Final_Report_1.pdf

Identification of Effective Next Generation Pavement Performance Measures and Asset Management

Methodologies to Support MAP-21 Performance Management Requirements

Volume 1: Pavement Performance Measures Final Report

Submitted to:

Research, Development, and Technology

Turner-Fairbank Highway Research Center 6300 Georgetown Pike

McLean, VA 22101-2296

Submitted by:

1015 Half Street SE, Suite 650

Washington DC, 20003

January 17, 2017 ii

Notice

This document is disseminated under the sponsorship of the U.S.

Department of Transportation in the interest of information exchange.

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Technical Report Documentation Page

1. Report No.

2. Government Accession No.

3. Recipient’s Catalog No.

4. Title and Subtitle Identification of Effective Next Generation Pavement Performance Measures and Asset Management Methodologies to Support MAP-21 Performance Management Requirements. Volume 1: Pavement Performance Measures

5. Report Date January 2017

6. Performing Organization Code

7. Author(s) Suri Sadasivam and Jagannath Mallela WSP | Parsons Brinckerhoff

Leslie Titus-Glover, Consultant

8. Performing Organization Report No.

9. Performing Organization Name And Address WSP | Parsons Brinckerhoff 1015 Half St SE, Suite 650 Washington, DC 20590

10. Work Unit No. (TRAIS)

11. Contract or Grant No.

DTFH6115C00043

12. Sponsoring Agency Name and Address Federal Highway Administration Research, Development, and Technology Turner-Fairbank Highway Research Center 6300 Georgetown Pike, McLean, VA 22101-2296

13. Type of Report and Period Covered September 2015-January 2017

14. Sponsoring Agency Code

15. Supplementary Notes Contracting Officer’s Technical Representative: Nadarajah Sivaneswaran

16. Abstract Pavement condition is measured using condition indicators that capture surface deformation and structural deterioration, which are then aggregated and reported using a composite index for pavement management applications. The pavement condition indices have served reasonably to characterize both the structural and functional condition of the pavement. However, these indices fall short in capturing the structural health over the whole life of the pavement. In this context, there is a need for the next generation pavement measures that capture the life-cycle perspective of pavements, consider the consequences of both past and future actions, distinguish between the competing needs of service delivery and investment needs, and provide insights into long-term performance and funding needs. The objectives of this study are (i) to identify or conceptually develop a more strategic pavement performance measure(s) to ensure effective and timely assessment of investments that will “maintain the highway infrastructure asset system in a state of good repair in relation to pavement assets” and (ii) identify or conceptually develop methodologies to guide full implementation of comprehensive asset management. This study proposes four sets of pavement performance measures: remaining service life to surface repairs, remaining service life to structural rehabilitation, remaining service life to reconstruction, life-cycle cost metrics (annualized cost per lane-mile, cost accrual ratio).

17. Key Words Pavement performance measures, life-cycle, asset management, state of good repair, maintenance, preservation and rehabilitation, life-cycle cost analysis, structural integrity, surface condition, deflections

18. Distribution Statement No restrictions

19. Security Classif. (of this report) Unclassified

20. Security Classif. (of this page) Unclassified

21. No. of Pages

22. Price N/A

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized iv

SI* (MODERN METRIC) CONVERSION FACTORS

Approximate Conversions to SI Units Symbol When You Know Multiply By To Find Symbol

Length in inches 25.4 millimeters mm ft feet 0.305 meters m yd yards 0.914 meters m mi miles 1.61 kilometers km

Area in2 square inches 645.2 square millimeters mm2 ft2 square feet 0.093 square meters m2 yd2 square yard 0.836 square meters m2 ac acres 0.405 hectares ha mi2 square miles 2.59 square kilometers km2

Volume fl oz fluid ounces 29.57 milliliters mL gal gallons 3.785 liters L ft3 cubic feet 0.028 cubic meters m3 yd3 cubic yards 0.765 cubic meters m3

NOTE: volumes greater than 1000 L shall be shown in m3 Mass oz ounces 28.35 grams g lb pounds 0.454 kilograms kg T short tons (2000 lb) 0.907 megagrams (or "metric ton") Mg (or "t")

Temperature (exact degrees) °F Fahrenheit 5 (F-32)/9 or (F-32)/1.8 Celsius °C

Approximate Conversions from SI Units

Symbol When You Know Multiply By To Find Symbol Length mm millimeters 0.039 inches in m meters 3.28 feet ft m meters 1.09 yards yd km kilometers 0.621 miles mi

Area mm2 square millimeters 0.0016 square inches in2 m2 square meters 10.764 square feet ft2 m2 square meters 1.195 square yards yd2 ha hectares 2.47 acres ac km2 square kilometers 0.386 square miles mi2

Volume mL milliliters 0.034 fluid ounces fl oz L liters 0.264 gallons gal m3 cubic meters 35.314 cubic feet ft3 m3 cubic meters 1.307 cubic yards yd3

Mass g grams 0.035 ounces oz kg kilograms 2.202 pounds lb Mg (or "t") megagrams (or "metric ton") 1.103 short tons (2000 lb) T

