among com- peting alternatives and rehabilitation strategies. These periods should encompass several maintenance and rehabilitation cycles, and for some pavement designs may include reconstruction as well. • All significant differences in agency and user costs bet- ween alternatives should be considered in the analysis. • Considerable uncertainties in key aspects of the analy- sis should be recognized and addressed through quan- titative and qualitative assessments such as sensitivity analysis, probabilistic techniques or risk analysis, expert panels, or other mechanisms. • Streams of agency and user costs through the analysis period should be discounted to net present value (or converted to equivalent uniform annual cost) using dis- count rates that are consistent with OMB Circular A-94. In a subsequent clarification of FHWA policy regarding alternate pavement type bidding, FHWA noted that “discount rates should be consistent with OMB Circular A-94” and that “The trend over the past 10 years indicates a [real] discount rate in the range of 2 to 4 percent is reasonable.” The FHWA guidance also requires that any price adjustments used in comparing alternate pavement types during bid evaluation must be approved under Special experimental Project #14, commonly referred to as SeP-14 (Stephanos Nov. 13, 2008). The FHWA has produced a software package, RealCost, as a spreadsheet workbook that conducts LCCAs of pave- ment alternatives at the project level (RealCost User Manual May 2004). A number of state DOTs employ RealCost in analyzing pavement type-selection options. State DOT Guidance As state DOT examples, California and Colorado have issued guidance documents addressing LCCA use for pave- ment investment analyses. • Caltrans has issued a policy statement directing the use of LCCA for most projects involving pavement work on the state highway system, regardless of funding source (exceptions are noted in the policy document). Corresponding changes have been made to the agency’s design manual and project development manual (Land Mar. 7, 2007). Procedures for conducting pavement project analyses within Caltrans, using FHWA’s Real- Cost software, are outlined in a Caltrans procedures manual (Life-Cycle Cost Analysis Procedures Manual Nov. 2007). Concurrently with this synthesis proj- ect, Caltrans is involved in NCHRP Synthesis 42-08 to investigate full-scale accelerated pavement testing (APT). The APT-related synthesis includes consider- ation of the economic costs and benefits of full-scale APT research, using the methods and criteria described in chapter two of this report (Steyn 2012). • The Colorado DOT (CDOT) issues its guidance in the form of procedural reports. CDOT’s history of written procedures for LCCA goes back to 1972. Although the original process remains essentially in place, it has been updated several times in the intervening years, with the latest update coming in 2009 (Harris 2009). CDOT also uses RealCost to conduct a probabilistic LCCA, primarily to compare alternatives in asphalt and con- crete pavements. methods and measures In 2005–2006 a two-staged survey was conducted by Clem- son University for the South Carolina DOT (SCDOT) on the use of LCCA for pavement type selection (Rangaraju et al. 2008). These findings are noteworthy because they provide an indication of agency practices in LCCA nationwide. Sev- eral of the findings below report data from the Stage 1 sur- vey, which elicited 35 responses. Among the findings of this survey were the following, focusing on the economic dimen- sion of the responses: • Thirty-two of 35 agencies, or 91%, reported that they use LCCA as part of the decision process for selecting pavement type. • Fifteen agencies (47%) reported using specialized soft- ware for LCCA; for example, RealCost and Darwin (an AASHTOWare product). • Thirteen agencies (41%) include user costs in their analyses; 19 (59%) reported that they do not. • The responses indicated a distribution of lengths of analysis period used in LCCA. Among 27 respondents, 4% used 20 to 29 years; 30% used 30 to 39 years; 40% used 40 to 49 years; and 26% used 50 to 59 years. • There were also considerable ranges of values in the initial performance lives of flexible and rigid pave- ments. Flexible pavements elicited responses extending from 10 to 14 years to 30 to 34 years. Rigid pavement responses extended from 15 to 19 years to 35 to 40 years. Recommended values by CDOT and Caltrans fall within the ranges of values cited earlier for each parameter, but exhibit the individual differences in practice between the agencies. For example, regarding lengths of the recommended analysis period, CDOT now recommends 40 years, whereas Caltrans recommends a range of values from 20 years to 55 years that depends on the respective alternatives being compared. The rationale of the two agencies in their selection of discount rate

59 is also interesting to compare. Although both agencies arrive at a rate that conforms to FHWA guidance, they arrive at their recommendation in different ways. • Caltrans considered the national data supporting a dis- count rate that was reported in OMB Circular A-94, and decided to compare those data with local experi- ence. It considered returns to the state’s Pooled Money Investment Account, a repository for surplus state cash, and found real returns for the past 20 and 30 years of 2.8% and 3.2%, respectively. Although the California data were backward-looking and the OMB data (OMB Circular A-94, Appendix C) are forward-looking, both suggested a real discount rate of 3%. The Caltrans team, which was considering changing the discount rate in its Cal-B/C benefit–cost program, was uncomfortable with a significant reduction from 5% (the former dis- count rate in Cal-B/C) to the proposed 3%, and opted instead for the compromise value of 4%. This rate is the Caltrans default value for all its BCAs. The Cal- trans team recommended that future changes to the Cal- B/C discount rate be based on the OMB Circular A-94 Appendix C data directly, which are readily available and updated annually (System Metrics Group, Inc. et al. Feb. 2009, pp. III-2–III-5). • CDOT recently updated its approach to setting a dis- count rate. The approach is based on the 10-year mov- ing average of the 30-year Real Treasury interest rates reported in OMB Circular A-94, Appendix C. This computation reflects, in CDOT’s view, a stable estimate of interest rates corresponding to the most conserva- tive, longest maturity investment strategy—a criterion appropriate to the assumption of a 40-year analysis period. When CDOT uses the 10-year moving aver- age, the analysis covers a span of 20 years of averages, smoothing out the fluctuations. even so, each year has a slight change in the computed interest rate. Because CDOT’s intent is to use a stable, no changing yearly rate, an additional check is performed: to compare the current CDOT discount rate with the 10-year moving average plus or minus two standard deviations. Only if the interest rate changes more than two standard deviations from the current CDOT rate will a new dis- count rate be determined. This comparison is checked annually. For 2008 data, CDOT computed the 10-year moving average for 1999–2008 as 3.3%, which is the recommended discount rate (Harris 2009, pp. 5–8). For 2010, the discount rate remained at 3.3%. Decision support FHWA and the state DOTs recognize that precise cost esti- mates and precise knowledge of life-cycle actions (e.g., the performance of pavement maintenance and repair) are not possible for the long analysis periods that are recommended. Many agencies therefore introduce a tolerance when compar- ing LCCA results, recognizing that small differences in cost may be the result of inherent uncertainties, and not to material differences between pavement alternatives. The Clemson– SCDOT nationwide survey indicated that, of 32 res ponses, 4 states base their pavement decision on the alternative with the lowest present value; eight selected the lowest-cost alternative if the cost difference exceeded 10%; and one res- pondent used a threshold value of 5%, another 15%, and yet another 20%. If the cost differences between alternatives are less than these threshold values, then one or a group of decision makers (e.g., a regional pavement designer or a pavement selection panel) makes the final decision. Other factors besides lowest life-cycle cost that are considered include constructability, material availability, design and envi- ronmental factors, continuity of pavement type, traffic control costs, availability of qualified constructors, and public/political issues (Rangaraju et al. 2008, p. 36). • Caltrans uses a tolerance threshold of 5% between alternatives, or 2% if initial costs exceed $100 million (Life-Cycle Cost Analysis Procedures Manual Nov. 2007, p. 80). • With its probabilistic approach, CDOT bases its deci- sion on a comparison of the probabilistic results of the two alternatives when evaluated at a 75% confidence level (Harris 2009, p. 4). • The use of probabilistic results in this way was also dis- cussed by Rangaraju et al. as an effective way of manag- ing risk. A threshold value of less than 100% recognizes that while using a 100% confidence level removes all risk from the evaluation, the result may not be economical. In addition to CDOT’s threshold criterion, Maryland’s 85% confidence limit was also cited (Rangaraju et al. 2008, p. 57). resources required and other Information Resources The resources required are implied by the previous discus- sion: knowledge of applicable guidelines, development of required data, and knowledge of the LCCA tools that are used. Responses to the Clemson–SCDOT survey indicated that, of 22 agencies that use LCCA for pavement type selec- tion and that responded to the second-stage survey, 15 agen- cies (68%) were satisfied or had only minor concerns with their respective processes; 7 agencies (32%) had significant concerns about current LCCA application to pavement type selection. Among these issues were the following (Rangaraju et al. 2008, pp. 38–39, 81): • Unreliable data quality. • Lack of adequate training regarding LCCA programs such as RealCost, and inadequate understanding of the significance and implications of the input parameters to these programs.

