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Return on Investment in Transportation Asset Management Systems and Practices (2018)

Chapter: Appendix B - Annotated Bibliography

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Suggested Citation:"Appendix B - Annotated Bibliography." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Appendix B - Annotated Bibliography." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Appendix B - Annotated Bibliography." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Appendix B - Annotated Bibliography." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Appendix B - Annotated Bibliography." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Appendix B - Annotated Bibliography." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Appendix B - Annotated Bibliography." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Appendix B - Annotated Bibliography." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Appendix B - Annotated Bibliography." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Appendix B - Annotated Bibliography." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Appendix B - Annotated Bibliography." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Appendix B - Annotated Bibliography." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Appendix B - Annotated Bibliography." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Appendix B - Annotated Bibliography." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Appendix B - Annotated Bibliography." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Appendix B - Annotated Bibliography." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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Suggested Citation:"Appendix B - Annotated Bibliography." National Academies of Sciences, Engineering, and Medicine. 2018. Return on Investment in Transportation Asset Management Systems and Practices. Washington, DC: The National Academies Press. doi: 10.17226/25017.
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123 A P P E N D I X B Annotated Bibliography This appendix provides additional detail on the materials reviewed for the research and summarized in Appendix A. AASHTO, “Pavement Management Guide,” 2nd Edition, 2012. The Guide describes the use of pavement management to assess current and future pavement condition, estimate funding needs to achieve target condition levels, identify optimal preservation and rehabilitation actions, illustrate the consequences of different investment levels and treatment strategies, justify increases in funding for pavements, and evaluate the long-term impacts of changes in material properties, construction practices, and design procedures. Chapter 2 of the Guide provides an overview of the components of a pavement management system; the use of pavement management at the project, network, and strategic levels; and the differences among the types of information used at each of the three levels. This chapter also discusses the benefits of using pavement management to support agency decisions. Chapter 3 covers inventory data collection and integration issues. It introduces several methods of integrating pavement management data, including the use of a geographic information system. Chapter 4 discusses methods for assessing the structural and functional condition of a pavement, including surface characteristics (e.g., pavement distress, longitudinal profile and roughness, and surface texture and friction), subsurface characteristics, and structural evaluation. The chapter also discusses new Highway Performance Monitoring System reporting requirements for data on cracking, rutting, and faulting as well as pavement data requirements associated with new mechanistic-empirical design procedures. Chapter 5 discusses the development and use of pavement performance models to analyze different funding scenarios, estimate changes in resource needs to address pavement deficiencies, and determine the best use of available funds. It also discusses the use of these models to evaluate new designs and mixes, to determine the benefit of preventive maintenance treatments, to support forensic analysis, to estimate remaining service life, and to calibrate mechanistic-empirical design models. Chapter 6 is focused on the project level. It illustrates methods used to develop treatment and impact rules. The treatment rules describe the conditions under which a treatment is considered feasible and impact rules describe the pavement performance that might be expected following the application of the treatment. Chapter 7 presents methods for using pavement management results to determine pavement needs, consequences associated with different strategies, and projects and treatments that make the best use of available funding. It also describes the use of pavement management in allocating funding, establishing performance targets, and long-term planning.

124 Return on Investment in Transportation Asset Management Systems and Practices Chapter 8 discusses the implementation of a pavement management system, including the different types of software available and institutional issues that agencies face in adopting pavement management practices. Chapter 9 discusses evolving issues such as national initiatives in sustainability and livability, and increased privatization of highway maintenance activities. AASHTO, “Transportation Asset Management Guide: Volume I,” prepared for NCHRP Project 20-24(11) by Cambridge Systematics, Parsons Brinckerhoff Quade & Douglas, Inc., Ray Jorgenson Associates, Inc. and Paul D. Thompson, November 2002. This Guide was designed to help DOTs and other agencies develop and apply the principles, techniques, and tools that can advance the management of transportation assets. Chapter 2 of the Guide presents a set of evaluation matrices that structure the concepts, principles, and “ideal practices” of asset management in four areas: Policy goals and objectives, including the role of policy formulation in asset management and ways in which policy guidance can benefit from improved asset management; Planning and programming, focusing on best practices in reaching decisions on resource allocation for investments in transportation infrastructure; Program delivery, looking at options in resource utilization and management methods to deliver programs and services; and Information and analysis, including use of information technology at each stage of asset management; monitoring of asset performance; and reporting of key results. The matrices indicate basic characteristics of good asset management practice applicable to transportation agencies, specific evaluation criteria for each characteristic, and the current state-of- the-art practice for each criterion. Chapter 3 provides a self-assessment exercise to assist agencies in identifying where they may wish to focus their asset management efforts. It is organized under the four areas listed above. It consists of a set of statements with possible responses ranging from “Strongly Agree” to “Strongly Disagree.” Based on the self-assessment, the Guide provides information on how agencies might focus their efforts to improve asset management. Chapter 4 provides guidance on developing an overall strategy to improve asset management, including setting the stage, designing the scope of asset management, roles and responsibilities, and building an action plan. Chapters 5, 6, 7, and 8 provide more detailed guidance on improving asset management in each of the four areas listed above. Chapter 9 deals with implementation issues. The Guide does not specifically deal with quantitative measures of the benefits of transportation asset management investments in better data collection, models, and other analytical tools. However, it does provide extensive qualitative criteria that might be considered as a starting point for developing quantitative measures. The matrices in Chapter 2 and the self-assessment statements in Chapter 3 may be especially useful in this regard.

