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Publication Number: FHWA-RD-02-057
Date: OCTOBER 2002

Pavement Smoothness Index Relationships, Final Report

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Foreword

A key factor in the long-term performance of both asphalt and portland cement concrete pavements is initial pavement smoothness. In general, the smoother a pavement is built, the smoother it stays over time, resulting in lower maintenance costs and more comfort and safety for the traveling public. State highway agencies recognized in the 1960s the importance of controlling initial pavement smoothness, and began developing and implementing smoothness specifications. As the technology and equipment for measuring pavement smoothness advanced, two predominant methods emerged.

The profilograph is widely used to measure and control initial smoothness by producing profile traces, which can be evaluated to identify severe bumps and to establish an easily understood, overall measure of smoothness, the profile index (PI). However, concerns about the accuracy of the profilograph have grown significantly in the last decade. The more recently developed inertial profiler is used to quickly and accurately monitor in-service pavements, and produces a more definitive profile of a pavement from which the widely accepted International Roughness Index (IRI) can be computed. Use of inertial profilers has remained limited in initial construction acceptance testing due to their higher cost and constraints on timeliness of testing. Thus, in many agencies, initial pavement smoothness has been measured one way (profilograph PI) and smoothness over time has been measured another way (inertial profiler IRI).

Despite efforts to make adjustments for more accuracy in the computation of PI, it is evident that IRI will become the statistic of choice in future smoothness specifications. So how do agencies make the switch from their current PI-based specifications to IRI specifications? This study attempts to provide answers through the analysis of comprehensive time history smoothness data collected by high-speed inertial profilers under the Long-Term Pavement Performance (LTPP) program. Using advanced computer simulation algorithms, it is possible to compute PI values from surface profile data, thereby allowing detailed comparisons between IRI and PI.

T. Paul Teng, P.E.
Director, Office of Infrastructure Research and Development

Notice

This document is disseminated under the sponsorship of the Department of Transportation in the interest of information exchange. The U.S. Government assumes no liability for its contents or use thereof. This report does not constitute a standard, specification, or regulation.

The U.S. Government does not endorse products or manufacturers. Trademarks or manufacturers' names appear in this report only because they are considered essential to the objective of the document.

Technical Report Documentation Page

1. Report No.

FHWA-RD-02-057

2. Government Accession No. 3 Recipient's Catalog No.

4. Title and Subtitle

Pavement Smoothness Index Relationships, Final Report

5. Report Date

OCTOBER 2002

6. Performing Organization Code

C6B

7. Author(s)

Kelly L. Smith, Leslie Titus-Glover, Lynn D. Evans

8. Performing Organization Report No.

 

9. Performing Organization Name and Address

ERES Division of Applied Research Associates, Inc., 505 W. University Avenue, Champaign, IL 61820.

10. Work Unit No. (TRAIS)

11. Contract or Grant No.

GS-10F-0298K

12. Sponsoring Agency Name and Address

Office of Pavement Technology, Federal Highway Administration, 400 Seventh St., S.W., Washington, D.C. 20590

13. Type of Report and Period Covered

Final Report, February - November 2001

14. Sponsoring Agency Code

 

15. Supplementary Notes

FHWA Contracting Officer's Technical Representative (COTR): Mark Swanlund, HIPT-1

16. Abstract

Nearly all State highway agencies use smoothness specifications to ensure that hot-mix asphalt (HMA) and Portland cement concrete (PCC) pavements are built to high levels of smoothness. Not only is an initially smooth pavement generally indicative of quality workmanship, but it has been shown to last longer than a pavement built rougher.

About half of all current State smoothness specifications for HMA and more than three-fourths of all current PCC smoothness specifications are centered around the Profile Index (PI), as often measured using a profilograph. The vast majority of these specifications utilize a 5-mm (0.2-inch) blanking band in computing PI (i.e., PI5-mm). Unfortunately, because of the technical limitations of the profilograph equipment and PI computation procedures, the adequacy of PI5-mm in characterizing roughness and having it relate to user response has come into question.

The International Roughness Index (IRI) or the Profile Index using a 0.0-mm blanking band (PI0.0) seem to provide better measures of smoothness and better correlation with user response. However, one barrier to more widespread implementation of these new smoothness standards is the lack of objective, verifiable correlation methods for use in establishing specification limits using the IRI or PI0.0. Assistance in selecting appropriate IRI and PI0.0 specification limits is needed to provide a basis for modifying current specifications to these more reproducible and portable smoothness indices.

This research effort has developed a series of relationships between IRI and PI that can assist States in transitioning to an IRI or PI0.0 smoothness specification for HMA and PCC pavements.

17. Key Words

LTPP, pavement smoothness, profilograph, inertial profiler, international roughness index, profile index, smoothness limits.

18. Distribution Statement

No restrictions. This document is available to the public through the National Technical Information Service, Springfield, VA 22161.

19. Security Classification
(of this report)

Unclassified

20. Security Classification
(of this page)

Unclassified

21. No. of Pages

116

22. Price
Form DOT F 1700.7 Reproduction of completed page authorized

Technical Report Documentation Page

 

SI* (MODERN METRIC) CONVERSION FACTORS

Approximate Conversions to SI Units

Length:
inches (in) multiply by 25.4 to get millimeters (mm)
feet (ft) multiply by 0.305 to get meters (m)
yards (yd) multiply by 0.914 to get meters (m)
miles (mi) multiply by 1.61 to get kilometers (km)

Area:
square inches (in2) multiply by 645.2 to get square millimeters (mm2)
square feet (ft2) multiply by 0.093 to get square meters (m2)
square yard (yd2) multiply by 0.836 to get square meters (m2)
acres (ac) multiply by 0.405 to get hectares (ha)
square miles (mi2) multiply by 2.59 to get square kilometers (km2)

Volume:
fluid ounces (fl oz) multiply by 29.57 to get milliliters (mL)
gallons (gal) multiply by 3.785 to get liters (L)
cubic feet (ft3) multiply by 0.028 to get cubic meters (m3)
cubic yards (yd3) multiply by 0.765 to get cubic meters (m3)
NOTE: volumes greater than 1000 L shall be shown in m3

Mass:
ounces (oz) multiply by 28.35 to get grams (g)
pounds (lb) multiply by 0.454 to get kilograms (kg)
short tons - 2000 lb (T) multiply by 0.907 to get megagrams or "metric ton" (Mg or "t")

Temperature (exact degrees):
Fahrenheit (°F) multiply by 5 (F-32)/9 or (F-32)/1.8 to get Celsius (°C)