60 • Difficulty in predicting materials costs given their rapid and significant fluctuations in price. • Lack of sufficient historical performance data for newer pavement designs and materials (from which to esti- mate service life and rehabilitation/maintenance needs reliably and credibly for LCCA). • Lack of “rational and predictable triggers” that signal the need for rehabilitation and maintenance. • Lack of agreement with the asphalt and pavement con- struction industries on key parameters that are input to the LCCA. • Concerns “from a political/market standpoint; that is, LCCA is not popular.” Issues raised by Canadian agencies in the same study reflected some similar concerns; for example, regarding data and methods, and need for training. Canadian respondents also cited lack of communication within agencies and between agency and political officials. value engIneerIng Introduction The latest (2008) FHWA statistics on the use of Ve by state DOTs show that among 382 studies completed nationwide, 139 (36%) were accounted for by 4 states (“FY 2008 Value . . .” 2009). Of these, the top two states, Florida and Califor- nia, accounted for 82 studies, or 21%. This section presents two case examples, California and Florida, on a comparative basis to highlight similarities and differences. Florida refers to its effort as Ve; California’s process is discussed as Value Analysis, or VA. The two terms are treated synonymously in this section. When discussing the topic generally or when refer- ring to Florida, Ve will be used; when referring to California’s approach specifically, Value Analysis or VA will be used. Ve is a systematic, structured process that reviews and ana- lyzes a project typically during the concept development and design phases (“Value engineering” 2010). Although Ve may also apply during the construction phase, inviting suggestions by the contractor for an improved product, this case focuses on the project level and the design phase of the development cycle. The following discussion is limited to conventional con- struction projects and does not address design–build. Further information on Ve practices among highway transporta- tion agencies in the United States and Canada is provided in NCHRP Synthesis 352, including FHWA and OMB regula- tory requirements for using Ve (Wilson 2005). role of economic analysis in Highway Investment FDOT defines Ve in its guidance as follows: Value engineering is the systematic application of recognized techniques by a multi-disciplined team which identifies the func- tion of a product or service; establishes a worth for that function; generates alternatives through the use of creative thinking; and provides the needed functions to accomplish the original intent of the project, reliably and at the lowest life-cycle cost without sacrificing project requirements for safety, quality, operations, maintenance, and environment. Source: Value Engineering Pro- gram, May 15, 2008, p. 2. The FHWA noted that the multi-disciplinary team appointed to conduct a Ve analysis consists of persons who are not involved in the project and must include “at least one individual who is trained and knowledgeable in Ve tech- niques and able to serve as the team’s facilitator and coordi- nator” (“Order . . .” May 25, 2010). Project recommendations potentially provide the following benefits (“Value engineer- ing” 2010): • Providing needed functions safely, reliably, efficiently, and at lowest overall cost; • Improving the value and quality of the project; and • Reducing the time to complete the project. Caltrans identifies additional, more specific benefits in its guidance Project Development Procedures Manual (PDPM Chapter 19, p. 19–7; Value Analysis Team Guide 2003, p. 1.3): • To foster a team approach to problem-solving and proj- ect development; • To help build consensus among stakeholders; • To identify and develop strategies that avoid or mitigate risks and associated costs; and • To identify opportunities for Context Sensitive Solutions. Ve is an outgrowth of work in private industry during World War II focusing on managing value and innovation in a systematic way. The driving force was the wartime scarcity of critical materials, with impacts on U.S. defense manufacturers. The crucial insight was: If these materials were understood in terms of the functions they performed, then a focus on the function—function analysis—could, with creative thinking, lead to alternate materials, or dif- ferent design concepts or manufacturing approaches, that might achieve the same function. This logic was later for- malized in a “value analysis” process (Value Standard . . . June 2007). Ve in the public sector builds on these concepts of the analysis of value and function. The process has a long history of use by federal agencies, including its requirement in trans- portation beginning four decades ago. The FHWA maintains an active website on Ve policy, practice, and accomplish- ment (www.fhwa.dot.gov/ve/). AASHTO provides guidance on Ve (Guidelines for Value Engineering 2010), and state DOTs typically issue further guidance on Ve within their own programs. Table 14 identifies the scope of Ve as required by FHWA for federal-aid highways, and by the two case example states