Appendix B 125 AASHTO, “Transportation Asset Management Guide—A Focus on Implementation,” prepared for NCHRP Project 8-69 by AECOM, Spy Pond Partners, and Paul D. Thompson, 2011. This report takes the 2002 AASHTO Transportation Asset Management Guide as a starting point and focuses on practical steps for successful implementation. Chapter 1 provides an overview of the Guide and provides linkages to the concepts and frameworks from the 2002 report. Chapter 2 further develops the self-assessment approach from the 2002 report. It includes a gap analysis method for identifying specific improvement tasks relating to TAM business processes. Chapter 3 deals with organizational considerations, including the development of a change strategy, the integration of TAM into the organizational culture and business processes, the establishment of asset management roles, and performance standards. Chapter 4 describes the general structure of a transportation asset management plan and provides a guide to writing and updating it. Chapters 5, 6, and 7 focus on enabling processes and tools for service planning, life cycle management and asset preservation, and TAM integration. Chapter 8 deals with information systems and data. It addresses systems integration, information architecture, data structure, system selection and development, and data quality. Appendices of the report present case studies describing TAM implementation experience and products from Colorado, Missouri, New Zealand, and Wyoming. As with the 2002 Guide, this report does not specifically deal with quantitative measures of the benefits of transportation asset management investments in better data collection, models, and other analytical tools. However, this report provides an extensive discussion of key considerations in implementing these investments and how the results of these investments can be used to improve agency decisions and the quality of information available to all stakeholders. Akofio-Sowah, M., “Quantifying the Benefits of Ancillary Transportation Asset Management,” Master’s Thesis, Georgia Institute of Technology, December 2011. This thesis describes the state of practice of ancillary transportation asset management in the United States and discusses problems and opportunities for quantifying the benefits of improved procedures for managing these assets. The asset classes considered are culverts, earth retaining structures, guardrails, mitigation features, pavement markings, sidewalks and curbs, street lights, traffic signals, traffic signs and utilities and manholes. The thesis included both a literature review of current practice and a survey targeting state and local agencies identified from the literature as making significant progress with ancillary transportation asset management. It evaluated opportunities to quantify the benefits of ancillary transportation asset management based on a review of previously proposed methods and identified difficulties in applying benefit-cost analysis to this task. Amekudzi, A., Meyer, M., Akofio-Sowah, M., Boadi, R., “Comprehensive Transportation Asset Management: Making a Business Case and Prioritizing Assets for Inclusion in Formal Asset Management Programs,” Georgia DOT Research Project 10-21, December 2011. This report assesses the state of the practice in managing ten main ancillary transportation assets (culverts, earth retaining structures, guardrails, mitigation features, pavement markings, sidewalks and curbs, street lighting, traffic signals, traffic signs and utilities and manholes), and one information asset: data. A literature review and targeted survey were conducted to determine the

126 Return on Investment in Transportation Asset Management Systems and Practices state of the practice in ancillary TAM and collect data for the development of the evaluation framework. Very little was found on data collection costs and specific cost savings due to TAM systems implementation. The study found that making a business case for formal asset management programs is more meaningful when approached as an ongoing activity rather than a snapshot action because asset management programs are evolving and at different levels of maturity. At present, the data available for several programs is not adequate enough to conduct a comprehensive benefit-cost analysis of such programs. With regard to prioritizing assets for inclusion in a formal asset management program, the study recommends that the objective of the prioritization should be risk reduction relative to agency strategic goals. A risk framework is provided and data needs are outlined for conducting such an analysis adequately. The framework is illustrated using hypothetical data for culverts, guardrails, and traffic signals. Babinski, G., Fumia, D., Reynolds, T., Singh, P., Scott, T., Zerbe, R., “An Analysis of Benefits from Use of Geographic Information Systems by King County Washington,” Richard Zerbe and Associates, March 2012. This report presents the results of a return on investment (ROI) study of the development and use of geographic information systems by King County in Washington State. It includes benefits received from cost savings due to more efficient production of original output and benefits generated from increased productivity beyond the original production level. Benefits were estimated for the use of GIS by the Waste Water Treatment Division, other divisions of the Department of Natural Resources and Parks, Department of Transportation, Department of Assessment, and several other smaller departments. The analysis of benefits was based on a survey of 175 GIS professionals and users. Survey respondents were asked to estimate their “pre-GIS” and “with-GIS” levels of output and costs required to produce the output. The GIS users who responded to the survey included both managers and individual workers. The responses from managers were the primary source for estimating benefits since the managers’ estimates tended to be more conservative than the estimates produced by adding up responses from individual workers. The benefits due to more efficient production of original output were calculated as the original number of output units times the difference between the pre-GIS and with-GIS cost per unit. Two different approaches were used to calculate the benefits due to increases in the number of output units produced. In the first approach, these benefits were estimated as the product of (1) the difference in number of units produced and (2) the difference in cost per unit. In the second approach, the benefits from the first approach were cut in half. The second approach is consistent with the conventional use of consumer surplus to estimate benefits in economic efficiency analyses. Becker, S., McDaniel, T., and Baeverstad, E., “Development and Implementation of Highway Structures Information System for Wisconsin Department of Transportation,” Transportation Research Record, No. 1958 , 2006. This paper describes considerations leading to Wisconsin DOT’s decision to develop their Highway Structure Information System (HSI) and features of the new system. It includes an extensive discussion of problems with the pre-existing data structure and how they were addressed in developing the HSI. The paper does not attempt to quantify the benefits of the HSI. However, it