Temperature (exact degrees) °C Celsius 1.8C+32 Fahrenheit °F v

TABLE OF CONTENTS

EXECUTIVE SUMMARY ........................................................................................................ XI

CHAPTER 1. INTRODUCTION

BACKGROUND

Pavement Performance Measures

Transportation Asset Management Plan

STUDY OBJECTIVES

REPORT ORGANIZATION

CHAPTER 2. ASSET PERFORMANCE AND STATE OF GOOD REPAIR

PRINCIPLES OF PERFORMANCE AND ASSET MANAGEMENT

Performance Management

Link to Asset Management

MAP-21 and Asset Management

STATE OF GOOD REPAIR

Defining the State of Good Repair

State of Good Repair for Pavement Assets

PAVEMENT PERFORMANCE MEASURES FOR STAKEHOLDERS

Information for Pavement Performance Measurement

CHAPTER 3. PAVEMENT PERFORMANCE MEASURES – STATE OF THE

PRACTICE

HISTORICAL OVERVIEW OF PAVEMENT PERFORMANCE MEASURES

STATE OF THE PRACTICE

National Condition Data Collection and Processing—State of the Practice

STATE-OF-THE-PRACTICE INTERNATIONAL

EMERGING PAVEMENT MEASURES

Surface Image and Laser Scanning-based Technologies

Continuous Deflection Devices

Ground Penetrating Radar

Others

ANALYSIS OF EXISTING MEASURES

State of the Practice: Performance Measures for Strategic and Tactical Decision Making . 36 vi

TABLE OF CONTENTS

CHAPTER 4. PROPOSED STRATEGIC PAVEMENT PERFORMANCE MEASURES

OVERVIEW OF CONCEPTS

Requirements of the Strategic Measures

Planning Framework—More than Measures

FRAMEWORK TO SUPPORT STRATEGIC PERFORMANCE MEASURES

PROPOSED PERFORMANCE MEASURES FOR PAVEMENTS

Remaining Service Interval to Surface Repair

Remaining Service Interval to Structural Rehabilitation

Remaining Service Interval to Reconstruction

Life-Cycle Cost Measures

Example

CHAPTER 5. INTEGRATION OF PROPOSED MEASURES FOR PAVEMENT

MANAGEMENT DECISION MAKING

IMPLEMENTING PROPOSED PAVEMENT MEASURES

Applications of Proposed Performance Measures At the Project Level

STATE DOT CASE STUDIES

Utah Department of Transportation (UDOT)

Minnesota Department of Transportation (MnDOT)

Mississippi Department of Transportation (MDOT)

CHAPTER 6. CONCLUSIONS AND RECOMMENDATIONS FOR FUTURE WORK .

SUMMARY AND CONCLUSIONS

RECOMMENDATIONS FOR FUTURE WORK

REFERENCES

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LIST OF FIGURES

Figure 1. Generic framework of a typical pavement management system (Hass et al, 2015) Figure 2. Siloed vs. integrated resource allocation proposed by NCHRP Project 8-91 Figure 3. Hierarchical structure linking policy objectives to performance indicators and implementation targets Figure 4. Interaction of stakeholder’s goals (Haas 2003) Figure 5. Information flow at different hierarchical levels Figure 6. Flowchart showing development of performance indicators in the COST 354 Figure 7. Framework for processing 3D imaging and transverse profile data Figure 8. Typical Pavement Lifecycle Stages Figure 9. Example pavement life-cycle plan Figure 10. Schematic of proposed framework for pavement life-cycle planning Figure 11. Schematic illustrating RSI to surface repair Figure 12. Schematic illustrating RSI to structural rehabilitation Figure 13. Schematic illustrating RSI to reconstruction Figure 14. Schematic showing the annualizing schema to compute real annualized costs Figure 15. Schematic comparing real and overall annualized costs Figure 16. Example comparing two cost accrual approaches Figure 17. Timeline of XYZ DOT’S MP&R plan with no preventive maintenance Figure 18. Pavement surface condition of XYZ DOT’s MP&R plan with no preventive maintenance Figure 19. Pavement structural health of XYZ DOT’s MP&R plan with no preventive maintenance Figure 20. NPV of XYZ DOT’s life-cycle investments for a MP&R plan with no preventive maintenance Figure 21. Annualized costs of XYZ dot’s life-cycle investments for a MP&R plan with no preventive maintenance Figure 22. Timeline of XYZ DOT’s MP&R plan with preventive maintenance Figure 23. Pavement surface condition of XYZ DOT’s MP&R plan with preventive maintenance Figure 24. Pavement structural health of XYZ DOT’s MP&R plan with preventive maintenance.

