Consequences of Delayed Maintenance of Highway Assets (2017)

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59 4.1 Research Contributions The major contribution of this research has been the development of procedures to quantify the consequences of delayed maintenance and support better-informed investment decisions for the preservation of highway assets. A three-step general framework describes the process developed in this study to quantify the consequences of delayed maintenance for the highway asset groups: Step 1. Define the asset preservation policy: 1.1. Identify the types of maintenance, 1.2. Establish performance objectives, and 1.3. Formulate decision criteria for maintenance activities. Step 2. Determine maintenance and budget needs: 2.1. Assess condition or remaining service life, 2.2. Select performance models to forecast condition and/or remaining life, and 2.3. Perform a needs analysis to identify maintenance activities to meet the established objectives. Step 3. Conduct analyses of delayed maintenance scenarios: 3.1. Formulate delayed asset maintenance scenarios, 3.2. For each scenario, perform the delayed maintenance scenario analysis, and 3.3. Determine the effects of delayed maintenance and report the consequences. Using the general framework and collective expert knowledge, the researchers developed proce- dures to address delayed maintenance for pavements, bridges, culverts, guardrails, lighting, pave- ment markings, and signs. The procedures consider agency preservation policies, performance measures, availability of asset condition data and maintenance records, and analytical tools. State-of-the-art maintenance practices and robust analytical methods for scenario analyses pro- vide the basis for the developed procedures. The procedures conclude with a discussion of reports to assist agencies in quantifying the consequences of delayed maintenance. The procedures have been prepared in a practical, adaptable, and easy-to-follow format with focus on implementation. They can be implemented using agency-specific analysis tools from existing management systems (e.g., PMS, BMS) or customized spreadsheet-based models (e.g., for guardrails, pavement markings, signs). Guidelines and recommendations for the development and/or selection of performance models and analytical tools for scenario analysis, including details of the examples developed for each highway asset group, are described in Appendices C through I. These examples are representative of typical highway asset information required for formulating preservation programs and demonstrate the feasibility of the procedure implemen- tation effort. C H A P T E R 4 Research Contributions and Suggestions

60 Consequences of Delayed Maintenance of Highway Assets 4.2 Quantifying the Consequences of Delayed Maintenance Comparing the outcomes of the agency-defined preservation policy with the outcomes of the delayed maintenance scenarios allows the agency to quantify the consequences of delayed maintenance. Performance models and analytical tools are used for this purpose. 4.2.1 Performance Models and Analytical Tools In practice, the most advanced management systems currently in use are for pavements (PMS), bridges (BMS), and culverts. PMSs and BMSs have unique performance models. Many PMSs incorporate deterministic models, with some systems also including probabilistic models. BMSs commonly employ probabilistic Markovian prediction models in which the bridge network con- dition is dependent on the previous condition. Bridge performance models can be adapted for culverts using a Markovian transition-condition model to predict the likelihood of changes to the culvert condition and simulate the effects of maintenance and culvert replacement actions. The development and use of analytical tools for lighting, guardrails, pavement markings, and signs is less mature. In addition, highway agencies may have limited maintenance records for lighting, guardrails, pavement markings, and signs. Data limitations on treatment application dates, type of treatment, cost, asset condition before and after treatment, and life expectancy make it challenging to development of performance models to quantify the consequences of mainte- nance strategies. Consequently, highway agencies typically rely on regular field inspections to formulate preservation programs for lighting, guardrails, pavement markings, and signs. Main- tenance is mainly corrective, and development of medium-term and long-term strategic man- agement plans exclude performance modeling. Individual asset components are simply replaced when they fail or when they are about to fail. Despite these limitations, performance models for guardrails, lighting, pavement markings, and signs can be developed based on straight-line deterioration (condition-based or age-based), Weibull survivor curves, or simplified Markov transition probability matrices. In this study, per- formance models for these highway asset groups follow a hybrid approach that combines data from selected state highway agencies and collective expert knowledge. For guardrails, a life-expectancy probabilistic model predicts the time of failure, with failure defined as “not functioning as intended.” For lighting, the model considers both HPS and LED lighting. The lighting model is also a life-expectancy probabilistic model and uses a Weibull dis- tribution to simulate failure of lights over time, as well as relamping of HPS and replacement of LED lights. Relamping can occur reactively as lamps fail, or proactively prior to lamp failure. For pavement markings and signs, the researchers recommend a transition-condition probabilistic model based on retroreflectivity or a life-expectancy probabilistic model. Table 31 summarizes the performance models and analytical tools recommended for each highway asset group as described in Chapter 3. Additional details are provided in the corre- sponding appendices. 4.2.2 Delayed Maintenance Scenarios The following maintenance scenarios are recommended to evaluate the consequences of delayed maintenance: • All needs. This scenario is based on the agency-preferred maintenance policy with no funding constraints. It serves as the “baseline” scenario because a baseline budget is estimated from this scenario.