Appendix B 127 provides useful descriptions of how the HSI reduced the effort required for data collection and improved data quality and ease of use. Bernhardt, S., and McNeil, S., “Impacts of Condition Assessment Variability on Life Cycle Costs,” ASCE, 2006. This paper illustrates the effects of variability in the assessment of pavement condition on life cycle user and agency costs. A simulation model was run for 1,000 pavement segments, in which reported pavement conditions (measured in PCI) were assumed to differ from actual pavement conditions. It was assumed that: (1) initially, the PCIs of the segments were uniformly distributed in the range from 30 to 95, (2) when the reported (as distinct from the actual) PCI reached 30, the pavement would be rehabilitated, (3) the PCI of a newly rehabilitated pavement was 95, (4) actual PCI decreases linearly with time, and (5) user costs were calculated based on actual PCI while agency costs were based on reported PCI. Four scenarios were simulated: (1) reported PCI was 5% higher than actual PCI, (2) reported PCI was 5% lower than actual PCI, (3) the difference between reported and actual PCI was a uniformly distributed random variable ranging from -5% to +5% of actual PCI, and (4) the difference between reported and actual PCI was a uniformly distributed random variable ranging from -2.5% to +2.5%. Agency costs and user costs for each of the four scenarios were compared with a base case in which reported and actual PCI were assumed to be the same. Table B-1 summarizes the results: Table B-1. Agency and User Costs for Base Case and Scenarios. Scenario Reported PCI NPV Agency Costs ($/sq. m) NPV User Costs ($/sq. m) Equal to Actual (Base Case) 21,546 70,600 5% Higher than Actual 20,654 91,613 5% Lower than Actual 22,412 61,221 -5% to +5% of Actual 23,084 94,004 -2.5% to +2.5% of Actual 20,631 71,961 The results show the large effects of variability in pavement condition assessments, particularly on user costs. Interestingly, the table shows that the assumed maintenance and rehabilitation policies do not minimize total (agency plus user) life cycle costs. By underestimating actual PCI by 5%, user costs are reduced by about $8,400 while agency costs are increased by only about $1,100. This may reflect that the state of assets at the start of the analysis period impacts the outcome. Cambridge Systematics, “Best Practice Methodology for Calculating Return on Investment for Transportation Programs and Projects,” NCHRP Project 8-36, Task 62, September 2008.

128 Return on Investment in Transportation Asset Management Systems and Practices The purpose of this report is to develop best practice methodology for calculating ROI, emphasizing a more comprehensive set of factors and impacts to include within ROI analysis. It focuses on incorporating the concepts of: (1) life cycle costs, (2) travel-time reliability, (3) economic development and growth, and (4) public-private partnerships into ROI evaluations for transportation projects. The discussion of life cycle cost analysis emphasizes (1) the development of cost templates for estimating initial and future agency costs, (2) the refinement of cost estimates through planning, design, and engineering stages, (3) the development of a consistent set of unit costs across geographies and facility types, (4) relating future costs to asset age, and consideration of cost uncertainty. The discussion of travel-time reliability emphasizes the use of a buffer index concept. This is the additional time required to ensure on-time arrival 95% of the time, taking into account the variability of travel time. The discussion of economic development focuses on measures of net economic development including gross regional product and personal income impacts. It emphasizes the importance of avoiding double counting benefits and not including the economic development impact from construction and O&M costs. It also emphasizes the importance of geographic and jurisdictional perspectives in measuring economic development. The discussion of public-private partnerships emphasizes differences in public and private perspectives, requiring increased use of risk analysis and a multi-faceted evaluation framework. The report does not focus on estimating the ROI of transportation asset management investments to improve data collection technology and practices, forecasting models, and programming procedures. However, many of the report’s recommendations are applicable to calculating ROI for TAM, especially the emphasis on using templates for estimating agency costs and refining these costs through planning, design, and engineering. Also, the report describes tools and models that might be useful in TAM, including Bridge Life Cycle Cost Analysis (BLCCA), BridgeLCC, RealCost, HERS, IDAS, Pontis Bridge Management System, Caltrans BCA Tool, PennDOT Benefit/Cost Analysis spreadsheet tool, Priority Economic Analysis Tool (PEAT), and Washington DOT BCA Tool. Cambridge Systematics, Inc., with Meyer, M., “U. S. Domestic Scan Program: Best Practices in Transportation Asset Management SCAN-TOUR REPORT,” NCHRP Project 20-68, February 2007. The purpose of this scan was to identify best case examples of the application of asset management principles and practice in U.S. transportation agencies. The scan team met with a range of organizations, including state transportation agencies (Florida, Michigan, Minnesota, Ohio, Oregon, and Utah), a city transportation department (Portland, Oregon), metropolitan planning organizations (SEMCOG in Detroit and Grand Valley Metropolitan Council in Grand Rapids, Michigan), two county transportation departments (Hillsborough County, Florida and Kent County, Michigan), a tollway authority (Florida Turnpike Enterprise) and a statewide asset management association in Michigan. Michigan DOT and Ohio DOT provided quantitative estimates of TAM improvements. As a result of its system preservation strategy, Ohio showed very substantial decreases from 1997 to 2005 in the percentages of pavements with PCR less than 65 and in the percentages of deficient bridge square footage. Similarly, Michigan showed substantial improvements in pavement and bridge