Figure 25. NPV of XYZ DOT’s life-cycle investments for a MP&R plan with preventive maintenance Figure 26. Annualized costs of XYZ DOT’s life-cycle investments for a MP&R Plan with preventive maintenance Figure 27. Comparison of XYZ DOT’s life-cycle investments for a MP&R plan with and without preventive maintenance Figure 28. Cost accrual of XYZ DOT’s investments over minimum practicable life-cycle cost. 72 Figure 29. Sample MP&R treatment matrix Figure 30. MnDOT MP&R strategy decision tree for for flexible pavements Figure 31. MissDOT decision tree for determining treatment option for flexible pavements viii

LIST OF TABLES

Table 1. MAP-21 performance goals Table 2. Stakeholders and associated performance indicators Table 3. Summary of recent initiatives to standardize and improve pavement condition performance Table 4. Proposed NPRM pavement performance measures, targets, and reporting Table 5. State DOT measures for determining and reporting pavement condition (summarized from Papagiannakis et al. 2009) Table 6. Measures for characterizing pavement structural and functional condition Table 7. AUSTROADS measures for determining and reporting pavement condition Table 8. Example rating criteria for pavement surface condition Table 9. Example rating criteria for pavement structural health Table 10. XYZ DOT’s MP&R plan with no preventive maintenance strategy for life-cycle management of pavements Table 11. Cost analysis of XYZ DOT’s MP&R plan with no preventive maintenance Table 12. Cost analysis of analysis with a hypothetical “do-nothing” strategy Table 13. XYZ DOT’s MP&R plan with preventive maintenance strategy for life-cycle management of pavements Table 14. Cost analysis of XYZ DOT’s MP&R plan with preventive maintenance Table 15. Comparison of XYZDOT’s MP&R Plans Table 16. Sample performance thresholds for flexible pavements Table 17. Broad categories of MP&R treatments and their purpose Table 18. Typical costs per lane-mile assumed in HERS, by type of improvement Table 19. Distress indices captured in the Utah DOT dTIMS pavement modeling system Table 20. Empirical formulations for distress and composite indices used within the UDOT dTIMS pavement modeling system Table 21. UDOT’s condition triggers for various rehabilitation and reconstruction treatments. . 84 Table 22. MnDOT pavement condition indices Table 23. Pavement distress types and individual distress weighting factors used to determine

Surface Rating Table 24. Mississippi DOT PCR coefficients ix

LIST OF ABBREVIATIONS

AASHTO American Association of State Highway and Transportation Officials CRCP Continually Reinforced Concrete Pavement DOT Department of Transportation EUAC Equivalent Uniform Annual Cost FHWA Federal Highway Administration GPR Ground Penetration Radar HERS Highway Economic Requirements System HMA Hot Mix Asphalt IRI International Roughness Index LCCA Life-Cycle Cost Analysis MAP-21 Moving Ahead for Progress in the 21st Century Act MDOT Mississippi Department of Transportation MnDOT Minnesota Department of Transportation MP&R Maintenance, Preservation, and Rehabilitation NCHRP National Cooperative Research Program NPRM Notice of Proposed Rulemaking NPV Net Present Value OCI Overall Condition Index PCI Pavement Condition Index PCR Pavement Condition Rating PSC Pavement Structural Condition PSI Present Serviceability Index PSR Present Serviceability Rating RSI Remaining Service Interval RSL Remaining Service Life SGR State of Good Repair TAM Transportation Asset Management UDOT Utah Department of Transportation x xi

EXECUTIVE SUMMARY

Pavement condition is a critical piece of information that every highway agency needs to achieve the objectives of pavement management. Pavement condition captures and communicates to stakeholders how well the pavement is serving its intended purpose of providing a smooth, safe, and comfortable riding surface. Pavement condition is measured using condition indicators that capture surface deformation and structural deterioration, which are then aggregated and reported using a composite index for pavement management applications. The condition indices are typically fed into a data-driven analysis, such as deterioration modeling, to identify future Maintenance, Preservation, and Rehabilitation (MP&R) strategies, investment needs, and their timing at the project level. At the network level, they measure the current system-level performance, prioritize programming, and analyze the consequences of budget decisions.

In spite of the diversified practices of most highway agencies, most derive an overall pavement condition index that aggregates key surface distresses and smoothness. To date, the pavement condition indices have served reasonably well in characterizing the composite condition of a pavement’s structural and functional state. However, as performance measures, these indices rely too heavily on the current pavement condition and fall short in capturing the long-term structural integrity or health of the pavement. In general, structural health is inferred from an analysis of distresses that are caused by structural factors as well as those that contribute to structural deterioration. For example, these indices seldom discriminate between two pavements that have similar surface conditions but were built along different timelines to provide adequate insights about the future investment needs and performance risks. In this sense, the condition indices are “output” oriented and lagging indicators of the investments already made, as they do not directly convey insight on long-term performance and investment needs.

Some agencies have extended pavement condition indices to forecast the remaining service interval (RSI). RSI is based on identifying a structured sequence of the type and timing of various intensities of repair and replacement actions required to provide the desired levels of service to users over the asset life-cycle at minimum practicable costs. RSI provides a framework to incorporate a whole life perspective in determining future repair and replacement actions (i.e., considering both current condition and past actions in determining and future actions, performance risks, and investment needs). In essence, RSI provides an optimum life-cycle management plan that makes assets serviceable to users at lowest lifecycle costs. The accuracy of RSI is a reflection of the mix of “performance indicators” used in forecasting of future performance, and repair and replacement actions, and investment needs. In other words, the RSI is very much dependent on what “conditions” are captured (lagging or leading) and how they are aggregated in the performance indicator. Conventional wisdom suggests that utilization of new technologies such as continuous deflection measurement devices, MIT Scan, GPR, etc. along with construction QA test data will provide more accurate estimates of RSI.