61 for nonfederal-aid projects. Table 15 describes team compo- sition, process overview, and presentation of results as speci- fied by California and Florida. At the heart of the economic evaluation is a BCA. The scale of the Ve analysis that will be needed depends on the scale of the project itself and other elements such as need for environmental review. Major projects will require a longer period for Ve analysis, and more than one analysis may be called for at different stages through concept devel- opment, environmental review, and design. methods and measures The life-cycle costs and benefits supporting the Ve proposals are applications of the net-present-value method applied to a TABLe 14 SCOPe OF VALUe eNGINeeRING PROGRAM Scope or Scheduling Item California DOT Value Analysis Florida DOT Value Engineering Federal-Aid Highway Projects; Federal-Aid Bridge Projects (i.e., those that use FAHP funding, whether or not on Federal-Aid sy stem ) All projects $25 million Bridge projects $20 million Costs above encom pass desi gn, ROW, construction, project support U.S.DOT secretary ma y require VE (e.g., projects $500 million, or projects “of special interest”) No waivers or exceptions All projects $25 million Bridge projects $20 million Costs above encom pass desi gn, ROW, construction, project support U.S.DOT secretary may require VE (e.g., projects $500 million, or projects “of special interest”) No waivers or exceptions Non-Federal-Aid Projects All projects $25 million Bridge projects $20 million Costs above encom pass desi gn, ROW, construction, project support U.S.DOT secretary ma y require VE (e.g., projects $500 million, or projects “of special interest”) No waivers or exceptions Projects $25 million Waiver may be requested case-by- case; director of Transportation Development must approve in writing for single project District flexibility to conduct VE on projects below $25 m illion threshold Typical Candidates Am ong Projects Less Than $25 Million Threshold VA “should be” perform ed on projects $15 million to enhance project value through use of VA and to avoid need to apply VA later in project developm ent [PDPM, p. 19-7]. Caltrans districts are encouraged to vol untarily identify studies. Criteria might include; e.g., projects with: potential cost overruns, few iden tified alternatives, high maintenance costs, difficult safety/construction/ operational/ROW/ maintenance/ environm ental issues, com plex geom etry, ma jo r structures. Specific examples of candidate projects are not cited, but guidance docum ents support a broad scope of potential VA applications, in cluding highway construction projects, highway product studies, and Caltrans process studies. VA can be used to build consensus am ong stakeholders Projects substantially exceeding initial cost estimate Complex projects; capacity projects Corridor studies; interchanges Projects requested for VE by PM Projects with high ROW costs Projects, processes with unusual proble ms Scheduling by Phase Any stage of project development and construction, although VA is most effective in early stages of developm ent process For DB: prior to RFP release. One of following: Planning, Project Developm ent & Environm ental (PD&E), Initial Engineering Design For DB: prior to RFP release. Sources: PDPM, Chapter 19; Value Analysis Team Guide 2003; Value Engineering Program 2008. Regarding Caltrans requirements for non-federal-aid projects: Caltrans policy states that federal VE requirements for highway projects of $25 million or more (bridge projects of $20 million or more) apply regardless of funding source (Deputy Directive DD-92 July 2007). Therefore, non-federal-aid projects have the same VE requirements as federal-aid projects (based on 2007 SAFETEA-LU requirements). Notes: = “equal to or greater than”; DB = design-build; FAHP = Federal-Aid Highway Program; PDPM = Project Development Procedures Manual; PM = project manager; RFP = Request for Proposals; ROW = right-of-way; VA = value analysis; VE = value engineering.

62 TABLe 15 VA/Ve TeAM, TOOLS, AND ReSULTS Item California DOT Value Analysis Florida DOT Value Engineering Typical VA/VE Team Composition VA team selection is initiated by the DVAC and co mp leted by the VA Tea m Leader in coordination with the DVAC, PM, and others attending a pre-study meeting. Key disciplines/functions needed on the project study should be represented. DVAC should contact function ma nagers in advance of the st udy to identify and recruit candidate members. Roster lists VA team leaders and full-tim e study team me mb ers, project contacts, team resource advisors, study technical reviewers, and project decision ma kers. Expertise levels are identified for all except external stakeholders and decision ma kers. VA team members should be at either advanced or expert levels. VE team selection coordinated between DVE and PM. Me mb ership structured to include appropriate expertise to evaluate ma jor aspects of project. Minim um : design, construction, and maintenance should be represented. Federal-Aid projects: personnel involved in design are inform ation resources, but should not be team me mb ers. Districts determine whether membership comprises FDOT personnel, consultants, or combination. Study Elements Preparation Initiate study Organize study Prepare data VA Study Segment 1 Inform team Analyze functions Create ideas Evaluate ideas Segment 2 Develop alternatives, including LCC, benefits, and costs Critique alternatives Present alternatives Segment 3 Assess alternatives Resolve alternatives Present results: summarize performance, value, and cost improvements Report Publish results Close out VA study 1. Define original project objective 2. Identify design criteria for project 3. Verify all valid project constraints 4. Identify specifically the components and elements of high cost 5. Determine basic and secondary functions 6. Evaluate the alternatives by comparison 7. Consider life-cycle costs of alternatives 8. Develop detailed implementation plan 9. Determine which VE alternatives can be grouped together and which stand alone. Select the combination of solutions to recommend specifically. Presentation of Results Description of alternative Sketches (original design and alternative) Calculations Benefits Initial costs LCC Description of alternatives Advantage/disadvantage comparison Evaluation matrix with weighted criteria Sketches: base design, proposed design Discussion, pros and cons Cost summary (see below) with supporting calculations Form of Economic Results Initial cost, annual cost, subsequent single costs (e.g., for repair, rehabilitation, and salvage value), and total LCC computed at specified discount rate Above costs computed for base design and alternative design. Yields result: Total Present Value Cost of each alternative, and difference between the two. Discount rate used in example reviewed: 4% Initial cost, annual cost, and total LCC computed at specified discount rate Above costs reported for base design, proposed design (including implementation costs), and difference between base design and proposed design options. Yields result: either cost savings or the additional cost due to adopting the proposed design. Discount rate used in example reviewed: 7% Sources: TVI International (1999); Value Analysis Team Guide (2003); Value Engineering Program (2008). Notes: DVAC = District Value Analysis Coordinator; DVE = District Value Engineer; LCC = life-cycle costs; PM = project manager; VA = value analysis; VE = value engineering.