Appendix B 129 conditions from 1996 to 2005. Information from the Michigan TAM was used by the governor and legislature in providing substantial increases in funding for pavement and bridge preservation in 1997. Crosswell, A., “Return on Investment in Information Technology: A Guide for Managers,” Center for Technology in Government, University at Albany, SUNY. August 2004. This report provides guidance on: (1) the strategic objectives of an ROI analysis, (2) the place of the proposed IT investment in the overall enterprise, (3) what data and methods of analysis are best suited to the objectives of the analysis, and (4) how the ROI analysis fits in the overall decision context for IT investments. The report describes four types of ROI analyses: (1) financial (Can we afford this? Will it pay for itself?); (2) effectiveness (How much “bang for the buck” will we get out of this project?); (3) efficiency (Is this the most I can get for this much investment?); and (4) impact (Will the benefits to society justify the overall investment in this project?). The report discusses the importance of understanding business processes that might be affected by the proposed IT investment and provides an overview of business process models and analysis methods. The models include agent-based, operations research and statistical, system dynamic, use case, and work flow modeling. De la Garza, J. M., Howerton, C. G., Sideris, D., “A Study of Implementation of IP-S2 Mobile Mapping Technology for Highway Asset Condition Assessment,” Virginia Tech. This paper presents a preliminary study of Topcon’s IP-S2 Mobile Mapping system. It compares the IP-S2 with the traditional data collection method in terms of the time to collect data and accuracy. Data were collected, processed, and analyzed for tenth-mile highway segments using traditional methods, IP-S2 at high speed (60-65 mph), and IP-S2 at low speed (15-20 mph). The types of assets were cross pipes, pipes and culverts (<36 ft2), paved ditches, storm drains/drop inlets, guardrail, signs and object markers. The three methods were compared in terms of time required. Also, the total number of assets and the number identified and assessed by IP-S2 were shown for each type of asset. Deighton Associates Limited, “Good Roads Cost Less: 2006 Study Update,” prepared for Utah Department of Transportation, 2006. This report presents an analysis of a large number of alternative strategies for maintaining and rehabilitating the UDOT highway network over a 20-year analysis period. The analysis was performed using UDOT’s dTIMS CT Pavement Management System. The strategies studied included Do Nothing, Maintenance Only, Reconstruction Only, Current Model, as well as other strategies that altered the timing of pavement preservation and rehabilitation activities, pavement condition levels, and funding levels. In addition to agency costs, the report estimated for each strategy safety costs, vehicle operating costs (including fuel and wear and tear on vehicles and tires), and delay costs associated with preservation and rehabilitation activities. The study found that reducing pavement budgets in the short term would reduce safety, increase vehicle operating costs, and increase delay. Also, future agency costs would be much higher.

130 Return on Investment in Transportation Asset Management Systems and Practices Dye Management Group, Inc., “Monitoring Highway Assets with Remote Technology,” Michigan Department of Transportation, July 2014. This report describes and evaluates remote technologies available for use when collecting data about attributes of twenty-seven MDOT priority assets. The technologies included mobile imaging, mobile imaging with LiDAR, and aerial imaging with LiDAR. Results obtained for remote technologies were compared with manual data collection. The alternatives were compared in terms of data collection costs per mile, with cost estimates for remote technologies provided by vendors. The quality of data provided by remote technologies was evaluated in qualitative terms. Based on the evaluation, the report presents recommendations to MDOT to provide guidance in the acquisition of such technologies. The report includes an assessment of asset priorities for data collection. The following metrics were applied to each of the 27 assets: (1) annual maintenances expenditures on the asset, (2) importance of the asset to the agency and road users, (3) relative data collection costs, and (4) data collection frequency required. A set of weights was used to combine results for the four metrics into an overall priority rating. Federal Highway Administration. “An Analysis of the Economic and Non-Economic Costs and Benefits of Implementing MAP-21 Asset Management Plans and Related Provisions,” 2015. This document presents a draft regulatory impact analysis (RIA) of a proposed rule that would establish a process for the development of state transportation asset plans and define minimum standards for pavement and bridge management systems. Note that as of the time of the review, the proposed rule was still under development, and over a dozen of the 58 comments received by FHWA on the proposed rule, including those from AASHTO, questioned the cost and benefit assumptions in the RIA. Commonly cited issues in the comment are the costs assumed by FHWA appear low, and that many agencies have already implemented an asset management approach, and thus have already gained the benefits projected by FHWA. As described in this document, the minimum contents of a MAP-21 asset management plan are: A summary listing of the pavement and bridge assets on the National Highway System in the state, including a description of the condition of those assets; Asset management objectives and measures; Performance gap identification; Life cycle cost and risk management analysis; A financial plan; and Investment strategies. As of when this document was written, no state has a transportation asset management plan, but nine were actively involved in developing such plans. All states have bridge management systems and all but four states have pavement management systems. The document presents estimates of the costs and benefits of developing asset management plans and pavement management systems (for those states that do not have a PMS). The benefit analysis includes quantitative estimates of benefits, breakeven analyses (described below), and descriptions of

Appendix B 131 qualitative benefits. The report also provides case study examples of instances where preventive maintenance actions for pavements and bridges provided savings relative to more costly actions. The benefits are quantified based on a 2004 Iowa study, which found that using pavement actions selected by a proposed pavement management system could achieve the same pavement condition that was achieved in practice at a savings of about $1 million per year for Iowa’s Interstates. The RIA assumed that, under the proposed rule, all states, DC, and Puerto Rico could save $1 million per year on average starting in the third year after implementation. With this assumption, the benefit-cost ratio of the proposed rules was 9.3 with a discount rate of 7% and 10.5 with a discount rate of 3%. A breakeven analysis was conducted to determine the number of road miles of poor pavement that would have to be improved to offset the costs of developing the asset management plan and purchasing a PMS. The savings due to driving on pavements in good (or better) condition vs. poor condition included reduced vehicle repair and maintenance cost, fuel consumption, and tire wear. The savings per vehicle mile were 0.78 cents for cars and 1.84 for trucks. It was found that improving 1.9% of the NHS miles currently in poor condition would offset the cost of the proposed rule. Another breakeven analysis was conducted to determine the number of year-long bridge postings that would have to be avoided to offset the costs of the proposed rule. Bridge posting costs were estimated based on the assumption that truck detours around weight posted bridges would be 20 miles. The costs included truck travel time (at $0.71 per vehicle mile) and operating costs (at $0.98 per vehicle mile). The analysis found that avoiding 0.17 year-long bridge postings could offset the cost of the proposed rule. Federal Transit Administration, “Asset Management Guide,” prepared by Parsons Brinckerhoff, 2012. The objectives of this Guide are to: Introduce key asset management concepts for transit agencies; Present an asset management framework and business model that define and communicate “best practice;” Provide guidance that can be used for assessing and advancing asset management maturity within any agency; and Include tools and case studies that support implementation. The transit asset management framework presented in the Guide has three categories of business processes: Processes that establish the organization-wide asset management policy and strategy and drive resource allocation; Life cycle management processes for individual asset classes, including managing inventory data, monitoring asset condition and performance, and developing life cycle management plans; and Cross-asset planning and management processes that consider information from all asset classes to support agency-wide capital programming and operations and maintenance budgeting.