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Through the definition of the term “asset management,” the Moving Ahead for Progress in the 21st Century Act (MAP-21) legislation introduces the concept of the State of Good Repair (SGR) and places further emphasis on achieving and sustaining a desired SGR for physical assets at minimum practicable cost over their life-cycle. While the RSI provides an analytical framework to achieve pavement SGR at minimum practicable life-cycle costs, it becomes equally paramount to connect the analytical framework with the business objectives of an agency’s pavement program and use that to identify the next generation set of pavement performance measures.

The pavement program of any highway agency has the following foundational business objectives:

• Customer focus—Address all needs to maintain pavement assets in a condition necessary to deliver the desired levels of service to users in terms of providing a smooth, safe, and rideable pavement surface for vehicular traffic

• Fiscal stewardship—Consistent with the agency’s fiduciary duties, sustain the service potential through efficient utilization and life-cycle management of assets at minimum practicable cost and, accordingly, manage risks that may affect the preservation of asset value

• Process efficiency—Utilize investments to achieve, sustain, or maximize level of service at the system level and reduce the backlog of pavement MP&R needs

In this context, this study defines the SGR as follows: An asset is in a state of good repair if its condition is at a level where it is feasible to maintain a lowest life-cycle cost strategy; however, the asset ceases to exist in a state of good repair if the opportunities to minimize life-cycle cost through maintenance, preservation and rehabilitation have been lost because of deterioration.”

This definition focuses on devising an effective life-cycle management plan at minimum practicable costs without compromising on the delivery of the expected service levels through various phases of the pavement life-cycle, and using the same framework to measure, monitor, and report using the next-generation pavement performance measures.

Pavement performance describes the ability of the pavement to provide over a period of time both a reasonable level of service (i.e., serviceability in terms of functionality and safety) to the user public and structural adequacy (i.e. ability to withstand traffic) (Carey and Irick, 1960).

Thus, the term “performance” comprises user satisfaction (functionality) and ability to carry traffic satisfactorily, safely and economically. The earlier versions of pavement performance indices had a heavy emphasis on serving the user public; however, these indices have evolved into a composite “super variable” index that captures both serviceability and structural adequacy.

The state-of-the-practice is that most agencies still use a form of composite performance indices to characterize performance. This is partly due to their historical dependence on serviceability based indices as well as need to identify exact causes of pavement deterioration which is best identified using surface-based distresses. With the development of new technologies (sensors, xiii acoustics, laser, etc.), new robust indicators are becoming available to capture user-related level of service concerns, such as continuous deflections, material conditions (GPR), longitudinal/transverse laser profilers (International Roughness Index (IRI), rutting, faulting) and friction for ride comfort and safety. However, there is still a heavy dependence on surface-based structural distresses to evaluate pavement structural integrity. Note that the surface-based structural distresses are themselves manifested consequences of structural deficiencies and can serve only as lagging indicators.

Even with the dependence on surface-distress based composite indices, most agencies have configured the MP&R decision trees in a more effective and structured manner to identify the treatment type based on the type of distresses (i.e. metrics indicating ride quality and safety concerns, defects and distresses contributing to structural deterioration, and distresses representing structural deficiency)

In the future, with the advent of newer technologies, such as high speed deflection measurements, and applications of geophysical test methods, there is a reasonable chance to deploy these technologies for network level assessment of pavement structural integrity. These technologies provide an alternative to capture leading indicators, such as measures of structural adequacy, rather than relying on lagging indicators, such as surface-based structural distresses. In other words, the use of these technologies can lead to making MP&R decisions, such as structural capacity improvements, even before the pavement structure exhibits signs of distresses. However, at least in the shorter term, it is imperative to depend on traditional condition indices, until the new technologies are operationalized.

Given the interactions between surface condition and structural health, this study makes no attempt to decouple them. Note that any deterioration of surface condition might contribute to worsening structural health and vice versa (e.g. effect of surface-initiated cracking on ride quality and full-depth deterioration), and similarly, the application of surface treatments for ride quality purposes may also provide some structural benefits (e.g. temporary retardation of structural deterioration) as well. However, recognizing the differences between level of service and structural needs would help make risk-related and asset life-cycle management decisions more effectively.

This study proposes tracking two indices for characterizing performance/condition: first, the traditional surface-condition index that captures surface deformation and discontinuities to identify the next preservation activity; and second, a health index that captures the structural health of the pavement to identify structural rehabilitation and reconstruction needs.

The surface condition of a pavement is typically characterized using defects, such as raveling, loss of friction, loss of smoothness, non-structural and structural cracking, faulting, and non-structural rutting. Potential consequences of deferring or neglecting surface repairs include loss of riding comfort, an increase in vehicle operating costs, an increase in crashes due to rutting or loss of friction, earlier-than-expected structural failures, and increased life-cycle costs.