63 specified period (e.g., 20 years) at the discount rate indicated in Table 15. examples of cost-benefit information used in and produced by a VA analysis are as follows (TVI Inter- national 1999). Project Cost Information in Value Analysis (Caltrans example) These cost items are computed by year for the base design and the proposed design alternative: • Direct project costs: right-of-way, construction, and project support. • Subsequent costs: maintenance and operations, rehab- ilitation. • Mitigation costs: environmental mitigation actions for air quality, water quality, noise control, etc. • Other costs: as specified by VA team. • Total costs: totaled in constant dollars by year through the analysis period, with computation of present value. Road User Cost Information in Value Analysis (Caltrans example) These data items are computed by year for the base design and the proposed design alternative: • Travel time: average annual traffic volume, total travel time, travel time reduction owing to the defined alter- native, and travel time savings in constant dollars by year through the analysis period, with computation of present value. • Vehicle operating cost (VOC): annual vehicle-miles of travel, total VOC, and VOC savings in constant dollars by year through the analysis period, with computation of present value. • Accident cost: annual vehicle-miles of travel, annual number of accidents, accident cost savings as a result of the indicated reduction in number of accidents under the proposed design alternative; these cost savings are expressed in constant dollar by year through the analy- sis period, with computation of present value. Tally of Cost and Benefit Results for VA (Caltrans Example) • Net present value: computed by subtracting the pres- ent value of total project costs from the present value of total user savings comprising savings in travel-time costs, VOC, and accident costs. • Internal rate of return: computed by testing at what dis- count rate the total (constant-dollar) benefits and the total (constant-dollar) costs are equal. If the computed IRR is greater than the discount rate used to conduct the analysis (i.e., 4% in Table 15), then the IRR result is equivalent to benefits exceeding costs and the net pres- ent value being positive; that is, the project alternative is economically justified. As a further note on applications, Table 14 indicates that Caltrans’ scope of VA analyses can include products and processes, in addition to transportation projects. examples of these types of studies have been cited by FHWA in its Ve website: In addition to studies conducted for the Federal-Aid Highway Program, Caltrans utilizes the Ve techniques [Caltrans’ VA pro- cess] to recently analyze improvements proposed for their ‘Utili- ties Database’ and ‘Purpose and Need’ processes. Caltrans also used Ve to study a series of Safety Rest Area projects that had come in over estimated budgets to develop alternative ways to reduce construction cost while maintaining or improving project quality. Source: “FY 2007 Annual Federal-aid . . .” 2008. Decision support An example of subsequent review and implementation of VA findings is provided by a Caltrans example for a new State Route, SR-138 (“Value Analysis Study . . .” 2009): • VA team recommendations were submitted for review to identified agency managers and stakeholders; a 4-week review period was allotted. This particular study involved 11 VA alternatives. • Following review, an implementation meeting was held to resolve the disposition of the 11 alternatives. An updated set of alternatives to be developed was agreed to by the VA team members. • The VA team formally developed the agreed-on alterna- tives and suggestions that were accepted by the majority of stakeholders. (Note the entry in Table 14 that Caltrans guidance recognizes the use of VA to help build consen- sus among stakeholders.) • These updating findings of the VA team were applied in the developmental phase of the project. resources needed and other Information Resources Overall team composition in FDOT is a district decision. Consultants often produce the Ve reports, although there is no policy that dictates this practice. California’s VA team composition is likewise tailored for each project, including representatives from the DOT, local stakeholders, consultants, and academics; the team may also use consultants to pro- duce VA reports. Caltrans also explicitly considers the level of expertise for team members who are not stakeholders or agency decision makers. Key disciplines typically represented on a Ve/VA team might include the following, as appropriate to the specific project: highway design, bridges or other struc- tures, infrastructure construction, traffic operations (including access to modeling capability if user costs-benefits are to be

64 compresses the time schedule and begins to constrain the ability to make changes; and limitations on resources avail- able (e.g., limits on Caltrans participation in local VA studies or the inability to schedule good meeting rooms for the time needed) (Tusup and Hays 2009). aCCeleratIon of projeCt DelIvery Introduction The Minnesota DOT (Mn/DOT) applies economic analysis to a number of transportation issues that it faces and main- tains a website providing guidance on benefit–cost meth- ods (“Benefit–Cost Analysis for Transportation . . .” n.d.). Recently it applied economic concepts and methods to exam- ine the benefits and costs of accelerating project delivery (HDRHLB Decision economics Inc. 2006). On-time, on- budget project delivery is becoming a major issue among national, state, and local transportation organizations across the nation. Streamlining project approvals and permits, together with accelerated project design and construction, are seen as critical to cost saving, improving mobility and safety, and maintaining economic competitiveness, while successfully preserving environmental quality and energy efficiency. Accelerating project schedules also entails risks, however, as in potentially greater mobilization costs and the possibility of missing and having to correct project details. Mn/DOT therefore sought to develop a methodological approach to analyzing the economic impacts of accelerating project delivery, accounting for the risks involved, and pos- sible ways to mitigate these risks. In terms of the criteria for including this Mn/DOT work within this synthesis, the study is unique: It was believed to be a “first” in developing a “compre- hensive methodological approach to estimating the economic impacts of transportation project delivery acceleration,” and to assessing the risk–reward tradeoffs of accelerated-delivery mechanisms such as design–build (HDRHLB Decision economics Inc. 2006, p. v). The case study used by Mn/ DOT and its consultant to illustrate this approach was State Highway 52 in Rochester (ROC 52). In terms of the research framework established for this synthesis, this case example is at the individual highway project level, focusing on the project delivery stage. role of economic analysis in Highway Investment Risk-Reward Framework The rewards of accelerating highway project completion are described in the Mn/DOT study as follows (HDRHLB Decision economics Inc. 2006): • The highway agency saves costs by reducing the effects of general inflation on project expenses as well as the impacts of possibly more rapid cost increases in items that are unique to highway construction; for example, estimated), environmental protection and mitigation, and maintenance and operations. The tabulation of agency and road-user costs and benefits and the comparison of costs to benefits are accomplished using the Cal-B/C program (System Metrics Group, Inc. and Cambridge Systematics, Inc. 2004). Part of the information anticipated to be needed by the VA team is included in the project documentation for the existing design. This informa- tion includes project costs and data on current and projected traffic conditions for the existing design. Other data that may be needed can be generated by the VA team using traf- fic models (for impacts on travel time, VOC, and accident costs), engineering estimates (e.g., for initial, recurring, and annual costs of construction, maintenance, and operation of alternatives), and look-up tables that are part of Caltrans soft- ware (TVI International 1999, pp. 6.21–6.22). Caltrans has performed a review of its VA program in terms of returns on effort, project dollar savings, and resources required to conduct VA studies in relation to benefits. Key findings were as follows for 286 VA efforts completed between 2002 and 2009 (Tusup and Hays 2009, updated by input from Tusup in 2010 for this report): • The standard time devoted to a VA study is 6 days, ideally divided into two 3-day sessions. Five days is acceptable for smaller projects. • Three days or less is not acceptable for a proper VA study. Four days would be the minimum for small, local projects that are off the National Highway System. • Increasing the duration of the VA study can pay off in terms of both greater total project savings per VA study and the average savings realized for each day of the VA study effort. For example, although 3-day studies produced average construction savings of $2.81 million per VA study ($0.94 million per day of study), studies of 7 days or longer produced average savings per study of $18.45 million (roughly $2 million or more per day of VA effort). • The VA team leader must be a Certified Value Special- ist, with certification administered by SAVe Interna- tional® (“Certification Program” 2010). The VA team leader preferably has experience in the Caltrans VA process. Team leaders must be independent of the proj- ect and of its design team. • Qualified consultants may be used to conduct VA stud- ies on federal-aid projects. Consultants with indepen- dent VA affiliates can perform Ve on their own design, with independent team members not affiliated with the project. Caltrans has identified typical problems using VA, but none of the listed items relates to the benefit–cost component of the analysis. Most of the issues relate to management and logistics; for example, failure to plan enough time and bud- get to do the job right; impact of accelerated design, which