Illumination:
foot-candles (fc) multiply by 10.76 to get lux (lx)
foot-Lamberts (fl) multiply by 3.426 to get candela/m2 (cd/m2)

Force and Pressure or Stress:
poundforce (lbf) multiply by 4.45 to get newtons (N)
poundforce per square inch (lbf/in2) multiply by 6.89 to get kilopascals (kPa)

Approximate Conversions From SI Units

Length:
millimeters (mm) multiply by 0.039 to get inches (in)
meters (m) multiply by 3.28 to get feet (ft)
meters (m) multiply by 1.09 to get yards (yd)
kilometers (km) multiply by 0.621 to get miles (mi)

Area:
square millimeters (mm2) multiply by 0.0016 to get square inches (in2)
square meters (m2) multiply by 10.764 to get square feet (ft2)
square meters (m2) multiply by 1.195 to get square yards (yd2)
hectares (ha) multiply by 2.47 to get acres (ac)
square kilometers (km2) multiply by 0.386 to get square miles (mi2)

Volume:
milliliters (mL) multiply by 0.034 to get fluid ounces (fl oz)
liters (L) multiply by 0.264 to get gallons (gal)
cubic meters (m3) multiply by 35.314 to get cubic feet (ft3)
cubic meters (m3) multiply by 1.307 to get cubic yards (yd3)

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

Temperature (exact degrees):
Celsius (°C) multiply by 1.8C+32 to get Fahrenheit (°F)

Illumination:
lux (lx) multiply by 0.0929 to get foot-candles (fc)
candela/m2 (cd/m2) multiply by 0.2919 to get foot-Lamberts (fl)

Force and Pressure or Stress:
newtons (N) multiply by 0.225 to get poundforce (lbf)
kilopascals (kPa) multiply by 0.145 to get poundforce per square inch (lbf/in2)

*SI is the symbol for the International System of Units. Appropriate rounding should be made to comply with Section 4 of ASTM E380.
(Revised March 2002)

TABLE OF CONTENTS

Chapter 1.Introduction

Background
Problem Statement
Study Objectives
Chapter 2. Literature Review
Introduction
Past Studies on PI-IRI Relationships
Summary
Chapter 3. LTPP Data Collection and Project Database Development
Introduction
Collection of LTPP Profile Data
Conversion of Profile Data to Simulated PI Values
Populating the Project Database
Chapter 4. Development of LTPP-Based Smoothness Index Relationships
Introduction
Step 1 -- Preliminary Evaluation
Step 2 -- Selection of Appropriate Model Form
Step 3 -- Group Data into Sets with Similar Smoothness Relations
Steps 4 and 5 -- Develop Tentative Models and Assess Models for Reasonableness
Step 6 -- Select Final Models
Chapter 5. Adaptation of LTPP-Based Models to Current State Smoothness Specifications
Introduction
Overview of State Smoothness Specifications
Development of Recommended Initial IRI and PI0.0 Levels
Chapter 6. Conclusions and Recommendations
Conclusions
Recommendations
Appendix A: IRI and PI Relationships for AC Pavements

Appendix B: IRI and PI Relationships for PCC Pavements

LIST OF FIGURES

1. Sensitivity of simulated profilograph to spatial frequency.

2. Relationship between IRI and manually generated PI in PTI profilograph calibration study.

3. Relationship between IRI and computer-generated PI in PTI profilograph calibration study.

4. Correlation of IRI and PI in Arizona pavement smoothness study.

5. IRI-PI5-mm (PI0.2-inch) correlations established in Florida's ride quality equipment study.

6. IRI-PI2.5-mm (PI0.1-inch) and IRI-PI0.0 correlations established in Florida's ride quality equipment study.

7. Relationship between IRI and computer-simulated PI values in TTI equipment comparison study.

8. Plots of IRI and simulated PI0.0 values generated by various profilers in Kansas DOT lightweight profiler comparison study.

9. Relationship between IRI and California profilograph PI0.0 in Kansas DOT lightweight profiler comparison study.

10. Relationship between IRI and simulated PI0.2-inch (PI5-mm) in Illinois DOT bridge smoothness study.

11. Graphical comparison of documented PI5-mm-IRI smoothness relationships.

12. Graphical comparison of documented PI2.5-mm-IRI smoothness relationships.

13. Graphical comparison of documented PI0.0-IRI smoothness relationships.

14. Flow chart for developing pavement smoothness models.

15. Histogram showing the distribution of IRI data used in model development (all AC pavements).

16. Histogram showing the distribution of IRI data used in model development (all PCC pavements).

17. Histogram showing the distribution of PI5-mm data used in model development (all AC pavements).

18. Histogram showing the distribution of PI5-mm data used in model development (all PCC pavements).

19. IRI vs. PI0.0 for all AC pavements and climates.

20. PI0.0 vs. PI5-mm for all PCC pavements and climates.

21. IRI vs. PI0.0 by AC pavement type for all climates.

22. PI0.0 vs. PI5-mm by climate for all PCC pavement types.

23. Graphical comparison of PI5-mm-IRI smoothness relationships for AC pavements.

24. Graphical comparison of PI5-mm-IRI smoothness relationships for PCC pavements.

25. Graphical comparison of PI2.5-mm-IRI smoothness relationships for AC pavements.

26. Graphical comparison of PI0.0-IRI smoothness relationships for AC pavements.

27. Graphical comparison of PI0.0-IRI smoothness relationships for PCC pavements.

28. Conceptual plot showing relationships of smoothness indices within and between cells.

29. Histogram showing the distribution of slope for IRI versus PI0.0 (for cells in block 1, AC surface pavements).

30. Histogram showing the distribution of slope for IRI versus PI0.0 (for cells in block 2, PCC surface pavements).

31. Histogram showing the distribution of slope for PI0.0 versus PI5-mm (for cells in block 1, AC surface pavements).

32. Histogram showing the distribution of slope for PI0.0 versus PI5-mm (for cells in block 2, PCC surface pavements).

LIST OF TABLES

1. Summary of documented PI-IRI relationships.

2. Breakdown of test sections by LTPP experiment.

3. Breakdown of test sections by State.

4. Summary of basic statistics of data used in model development.

5. Matrix of scatter plots created for model development.

6. Factorial of cells used for model development.

7. ANOVA results on the effect of pavement type and climate on PI-IRI relationship for AC pavements.

8. ANOVA results on the effect of pavement type and climate on PI-IRI relationship for PCC pavements.

9. Summary of groupings (merged cells) used for model development.

10. PI-to-IRI index conversion equations and variability indices for AC pavements.

11. PI-to-PI index conversion equations and variability indices for AC pavements.

12. PI-to-IRI index conversion equations and variability indices for PCC pavements.

13. PI-to-PI index conversion equations and variability indices for PCC pavements.

14. State agency smoothness specifications for asphalt pavements.

15. State agency smoothness specifications for concrete pavements.

16. Estimated equivalent PI0.0 and IRI values for PI-based smoothness specifications for new AC pavement.

17. Estimated equivalent PI0.0 and IRI values for PI-based smoothness specifications for AC overlays on AC pavement.

18. Estimated equivalent PI0.0 and IRI values for PI-based smoothness specifications for AC overlays on PCC pavement.

19. Estimated equivalent PI0.0 and IRI values for PI-based smoothness specifications for new PCC pavement and PCC overlays.