132 Return on Investment in Transportation Asset Management Systems and Practices The Guide includes transit asset management case studies from the London Underground, King County Metro Transit (Seattle), Valley Regional Transit (Meridian, Idaho), MARTA (Atlanta), RTA and CTA (Chicago), Victoria Department of Transport (Australia), Massachusetts Bay Transportation Authority, Bay Area Rapid Transit District, and Valley Transportation Authority (Santa Clara, CA). The Implementation section of the Guide provides guidance on the development of an asset management plan, including key asset management activities, roles, and responsibilities. Appendix A of the Guide identifies the fundamentals that should be considered in the life cycle management of each asset class and provides information to support the development of an agency’s asset class specific life cycle management plans, including industry standards and life cycle principles associated with each asset class. Grussing, M., Uzarski, D., and Marrano, L., “Optimizing Facility Component Maintenance, Repair, and Restoration Investment Strategies Using Financial ROI Metrics and Consequence Analysis,” ASCE, 2006. This paper discusses the need for facility performance metrics that are: (1) affordable; (2) consistent, objective, and repeatable across different assessors; (3) engineering- and science-based; (4) correlated to physical condition, work requirements, and resource justification. The authors note that one single metric will not address all these requirements and recommend a collection of metrics including a condition index, a functionality index, a performance index, remaining service life, remaining maintenance life, component importance index, and mission dependency index. The condition index (CI) is the main metric discussed in the paper. The paper briefly describes the use of CI thresholds as the basis for determining candidates for corrective action, the evaluation of corrective work actions using curves in which component repair costs (as a percentage of replacement costs) increase as CI worsens, prioritization of work in the short term, and the development of a long-term maintenance, repair, and capital renewal plan for an organization. Harrison, F., and Mack, J., “Pavement Management System (PMS) Project Proposal,” Virginia Department of Transportation, September 2005. This Excel workbook presents a pavement management system (PMS) project proposal for the Commonwealth of Virginia. It includes an analysis of benefits and costs of PMS acquisition and implementation over a ten-year period. Most of the benefits result from cost savings due to increases in pavement life. These savings are estimated as 0.25% of Virginia’s $280 million annual budget for asphalt paving, based on national research showing savings from using a PMS to develop and implement a preventive maintenance program. Hendren, P., Asset Management in Planning and Operations: A Peer Exchange, Transportation Research Circular, No. E-C076, 2005. This report documents a peer exchange on September 7-8, 2004 sponsored by FHWA and conducted by TRB on Asset Management in Planning and Operations. Agencies participating in the peer exchange were asked how their organization is using asset management, benefits, barriers, and

Appendix B 133 recommended improvements. Three of the participating agencies provided quantitative estimates of the benefits of TAM. Michigan DOT showed significant statewide improvements in the remaining service life of pavements after the implementation of its asset management system. Jackson County Missouri showed significant improvements in pavement condition, number of employees required, accidents, complaints, and percent of total maintenance budget used for preventive maintenance. Ohio DOT showed substantial improvements in pavement condition for its priority highway system and in the condition of bridges. The quantitative measures provided by the three agencies in this report were based on time series data comparing conditions before and after the implementation of asset management systems. Hoekstra, R., and Breyer, J., “Multi-Level Linear Referencing System (MLLRS) Cost/Benefit Value Analysis Study,” requested by AASHTO, May 2011. This report documents a study of the costs and benefits of implementing and maintaining a statewide MLLRS. It is based on a value analysis study conducted at the Iowa Department of Transportation in 2011. Benefits were estimated for a baseline MLLRS and for two optional functional elements. Quantitative estimates of benefits were developed for GIS staff time savings, operational staff time savings, savings in administrative staff hours for other departments, safety improvements, reduced level of risk for litigation, reduced impacts to projects (construction), and reduced maintenance costs. The time savings for GIS staff, operational staff, and administrative staff for other departments were calculated as dollars per FTE. The other quantified benefits were calculated by applying percentages to budget expenditures. The cost-benefit analysis assumed that the state had at least 25,000 miles of road and already had a linear referencing system (LRS) in place. Yen, K. S., Ravani, B., and Lasky, T., “LiDAR for Data Efficiency,” Washington State Department of Transportation, September 2011. This report evaluates vehicle-mounted mobile Light Detection and Ranging (LiDAR) technology with a focus on collection, processing, and storage of the data in current WSDOT business processes. A field pilot study was conducted to collect empirical data for feasibility evaluation and cost-benefit analyses. Seven options for mobile LiDAR deployment were defined and evaluated. For each option, quantitative estimates of benefits were developed for three existing WSDOT data collection programs: Roadside Feature Inventory Program (RFIP), bridge clearance measurement, and ADA feature inventory. Quantified benefits included savings in FTEs, vehicles, and CO2 emissions. Other benefits of mobile LiDAR to these and other WSDOT data collection programs were presented in qualitative terms. Lawrie, M., “Intelligent Asset Management,” Thales Transportation Systems GmbH, November 2013. This paper discusses a condition based maintenance philosophy and describes the Intelligent Asset Management system as a means for implementing this philosophy. The paper includes a case study in which point machines on a busy mainline rail section were instrumented and the Intelligent Asset Management system was used for data acquisition, analysis, and decision support. The benefits of the system were measured using a before and after analysis of mean time between service affecting faults on the rail line.