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The structural health index may include surface-measured indicators (e.g. structural and non-structural cracks), mechanistic response based (e.g. direct mechanistic responses such as deflection, or engineering properties, such as elastic modulus, moisture, density, load transfer etc) indicators and surrogate indicators (e.g. effective structural number or effective thickness) that measure the adequacy or integrity of the pavement structure.

While both surface condition and structural health based indicators help to identify near-term needs, the latter health-based index encapsulates the whole life perspective of long-term structural deterioration. Based on these two indices—surface condition and structural health— the research team has proposed four sets of next-generation strategic performance measures:

• Remaining Service Interval to Surface Repairs: This measure, which is based on surface condition, capture the users’ needs and helps identify the next event. Based on the type of MP&R action, the RSI to surface repairs can be further broken down into:

o RSI to preventive maintenance o RSI to minor rehabilitation

• Remaining Service Interval to Structural Rehabilitation: This measure, which is based on structural health and/or surface condition, capture the needs for structural enhancements and repairs to substantially increase the load carrying capacity and extend the service life of an existing pavement. Examples include structural overlays, full-depth repairs, load transfer restoration, concrete pavement restoration etc.

• Remaining Service Interval to Reconstruction: This measure, which is based on structural health, provides insights on what life-cycle stage the pavement structure is in, how long the agency can continue to preserve the asset cost-effectively, and the long-term funding needs. This measure indicates the terminal event at which removal and replacement of the bound layer(s) or total reconstruction remain the only cost effective option to restore serviceability as the pavement approaches structural failure.

• Life-Cycle Cost Measures: These measures, which are based on net present value (NPV) and equivalent uniform annual cost (EUAC) of all past and future investments, include two sub-measures:

o Annualized Cost per Lane-mile: This measure is the EUAC of all cost expenditure expected over the pavement life-cycle. This efficiency-based measure indicates the amount of resources the agency expends to provide the desired level of service to users every year.

o Cost Accrual Ratio: This measure is a ratio of NPV of all costs incurred to date against the NPV of the agency’s optimized life-cycle plan. This effectiveness-based measure compares the actual investments made to date against the optimized life-cycle plan that requires the minimum practicable life-cycle costs.

The proposed set of performance measures finds applications in optimizing the life-cycle plans at the project level and maximizing performance at the network level within financial constraints.

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Furthermore, these measures help communicate with agency executives and legislatures a realistic estimate of the funding requirements and the overall state of repair of pavement assets at the network level.

A review of the pavement performance monitoring practices of highway agencies indicates that most agencies are prepared for any future adoption of the proposed performance measures. In addition, the research team conducted telephone interviews with three state agencies—Utah, Minnesota, and Mississippi—to obtain their feedback on proposed pavement performance measures. The team presented the concepts, the need for capturing structural deterioration, and the proposed measures. The research team solicited the views of the agencies on the appropriateness of using a structural health-based measure, the value they perceive, and potential issues if the agency were to adopt these measures.

While a composite, serviceability-based, pavement condition index is being used by most agencies, the structural health indicators are duly considered as evident in the decision hierarchy of their MP&R treatment matrix. Most agencies have the necessary tools to adopt the proposed pavement performance measures: surface distresses to measure structural health, empirically derived models for condition forecasting, tentative life-cycle plans, and a life-cycle cost analysis framework. Furthermore, the proposed measures are flexible enough to accommodate any emerging condition monitoring practices, including network-level deflection measurements, ground penetrating radar, or other imaging methods. The availability of locally calibrated mechanistic-empirical models, such as with the Pavement Health Track tool, will help agencies assess the structural health of their pavements (Titus-Glover et al, 2010). It would help these agencies to show them how to formulate a structural health index from condition information and demonstrate the application of this index within the realms of current pavement management capabilities.

Under MAP-21, highway agencies are required to develop an asset management plan that includes the following, as a minimum:

• A performance gap analysis to identify deficiencies and address gaps between the existing condition of assets and their corresponding performance targets

• A life-cycle cost analysis to devise an optimal life-cycle management plan to make the assets serviceable and extend their service expectancy at minimum practicable costs

• A risk management analysis to identify, assess, and prioritize risks that can affect the condition and effectiveness of physical assets, as well as an approach to monitor and manage high-priority risks

• A process to develop a 10-year financial plan that includes budgetary estimates of short-term and long-term work and potential funding sources

• Investment strategies to achieve, sustain, and improve a desired state of good repair of assets xvi

Many agencies have already developed their Transportation Asset Management (TAM) Plans, while other agencies were waiting for the final rule. In addition, the legislation calls for incorporation of a performance-based approach in planning and programming decisions, and makes it imperative to find a “trade-off” analysis that can be performed across assets to understand how condition and performance of separate classes of assets interact to influence overall system performance.