Chapter 1. Introduction

Background

Initial pavement smoothness is a key factor in the performance and economics of a pavement facility. All other things being equal, the smoother a pavement is built, the smoother it will stay over time. The smoother it stays over time, the longer it will serve the traveling public, thereby benefiting the public in terms of investment (initial construction and upkeep) and vehicular wear costs, as well as comfort and safety.

As a means of controlling initial pavement smoothness, several highway agencies began developing and implementing smoothness specifications in the late 1950s and 1960s. These specifications generally included straightedge testing and a form of ride quality testing using response-type mechanical equipment, such as the Bureau of Public Roads (BPR) Roughometer, the Mays Ridemeter, and the Portland Cement Association (PCA) Ridemeter, or simple profiling devices, such as the Chloe profilometer and the profilograph.

Between the late 1960s and the 1980s, the profilograph emerged as the clear choice among highway agencies for measuring and controlling initial smoothness, particularly for concrete pavements. This 7.6-meters (25-feet) rolling reference system is capable of producing profile traces, which can be evaluated to identify severe bumps and to establish an overall measure of smoothness (i.e., the profile index [PI]).

During this same period of time, more complex profiling systems were being developed and marketed, which provided a much quicker assessment and more accurate representation of pavement smoothness. Inertial profilometers or profilers consist of an integrated set of vertical displacement sensors, vertical accelerometers, and analog computer equipment mounted in a full-sized vehicle (usually a van or large automobile) equipped with a distance-measuring instrument (DMI). These pieces of equipment, which can be operated at highway speed, are capable of producing a more definitive profile of a pavement, from which the universally accepted International Roughness Index (IRI) can be computed.

Inertial profilers' first major role in the pavements realm involved long-term condition monitoring of in-service pavements. The reliability and repeatability of these devices greatly enhanced the quality of the pavement management data used by highway agencies in programming maintenance and rehabilitation (M&R) activities. Although the use of inertial profilers in condition monitoring increased substantially in the 1980s and early 1990s, their application in construction acceptance testing remained limited due to their high cost and constraints on the timeliness of testing (i.e., tests on rigid pavements could not be performed until after a few days of curing). Thus, in many agencies, initial pavement smoothness has been measured one way (profilograph PI) and smoothness over time has been measured another way (inertial profiler IRI).

In recent years, the technology of inertial profiling systems present on full-sized vehicles has been adopted on smaller motorized vehicles, such as the John Deere and Kawasaki utility carts and four-wheel all-terrain vehicles (ATVs). These lightweight profilers, which are currently being evaluated by several agencies and have been approved for use by a few, enable testing personnel to obtain timely and highly definitive measurements of surface profiles at rates of speed significantly higher than profilographs (24 kilometers/hour [15 miles/hour] versus 5 km/hr [3 mi/hr]). The profilers are capable of producing IRI and other indices (e.g., simulated PI and Mays output, ride number [RN]) commonly used in controlling and monitoring pavement smoothness.

Problem Statement

Although the profilograph has served the highway community fairly well as an easily understood index of initial pavement smoothness, concerns about its accuracy and relationship with user response (fair to poor) have grown significantly in the last decade. For instance, because the device measures only wavelengths within the range of 0.3 to 23 m (1 to 75 ft) and because it amplifies wavelengths that are factors of its length (i.e., 7.6 m [25 ft]), the profile it produces is biased from a pavement's true profile. This can be seen in figure 1, where a true profile would be represented by a gain of 1.0. Coupled with the fact that a 2.5- or 5-millimeter (0.1- or 0.2-inch) blanking band is often applied when computing PI, thereby masking some roughness, it is understandable how correlation with user response is generally deemed inadequate.

Over the last 6 years, a handful of State agencies have moved toward using a zero blanking band PI (PI0.0) statistic for construction acceptance testing. This has reportedly improved the ability to control initial smoothness and bettered the relationship between profilograph PI and user response. However, the fact that the same biased profiles are being used to compute PI0.0 does not fully alleviate the major concerns with the profilograph. Among many agencies, the belief persists that inertial profilers are the best means for specifying and evaluating initial smoothness.

Figure 1. Sensitivity of simulated profilograph to spatial frequency.

Figure 1. Sensitivity of simulated profilograph to spatial frequency. The graph shows Spatial Frequency (cycles per feet) on the horizontal axis; and Gain on the vertical axis. For the profilograph, the gain varies in the range of 0 to 2 in the spatial frequency range of 0.01 to 10.

Additional support for using inertial profilers in construction acceptance testing comes from the desire for a "cradle-to-grave" smoothness index. Since it has been shown that future smoothness is a function of initial smoothness, use of one index for tracking smoothness over the entire life of a pavement would significantly benefit pavement managers and designers through improved performance prediction modeling.

Recent surveys of State highway agencies indicate that about 10 percent (4 of 34 respondents) use IRI to control initial smoothness (Baus and Hong, 1999), while about 84 percent (31 of 37 respondents) use IRI to monitor pavement smoothness over time (Ksaibati et al., 1999).). It is quite evident that IRI will become the statistic of choice in future smoothness specifications, given that: many agencies are investigating lightweight inertial profilers, and that the proposed 2002 Design Guide under development by the National Cooperative Highway Research Program (NCHRP) will include IRI prediction models that are a function of initial IRI (IRI0).

So, how do agencies make the switch from their current PI-based specifications to IRI specifications? What levels of IRI should be specified which would be comparable or equivalent to the PI values currently stipulated? How confident can an agency be that newly established IRI levels reflect the levels of ride quality previously specified? These are all questions that must be properly addressed in light of the fact that several past pavement smoothness studies show poor correlation between PI values produced by a profilograph and IRI values generated by inertial profilers.