65 right-of-way acquisition in areas experiencing com- mercial and residential growth. • Road users experience lower direct costs of traffic dis- ruption resulting from construction in terms of travel- time costs, VOC, and costs of safety hazards. • Communities experience less adverse impacts on the local economy in terms of reduced business volume and temporary reductions in housing values resulting from construction-related congestion, noise, and impaired accessibility. • Project beneficiaries—road users, local citizens and businesses, the public at large—are able to realize sooner the economic benefits of the project because of the quicker completion of construction and the earlier opening of the highway to traffic. Within a discounted CBA, the discounted value of benefits is greater than would have been the case given a conventional con- struction time frame. • Various ancillary benefits also accrue; for example, in program scheduling and management (project comple- tions close existing commitments and enable schedulers to turn to new work); in reduced overhead and construc- tion management costs; and in gains in productivity and efficiency necessitated by the tighter deadlines and the closer interaction between design and construction. The HDR report to Mn/DOT acknowledges several risks in accelerated construction that are related to budget, proj- ect management/scheduling, engineering, and institutional arrangements (particularly those needed to prepare for actual construction; for example, right-of-way acquisition and util- ity work). The report discusses strategies to mitigate these risks, illustrated by the following examples (HDRHLB Decision economics Inc. 2006): • Budget risks can be mitigated through clear delineation of funding sources and arrangements, a clear and real- istic scope of work and project schedule, and a reliable cost accounting system with features that support effec- tive cost tracking and management. • Project management and scheduling risks can be miti- gated by adopting and applying an effective project scheduling and tracking system, employing good com- munication with affected parties, instituting quality assurance steps such as constructability reviews and a system of incentives and penalties governing time and cost performance, and building in scheduling flexibility to adjust to project circumstances. • engineering risks can be mitigated through good man- agement of the technical tasks and processes involved. Good practices include streamlining activities, main- taining good communications and coordination among stakeholders, organizing work tasks clearly within per- forming units, decentralizing personnel skills, strength- ening organizational capabilities as through training, and shifting quality assurance responsibilities to the contrac- tor to ensure its awareness of quality requirements. • Institutional risks in utility relocation can be mitigated through mechanisms such as securing up-front contracts for major utility relocation and providing incentives for timely completion of utility relocation. Risk-mitigation strategies in right-of-way acquisition include offering various incentives to property owners such as signing bonuses, increased nominal values of parcels, and lati- tude in negotiating offers. Agencies can also provide employees training in environmental stewardship of sensitive land uses affecting the parcels being acquired. Structure of the Economic Analysis The analyses of these economic and financial effects of accel- erated project delivery are summarized in Table 16. Costs, benefits, and other impacts of accelerated project delivery are structured in three categories: micro-economic impacts, which focus on transportation-related effects experienced by highway users; macro-economic impacts, which are experi- enced by the commercial and residential sectors of the local community; and agency-related impacts, which reflect the economic and the financial dimensions of changes in project costs owing to accelerated delivery. • Micro-economic impacts comprise changes in the respec- tive costs of travel time, VOC, crash or accident rates and severity, and environmental pollution resulting from vehicle emissions. • Macro-economic impacts comprise changes in commer- cial business levels and residential housing values within the affected community. • Agency impacts include effects on project-related costs and benefits in both an economic and financial dimension. The table considers two distinct time periods: • The period during project construction. The economic and financial effects identified in Table 16 are com- pared for a project with a more accelerated construc- tion schedule versus that with a more conventional timetable. • The period following completion of project construction. These project-driven transportation benefits, which reflect after-construction versus before-construction compari- sons of highway performance and road user costs, would have been achieved by the project regardless of construc- tion method. The key benefit of accelerated delivery by the agency is to attain these benefits earlier than would otherwise have been possible using more conventional construction approaches. The ROC 52 example was intended as a first step by Mn/DOT to develop generalized economic analysis proce- dures that could be applied to accelerated-delivery options for other highways. In addition to the costs and impacts cited in Table 16, Mn/DOT and its consultant also ensured that

66 (These distributions were estimated at the risk analysis workshop mentioned in the first bulleted item.) Model outputs can also be obtained as probabilistic estimates, although for clarity they are often reduced to mean values or to a limited set of distributions. Confidence intervals and decumulative distributions can also be obtained. Table 16 describes several components of the analysis con- ducted by Mn/DOT and its consultant, organized for use in this case example. In keeping with the objectives of this syn- thesis and the approaches that have been applied in other case examples, the focus of the remaining sections is specifically on transportation-related benefits and costs: that is, the agency- related economic costs and benefits and the micro-economic effects to highway users that are identified in Table 16. Project Characteristics and Design–Construction Options The ROC 52 project involved the design and reconstruction of approximately 11 miles of Trunk Highway 52, with the following work items: • Widening from 4 to 6 lanes along part of the project length; the following characteristics of good practice would be met in estimating costs and benefits of accelerated construction for ROC 52: • Transparency: Analytic methods and assumptions were reviewed by a multi-disciplinary panel of experts in economics, traffic engineering, planning, and local stakeholder interests. Reviews and discussions occurred at both a risk analysis workshop on the ROC 52 project and in subsequent meetings with Mn/DOT’s Office of Investment Management. Suggestions were incorpo- rated into the analysis described in subsequent sections. • Accuracy: Quantitative data were obtained from authori- tative public sources including the U.S. Census Bureau, the Congressional Budget Office, the Minnesota Depart- ment of employment and economic Development, the Minnesota State Demographic Center, and studies con- ducted or sponsored by FHWA. • Transferability: The ROC 52 example provided a practical laboratory for developing and organizing the data, methods, and assumptions of the economic analy- sis into a computerized procedure (Microsoft® Office excel workbook) that can be applied to other projects. • Risk Analysis: Because the economic analysis embod- ies forecasts in its estimates, the value of each model parameter is expressed as a probability distribution. Type of Im pact Period During Construction Period After Completion of Project Construction Micro- Econom ic Reduced Period of Disruption to Highway User o Travel tim e cost o Vehicle operating cost o Crash or accident cost o Environm ental emissions cost Im pacts of Congestion Relief o Travel tim e cost savings o Vehicle operating cost savings o Crash or accident cost savings o Environm ental emissions cost savings Macro- Econom ic Im pacts on Local Econom y Due to: o Construction spending o Reduced period of disrupted access to local businesses o Reduced period of construction effect on housing values Im pacts on Local Econom y Due to: o Incre me ntal spending for operations and maintenance o Im proved access to local businesses o Potentially changed housing values Agency Econom ic Effects o Reduced costs for time - dependent project ite ms (e.g., construction ma nagem ent, project overhead, traffic management) Financial and Budget Effects o Reduced budget expenditures for tim e-dependent project items o Reduced impact of inflation on project costs Economic Benefits to Public Provided through Agency’s Decision on Accelerated Construction o Earlier attainment of project’s benefits listed above Source: Mn/DOT ROC 52 study (HDR|HLB Decision Economics Inc. (2006), Summary Table 1). Additional explanations and clarifications drawn from the report text, and a separate delineation of agency economic and financial effects, have been inserted by the author. This table presents impacts relevant to Mn/DOT and to ROC 52 highway users; other impacts (e.g., financial savings to city of Rochester associated with lower loan costs resulting from accelerated project completion) are not included. TABLe 16 STRUCTURe OF eNGINeeRING eCONOMIC ANALYSIS DeSCRIBING IMPACTS OF PROJeCT ACCeLeRATION