This study proposes a methodology to enable full implementation of a comprehensive TAM Plan as laid out by MAP-21. The proposed methodology considers all of the performance goals and management concerns that are required to be addressed in TAM Plans and allows agencies to add their own goals as needed. It provides the necessary means for agencies to set performance targets and to structure TAM business processes that make progress toward the targets in the near- and long-term. The proposed methodology is sufficiently general to support all infrastructure asset classes while representing the unique ways that each asset affects performance.

The proposed TAM methodology is based on the following premise:

• All TAM decisions are to be made so that the alternative selected is the one that maximizes long-term benefits. The concept of project benefit, which is the long-term social cost between two defined alternatives, is essential to integrate all relevant asset classes and stakeholder concerns in the tradeoff analysis.

• Each asset has a set of characteristics that affect cost, functionality, and risk. Forecasts of future condition, resilience, and utilization can change the cost, functionality, and risk. If a project is delayed, all of these characteristics and concerns can change.

While the proposed framework can be asset-specific in terms of defining asset condition, functional deficiencies, treatment selection, and cost estimation, the benefits calculation, in terms of cost avoidance to the agency and users, can be asset-generic.

The proposed TAM methodology has two major components: first, an asset-specific treatment planning model that incorporates multi-year forecasting of condition, resilience, and utilization, which all affect the future selection of appropriate treatments and associated future investment requirements; and second, an asset-generic performance model that converts condition forecasts and associated functional deficiencies, in conjunction with asset utilization and other asset characteristics, into user benefits or dis-benefits using metrics, such as crashes, time, distance, and cost. The outcomes of the proposed framework are simple metrics of incremental benefits and costs between any two scenarios: between two treatment types or between a treatment and a “do-nothing” decision.

This study presents a process on how to apply the proposed TAM methodology at both the project and network level for trade-off analyses and decision making relating to the following:

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• Performance targeting and tracking

• Long-term funding and policy

• Priority programming and resource allocation

• Optimal project scoping

• Needs identification

• Acceptable levels of service

This study also presents recommendations and work plans to implement the proposed pavement performance measures and TAM methodology.

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CHAPTER 1. INTRODUCTION

BACKGROUND

Highway agencies have longstanding pressure to balance the need to improve deteriorating pavement infrastructure under growing traffic with a limited availability of funds. Many highway agencies are responding to funding constraints through the adoption of effective transportation asset management practices to increase efficiency and innovation. Transportation Asset Management (TAM) provides a systematic framework and analytical tools that agencies can use to manage their assets effectively, from creation to disposal, to achieve the twin objectives of delivering the required levels of service to users while minimizing the total cost of ownership.

The asset management framework allows agencies to make optimized decisions through economic assessment of trade-offs among competing needs, such as capital investments vs.

maintenance, resource allocation among pavements, bridges, mobility and safety projects, and so on.

Pavement management, which is a critical component of TAM, has evolved since the 1960s to allow highway agencies to make optimized and cost-effective decisions at both the project and network levels. Figure 1 presents a schematic of a generic pavement management framework that caters to various applications at the project and network levels. The key components of pavement management include pavement inventory data, condition data, performance forecasting and other analytical tools, list of pavement life-cycle actions for maintenance, preservation and rehabilitation (MP&R), criteria to trigger MP&R actions, and a history of MP&R work types undertaken. Most agencies have mature pavement management systems.

Figure 1. Generic framework of a typical pavement management system (Hass et al, 2015)

PAVEMENT PERFORMANCE MEASURES

Pavement condition is a critical piece of information toward achieving the objectives of pavement management. Although there is immense diversity in the pavement management practices of an agency with respect to defining, measuring, recording, and summarizing pavement condition information, there are commonalities as well: all state agencies conduct pavement condition surveys at the network level, typically annually on primary roadways and biannually on secondary roads, to collect surface distress and smoothness information; and the collected information typically includes attributes that characterize surface condition, including smoothness, rutting or faulting, structural and non-structural cracking, and other defects.

While these raw distresses are aggregated into a composite index, often called by a myriad of names, most agencies derive an overall pavement condition index that aggregates pavement distresses and smoothness. The condition indices are typically fed into a data-driven analysis, such as deterioration modeling, to identify future MP&R strategies, investment needs and their timing at the project level; and, at the network level, to measure the current system-level performance, priority programming, and analyze the consequences of budget decisions.

The pavement condition indices have served reasonably to characterize both the structural and functional condition of the pavement. However, these indices fall short in capturing the structural adequacy or health of the pavement. In general, the structural health is inferred from an analysis of distresses that are caused by structural factors as well as those that contribute to structural deterioration. In this sense, the condition indices are “output” oriented and lagging indicators of the investments already made, as they do not directly convey insight on long-term performance and investment needs.

Some agencies have extended pavement condition indices to forecast remaining service life (RSL). The RSL concept, or remaining service interval (RSI) with its refined terminology, is an indication of when “something” (i.e., a MP&R activity), needs to be done. Pavement RSL has been around at least since the 1986 American Association of State Highway and Transportation Officials (AASHTO) Guide for Design of Pavement Structures. Pavement RSL provides indication, in terms of expected number of years, of when a pavement would start falling short of acceptable levels of service. The concept of RSL or RSI has different meanings in different contexts: traffic consumption, pavement age, serviceability rating, structural distress (visual condition based) and structural adequacy (deflection based) (Vepa et al, 1996).