This study attempts to provide answers to the above questions through the analysis of comprehensive time history smoothness data collected by high-speed inertial profilers under the Long-Term Pavement Performance (LTPP) program. These smoothness data include archived surface profile data and corresponding computed IRI values for many General Pavement Studies (GPS) and Specific Pavement Studies (SPS) test pavements located throughout the United States. Using advanced computer simulation algorithms, it is possible to compute PI values from the surface profile data, thereby allowing detailed comparisons between IRI and PI.

Study Objectives

The specific objectives of the study include the following:

Chapter 2. Literature Review

Introduction

To begin the investigation of the relationship between IRI and PI, a fairly extensive literature search was performed focusing on national and State-sponsored pavement smoothness studies conducted in the last 15 years. This search resulted in the collection of many reports, papers, and articles on the topic of smoothness, but only a handful dealing specifically with the correlation of IRI and PI.

Presented in this section is a synopsis of seven documented studies and the PI-to-IRI correlations developed in those efforts. Most of the correlations involve PI readings from actual profilograph equipment; however, a few are based on computer-simulated PI values produced from surface profiles measured by inertial profilers.

Past Studies on PI-IRI Relationships

Pennsylvania Transportation Institute Profilograph Calibration Study

As part of a major effort to develop calibration procedures for profilographs and evaluate equipment for measuring the smoothness of new pavement surfaces, the Pennsylvania Transportation Institute (PTI) conducted a full-scale field-testing program on behalf of the Federal Highway Administration (FHWA) (Kulakowski and Wambold, 1989). Concrete and asphalt pavements at five different locations throughout Pennsylvania were selected for the experiment; each pavement was new or newly surfaced. Multiple 0.16-km (0.1-mi) long pavement sections were established at each location, resulting in 26 individual test sections over which 2 different types of profilographs (California and Rainhart), a Mays Meter, and an inertial profiler were operated. The resulting smoothness measurements were evaluated for correlation.

Figure 2 shows the relationship between the inertial profiler IRI and the PI5-mm (PI0.2-inch) determined manually from the California-type profilograph. As can be seen, the resulting linear regression equation had a coefficient of determination (R2) of 0.57. Figure 3 shows the relationship between the inertial profiler IRI and the computer-generated PI5-mm (PI0.2-inch) from the California-type profilograph. Although the resulting linear regression equation had a similar coefficient of determination (R2 = 0.58), its slope was considerably flatter. For any given IRI, the data show a wide range of PI5-mm (PI0.2-inch).

Although both of these relationships were based on measurements from both concrete and asphalt pavement sections, neither one is considerably different from regressions based solely on data from the concrete sections.

Figure 2. Relationship between IRI and manually generated PI5-mm (PI0.2-inch) in PTI profilograph calibration study (Kulakowski and Wambold, 1989).

Figure 2. Relationship between IRI and manually generated PI (5-millimeter) (PI (0.2-inch)) in PTI profilograph calibration study (Kulakowski and Wambold, 1989). The figure shows a graph with PI (0.2-inch) (analog strip chart, manual reduction), inches per mile, on the horizontal axis; and IRI, inches per mile, on the vertical axis. Points for PCC and AC pavements are graphed. The liner regression for both PCC and AC pavements starts at an IRI of 70 (PI of 0) and ends at an IRI of 140 (PI of 18). IRI = 4.0238*PI + 70.13, R-squared = 0.5654, N = 25.

Figure 3. Relationship between IRI and computer-generated PI5-mm (PI0.2-inch) in PTI profilograph calibration study (Kulakowski and Wambold, 1989).

Figure 3. Relationship between IRI and computer-generated PI (5-mm) (PI (0.2-inch)) in PTI profilograph calibration study (Kulakowski and Wambold, 1989). The figure shows a graph with PI (0.2-inch) (computerized, continuous scale), inches per mile, on the horizontal axis; and IRI, inches per mile, on the vertical axis. Points for PCC and AC pavements are graphed. The liner regression for both PCC and AC pavements starts at an IRI of 70 (PI of 2) and ends at an IRI of 150 (PI of 35). IRI = 2.4599*PI + 66.22, R-squared = 0.5806, N = 25.

Arizona DOT Initial Smoothness Study

In 1992, the Arizona Department of Transportation (AZDOT) initiated a study to determine the feasibility of including their K.J. Law 690 DNC Profilometer (optical-based inertial profiler) as one of the principal smoothness measuring devices for measuring initial pavement smoothness on PCC pavements (Kombe and Kalevela, 1993). At the time, the AZDOT used a Cox California-type profilograph to test newly constructed PCC pavements for compliance with construction smoothness standards.

To examine the correlative strength of the Profilometer (IRI) and profilograph (PI) outputs, a group of twelve 0.16-km (0.1-mi) pavement sections around the Phoenix area were selected for testing. The smoothness levels of the sections spanned a range that is typical of newly built concrete pavement-PI5-mm (PI0.2-inch) between 0 and 0.24 m/km (15 inches per mile). A total of three smoothness measurements were made with the Profilometer over each wheelpath of each selected section, whereas a total of five measurements were made by the profilograph over each wheelpath of each section. The mean values of each set of three or five measurements were then used to correlate the IRI and PI5-mm (PI0.2-inch) values.

Simple linear regression analyses performed between the left wheelpath, right wheelpath, and both wheelpath sets of values indicated generally good correlation between the two indexes. Figure 4 shows the scatter plots of each group, as well as the regression line associated with the both wheelpath data group. As can be seen, the R2 for the both wheelpath regression line was very high (0.93).

Figure 4. Correlation of IRI and PI5-mm (PI0.2-inch) in Arizona pavement smoothness study (Kombe and Kalevela, 1993).

Figure 4. Correlation of IRI and PI (5-millimeter) (PI (0.2-inch)) in Arizona pavement smoothness study (Kombe and Kalevela, 1993). The figure shows a graph with PI (0.2-inch), inches per mile, on the horizontal axis; and IRI, inches per mile, on the vertical axis. Points for Left Wheel Path (WP) and Right WP are graphed. The liner regression for both Left and Right WP starts at an IRI of 50 (PI of 0) and ends at an IRI of 145 (PI of 15). IRI = 6.1282*PI + 52.931, R-squared = 0.9245, N = 12.

University of Texas Smoothness Specification Study

In the course of developing new smoothness specifications for rigid and flexible pavements in Texas, researchers at the University of Texas conducted a detailed field investigation comparing the McCracken California-type profilograph and the Face Dipstick, a manual Class I profile measurement device (Scofield, 1993). The two devices were used to collect smoothness measurements on 18 sections of roadway consisting of both asphalt and concrete pavements. For both devices, only one test per wheelpath was performed.