67 • Construction or reconstruction of interchanges and frontage roads; • Construction of two new overpasses; • enhancements of ITS components; and • Other improvements; for example, in road surfacing, lighting, signage, pavement markings, noise and retain- ing walls, traffic signals, and detention ponds. Options to be considered in the economic analysis involved different construction-stage assumptions, including the use of design–build, to accelerate project completion. Mn/DOT and its consultant considered four options in establishing compara- tive estimates of time, cost, and impact: • Scenario 1, the Baseline: Conventional design and construction wherein the design stage spans approxi- mately 30 months (2.5 years) and the construction stage about 11 years, as estimated for the original project. • Scenario 2: Conventional design stage with same duration as that in Scenario 1, but with a shorter period of construction of 5 years with funding restrictions removed. • Scenario 3: Similar to Scenario 2, but with a further compressed construction duration of 3 years owing to some form of accelerated project delivery. • Scenario 4: Application of a design–build approach to conduct design and construction in parallel, leading to a combined duration of design and construction total- ing 3 years. Comparisons among these scenarios were structured as follows: • Scenario 2 compared with the Baseline Scenario 1; • Scenario 3 compared with the Baseline Scenario 1; and • Scenario 4 compared with the Baseline Scenario 1, and to Scenario 3. Costs were also estimated for a “No-Work” or “No-Build” option, which assumed no improvements to the highway during the analysis period. methods and measures Micro-Economic Highway User Impacts The beneficial impacts of project acceleration on highway users are measured in four categories of cost reduction: travel time, accidents or crashes, vehicle operation, and environ- mental emissions. The following sections discuss the factors included in calculations of each of these economic effects; mathematical formulas used in modeling computations are presented in the HDR report (HDRHLB Decision econom- ics Inc. 2006, pp. 10–15). Travel Time The total daily travel-time cost is computed at an aggregate level by vehicle type and peak versus off-peak period for each year of the analysis. In concept, the years may occur before construction (when congestion is affected by existing capacity prior to the project), during construction (when congestion is affected by work zone road occupancy and the duration of project work), and following construction (when congestion is presumably reduced owing to additional capacity provided by the project). Congestion effects are monetized in terms of total daily travel-time cost using a value-of-time calculation in each year that accounts for the following factors: • The value of time associated with each type of vehicle in each year, in $/hour; • A congestion premium expressed as the percent additional cost motorists are willing to pay to avoid congestion; • AADT by period of day, vehicle type, and year (number of vehicles); • The length of the project work zone in miles; and • The average speed through the work zone by period of day and year, in miles per hour. Accidents or Crashes Accident or crash costs are computed in terms of total daily accident-related costs by period of day, category of accident or crash, and year, accounting for these factors: • AADT by period of day, vehicle type, and year (number of vehicles); • The accident rate by period of day, category of accident, and year as estimated by FHWA for three categories of accidents: property-damage-only, injury, and fatal (accidents per some multiple of vehicle-miles); • The monetized cost of a crash as estimated by AASHTO for each category of accident by year; and • The length of the project work zone in miles. Vehicle Operation VOC is the monetized value of owning, operating, and maintaining a vehicle as affected by road characteristics and conditions. The model used by HDR for Mn/DOT considered VOC in two steps: • Constant-speed VOC for the following components: fuel consumption, oil consumption, vehicle maintenance and repair, tire wear, and roadway-related vehicle deprecia- tion estimated for a constant-speed condition. • excess VOC, comprising adjusted consumptions of the VOC components for the actual traffic, pavement, and speed-flow conditions anticipated to be encountered within the time frame of the analysis. The total daily VOC for each type of vehicle, period of day, and year of analysis was computed accounting for the following factors: • AADT by type of vehicle (auto, truck, or bus), period of day (peak or off-peak), and year of cost estimation within the analysis period (number of vehicles);

68 • A constant-speed VOC consumption rate and an excess VOC consumption rate for each VOC component: fuel, oil, tires, vehicle maintenance and repair, and road-related vehicle depreciation, estimated for each vehicle type, year, and (for excess VOC consumption) period of day; • Cost of each VOC component for each vehicle type and analysis year in terms of dollars per gallon of fuel, dollars per quart of oil, percentage of tire wear applied to total cost of each tire, percentage of average vehicle maintenance and repair cost, and percentage of vehicle- depreciable dollar value; • Length of the project work zone in miles; and • A pavement adjustment factor to reflect the influence of pavement condition on excess VOC. Vehicle Emissions Vehicle emissions costs are the monetized values of air pollution released daily by vehicles. The daily cost of air pollution emissions is computed for each combination of the following: type of emission, vehicle type, period of the day, and analysis year, using the following factors: • The rate of vehicle emission (in tons per numbers of vehicles) of each type of air pollution (hydrocarbons, carbon monoxide, and nitrogen oxides) by vehicle type, period of the day, and analysis year, obtained from FHWA emission-rate tables; • AADT by vehicle type, period of the day, and analysis year (number of vehicles); • Length of the project work zone in miles; and • The emission cost per ton of each of the three types of emissions, respectively, in each analysis year. Daily to Annual Conversion The four highway-user models described earlier yield results in cost per day. These cost results are converted to annual amounts using 365 days per year. Results for different project scenarios are also organized by whether the year corresponds to “during construction” or “post-construction” conditions. Role of Forecasting The four models above all depend on forecasts of key variables: • AADT is projected from baseline–year traffic volume using an average annual growth rate. Splits are applied to results in terms of peak versus off-peak periods of the day and vehicle type (autos, trucks, and buses). • Volume-capacity ratios (v/c) are estimated for peak and off-peak periods based on AADT, assumed truck- equivalency factors, and proposed work-zone configu- rations and capacities. • Average vehicle travel speeds for peak and off-peak periods are estimated using speed-flow relationships as a function of v/c and posted speed limits. Benefits of Accelerated Construction Completion The benefits of accelerated project completion are illus- trated in Figure 3, using the example of the congestion index (CI). (CI is a measure of urban traffic density on major metropolitan roadways. A value of CI greater than 1.0 indicates an undesirable level of congestion. This example is provided in the HDR report to suggest the gen- eral idea involved in calculating benefits of project accel- eration. Other measures can be used for the four road-user models described earlier; however, the basic idea would be the same.) In the absence of a project (the “No Work” scenario), the congestion index is assumed to increase with growth in traffic demand (AADT). A project to increase road capacity would reduce the congestion index, provid- ing a benefit to road users. In the upper chart of Figure 3, project construction extends through Duration 1. At project completion the level of con- gestion is reduced, providing a benefit corresponding to the area B1 between the two CI curves. The lower chart in Fig- ure 3 illustrates an accelerated project schedule that finishes project work within Duration 2, a shorter period of time. The resulting benefits are illustrated by areas B1 plus B2 between the two CI curves, providing an increased benefit. There may also be benefits owing to the shorter project duration in the second chart, but these need to be confirmed using the several models discussed earlier. For example, it would be reasonable to assume that total work-zone con- gestion would be less with Project Duration 2, leading to additional travel-time savings in accelerated-completion scenarios. Incremental costs resulting from work-zone crashes are also expected to be lower with shorter construc- tion duration, leading to greater safety benefits in terms of costs avoided. However, incremental VOC savings (espe- cially in the fuel consumption component) may not be posi- tive with shorter project duration, depending on the specific changes in speed and the number of stop-go cycles expe- rienced by traffic through the work zone. The actual varia- tions in road user costs that were computed across the four design–construction scenarios investigated are given later in this case. Project Costs to Agency Project costs for construction were estimated by HDR for each of the four scenarios defined earlier. Costs included direct project construction as well as several items that vary with project duration: temporary construction items, con- struction overhead, and construction management. Cost escalation (or inflation avoidance) was also included in the year-of-expenditure (Y.O.e.; that is, undiscounted) construc- tion cost estimates; this component was carried over into the discounted CBA as well. (To the extent that this adjustment reflects differential inflation effects in construction costs, it would be consistent with guidance by FHWA and others cited in chapter two that recommends constant-dollar esti- mates in the economic analysis.) The total estimated project costs are given in Table 17.