Research Contributions and Suggestions 61 • Do nothing. This scenario includes no maintenance activities over the entire period of analysis. • Delayed maintenance. This scenario includes no maintenance activities over a specified extent of time, during which only rehabilitation or replacement work is performed. Two versions of this scenario can be considered: One approach includes performing all needed work imme- diately after the time delay has elapsed. The second approach is to apply a cyclical time delay Asset Group Data Performance Models Analytical Tools Corresponding Appendix Pavements Pavement network inventory with condition assessment Deterministic Probabilistic Bayesian Expert-based model Pavement management systems (PMSs) C Bridges Bridge network inventory with condition assessment Example: NBI data for all 50 states Probabilistic—Markov models Example: NBIAS default performance models Bridge management systems (BMSs) D Culverts NBI data on bridge- length culverts with condition assessment Prediction of culvert rating (0–9) using a probabilistic approach similar to the bridge model Culvert management systems (CMS) Spreadsheet- based analytical tool E Guardrails Guardrail system inventory with condition assessment Transition probability matrices to model the increase/decrease of deficient guardrails Spreadsheet- based analytical tool F Lighting Lighting system inventory with condition assessment Weibull models for predicting likelihood of lamp or electrical failure Straight-line loss of service life based on expected life Spreadsheet- based analytical tool G Pavement Markings Pavement markings inventory with condition assessment Weibull models for predicting pavement marking retroreflectivity failure Straight-line deterioration model Spreadsheet- based analytical tool H Signs Sign system inventory with condition assessment Transition probability matrices to model the increase/decrease of deficient signs Spreadsheet- based analytical tool I Table 31. Summary of performance models and analytical tools for highway asset groups.

62 Consequences of Delayed Maintenance of Highway Assets over the entire period of analysis. The duration of the time delay varies depending on the asset group, agency maintenance practices, and expected asset service life. • Budget driven with limited maintenance funds. This scenario involves using a percentage of the baseline budget (calculated in the all needs scenario) to perform the budget-driven scenarios. Funding allocations are prioritized through agency-defined criteria, and maintenance delays reflect the limitations of the budget following the priorities set by the criteria. Table 32 summarizes the maintenance scenarios considered in this study for pavements, bridges, culverts, guardrails, lighting, pavement markings, and signs. Detailed descriptions for each scenario and results are provided in their respective appendices. Table 33 provides recommended analysis periods for pavements, bridges, culverts, guardrails, pavement markings, and signs. These recommended analysis periods should be updated, as needed, based on agency experience. 4.3 Reporting the Consequences of Delayed Maintenance The reports used to communicate the consequences of delayed maintenance vary by man- agement levels. The three major management levels are strategic, network, and project. At the strategic level, management decisions include agency’s policies and funding allocation across the asset groups. At the network level, management decisions include allocating funding of maintenance and rehabilitation programs for individual asset components in the highway asset group (e.g., pavements, bridges). Finally, management decisions at the project level include applying the most cost-effective treatment for an individual component of the highway asset group (AASHTO 2012a). Reports to communicate the consequences of delayed maintenance differ to reflect the asset- specific decision information needs of each management level. At the strategic level, it is important to provide reports that can facilitate comparison of the consequences of delayed maintenance across asset groups so that management can evaluate the overall effect of the agency preservation policy. The decision-making process is less structured and speculative at the strategic management level; therefore, the information need not be as detailed as at the other management levels. At the network management level, decisions are made about funding of maintenance and rehabilitation programs for individual asset groups (e.g., pavements, bridges). At the project management level, the most cost-effective treatment is selected for each component of the asset group. Table 34 summarizes the main performance measures report categories recommended at the strategic and network management levels. Performance measures that are common to all asset groups and can be used to report the consequences of delayed maintenance in each of these categories include, but not limited, to the following: • Asset group condition: – At the beginning of the analysis, – At the end of the analysis, – At the critical year, and – Changes over time. • Asset group remaining service life (RSL): – At the beginning of the analysis, – At the end of the analysis, – At the critical year, and – Changes over time.

