Transit Asset Condition Reporting (2011)

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41 Eight articles, papers, or reports were identified and judged important to this synthesis project. Seven publications document efforts to esti- mate transit capital needs at three different aggregation levels: 1. National. Two publications summarize efforts to estimate national transit needs. The AASHTO report (Cambridge Systematics, Inc. 2009) estimated national investment needs for both highways and public transportation. FTA’s Transit Economic Requirements Model (TERM) is described in the second paper (Laver 2009). FTA uses TERM estimates in its biennial report to Congress on the conditions and perfor- mance of transit. 2. State. Two publications describe the approaches used in Alabama (Anderson and Davenport 2005), and in Illinois (Booz Allen Hamilton 2003) to estimate statewide needs. The Illinois (Booz Allen Hamilton 2003) approach is also interest- ing in that needs assessments are also prepared for the indi- vidual transit systems. 3. Local systems. Three publications describe how the tran- sit systems in Boston (Massachusetts Bay Transportation Authority) (D’Allessandro et al. 2009; McCollom 2006) and Chicago (Regional Transportation Authority; RTA) (Yoder and Delaurentis 2003) have developed transit asset manage- ment systems in efforts to bring their systems to a State of Good Repair (SGR). The two publications about the Boston experi- ence cover the model development and initial application in 2001 (McCollom 2006) and the recent use of the approach in 2009 (D’Allessandro et al. 2009). The approaches described in these reports also varied in several respects including assets costs, SGR measure, and scenario testing (see Table D1). The last publication in the literature review, Transit State of Good Repair: Beginning the Dialogue, is a summary of a workshop that FTA recently held with 14 transit managers to discuss current practice in transit asset management. The report identified a number of techni- cal issues that need further research including: (1) the definition of state of good repair, (2) the effective use of condition ratings instead of just age, (3) the determination of optimal preventive maintenance, and (4) the estimation of the benefits (or consequences) of investment deci- sions on operating costs, reliability, and safety. The participants in the workshop stated that few transit systems used ordinal ranking or other methods for prioritizing their expan- sion, rehabilitation, and replacement investment needs. Instead, the needs typically are prioritized in meetings of agency department managers. They also expressed strong interest in learning more about the use of decision support tools as a means of assessing and prioritizing SGR needs. Anderson, M.D. and N.S. Davenport, A Rural Transit Asset Man- agement System, University Transportation Center for Alabama, Tuscaloosa, June 2005. This describes an Alabama Department of Transportation (DOT) asset management system used for transit vehicles purchased under the FTA Section 5310 and 5311 funding programs. According to the report, Alabama DOT uses the system to estimate the overall fleet quality, identify annual vehicle replacement needs, and to predict future funding and budgetary needs. The model employs regression analysis to predict the level of vehicle procurement necessary. It uses vehicle fleet characteristics including make, model, and year of manufacture; mileage; and capacity. The model assigns a vehicle condition rating based on: • Engine starting trouble • Engine running condition • Interior condition (upholstery damage, seats missing) • A/C condition • Wheelchair lift operation • Exterior condition • Mileage. The condition rating is a five-point scale: 1. Bad: Vehicle needs immediate replacement. 2. Poor: Vehicle should be replaced. 3. Fair: Vehicle is acceptable. 4. Good: Vehicle has no outstanding problems. 5. Excellent: Vehicle is in new condition. A series of regression models are tested using variables that included vehicle age, annual vehicle mileage, wheelchair accessi- bility, and population over 65 years of age. The results show that vehicle age is the best predictor of vehicle condition. Booz Allen Hamilton, Downstate Illinois Capital Needs Assess- ment, PowerPoint prepared for Illinois Public Transportation Association, funded by Illinois Department of Transportation, Springfield, Oct. 2003. Illinois DOT developed a capital asset needs model to estimate 10-year capital needs for “downstate” transit agencies—Illinois sys- tems located outside of the Chicago metropolitan area. The transit agencies completed a detailed survey of existing asset inventory (vehicle fleet and major facility components) and known investment needs. The data included asset ages, acquisition costs, and lifetime mileages. In addition, on-site capital cost data collection and inspections of asset physical conditions were conducted at five agencies—three urban and two rural systems. Historical cost data were collected for: • Facility construction and capital repairs • Annual capital expenditures on other needs such as security- related equipment, shelters, and radios • Annual operating and maintenance costs • Engine/transmission rebuilds. These onsite visits provided the data required to establish life- cycle cost curves for four types of buses and seven types of para- transit vehicles. The life-cycle costs included (Figure D1): • Original purchase (investment) cost • Lifetime rehabilitation costs (engine and transmission rebuilds, mid-life overhauls) • Annual operating and maintenance costs. A minimum cost replacement strategy was used to minimize total life-cycle costs. These costs were allocated over the life of a vehicle APPENDIX D Annotated Bibliography