Results of linear regression analysis showed a strong correlation (R2 = 0.92) between the IRI and PI5-mm (PI0.2-inch) values. The resulting linear regression equation had a higher intercept value than those obtained in the PTI and AZDOT studies, while the slope of the equation was more in line with the slopes generated in the PTI study.

Florida DOT Ride Quality Equipment Comparison Study

Looking to upgrade its smoothness testing and acceptance process for flexible pavements, the Florida DOT (FLDOT) undertook a study designed to compare its current testing method (rolling straightedge) with other available methods, including the California profilograph and the high-speed inertial profiler (FLDOT, 1997). A total of twelve 0.81-km (0.5-mi) long pavement sections located on various Florida State highways were chosen for testing. All but one of the sections represented newly constructed or resurfaced asphalt pavements.

The left and right wheelpaths of each test section were measured for smoothness by each piece of equipment. The resulting smoothness values associated with each wheelpath were then averaged, yielding the values to be used for comparing the different pieces of equipment. The inertial profiler used in the study was a model manufactured by the International Cybernetics Corporation (ICC). Because one of the objectives of the study was to evaluate different technologies, the ICC inertial profiler was equipped with both laser and ultrasonic sensors. Separate runs were made with each sensor type, producing two sets of IRI data for comparison.

Figure 5 shows the relationships developed between the profilograph PI5-mm (PI0.2-inch) and the IRI values respectively derived from the laser and ultrasonic sensors. As can be seen, both correlations were fairly strong (R2 values of 0.88 and 0.67), and the linear regression equations were somewhat similar in terms of slope. As is often the case, however, the ultrasonic-based smoothness measurements were consistently higher than the laser-based measurements, due to the added sensitivity to items such as surface texture, cracking, and temperature. This resulted in a higher y-intercept for the ultrasonic-based system.

Figure 6 shows the correlations developed between IRI and PI2.5-mm (PI0.1-inch) and IRI and PI0.0. It is quite clear from this and the previous figure that the application of smaller blanking bands results in higher PI values, since additional components of roughness are considered. More significant, however, is the fact that both the slopes and the y-intercept values in the resulting linear regression equations decrease with smaller blanking bands. This is, again, the result of additional profile roughness being considered.

Figure 5. IRI-PI5-mm (PI0.2-inch) correlations established in Florida's ride quality equipment study (FLDOT, 1997).

Figure 5. IRI-PI (5-millimeter) (PI (0.2-inch)) correlations established in Florida's ride quality equipment study (Florida DOT, 1997). The figure shows a graph with PI (0.2-inch), inches per mile, on the horizontal axis; and IRI, inches per mile, on the vertical axis. Points for Laser and Ultrasonic Profilometers were graphed. The regression line for the Laser Profilometer starts at an IRI of 40 and ends at about 92 and for the Ultrasonic Profilometer it starts at 55 and ends at 90. For Laser, IRI = 3.9519*PI + 39.927, R-squared = 0.8846, N = 12. For Ultrasonic, IRI = 3.1539*PI + 52.196, R-squared = 0.6665, N = 12.

Figure 6. IRI-PI2.5-mm (PI0.1-inch) and IRI-PI0.0 correlations established in Florida's ride quality equipment study (FLDOT, 1997).

Figure 6. IRI-PI (2.5-millimeter) (PI (0.1-inch)) and IRI-PI (0.0) correlations established in Florida's ride quality equipment study (Florida DOT, 1997). The figure shows a graph with PI, inches per mile, on the horizontal axis; and IRI, inches per mile, on the vertical axis. Points for Laser IRI vs PI (0.1-inch), Laser IRI vs PI (0.0-inch), Ultrasonic IRI vs PI (0.1-inch), and Ultrasonic IRI vs PI (0.0-inch) are graphed. The regression line for Ultrasonic IRI vs PI (0.1-inch) starts at an IRI of about 45 (PI 2.5) and ends at about 90 (PI 20) and for Laser IRI vs PI (0.1-inch) it starts at 40 (PI 2.5) and ends at 85 (PI 20). The regression line for Ultrasonic IRI vs PI (0.0-inch) starts at an IRI of about 40 (PI 10) and ends at about 85 (PI 30) and for Laser IRI vs PI (0.1-inch) it starts at 35 (PI 10) and ends at 75 (PI 30). For the Laser profilograph for PI (0.1-inch, IRI = 2.7345*PI (0.1-inch) + 31.907, R-squared = 0.9586, N = 5; and for PI (0.0-inch, IRI = 2.1899*PI (0.0-inch) + 13.75, R-squared = 0.8784, N = 5. For the Ultrasonic profilograph for PI (0.1-inch), IRI = 2.708*PI (0.1-inch) + 37.969, R-squared = 0.9568, N = 5; and for PI (0.0-inch) IRI = 2.1991*PI (0.0-inch) + 19.361, R-squared = 0.9016, N = 5.

It is reasonable to surmise from these observations that, if the PI0.0 was computed from a more accurate pavement profile than the one generated by a profilograph, the y-intercept would be much closer to zero. This is because the roughness associated with long wavelengths (e.g., long dips or humps) is automatically filtered out as a result of the short baselength of profilographs.

Texas Transportation Institute Smoothness Testing Equipment Comparison Study

As part of a multi-staged effort to transition from a profilograph-based smoothness specification to a profile-based specification, the Texas Transportation Institute (TTI) was commissioned by the Texas DOT (TXDOT) in 1996 to evaluate the relationship between IRI and profilograph PI (Fernando, 2000). The study entailed obtaining longitudinal surface profiles (generated by one of the Department's high-speed inertial profiler) from 48 newly AC resurfaced pavement sections throughout Texas, generating computer-simulated profilograph traces from those profiles using a field-verified kinematic simulation model, and computing PI5-mm (PI0.2-inch) and PI0.0 values using the Pro-Scan computer software.

A total of three simulated runs per wheelpath per section were performed, from which an average PI value for each section was computed. The resulting section PI values were then compared with the corresponding section IRI values, which had been computed by the inertial profiling system at the time the longitudinal surface profiles were produced in the field. Since both the PI and IRI values were based on the same longitudinal profiles, potential errors due to differences in wheelpath tracking were eliminated.

Illustrated in figure 7 are the relationships between the IRI and the simulated PI response parameters. As can be seen, a much stronger trend was found to exist between IRI and PI0.0 than between IRI and PI5-mm (PI0.2-inch). Again, this is not unexpected since the application of a blanking band has the natural effect of masking certain components of roughness. In comparison with the other IRI-PI5-mm (IRI-PI0.2-inch) correlations previously presented, the one developed in this study is quite typical. The linear regression equation includes a slightly higher slope but a comparable y-intercept value.