Pavements Bridges Culverts Guardrails Lighting Pavement Markings Signs 1. All needs (baseline) 2. Do nothing 3. Delayed mainte- nance with treat- ments delayed: a. By a set period of time (e.g., 2 years) b. Until pavement condition deteriorates beyond an established trigger value (treatment condition category) 4. Budget driven with limited funds, such as: a. 40% of annual baseline maintenance budget b. 80% of annual baseline maintenance budget 1. All needs (baseline) 2. Do nothing 3. Delayed mainte- nance a. Condition-based treatments delayed by 10 years b. Condition-based treatments delayed by 20 years c. Cyclical preventive maintenance delayed by X years 4. Budget driven with limited funds for maintenance 5. Maintenance performed only on selected bridge systems 6. Maintenance performed only if treatment activity meets a selected BCR or if asset condition falls below threshold condition 1. All needs (baseline) 2. Do nothing 3. Delayed mainte- nance with a. 5-year cyclical delay of maintenance treatments b. Maintenance treatments deferred but rehabilitation/ replacement treatments performed 4. Budget driven with limited funds a. 50% of annual baseline maintenance budget b. 80% of annual baseline maintenance budget 1. All needs (baseline) 2. Do nothing 3. Delayed mainte- nance with a. 1-year cyclical delay of maintenance treatments b. 3-year cyclical delay of maintenance treatments 4. Budget driven with limited funds a. 80% of annual baseline maintenance budget b. 55% of annual baseline maintenance budget 1. All needs (baseline), failed lamps replaced in 2 weeks with a. HPS-to-LED over 10 years (no addi- tional proactive replacements) b. HPS-to-LED over 10 years (plus pro- active replacements when failure proba- bility exceeds 90%) c. No proactive replace- ments (no additional HPS-to-LED conver- sions) 2. Do nothing (replace- ments deferred for 10 years) 3. Delayed maintenance (replacements deferred for 5 years)* 4. Budget driven with limited funds* a. 90% of failed lamps/fixtures replaced b. 75% of failed lamps/fixtures replaced c. 50% of failed lamps/fixtures replaced * No proactive replacements; no additional HPS-to- LED conversions 1. All needs (baseline) 2. Do nothing 3. Delayed mainte- nance with treat- ments delayed by a. 1-year cyclical delay b. 3-year cyclical delay 4. Budget driven with limited funds a. 80% of annual baseline main- tenance budget b. 40% of annual baseline main- tenance budget 1. All needs (baseline) 2. Do nothing 3. Delayed mainte- nance with treat- ments delayed by a. 1-year cyclical delay b. 3-year cyclical delay 4. Budget driven with limited funds a. 80% of annual baseline main- tenance budget b. 60% of annual baseline main- tenance budget Table 32. Summary of maintenance scenarios for highway asset groups.