42 D’Alessandro, D.F., P.D. Romary, L.J. Scannell, and B. Woliner, “MBTA Review,” Boston, Mass., Nov. 1, 2009. This summary is an update of the capital program using the SGR plan- ning process implemented by MBTA in 2001. It comments on the cur- rent backlog of projects and annual funding requirements as follows: For FY2010, over $3 billion worth of projects were identified by the MBTA as needed to address SGR issues. Only 15 of those 201 projects totaling $203M were funded. In other words, all but 6 percent of what was requested to address SGR issues went unfunded. Because it can fund only a small portion of the SGR backlog, MBTA prioritizes annual capital projects against predetermined cri- teria. Each project is scored with low to high priority to a maximum of 100, based on: • Safety • Health • Environment • SGR • Operations impact • Cost/benefit • Legal commitments. This paper suggests that the SGR planning process implemented by the MBTA in 2001 has and continues to be useful for estimating capital funding needs. However, the paper indicates that the MBTA has not used its methodology to prioritize annual capital projects. Laver, R., First FTA SGR Roundtable, Transit Economic Require- ments Model (TERM), PowerPoint presentation to the FTA First State of Good Repair Roundtable, Washington, D.C., July 10, 2009. This presentation gives an overview of the Transit Economic Require- ments Model (TERM). TERM is used to analyze current asset condi- tions with the objective of either maintaining condition or to improve condition and performance. TERM focuses on needs assessment—the replacement of assets and the expansion of the existing system. The presentation also describes how TERM is used to determine investment needs for reaching a SGR over specified time periods, based on funding level scenarios. FTA uses TERM in its biennial report to Congress on the conditions and performance of transit. TERM COMPONENTS The TERM model consists of: • Model database – Inventory of U.S. transit assets – Agency-mode operating characteristics Authors Geogra- phic Area Asset Costs SGR Measure Scenario Testing Replace- ment Mid- Life O&M Age Condition Ratings SGR Condition Service Performance Prioritized Funding Pisarski/Reno U.S. X X X X X X Laver U.S. X X X X X X Illinois DOT Illinois X X X X Anderson/Davenport Alabama X X X Yoder/Delaurentis Chicago X X X X X McCollom Boston X X X X X X on a per mile basis. The purchase and rehabilitation costs per mile decline over the life of the vehicle. In contrast, operating and main- tenance costs per mile tend to increase as a vehicle ages. When these divergent unit costs are combined to produce a total life-cycle cost curve, a minimum unit cost and its corresponding lifetime mileage can be determined (Figure D2). This lifetime mileage was used to establish when the vehicles should be replaced in the Illinois DOT capital needs model. In con- trast to vehicles, replacement needs for all facilities components were determined based on standard useful lives. The on-site data collection also provided the data required to evaluate the physical condition of downstate transit assets. The FTA vehicle decay curves (see Laver above) were recalibrated to reflect the Illinois experience. Illinois DOT has used the capital assets needs model annually since 2003 to estimate statewide capital needs. It also prepares needs assessments for the individual transit systems that they can use in their capital planning. Cambridge Systematics, Inc., A.E. Pisarski, and A.T. Reno, Bottom Line Technical Report: Highway and Public Transportation National and State Investment Needs, prepared for American Association of State Highway and Transportation Officials, Washington, D.C., Mar. 2009. The report addresses the types of public transportation capital needs including the: • Elimination of the backlog of vehicle needs and replacement; and • Rehabilitation of other existing transit assets, including track, signals, maintenance facilities, passenger stations, and pas- senger fare systems to bring transit systems to a SGR. Urban and rural systems are looked at separately. The analysis identified four different investment scenarios by applying combinations of physical conditions and service performance: 1. Maintain physical condition (insufficient funds to replace asset based on recommended service life). 2. Improve physical condition (sufficient funds to replace asset based on recommended service life). 3. Maintain service performance. 4. Improve service performance. The estimation models use an age-based approach to estimate SGR needs using data from the National Transit Database and other FTA sources. The analyses parallel prior biennial reporting from the U.S.DOT Condition and Performance Report to Congress. TABLE D1 SUMMARY OF ASSESSMENT APPROACHES IDENTIFIED IN LITERATURE REVIEW