69 Time Congestion Index Project Duration 1 B1 Effect of Traffic Growth Assuming “No Work” Scenario Time Congestion Index B1 B2 Project Duration 2 Effect of Traffic Growth Assuming “No Work” Scenario FIGURE 3 Illustration of highway user cost savings due to project acceleration. Source: HDRHLB Decision Economics Inc. (2006), Figure 7, p. 11, with additional annotations by author. Risk Analysis The risk analysis conducted by Mn/DOT and its consultant was based on probabilistic input values of key variables. These ranges of values were then subjected to a Monte Carlo simulation, with results produced likewise as probabilistic distributions of costs and impacts. • Input values were specified by three data points: an anticipated median value (i.e., with 50% probability of being exceeded); a lower-10% value (with a 90% prob- ability of being exceeded); and an upper-10% value (with a 10% probability of being exceeded). These estimates were developed at a risk analysis workshop conducted at the Mn/DOT district office in Rochester before performing the economic analysis. The Monte Carlo procedure analyzed these data to infer a probabil- ity distribution for each input variable. • The Monte Carlo simulation was performed employing the analytic models discussed earlier and the probabilistic Scenario No. Scenario Cost, $ Millions 1 (Baseline) Conventional design (2.5 years) and construction (11 years) $371.4 2 Design (2.5 years) + reduced construction (5 years) $280.2 3 Design (2.5 years) + accelerated construction (3 years) $253.2 4 Design-build (3 years for design and construction) $236.0 Source: HDR|HLB Decision Economics Inc. (2006), Summary Figure 4, p. xii, and Figures 20 and 22, pp. 37 and 38. TABLe 17 eSTIMATeD YeAR-OF-exPeNDITURe PROJeCT COSTS BY SCeNARIO

70 scenarios, construction was scheduled to begin in 2005. Undiscounted or Y.O.e. costs were discounted to 2005 at a 4% discount rate. (Bear in mind that the ROC 52 project was serving as a case study for Mn/DOT and its consultant to develop this economic analysis for use in subsequent high- way projects. Costs were thus discounted to the then “pres- ent year” of 2005, the year in which the economic analysis was developed, rather than, say, to 2002 or 2003, which would have been a more typical “decision point” for considering ROC 52 construction options in an actual project-development setting.) Selected tables of results are presented here to illustrate different facets of the analysis results. The examples are for highway-user cost savings, relating to the models discussed earlier. Cost results are presented in Y.O.e. and total dis- counted amounts. Scenario comparisons are as discussed earlier: S2 versus S1 Baseline, S3 versus S1 Baseline, S4 versus S1 Baseline, and S4 versus S3, where “S” denotes Scenario. • Table 19 shows predicted cost savings to highway users by component of user cost for each scenario, and the incremental cost savings for each scenario compari- son. All costs in this table are in 20-year undiscounted Y.O.e. dollars. inputs. Results were produced as decumulative prob- ability curves; that is, curves indicating the probability that a predicted result will be exceeded by the actual result. These curves enabled Mn/DOT and HDR per- sonnel to identify the mean expected value, the value with 90% probability of being exceeded, and the value with 10% probability of being exceeded. Tables of results presented in a later section are based on mean- value results in each case. To illustrate how the risk analysis was structured, Table 18 presents selected input variables in terms of probabilistic data developed at the Mn/DOT workshop. Where different time periods are cited (e.g., hourly vs. monthly vs. annual costs), the analysis translates these to commensurate project amounts. Costs in Table 18 are undiscounted. Decision support Economic Analysis Results The economic analysis of the ROC 52 construction options was conducted for a 20-year analysis period, 2003 through 2022. Project design was assumed to start in 2003 across all four scenarios. For Scenario 4 (the design–build option), construction was also assumed to start in 2003; for other Input Variable or Factor Median Lower 10% Upper 10% Project Costs (2002 $) Total direct project construction costs $197,172,764 $197,172,764 $197,172,764 Monthly overhead costs (collocation office) $97,222 $77,778 $116,667 Monthly construction ma nagement costs $431,944 $345,556 $518,333 Warranty bond, cost per year $52,350 $52,350 $52,350 Road User Value of Time (2005 $) Aut o, $/hour $10.46 $8.00 $14.10 Heavy comm ercial vehicle, $/hour $19.39 $16.00 $24.00 Traffic Distribution Passenger cars and light trucks 93.5% 92.0% 95.0% Heavy comm ercial vehicles 6.5% 8.0% 5.0% Peak vs. Off-Peak Periods Length of the peak period, hours 5.0 4.0 6.0 Peak-hour traffic volum e, % of daily volum e 10.0% 8.0% 12.0% Peak-period traffic volum e, % of daily volume 65.0% 60.0% 70.0% Source: HDR|HLB Decision Economics Inc. (2006), pp. 26–29. TABLe 18 SeLeCTeD exAMPLeS OF RISK-ANALYSIS INPUT DATA