134 Return on Investment in Transportation Asset Management Systems and Practices Markow, M., and Hyman, W., NCHRP Synthesis of Highway Practice 397: Bridge Management Systems for Transportation Agency Decision Making, 2009. This report provides information on current practices for making network-level investment and resource allocation decisions for bridge programs and the application of bridge management capabilities to support these decisions. It includes discussions of the following topics: Condition and performance measures that are used to define performance targets; Methods of establishing funding levels and identifying bridge needs; Methods and organizational responsibilities for resource allocation between the bridge program and other programs (pavement, safety, etc.); Methods of allocation among districts and selection and prioritization of projects; The role of automated bridge management systems in planning, programming, resource allocation, and budgeting; Use of economic analysis procedures in bridge management; and Methods to promote accountability and communication of the status of the bridge inventory and the bridge program. The report describes national bridge inspection standards and the national bridge inventory condition and appraisal ratings are described. It also describes the use of these ratings to identify structurally deficient and functionally obsolete bridges. The report also describes the use of Pontis (now AASHTOWare Bridge Management Software) in bridge management systems. At the time of the report, Pontis was licensed by over 40 states. McNeil, S., and Mizusawa, D., Measuring the Benefits of Implementing Asset Management Systems and Tools, Midwest Regional University Transportation Center, University of Wisconsin, Madison, 2008. This report documents the development of a generic methodology for quantifying the benefits derived from implementation of asset management systems. The generic methodology involves descriptive analysis, regression analysis, and benefit-cost analysis. The methods are applied in both ex ante and ex post facto evaluations. The report focuses on pavement management as a key element of asset management for transportation agencies. The report demonstrates the application of the methodology to two case studies: one involving the pavement management system used by the Vermont Agency of Transportation (VTrans) and one involving FHWA’s Highway Economic Requirements System-State Version (HERS-ST) applied to New Mexico data. HERS-ST is a highway investment/performance computer model, which determines the impact of alternative highway investment levels and program structures on highway conditions; performance; and agency, user, and external costs. The descriptive analysis portrays trends over time in performance measures (such as traffic-weighted average pavement condition by year) with and without the pavement management system. The regression analysis uses time series data on performance measures as the dependent variable. The independent variables might include AADT, length, M&R expenditures, etc. as well as a dummy (0

Appendix B 135 or 1) variable indicating whether or not there is a pavement management system. The benefit-cost analysis quantifies agency, user, and external costs and benefits in monetary terms. The VTrans case study demonstrated the descriptive and regression analyses. The effects on pavement condition of a “worst-first” strategy (the “without PMS” alternative) was compared with an optimal strategy as determined by application of the PMS (the “with PMS” alternative). The HERS-ST case study demonstrated the descriptive, regression, and benefit-cost analyses. In the case study, two scenarios were compared: a worst-first strategy and the strategy generated by HERS- ST. HERS-ST was then applied to calculate traffic-weighted pavement condition and agency, user, and external costs and benefits of implementing HERS-ST. An appendix to this report describes and evaluates six research papers published between 1997 and 2004 on methods for evaluating transportation asset management applications. The papers are summarized in terms of research strategy, data, model, results, and pros and cons. McNeil, S., Mizusawa, D., Rahimian, S., Bittner, J., Assessing and Interpreting the Benefits Derived from Implementing and Using Asset Management Systems, Project 06-06, Phase 2, Midwest Regional University Transportation Center, June 2011. This report presents a methodology for analyzing and communicating the benefits of an investment strategy based on HERS-ST with a naïve “worst-first” strategy. The benefits of using HERS-ST are quantified using net present value, benefit-cost ratio, and other performance measures such as average pavement condition, travel time, safety, and maintenance costs. The “worst-first” strategy is run first, using pavement condition triggers to select highway sections to be resurfaced or reconstructed. Expenditures from the “worst-first” run are then used as budget constraints in a HERS-ST run in which improvements are selected based on economic efficiency. The methodology is demonstrated for three case studies using data from New Mexico, Kentucky, and Delaware. The data from New Mexico are used to demonstrate strategies for communicating the analysis results using charts, graphs, and tables. A step-by-step guide for implementing the methodology and a training module are also presented. Nokes, W., du Plessis, L., Mahdavi, M., Burmas, N., Holland, T.J., Harvey, J., “Tools and Case Studies for Evaluating Benefits of Pavement Research,” 8th International Conference on Managing Pavement Assets. This paper presents a quantitative analysis of the benefits from Heavy Vehicle Simulator (HVS) testing of pavement rehabilitation alternatives. The case study evaluates benefits from research using accelerated pavement testing that validated expected performance of innovative mixes and designs before using them in rehabilitating a high-traffic urban interstate freeway in the Los Angeles area. Five rehabilitation alternatives were identified for the case study: (1) Caltrans Standard Crack & Seat Overlay (CSOL), (2) Innovative CSOL, (3) Caltrans Standard Full Depth Asphalt Concrete (FDAC), (4) Innovative FDAC, and (5) Portland Cement Concrete lane replacement. For each of these five alternatives, total life cycle costs were calculated based on methods and guidance in the Caltrans Life Cycle Cost Analysis Procedures manual and its accompanying RealCost software. The total life cycle costs were the same for the “Without HVS test” and “With HVS test” cases. However, the probabilities of implementing a given rehabilitation alternative were different depending on whether the HVS test was conducted. That is, the innovative rehabilitation alternatives, which had lower life