43 – Urbanized areas demographics – Cost and investment benefits data by mode – User-defined investment scenarios – Asset rehabilitation and replacement polices – Budget constraints – Financial assumptions (inflation, discount rate). • Estimation of investment needs by type, mode, and urban area size. • Asset conditions forecasts. NEEDS INVESTMENT MODULE OVERVIEW The TERM model estimates national transit investment needs for six scenarios: 1. Rehab–Replacement (Maintain or Improve Condition): Total investment required for rehabilitation and replacement of the nation’s existing transit assets. 2. Asset Expansion (Maintain Performance): Total invest- ment in new, expansion assets as required maintaining exist- ing transit performance given projected growth in transit travel demand. 3. Reduce Crowding (Improve Performance I): Expansion investments to reduce crowding in local agency modes with high vehicle occupancies. 4. Increase Average Speed (Improve Performance II): Expansion investments in higher speed modes (heavy rail transit, light rail transit, or bus rapid transit) to improve per- formance in urbanized areas with low operating speeds. 5. Benefit-Cost I (Maintain/Improve Condition, Maintain Performance): Evaluates cost-effectiveness of rehab replacement and asset expansion investments. 6. Benefit-Cost II (Improve Performance): Evaluates cost- effectiveness of performance improvement investments. An Asset Decay Simulation methodology is used for the Rehab-Replacement scenario to make an SGR forecast and Assets Condition forecast. The methodology simulates the full asset life cycle and decay of all transit asset types based on the following factors: • Asset use (e.g., vehicle mileage, annual boardings, hours of service) • Annual maintenance • Aging (years of service) • Life-cycle events (capital maintenance, rehabs/rebuilds, and replacement). $5,0 $10,0 $15,0 $20,0 $25,0 $30,0 Co st p er M ile $0 00 00 00 00 00 00 0 200, Engine and Transmission Rebuilds 000 400,000 LTD Mile Transmission Rebuilds Engine Rebuilds 600,000 800,0 s 00 $ $5,00 $10,00 $15,00 $20,00 $25,00 $30,00 Co st p er M ile 0 0 0 0 0 0 0 0 200,000 400,000 LTD Miles Mid-Life Rehab 600,000 800,000 $0 $5 $10 $15 $20 $25 $30 Co st p er M ile 0 200,000 Initial Investment 400,000 6 LTD Miles 00,000 800,000 $1.20 $1.40 $1.60 $1.80 $2.00 $2.20 100,000 200,000 300,000 400,000 500,000 600,000 700,000 800,000 Minimum Cost Replacement FIGURE D1 Minimum cost replacement. FIGURE D2 Total life-cycle cost.

44 The analysis relies on: • A detailed transit asset inventory based on a five-point condition scale where 1 = poor condition and 5 = excellent condition. An asset reaches its mid-life when its condition rating = 3.5. An asset reaches the end of its useful life when its condition rating = 2.5 to 2.75. • Asset investment policy (timing of life-cycle events). • Empirically derived decay curves (predict asset condition based on asset type, age, maintenance and utilization). The analysis predicts current assets physical condition and timing/ cost of life-cycle events over the next 20 years. The aggregate physi- cal condition rating uses the five-point rating scale. McCollom, B., MBTA Systemwide Condition Assessment and Capital Investment Plan, presentation to the World Bank, Washing- ton, D.C., Mar. 28, 2006. This presentation discusses the Massachusetts Bay Transportation Authority’s SGR project. The objectives of the project were to demonstrate ongoing funding needs through an engineering assess- ment of current needs and to develop a long range capital planning model for project programming under limited funding availability. The model development focused on high-cost MBTA assets and did not try to establish a maintenance database of all assets. It also focused on the ability to run “what if” scenarios in a reasonable time frame—less than 5 minutes. The SGR scenario model inputs use annual budgets, asset table of key assets (vehicles, facilities, and systems), and condition mea- sures (age and life), and prioritization weighting scheme. The asset table lists three attribute areas: 1. “Condition” measures • Age • Life 2. Project “action” costs • Replacement/renewal • Contingency factors • Cash flow years 3. Ranking measures • Condition measures • Operational importance • Affected ridership. Candidate projects are then scored using a weighting scheme and based on the following: • Age (default weight 60%) – Age as a percent of service life. • Operational impact (default weight 20%) – Yes/no – Selected assets are essential to system operations – Critical projects include buses, track, signals, and power – Noncritical projects include stations, parking facilities. • Cost-effectiveness (default weight 20%) • Cost of action/ridership • Reflects customer service impacts. The methodology can be used to address the cost and timing of bring- ing and maintaining the system (existing assets) to a state of good repair. A baseline scenario is run that involves unconstrained funding availability. This establishes the minimum time and funds to reduce the backlog of projects and to maintain the transit system at SGR. Additional scenarios can be run that examine the consequences of constrained funding over a 20-year planning period. These con- sequences include a summary of asset actions (replacement or mid- life maintenance) funded on-time, later than scheduled, or not at all, and changes in the backlog of actions throughout the period. The presentation also suggests potential enhancements to the model. These include the use of decay curves based on a preventive maintenance program, treatment of multi-year funding of projects, and deferral of a portion of a project cost if insufficient funds are available. Transit State of Good Repair: Beginning the Dialogue, Federal Transit Administration, U.S. Department of Transportation, Wash- ington, D.C., Oct. 2008. FTA convened 14 representatives