Kansas DOT Lightweight Profilometer Performance Study

The major objective of this 1999/2000 study was to compare as-constructed smoothness measurements of concrete pavements taken by the Kansas DOT's (KDOT) manual California-type profilograph, four lightweight inertial profilers (Ames Lightweight Inertial Surface Analyzer [LISA], K.J. Law T6400, ICC Lightweight, and Surface Systems Inc. [SSI] Lightweight), and two full-sized inertial profilers (Kansas DOT South Dakota-type profiler, K.J. Law T6600) (Hossain et al., 2000). The simulated PI0.0 values produced by the various lightweight systems were statistically compared with the California-type profilograph PI0.0 readings to determine the acceptability of using lightweight systems to control initial pavement smoothness. In addition, IRI values generated by the lightweight systems were statistically compared with those generated by the full-sized, high-speed profilers to investigate whether the IRI statistic can be used as a "cradle-to-grave" statistic for road roughness.

Figure 7. Relationship between IRI and computer-simulated PI values in TTI equipment comparison study (Fernando, 2000).

Figure 7. Relationship between IRI and computer-simulated PI values in TTI equipment comparison study (Fernando, 2000). The figure shows a graph with PI, inches per mile, on the horizontal axis; and IRI, inches per mile, on the verticle axis. Points for 0.2-inch blanking band adn 0.0-inch blanking band are graphed. The linear regression for 0.2-inch blanking band starts at an IRI of about 55 (PI 2) and ends at an IRI of 90 (PI 8). For the 0.0-inch blanking band, the linear regression starts at an IRI of about 45 (PI 13) and ends at an IRI of 90 (PI 32). For 0.2-inch blanking band, IRI = 4.0871*PI (0.2-inch) + 52.735, R-squared = 0.5909, N = 48; and for 0.0-inch blanking band, IRI = 2.1425*PI (0.0-inch) + 19.328, R-squared = 0.8532, N = 48.

The field evaluation was performed at eight sites along I-70 west of Topeka. Each lane (driving and passing) at each site was tested with the KDOT's profilograph and full-sized profiler, while the remaining profilers tested at only some of the eight sites. At a given site, one run of each wheelpath was made with the profilograph, and the average of the two runs was determined and reported. For the lightweight and full-sized profilers, three and five runs were made, respectively, with both wheelpaths measured and averaged during each run.

Statistical analysis of the data indicated that the lightweight systems tended to produce statistically similar PI0.0 values when compared to the KDOT manual profilograph. It also showed similarities in IRI between the KDOT full-sized profiler and three of the four lightweight profilers, giving some credence to the "cradle-to-grave" roughness concept.

The study included correlation analysis between the PIs from the manual profilograph and those from the lightweight systems. It also included correlation analysis between the simulated PI and IRI values produced by each inertial profiler. Plots of these data are provided in figure 8, which also shows the linear IRI-PI0.0 relationship that results when data from all profiling devices are considered.

No correlations were made in the KDOT study between profilograph PI0.0 and inertial profiler IRI. However, using data from the report, several such trends have now been developed and are illustrated in figure in 9. Each data point in this figure represents the mean smoothness (profilograph PI0.0 and profiler IRI) of one lane at one test site. As can be seen, only the IRI data taken by two of the lightweight profilers (Ames LISA and ICC) and the KDOT full-sized profiler are represented. The other three profilers collected data from only two of the eight sites, which resulted in very limited data sets.

Figure 8. Plots of IRI and simulated PI0.0 values generated by various profilers in KDOT lightweight profiler comparison study.

Figure 8. Plots of IRI and simulated PI (0.0) values generated by various profilers in Kansas DOT lightweight profiler comparison study. The figure shows a graph with Simulated PI (0.0), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. Points for the KJ Law T6400 Lightweight, KJ Law T6600 Full-Sized Profiler, ICC Lightweight, Ames LISA Lightweight, SSI Lightweight, and KDOT Full-Sized Profiler are graphed. The regression line for all systems combined starts at about 1.000 IRI (0.250 PI) and ends at 1.800 IRI (0.650 PI). IRI = 1.9887*PI (0.0) + 0.5647 and R-squared = 0.5901.

Figure 9. Relationship between IRI and California profilograph PI0.0 in KDOT lightweight profiler comparison study.

Figure 9. Relationship between IRI and California profilograph PI (0.0) in Kansas DOT lightweight profiler comparison study. The figure shows a graph with KSDOT CA profilograph PI (0.0), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. Points for the KDOT Profiler, ICC Lightweight, and Ames Lightweight are graphed. The regression lines for all three profilers are nearly identical, starting at about 1.100 IRI (0.250 PI) and ending at 1.800 IRI (0.500 PI). For the KDOT Profiler: IRI = 2.7616*PI (0.0) + 0.3633, R-squared = 0.5773. For the ICC Lightweight Profiler: IRI = 2.8717*PI (0.0) + 0.3282, R-squared = 0.5645. For the Ames Lightweight: IRI = 2.7931*PI (0.0) + 0.3145 and R-squared = 0.7202.

Illinois DOT Bridge Smoothness Specification Development Study

As part of an effort to develop a preliminary bridge smoothness specification for the Illinois DOT (ILDOT), the University of Illinois coordinated a series of bridge smoothness tests in 1999 using the K.J. Law T6400 lightweight inertial profiler (Rufino et al., 2001). A total of 20 bridges in the Springfield, Illinois area were chosen and tested, with each bridge measured for IRI and PI5-mm (PI0.2-inch). At least one run per wheelpath of the driving lane was made, and each run extended from the front approach pavement across the bridge deck to the rear approach pavement.

A correlation analysis of the IRI and simulated PI5-mm (PI0.2-inch) values produced by the lightweight profiler was performed in the study, which resulted in the graph and linear relationship given in figure 10. Unlike other relationships presented earlier in this chapter, this relationship covers a larger spectrum of PI values -- PI5-mm (PI0.2-inch) values largely in the range of 0.4 to 1.0 m/km (25 to 63 inches per mile) -- due to the fact that bridges are often much rougher than pavements.

Figure 10. Relationship between IRI and simulated PI5-mm (PI0.2-inch) in ILDOT bridge smoothness study (Rufino et al., 2000).

Figure 10. Relationship between IRI and simulated PI (5-mm) (PI (0.2-inch)) in Illinois DOT bridge smoothness study (Rufino et al., 2000). The figure shows a graph with Simulated PI (0.2-inch), inches per mile, on the horizontal axis; and IRI, inches per mile on the vertical axis. The regression line runs from 75 IRI (2 PI) to 230 IRI (75 PI). IRI = 2.1645*PI (0.2-inch) + 73.657, R-squared = 0.83.