Although the term RSL can be defined to indicate the type of the next “event” (i.e., maintenance, preservation, or rehabilitation), the concept of RSI takes it further to incorporate the whole life perspective, in the context of past and future actions, to assess future performance risks and investment needs (Elkins et al, 2013). In essence, the RSI aims to provide an optimum life-cycle management plan by identifying a structured sequence of repair and replacement actions required to provide the desired levels of service at lowest practicable life-cycle costs.

In practice, the RSI is a reflection of “performance indicators” used in the forecast of future needs. In other words, the RSI is very much dependent on what “conditions” are captured and how they are aggregated in the performance indicator.

TRANSPORTATION ASSET MANAGEMENT PLAN

Since the passage of recent highway reauthorization legislations—the Moving Ahead for Progress in the 21st Century (MAP-21) signed in July 2012 and Fixing America’s Surface Transportation Act signed in December 2015—there is a renewed emphasis on the applications of performance management in transportation decision-making. Under MAP-21, state highway agencies and regional/metropolitan planning organizations are required to develop a risk-based transportation asset management plans (TAM Plans) to “improve or preserve the condition of the assets and the performance of the system.”

On February 20, 2015, the Federal Highway Administration (FHWA) published a Notice of Proposed Rule-Making (NPRM) to present its proposed regulations regarding the TAM Plan requirements (FHWA, 2015). After a period of comments solicitation, the FHWA published its final rule on required state-approved asset management plans and processes on October 24, 2016.

The legislation calls for highway agencies to have a long-term, strategic approach in place for preservation and management of physical infrastructure. The legislation mandates the establishment of condition and performance targets for at least pavements and bridges, and requires the TAM Plan “to include strategies leading to a program of projects that would make progress toward achievement of the targets.” Although only pavements and bridges are mandatory in the TAM Plans, states are encouraged “to include all infrastructure assets within the right-of-way corridor in such plan.” (23 United States Code 119(e)). The legislation also mandates state highway agencies to use pavement and bridge management systems to analyze the condition of National Highway System pavements and bridges.

23 United States Code 119(e)(4) of the MAP-21 legislation requires that a state asset management plan contain the following components (USGPO, 2012):

• A summary listing of the pavement and bridge assets on the state’s national highway system

• Asset management objectives and measures

• Performance gap identification

• Life-cycle cost analysis

• Risk management analysis

• Financial plan for a minimum period of 10 years

• Investment strategies

In response to the MAP-21 legislation, many agencies have already developed their TAM Plans, while other agencies were waiting for the final rule.

The MAP-21 legislation calls for incorporation of a performance-based approach in planning and programming decisions. The legislation makes it imperative to look for “trade-off” analysis to be performed across assets to understand how condition and performance of separate classes of assets interact to influence overall system performance. Specifically, the legislation explicitly links the TAM Plan to the Statewide Transportation Improvement Program, which is the primary vehicle for programming of transportation projects.

Traditionally, highway agencies have depended on pre-established selection criteria and priority weighting schema to make decisions on funding allocations among disparate sets of assets.

Although the pre-established selection criteria and priority weighting schema generally reflect the strategic policy objectives of an agency and their relative importance, this may not produce the most effective allocation of funds to maximize performance due to changing demands and public preferences. Furthermore, the traditional method promotes a narrower approach that tends to maximize performance within silos of asset classes (or transportation modes) rather than optimizing across the entire system.

Considering the deficiencies with formula-based resource allocation, highway agencies recognize the need for a performance-based process to facilitate better alignment of agency goals, investment decisions, and performance outcomes. In response to these needs, the National Cooperative Research Program (NCHRP) developed a prototype and guidance document, Report 806 (Project 08-91), to facilitate state departments of transportation (DOTs) and regional/ metropolitan planning organizations with analyzing likely performance impacts of investment decisions and allocation of limited resources among asset classes (Maggiore and Ford, 2015).

The NCHRP 08-91 prototype tool is a spreadsheet-based, proof-of-concept tool that facilitates a performance-based cross-asset or cross-investment resource allocation framework, as presented in Figure 2.

NCHRP Project 08-91 makes a significant leap in proposing a framework for a performance-based cross-asset resource allocation that integrates with the agency’s planning process, leverages existing pavement and bridge management practices, and layers on the MAP-21 driven performance metrics to produce a comprehensive trade-off analysis that considers all resource constraints.

However, the NCHRP Project 08-91 fell short of addressing critical issues relevant for this study.

As the selection and timing of future preservation, rehabilitation or replacement actions would only be evident in life-cycle planning. Any lack of emphasis on life-cycle cost also misses the consideration on consequences of past, future, and deferred actions. This is highly relevant at an asset level to achieve lower life-cycle costs as well as in a programming scenario where funding is limited and thus a needed project may have to be delayed until funding becomes available. In this context, there is a need to conceptually develop foundations to guide full implementation of comprehensive asset management methodologies.

Figure 2. Siloed vs. integrated resource allocation proposed by NCHRP Project 8-91.