71 • Table 20 provides a summary of the micro-economic impacts expressed as highway-user cost savings in sev- eral ways simultaneously: – In 20-year undiscounted Y.O.e. dollars and in dis- counted 2005 dollars for the 20-year analysis period; – In two stages of the 20-year analysis: during construc- tion (reflecting work zone and temporary road effects) and after construction (reflecting improvements derived from the project), and for the two stages combined; – In a comparison of total highway-user cost savings as compared with the No-Work (or No-Build) option; and – In comparisons among scenarios: S2 versus S1, S3 versus S1, S4 versus S1, and S4 versus S3. • Table 21 illustrates the results of the risk analysis for the 20-year highway-user cost savings in undiscounted Y.O.e. dollars, organized by the four scenario comparisons. Conclusions of the ROC 52 Analysis Mn/DOT’s consultant drew several conclusions from this eco- nomic analysis that are listed here. Although this case example has focused on micro-economic transportation impacts that are reflected in highway-user cost savings, the full Mn/DOT analysis considered other economic impacts as well; that is, changes in residential housing values, increases in local com- mercial activity, and reduced construction overhead costs. The HDR report includes findings that reflect these other aspects of the economic analysis. However, when conservative analytic assessments of transportation impacts were called for (specifi- cally, to discuss the business case favoring use of design–build, as in Strategy 4 of the ROC 52 project), HDR focused solely on the highway-user cost savings, eliminating any possible double- counting among the other categories of economic impacts. This approach is consistent with the information presented in this case example. With this background, the overall conclusions as compiled in the HDR report are quoted as follows: By shortening the construction period and associated traf- fic disruption, project acceleration typically reduces highway user costs, and losses in housing values and retail sales in the immediate vicinity of the construction project. [This conclusion addresses the “During Construction” impacts.] By bringing the completion of highway projects sooner, proj- ect acceleration generates real economic value to highway users, avoiding congestion delays, highway accidents, and vehicle operating costs. The early completion of highway improvements also brings upturns in retail sales and home values sooner. [This conclusion addresses the “After Construction” impacts: both the generation of real benefits to road users, and the fact that benefits accrue to road users and the community earlier than they would with conventional construction.] Finally, through inflation avoidance and ancillary project cost savings, project acceleration is expected to reduce construction spending. Source: HDRHLB Decision economics Inc. (2006), pp. 46–47. resources required and other Information Consultant Assistance with Methodology Mn/DOT was assisted in this analysis by HDRHLB Deci- sion economics Inc. (HDR), which developed the methodol- ogy, performed the economic analysis, and wrote the report cited in this case. Mn/DOT participated in this development through activities such as study oversight, provision of data, and conduct of the risk analysis workshop. Development of Scenario Comparison Travel Tim e Accidents or Crashes Vehicle Operation Emissions Total Highway User Cost Savings Over No-Work (or No-Build) Option Scenario 1 (Baseline) ($27.7) $38.9 $80.8 $16.8 $108.8 Scenario 2 $58.4 $62.8 $190.1 $1.9 $313.1 Scenario 3 $80.1 $69.5 $220.9 ($2.2) $368.2 Scenario 4 $87.5 $75.9 $242.7 ($3.0) $403.1 Increm ental Highway User Cost Savings By Co mp aring Strategies Scenario 2 vs. Baseline $86.1 $23.9 $109.2 ($14.9) $204.3 Scenario 3 vs. Baseline $107.8 $30.6 $140.0 ($19.0) $259.4 Scenario 4 vs. Baseline $115.2 $37.0 $161.9 ($19.8) $294.3 Scenario 4 vs. Scenario 3 $7.4 $6.4 $21.8 ($0.8) $34.9 Source: HDR|HLB Decision Economics Inc. (2006), Figure 18, p. 35. Notes: Highway user costs are shown as negative cost savings. Round-off errors occur in some of the totals. TABLe 19 20-YeAR HIGHWAY USeR COST SAVINGS BY COST CATeGORY ($ MILLIONS, UNDISCOUNTeD)

72 • Development of a model for analyzing project- acceleration benefits within a risk-analysis frame- work, addressing benefits in four areas: budget, finan- cial, micro-economic impacts (the highway-user cost savings), and macro-economic impacts. • Conduct of the risk-analysis workshop with Mn/DOT project stakeholders. the analysis involved the following tasks (HDRHLB Deci- sion economics Inc. 2006, p. 45): • Review of the available literature related to the benefits of project acceleration, and identification of local, state, national, and international data sources for relevant economic indicators. All Estimates for 2003–2022 $ Millions, Undiscounted Y.O.E. $ Millions, Discounted to 2005 Scenario Comparison During Project After Project Total During Project After Project Total Highway User Cost Savings Over No-Work (or No-Build) Option Scenario 1 (Baseline) ($123.7) $232.5 $108.8 ($90.8) $98.0 $7.2 Scenario 2 ($52.8) $366.0 $313.1 ($46.7) $182.2 $135.4 Scenario 3 ($33.0) $401.2 $368.2 ($31.3) $210.7 $179.3 Scenario 4 ($29.8) $432.9 $403.1 ($31.5) $239.6 $208.1 Incremental Highway User Cost Savings By Comparing Strategies Scenario 2 vs. Baseline $70.9 $133.4 $204.3 $44.1 $84.1 $128.2 Scenario 3 vs. Baseline $90.7 $168.7 $259.4 $59.5 $112.6 $172.1 Scenario 4 vs. Baseline $93.9 $200.4 $294.3 $59.3 $141.5 $200.9 Scenario 4 vs. Scenario 3 $3.2 $31.7 $34.9 ($0.2) $28.9 $28.7 Source: HDR|HLB Decision Economics Inc. (2006), Table 24, p. 44. Notes: Y.O.E. = Year-of-Expenditure. Highway user costs (shown as negative cost savings in the “During Project” column) reflect traffic disruption due to construction. Highway user cost savings after the project reflect the resulting improvement in traffic flow. Round-off errors occur in some of the totals. TABLe 20 20-YeAR HIGHWAY USeR COST SAVINGS DURING AND AFTeR PROJeCT CONSTRUCTION ($ MILLIONS) All Esti mates for 2003–2022 $ Millions, Undiscounted Y.O.E. $ Millions, Discounted to 2005 Scenario Comparison Mean Expected Value 90% Probability Exceeding 10% Probability Exceeding Mean Expected Value 90% Probability Exceeding 10% Probability Exceeding Scenario 2 vs. Baseline $204.3 $168.7 $267.3 $128.2 $106.2 $167.1 Scenario 3 vs. Baseline $259.4 $215.5 $335.2 $172.1 $143.6 $220.9 Scenario 4 vs. Baseline $294.3 $244.5 $380.9 $200.9 $167.4 $259.2 Scenario 4 vs. Scenario 3 $34.9 $28.9 $45.9 $28.7 $23.7 $38.4 Source: HDR|HLB Decision Economics Inc. (2006), Table 25, p. 45. Note: Y.O.E. = Year-of-Expenditure. “x% Probability Exceeding” means that actual savings have an x-percent probability of exceeding the predicted cost savings shown. TABLe 21 RISK ANALYSIS ReSULTS FOR 20-YeAR HIGHWAY USeR COST SAVINGS ($ MILLIONS)

73 cycle of a highway facility. each case, however, has focused on a particular application and the practices and viewpoints of a particular agency. The next chapter steps back from the set of cases to take a broader look at what economic methods mean to highway investment decisions overall. Chapter four addresses several important issues: the value of economic analyses, the role of economic analyses in strengthening agency decision making, the level of effort in using economic methods, factors favoring success, and useful resources avail- able. There are also discussions of the relationship between economic analysis and performance measurement, the role of reporting and communication, and ongoing and emerging areas of application. • Incorporation of expert panel comments within revi- sions to the analytic model. • Conduct of the analysis, including the Monte Carlo simulations used in the risk analysis. • Preparation of the report describing the analysis and results. Case Closure The several cases in this chapter have provided many exam- ples of how engineering economic methods and data can be applied to investment decisions at a number of points in the life

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TRB’s National Cooperative Highway Research Program (NCHRP) Synthesis 424: Engineering Economic Analysis Practices for Highway Investment explores how U.S. transportation agencies have applied engineering economics--benefit–cost analyses and similar procedures--to decisions on highway investments.

TR News 292: May-June 2014 includes an article about the report.

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