64 Consequences of Delayed Maintenance of Highway Assets Asset Analysis Period Recommended Pavements 20 years or more Bridges 20 years or more Culverts 20 years or more Guardrails 10 to 20 years Lighting 5 to 10 years Pavement markings 5 to 10 years Signs 5 to 10 years Table 33. Length of analysis period recommended for asset groups based on service life. Performance Measure Report Category Pavement Bridge Culvert Guardrail Lighting Pavement Marking Signs Asset condition Remaining service life Agency costs Asset value Sustainability ratio Sustainability and users’ costs 1 Safety (e.g., accident costs) Mobility (e.g., travel time, operating costs) Environmental (e.g., CO2 emissions) 1 Reports may include users’ costs or sustainability performance measures only if data and analytical tools are available to estimate these parameters. Table 34. Summary of performance measures for strategic-level and network-level reports. • Agency costs: – Budget needs for the agency-defined preferred preservation policy or baseline scenario, – Agency total costs under each delayed maintenance scenario over the analysis period, and – Changes in the backlogged costs. • Asset group value: – At the beginning of the analysis, – At the end of the analysis, – At the critical year, and – Changes over time. Reports that show the consequences of delayed maintenance should fit with the highway agency’s policies and preferred performance measures. At present, reporting all performance measures may not be feasible for some agencies for certain asset groups. Further descriptions of performance measures recommended for the reports for each highway asset group are included in the corresponding appendices.

Research Contributions and Suggestions 65 4.4 Areas of Future Research The general framework presented in this report also can be used to quantify the consequences of delayed maintenance to other asset groups. Further investigation is suggested to apply the framework to the following asset groups: • Information technology system assets, • Traffic signals, • Overhead sign structures, • Barriers and impact attenuators, • Tunnels, • Slopes and embankments, • Retaining walls, • Noise walls, • Landscape features, • Cattle guards and fencing, • Curbs and gutters, • Sidewalks and bike paths, • Americans with Disabilities Act features, • Vehicles and equipment, • Weigh stations, • Pump houses, • Storage areas, • Maintenance depots, • Rest areas, and • Communication buildings. The future incorporation of additional performance measures could help agencies communicate the effects of delayed maintenance in a more comprehensive manner. For example, sustainability performance measures toward reaching agency goals in safety, mobility, and the environment also deserve further study to understand the broader consequences of delayed maintenance. It will also be valuable to study how to incorporate improved performance models as part of project designs. In design, understanding of asset maintenance costs can assist in performing life-cycle cost analysis and produce cost-effective designs. Future research also can consider how to better integrate project level decision-making with network and strategic-level management decision-making processes. Another area of future research is the development of benefit-cost analysis procedures that explicitly consider maintenance needs and assumptions to evaluate trade-offs in investments across asset groups and investment categories, and that illuminate the effects of chronic under- investment in maintenance. Given the current state of the practice, it is difficult to quantify the relative benefits of performing needed maintenance versus investing in new capacity or mak- ing other improvements. Current practice often assumes that (1) new assets built as part of a project will be maintained following best practices, and (2) deferrals of needed maintenance are short-term and will be addressed in the next funding cycle. These assumptions result in an under emphasis of maintenance and complicate attempts to analyze the trade-offs between investing in maintenance or new capacity. Future research also is suggested to investigate the effects of delayed maintenance on user costs. Travel time costs, operating costs, and accident costs influence user costs. The magnitude of the effect depends primarily on the number of users affected or the traffic volume carried by a particular section. Delayed maintenance is likely to cause larger disruptions, increasing user costs and the risk of asset failure, and potentially increasing public safety issues.

66 Consequences of Delayed Maintenance of Highway Assets Finally, a follow-up research effort could include an implementation phase to document the results of applying the framework developed in this study through a set of targeted case studies with selected state highway agencies. The case studies could provide practical examples of how the framework presented in this report can assist agencies in developing preservation policies, setting performance targets, determining current funding needs, and reporting the effects of delayed maintenance scenarios. The development of case studies and refined procedures could foster better-informed decision-making with the aim of improving the performance of the entire highway system.