STUDY OBJECTIVES

The objectives of this study are summarized as follows:

• Identify or conceptually develop a more strategic pavement performance measure(s) to ensure effective and timely assessment of investments that will “maintain the highway infrastructure asset system in a state of good repair (SGR) in relation to pavement assets.”

The proposed measures are intended to not only assess current pavement condition but also provide adequate insights into long-term performance to ensure future SGR at a minimum practicable cost over the pavement life-cycle with appropriate considerations of their practicality for implementation.

• Identify or conceptually develop methodologies to guide full implementation of comprehensive asset management, including performance-based trade-off analysis from a common ground among disparate assets that are traditionally assessed and managed individually.

REPORT ORGANIZATION

The report is organized into two volumes: Volume 1 – Pavement Performance Measures, and Volume 2 – Methodologies, to enable full implementation of a comprehensive TAM Plan.

Volume 1 of this report includes six chapters:

• Chapter 1 provides background information on the pavement performance measures and MAP-21 asset management requirements, and establishes the need and objectives of this study.

• Chapter 2 describes the principles of performance and asset management in the context of MAP-21 legislation and establishes a SGR definition for pavement assets. This chapter also presents a discussion on what information the external and internal stakeholders would seek from pavement performance measures.

• Chapter 3 presents an in-depth discussion on pavement performance measures, the national and international state-of-the practice, and emerging trends. This chapter also presents a gap analysis of existing measures, their applicability for strategic use, and what the next-generation pavement performance measures should look like.

• Chapter 4 presents the proposed strategic pavement performance measures with examples and a framework to support the measures.

• Chapter 5 presents the concept of operations that provides guidance on how to integrate these measures for pavement management decision making. This chapter also includes a summary of case study findings with three state DOTs.

• Chapter 6 summarizes the conclusions of this study and provides recommendations for future work.

Volume 2 presents comprehensive asset management methodologies to guide full implementation of a TAM Plan.

• Chapter 1 presents a background discussion on the requirements on TAM as laid out by the MAP-21 legislation and a state-of-the practice review of TAM Plans and resource allocation frameworks. It also describes how to make the TAM Plans more comprehensive and how federal requirements and/or industry standards could evolve in the future.

• Chapter 2 presents a detailed discussion on the applications of trade-off analysis at the network, program, and project levels.

• Chapter 3 summarizes the applications of performance measures for making asset management decisions at the executive, program, and project levels.

• Chapter 4 summarizes data and analytical needs to create metrics consistent with the MAP-21 performance goals that describe asset condition, asset or system resiliency, cost, safety, mobility, and environmental sustainability.

• Chapter 5 lays out the recommended methodology in detail to enable full implementation of a comprehensive TAM Plan.

• Chapter 6 summarizes the recommendations for implementing the proposed methodologies as well as for future work.

CHAPTER 2. ASSET PERFORMANCE AND STATE OF GOOD

REPAIR

PRINCIPLES OF PERFORMANCE AND ASSET MANAGEMENT

PERFORMANCE MANAGEMENT

MAP-21 has placed a new emphasis on performance- and outcome-based programs within the Federal-aid highway program. The new “performance management” paradigm requires highway agencies to make investment and policy decisions using a data-driven process that collectively contributes toward achieving national performance goals with effective utilization of available resources. With an effective performance management framework, a highway agency brings context to its organizational structure, business practices, and decisions. The agency devises a strategic plan to translate its foundational goals to policy objectives and performance-focused initiatives, and link them to measurable outcomes.

Performance management complements the strategic planning of an agency, which involves a range of activities, including setting the strategic direction (i.e., “where the agency wants to go in the future”) using measureable goals and objectives; identifying performance measures in decision-making related to strategic, programmatic, operational, and organizational objectives;

establishing future trends and targets; identifying preferred strategies and investment needs;

devising an investment plan and associated resource allocation decisions; monitoring and reviewing the outcomes of those decisions; and proposing continual refinements (Grant et al, 2013).

Integral to this new approach is performance measurement that includes a system of business processes, resources, tools, and infrastructure to collect, manage, analyze, and report information. Performance measurement, in essence, provides an on-going cyclical process to capture performance data and metrics, and utilize them to support performance management objectives.

Figure 3, as proposed by Hass et al. 2008, presents a simple, hierarchical structure linking policy objectives to performance indicators and implementation targets. The schematic in Figure 3 shows how the performance measurement provides a link between the performance objectives, as derived from the agency’s mission statement and established by top management and senior decision makers, and the implementation targets at the tactical and operational levels.

Figure 3. Hierarchical structure linking policy objectives to performance indicators and implementation targets. (Haas et al. 2008).

Table 1 summarizes the performance goals set by the MAP-21 legislation, which also encapsulates the foundational principles of most highway agencies as articulated in their vision and mission statements (FHWA, 2016). These foundational principles have the following common underlying themes:

• Focus on the customer needs relating to safety, security, mobility and travel reliability, freight movements, economic vitality, and livability

• Foster stewardship of fiscal resources relating to creating efficiencies in life-cycle management of assets…