Summary

Table 1 summarizes the various regression equations found in the literature relating IRI from an inertial profiling system with PI statistics (PI5-mm, PI2.5-mm, and PI0.0) generated by California-type profilographs or simulated by inertial profilers. How these various relationships compare visually with one another can be seen in figures 11 through 13. Generally speaking, there is considerable disparity in the vertical positioning of each trend, but the slopes are rather similar. The fact that different pavement types, different roughness ranges, and different pieces of testing equipment are represented by the various trends is believed to account in large part for the disparities observed.

Table 1. Summary of documented PI-IRI relationships.

IRI vs. PI5-mm:

Study (Year)Pavement TypesNo. of Test SectionsRemarksLinear Regression Equation, m/kmLinear Regression Equation, inches per mile
PTI (1988)AC and PCC26Manual profilograph PI, Laser-type inertial profilerIRI = 4.02*PI + 1.11IRI = 4.02*PI + 70.13
PTI (1988)AC and PCC26Computerized profilograph PI, Laser-type inertial profilerIRI = 2.46*PI + 1.04IRI = 2.46*PI + 66.22
Arizona DOT (1992)PCC12Computerized profilograph PI, Laser-type inertial profilerIRI = 6.10*PI + 0.83IRI = 6.10*PI + 52.90
University of Texas (1992)AC and PCC18Computerized profilograph PI, Manually computed IRI (Dipstick)IRI = 2.83*PI + 1.16IRI = 2.83*PI + 73.70
Florida DOT (1996)AC12Computerized profilograph PI, Laser-type inertial profilerIRI = 3.95*PI + 0.63IRI = 3.95*PI + 39.93
Florida DOT (1996)AC12Computerized profilograph PI, Ultrasonic-type inertial profilerIRI = 3.15*PI + 0.82IRI = 3.15*PI + 52.20
TTI (1996)AC overlays48Computer-simulated PI, Laser-type inertial profilerIRI = 4.09*PI + 0.83IRI = 4.09*PI + 52.74
Illinois DOT (2000)Bridge decks20Simulated PI, Lightweight inertial profilerIRI = 2.16*PI + 1.16IRI = 2.16*PI + 73.66

IRI vs. PI2.5-mm:

Study (Year)Pavement TypesNo. of Test SectionsRemarksLinear Regression Equation, m/kmLinear Regression Equation, inches per mile
Florida DOT (1996)AC12Computerized profilograph PI, Laser-type inertial profilerIRI = 2.73*PI + 0.50IRI = 2.73*PI + 31.91
Florida DOT (1996)AC12Computerized profilograph PI, Ultrasonic-type inertial profilerIRI = 2.71*PI + 0.60IRI = 2.71*PI + 37.97

IRI vs. PI0.0

Study (Year)Pavement TypesNo. of Test SectionsRemarksLinear Regression Equation, m/kmLinear Regression Equation, inches per mile
TTI (1996)AC overlays48Computer-simulated PI, Laser-type inertial profilerIRI = 2.14*PI + 0.31IRI = 2.14*PI + 19.33
Florida DOT (1996)AC12Computerized profilograph PI, Laser-type inertial profilerIRI = 2.19*PI + 0.22IRI = 2.19*PI + 13.75
Florida DOT (1996)AC12Computerized profilograph PI, Ultrasonic-type inertial profilerIRI = 2.20*PI + 0.31IRI = 2.20*PI + 19.36
Kansas DOT (1999/2000)PCC8Manual profilograph PI, Full-sized and lightweight inertial profilersIRI = 2.00*PI + 0.56IRI = 2.00*PI + 35.50
Kansas DOT (1999/2000)PCC8Computer-simulated PI, Full-sized inertial profilerIRI = 2.76*PI + 0.36IRI = 2.76*PI + 22.82
Kansas DOT (1999/2000)PCC8Computer-simulated PI, Lightweight inertial profiler 1IRI = 2.87*PI + 0.33IRI = 2.87*PI + 20.92
Kansas DOT (1999/2000)PCC8Computer-simulated PI, Lightweight inertial profiler 2IRI = 2.79*PI + 0.31IRI = 2.79*PI + 19.65

Figure 11. Graphical illustration of documented PI5-mm -- IRI smoothness relationships.

Figure 11. Graphical illustration of documented PI (5-millimeter) -- IRI smoothness relationships. The figure shows a graph with PI (5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The following lines are graphed: 1992 AZDOT (PCC), 1996 FLDOT (AC, laser IRI), 1996 TTI (ACOL, computer-simulated PI), 1988 PTI (AC and PCC, computerized PI), 1992 University of Texas (PCC), 1996 FLDOT (AC, ultrasonic IRI), 1988 PTI (AC and PCC, manual PI), 2000 ILDOT (Bridges, computer-simulated PI). All lines begin between 0.6 and 1.25 IRI (PI 0.00) and end between 1.5 and 2.4 IRI (PI 0.24).

Figure 12. Graphical illustration of documented PI2.5-mm -- IRI smoothness relationships.

Figure 12. Graphical illustration of documented PI (2.5-millimeter)-IRI smoothness relationships. The figure shows a graph with PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. A graph of the 1996 FLDOT (AC, laser IRI) starts around 0.50 IRI at 0.0 PI and ends at 1.10 IRI at 0.24 PI. For the 1996 FLDOT (AC, ultrasonic IRI), the graph starts at 0.60 IRI (PI 0.00) and ends at 1.20 IRI at (PI 0.24).

Figure 13. Graphical illustration of documented PI0.0-IRI smoothness relationships.

Figure 13. Graphical illustration of documented PI (0.0)-IRI smoothness relationships. The figure shows a graph with PI (0.0), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The following lines are graphed: 1996 FLDOT (AC, laser IRI), 1996 TTI (ACOL, computer-simulated PI), 1999 KDOT (PCC, sim. PI, full profiler), 1999 KDOT (PCC, sim. PI, ltwt profiler 2), 1996 FLDOT (AC, ultrasonic IRI), 1999 KDOT (PCC), 1999 KDOT (PCC, sim. PI, ltwt profiler 1). The graph of the 1999 KDOT (PCC) profiler starts at nearly 0.60 IRI and ends at 1.00 IRI. The graphs of the 1999 KDOT (PCC, sim. PI, full profiler), 1999 KDOT (PCC, sim. PI, ltwt profiler 2), and 1999 KDOT (PCC, sim. PI, ltwt profiler 1) start at about 0.30 and end at about 1.00 IRI. The graph of the 1996 FLDOT (AC, ultrasonic IRI) and 1996 TTI (ACOL, computer-simulated PI) starts at about 0.30 and ends at 0.80 IRI. The graph of 1996 FLDOT (AC, laser IRI) starts at 0.20 and ends at 0.70 IRI.