136 Return on Investment in Transportation Asset Management Systems and Practices cycle costs, were less likely to be selected without the HVS test. The probabilities of selecting a given alternative under the “Without HVS” and “With HVS” cases were discussed with pavement engineers who were familiar with the project and had first-hand knowledge of the HVS test and implementation of the research products. For the “With HVS” and “Without HVS” cases, expected costs were calculated by multiplying the total life cycle cost of each alternative by its probability of implementation and summing the result over all alternatives. The benefits of HVS testing were the difference between expected costs for the two cases. These benefits were adjusted downward to account for the fact that HVS testing was not solely responsible for cost savings. Specifically, estimates of the contribution of HVS ranged from 20% to 85%, in accord with input received in the interviews. Using these contribution percentages and high and low estimates of probabilities, the benefit-cost ratio for HVS test ranged from about 5 to 30. Perrin, J., and Dwivedi, R., “Need for Culvert Asset Management,” Transportation Research Record: Journal of the Transportation Research Board, No. 1957, 2006. This paper identifies benefits of improved asset management practices for culverts to transportation agencies and highway users. It surveys culvert asset management practices in individual states. It also presents several culvert failure case studies. Pickering, W., “Understanding the Whole Life Costs of Technology Projects in the Highway Market,” Smart Moving Conference, ITS Strategies and Potentials Session, Rail Safety and Standards Board, “Detailed Overview of Selected RCM Areas—RCM Toolkit,” prepared by Asset Management Consulting Limited, London, 2012. This report documents a toolkit and methodology for assessing the benefits and costs of remote condition monitoring (RCM) systems to inform rail industry decisions. It provides guidance for qualitative assessment of the relative strengths, weaknesses, opportunities, and threats (SWOT) of current and alternative future RCM systems. It also describes a methodology for quantifying the costs and benefits of possible improvements. The methodology involves compiling current total cost data for the risk related to safety, risk related to service (measured by performance penalties), and risk related to damage caused by the asset during incidents, repairing asset failures, and maintaining and renewing assets. Estimating these current costs (the relative “size of the prize”) provides an indication of the potential benefits that can be obtained by improvements in each area. The report provides current total costs for six topic areas: axle journal bearings, wheel impact loads, pantographs, overhead lines, ride monitoring, and third rail interfaces. RCM options were identified for five of the topic areas. For each option, the investment and total (including benefits) present values were reported for data acquisition/data collection/state detection, health assessment, prognostic assessment, and advisory generation. Schiffer, A., “Automated Asset Inventory System,” Arizona DOT, April 2006. This report explores options for implementing a barcode inventory system to track fixed assets for the Arizona DOT. It includes a description of Arizona DOT’s current fixed asset inventory process, a technology and literature review, and results from a pilot implementation. Benefits and costs were estimated based on the pilot implementation, including the extrapolated reduction in person-hours

Appendix B 137 required for physical inventory collection, acquisition cost for hardware and software, and annual maintenance expense. Spy Pond Partners, NCHRP Report 800: Successful Practices in GIS-Based Asset Management, 2015. The report provides guidance for building a business case for GIS/TAM investments and assessing ROI. It covers: (1) articulating the business need, (2) defining options for meeting the need, (3) identifying costs for each option, (4) identifying benefits for each option, (5) identifying risks, and (6) summing up findings. It provides an extensive list of possible business needs, costs, benefits, and risks associated with GIS/TAM investments. A case study for adding agency-wide geospatial capabilities for program development is presented. The options studied provided both efficiency benefits (measured in terms of reduced staff time requirements) and increased effectiveness (due to better information to support program development and project prioritization, as well as better communication with customers and political officials). The effectiveness benefits were not explicitly quantified. Rather, it was noted that net costs (costs minus efficiency benefits) were only about 0.06% of the agency’s pavement and bridge programs. It was clear that the effectiveness benefits were worth far more than the net costs given the opportunity they represented to spend the available funds more wisely. Transport Research Laboratory, Crowthorne House, Nine Mile Ride, Wokingham, Berkshire RG40 3GA United Kingdom, 2007. This paper describes a generic whole life cost (WLC) model for highway technology assets and identifies benefits of adopting the WLC approach. WLC is presented as a systematic approach for balancing initial and ongoing capital expenditure with the costs of operation and in-service support for the lifetime of the asset under consideration. The paper notes that WLC model results can be used as a decision support tool for designing and evaluating new systems, correcting in-service problems, guiding maintenance and replacement strategies, and forecasting future asset costs and system performance. The paper identifies WLC model requirements for technology equipment: Details of the systems and equipment to be modeled, including an identification scheme that provides unique and universal reference for asset equipment data on faults, location, connectivity, resources, etc.; Resources needed for asset operations, including labor, materials, and support locations; Fault data and capabilities for analyzing these data to determine fault frequency and causes; Procurement costs for renewals and replacements; Representation of contract penalties or bonuses based on performance; and Damage and deterioration costs, including damage due to vandalism, impact damage, and the degradation over time from environmental effects such as water ingress, temperature, and vibration.