of transit systems and state DOTs in 2008 to discuss transit asset management and SGR at their agen- cies and what is needed to resolve critical capital needs. The intent was both to measure the extent of the problem and to look at cre- ative financing for maintaining and upgrading aging assets. Topics discussed included capital needs and financing for aging transit infrastructure, defining SGR, inventory and tracking of transit assets, maintenance/preventive maintenance practices and standards, and tools and research needed to address SGR. Seven papers are presented in the report covering: • Current conditions of the nation’s transit infrastructure • Defining and measuring state of good repair • Transit asset management • Standards for preventive maintenance • Core capacity of a transit system • Alternative approaches to financing • Research needs. The report documents that one-quarter of the nation’s bus and rail assets are in marginal or poor condition and the proportion increases to one-third in the nation’s largest rail systems. FTA estimates “. . . the total level of investment required to bring the nation’s bus and rail assets to a state of good repair is currently estimated at $25 billion ($ 2004) . . . [and that] . . . after eliminating the backlog, an additional $9 to $11 billion from all sources is required annually to maintain this state of good repair into the future.” The report identified a number of technical issues that need fur- ther research including: (1) the definition of state of good repair, (2) the effective use of condition ratings instead of just age, (3) the determination of optimal preventive maintenance, and (4) the esti- mation of the benefits (or consequences) of investment decisions on operating costs, reliability, and safety. The participants in the workshop stated that few transit systems used ordinal ranking or other methods for prioritizing their expan- sion, rehabilitation, and replacement investment needs. Instead, the needs typically are prioritized in meetings of agency department managers. They also expressed strong interest in learning more about the use of decision support tools as a means of assessing and priori- tizing SGR needs. Yoder, S.L. and J. Delaurentis, “The Framework for a Regional Transit Asset Management System,” ITE Journal, Institute of Trans- portation Engineers, Washington, D.C., Sep. 2003, pp. 2–3. This paper describes the efforts by the Regional Transportation Authority (RTA) to develop a framework for overseeing public transit funding in the six-county Chicago area. The RTA is not a transit oper- ator, but is legislatively responsible for fiscal planning and policy

45 oversight. To improve its oversight ability, in 2000 it laid out the framework for a regional transit asset management system (RTAMS). The RTAMS goals were to give RTA management the data and tools to support decision making on transit asset management strate- gies and investment tradeoffs. Five goals in particular emphasized the information base and analytical tools: 1. Provide multimedia retrieval on asset locations, conditions, usage, performance, capital projects, and maintenance prac- tices of the RTA system regardless of ownership. 2. Enable RTA to comprehensively analyze, maintain, and manage transit information. 3. Enable RTA to prioritize capital investments and capital replacement needs. 4. Develop applications and simulation tools linking to the RTA budgetary process and financial reporting requirements. 5. Develop data mining tools capable of simulating “what if” scenarios. In the planning process five transit asset management system func- tions were identified. The first function is a Multimedia Integrated Data Warehouse, including a condition rating of each asset containing: • Asset locations (e.g., for a rail station would have physical description of layout, escalators, entrances, and fare collec- tion equipment); • Conditions (e.g., station age, capital project descriptions, routine and preventive maintenance practices, and asset con- dition ratings); • Usage (e.g., rail station boardings and alightings, connecting transit lines, park-n-ride, fares, and schedules); and • Capital improvement information (e.g., asset performance information—station ridership ranking, on time-performance, and asset demand information for prioritizing capital investment including user profiles, adjacent land uses, station area development patterns, vicinity maps, tourist attractions, and demographics surrounding the station areas). Another function was scenario simulations. This built on earlier work during the 1990s that developed decay curves based on the compilation and analysis of the CTA engineering assessment data and asset purchasing information and maintenance records. The curves depict the relationship among asset condition, useful life, and maintenance practices. Using the decay curves, future asset conditions can be predicted given the asset age and maintenance practices. Therefore, the decay curves were the principal input for developing a life-cycle capital replacement/renewal tool. This tool permits RTA to simulate “what if” scenarios, answering questions such as: • What is the trade-off between maintenance cost and capital renewal cost? • Is it better to replace or repair a certain asset category? • How much capital funding is required for the next 10 years to bring all assets from poor condition to good condition? • To what condition will an asset deteriorate if no additional funding is provided?