138 Return on Investment in Transportation Asset Management Systems and Practices Vasquez, C., Heaslip, K., Louisell, W., “A Practice Proven Pavement Management System for Local Governments,” submitted for presentation and publication at the 89th Annual Meeting of the Transportation Research Board, Washington, D.C., 2010. The paper presents a case study of a pavement management system in the city of Tooele, Utah. It describes three pavement condition assessments that were performed for Tooele by the Utah Local Technical Assistance Program in the years 2000, 2004, and 2009. It presents budget allocations based on these assessments by pavement preservation strategy (Routine Maintenance, Preventive Maintenance, Rehabilitation, and Reconstruction). Of most interest in this literature review, it provides an economic analysis of no pavement management, partial pavement management, and full pavement management options for the city of Tooele. The “no pavement management” option consisted of applying complete base and pavement replacement after the road completely fails and no other preservation would be very effective. This option is expected to last for 12 years if no treatment is applied throughout the life of the pavement. The “partial pavement management” option consisted of applying preventive treatment 8 years after newly constructed and then completely replacing base and pavement after 6 more years. The “full pavement management” option consisted of applying preventive treatment 8 years after newly constructed, rehabilitation treatment 4 years later, and then applying complete base and pavement after 8 more years. Over 40 years, the net present value of future costs were about $75.6 million for the first option, $66.5 million for the second option, and $43.6 million for the third option. Veneziano, D., Fay, L., Ye, Z., Williams, D., Shi, X., “Development of a Toolkit for Cost- Benefit Analysis of Specific Winter Maintenance Practices, Equipment and Operations: Final Report,” prepared for the Wisconsin Department of Transportation and the Clear Roads Program, November 2010. This report describes the development of an online toolkit for benefit-cost analysis of the following winter maintenance practices, equipment, and operations: anti-icing, deicing, carbide blades, front plows, underbody plows, zero velocity spreaders, maintenance decision support systems (MDSS), Automatic Vehicle Location (AVL) and Geographic Positioning Systems (GPS), Road Weather Information Systems (RWIS), and mobile pavement or air/pavement temperature sensors. Four of these (MDSS, AVL/GPS, RWIS, and temperature sensors) are transportation asset management operations. The toolkit itself is available at http://clearroads.org/cba-toolkit/. For each item, the toolkit will calculate, discount, and sum up those benefits it can quantify, and will list other benefits it cannot. For MDSS, the quantified benefits are reduced material costs (estimated as 15% of base case material costs) and user savings due to improved safety and reduced traffic delay (also 15% of base case material costs). For AVL/GPS, the quantified user benefits are reduced operating cost (5% of base labor and vehicle costs) and reduced paperwork cost (10% of base paperwork cost). For road weather information systems, the quantified benefits are reduced agency costs (either 40% of material cost or 15% of labor and material cost) and improved safety (3% to 17% reduction in crash costs). For mobile air/pavement temperature sensors, the quantified benefits are reduced agency costs (11% to 14% reduction in salt use).

Appendix B 139 Wilde, J., Thompson, L., and Wood, T., “Cost-Effective Pavement Preservation Solutions for the Real Word,” Center for Transportation Research and Implementation, Minnesota State University, Mankato, September 2014. This report documents a project focused on the real-world application of pavement preservation techniques to extend the life of pavements. The project was initiated to investigate the types and methods of selecting pavement preservation techniques that are ongoing in Minnesota and to provide guidance and insight for local agency engineers and maintenance supervisors in the development of pavement preservation programs within their agencies. The report presents a summary of pavement preservation activities and recommended uses, expected longevity, and expected pavement life extension. It includes examples using real pavement engineering data from several cities and counties in Minnesota to demonstrate topics such as activity timing and the benefits of a preventive maintenance plan rather than a reactive one. The report does not attempt to quantify benefits of TAM investments in improved data collection and modeling capabilities. However, it does provide useful practical examples the effects of pavement preservation activities on pavement life. The report includes a section on estimating the costs and benefits of these activities, in which benefits are measured in terms of PSI-years (the area under a pavement performance curve in which PSI or present serviceability index is the y-axis and years is the x-axis). Ye, Z., Strong, C., Shi, X., Conger, S., and Huft, D., “Benefit-Cost Analysis of Maintenance Decision Support System,” Transportation Research Record: Journal of the Transportation Research Board, No. 2107, 2009. This paper presents the results of a benefit-cost study of a winter maintenance decision support system (MDSS). The MDSS evaluated was developed under a pooled fund study led by South Dakota. The MDSS is an integrated software application that provides users with real-time road treatment guidance for each maintenance route, addressing the fundamental questions of what, how much, and when according to the forecast road weather conditions, the resources available, and local rules of practice (the methods that a transportation agency uses in treating its roadways). Benefit-cost analysis was performed for two scenarios: one in which the same amounts of resources were used as in the base case, and one in which the same level of service was achieved as in the base case. In conducting the benefit-cost analysis, the MDSS itself was used to simulate conditions for the base case and the alternative scenarios. For the base case, existing maintenance practices were assumed; for the alternative scenarios, maintenance practices selected by the MDSS were assumed. Quantitative estimates of benefits included reductions in salt usage, crashes, and delays. To estimate both reductions in crashes and delays, adjustment factors to crash rates and speeds as a function of road conditions were used. For example, for deep slushy versus dry road conditions, crash rates were 75% higher and speeds were 16% lower. Other benefits of the MDSS, including reduced labor cost, equipment cost, response time, fleet replacement costs, infrastructure and vehicle damage due to road salts, and environmental degradation were noted, but not quantified.

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TRB's National Cooperative Highway Research Program (NCHRP) Research Report 866: Return on Investment in Transportation Asset Management Systems and Practices explores how transportation agencies manage their transportation assets, and provides guidance for evaluating the return on investment for adopting or expanding transportation asset management systems in an agency.

As the term is most generally used, transportation asset management (TAM) entails the activities a transportation agency undertakes to develop and maintain the system of facilities and equipment—physical assets such as pavements, bridges, signs, signals, and the like—for which it is responsible. Based on the research team’s work and the experiences of these agencies and others, the researchers describe a methodology that an agency may use to assess their own experience and to plan their investments in TAM system development or acquisition.

A spreadsheet accompanies the research report helps agencies evaluate the return-on-investment of TAM systems.The tool allows users to summarize data from various simulation tools. The calculator also includes factors and procedures from the Highway Economic Requirements System State Version (HERS-ST) to estimate user benefits for pavement projects. It does not estimate user benefits for bridge projects.

This software is offered as is, without warranty or promise of support of any kind either expressed or implied. Under no circumstance will the National Academy of Sciences, Engineering, and Medicine or the Transportation Research Board (collectively "TRB") be liable for any loss or damage caused by the installation or operation of this product. TRB makes no representation or warranty of any kind, expressed or implied, in fact or in law, including without limitation, the warranty of merchantability or the warranty of fitness for a particular purpose, and shall not in any case be liable for any consequential or special damages.

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