Chapter 3. LTPP Data Collection and Project Database Development

Introduction

As mentioned previously, the main thrust of this study involves the comprehensive analysis of LTPP smoothness data. Since the time the LTPP program was initiated in 1989, several hundred test pavements throughout the country have been tested for smoothness on an annual or biennial basis using full-sized, high-speed inertial profilers. In each test, the longitudinal surface profile of each wheelpatch was measured and recorded, and from those profiles the IRI of each wheelpath was computed and recorded for inclusion in the LTPP Information Management System (IMS) database. The sections below describe in detail the collection of LTPP data and the development of the project database used to examine the relationship between IRI and PI.

Collection of LTPP Profile Data

To retrieve the profile and smoothness data required for this study, a data request was submitted to the LTPP IMS database manager. All 1996 - 2001 archived profile data contained in the Ancillary Information Management System (AIMS) and IRI data contained in the IMS were requested, covering all LTPP test sections. Data for this time period only were requested, as they represented data collected by a specific model of profiling equipment -- the 1995 version of the K.J. Law T-6600 inertial profiler. Four such profilers were purchased by LTPP in 1996 for use by each LTPP Regional Contracting Office (North Central, North Atlantic, Southern, Western).

The 1995 T-6600 profiler is considered a class I accelerometer-established inertial profiling reference based on American Society of Testing and Materials (ASTM) E-950-98. It is a van-mounted system containing two infrared sensors spaced 1,676 mm (66 inches) apart. The system collects longitudinal profile data at 25.4-mm (1-inch) intervals, and these data are processed through a moving-average smoothing filter to generate 152-mm (6-inch) profile data, which are subsequently downloaded and stored in the IMS database. Also stored in the IMS database are the individual wheelpath IRI values computed from the 152-mm (6-inch) profile data.

The original 25.4-mm (1-inch) profile data are also archived, but they are done so in the AIMS databases managed by each Regional Contracting Office. Because current automated profilographs record profile traces on 32-mm (1.25-inch) intervals, the AIMS profile data represent a closer match of the profile traces than the 152-mm (6-inch) IMS profile data. Hence, in addition to requesting IRI and relevant test section data (e.g., State ID, SHRP ID, experiment number, pavement type, climatic information) contained in the IMS database, all available 25.4-mm (1-inch) profile data were solicited.

Conversion of Profile Data to Simulated PI Values

To model profilograph traces and generate simulated PI values from the AIMS profile data, a calibrated software modeling system was used. In 1995, K.J. Law developed software to model California-type profilograph traces and output PI values. This software is now used with their lightweight profilers to compute PI and IRI. K.J. Law's lightweight profilers use the same vertical elevation sensors that are mounted on the T-6600 profiler, which again has been the device used to collect profiles for the LTPP program. Although there are several good lightweight profilers and PI modeling systems available, the K.J. Law modeling software was selected for this study to provide the most compatibility with the available LTPP profile data.

Using the modeling and index computation software currently installed on their commercial lightweight profilers, K.J. Law developed interface for analysis of the LTPP data. Named "Indexer," the software computes PI, IRI, and ride number (RN) values using University of Michigan Transportation Research Institute (UMTRI) Engineering Research Department (ERD) format input files. The operator can set the blanking band, as well as several other parameters, such as the type of smoothing filter (moving average or third-order Butterworth) and the type of scallop filter (height, length, rounding).

In this study, the 25.4-mm (1-inch) AIMS profile data were processed into 0.0-, 2.5-, and 5-mm (0.0-, 0.1-, and 0.2-inch) blanking band PI values (herein designated as PI0.0, PI2.5-mm, and PI5-mm) for each profile data set using the K.J. Law Indexer 3.0 software. These simulated PI values were computed using a 0.76-m (2.5-ft) moving-average filter, along with minimum height, maximum height, and rounding scallop filters settings of 0.9, 0.6, and 0.25 mm (0.035, 0.024, and 0.01 inches), respectively.

During the conversion of profile data into simulated PI values, the issue of subsectioning of SPS profile data was addressed. Unlike GPS test sites, which serve as individual 152.5-m (500-ft) test sections, each SPS test site contains between 3 and 20 test sections comprised of different designs, materials, and construction practices. Profile data for each SPS site are collected in one pass, and the data are subsectioned only after conversion to 152-mm (6-inch) intervals.

To extract 25.4-mm (1-inch) profile data for each SPS test section, a special subsectioning program was developed and applied to each continuous SPS test site profile. Each subsectioned profile was then processed for IRI, PI0.0, PI2.5-mm, and PI5-mm using the Indexer program. As a data quality control measure, each IRI value computed by Indexer was compared with the IRI value computed in the field and subsequently reported in the IMS database. All profiler runs that showed more than 0.0075 m/km (0.475 inches per mile) difference between the Indexer-computed IRI and the IMS database IRI were excluded from the project database.

Populating the Project Database

IRI and relevant test section data obtained from the IMS database were downloaded into Microsoft® Access, a database management system that provides easy extraction of data into spreadsheets and statistical analysis input files. The IRI data consist of right and left wheelpath IRI values generated from individual profiler runs conducted on GPS and SPS sites between 1996 and 2001.

Simulated PI0.0, PI2.5-mm, and PI5-mm values derived from the 25.4-mm (1-inch) profile data were also added to the project database. Moreover, to successfully carry out the data analyses for the project, mean IRI and mean simulated PI values were computed from each pair of left- and right-wheelpath smoothness values. The resulting means were then added to the project database.

A total of 1,793 LTPP test sections located in 47 States and 8 Canadian Provinces formed the basis for this evaluation. The sections represent a variety of pavement types, including original and restored AC and PCC pavements, asphalt overlays of both AC and PCC pavements, and concrete overlays of PCC pavements. They also span all four climatic zones-dry freeze, dry nonfreeze, wet freeze, wet nonfreeze -- as defined by mean annual precipitation (wet being greater than 508 mm [20 inches] of precipitation per year) and mean annual freezing index (FI) (freeze being more than 66°C-days [150°F-days] per year).

Each test section in the database includes IRI and simulated PI values corresponding to individual profiler runs made between 1996 and 2001. Breakdowns of the test sections by LTPP experiment and by State are provided in tables 2 and 3, respectively.

Table 2. Breakdown of test sections by LTPP experiment.

GPS Experiment No.No. of GPS LTPP SectionsSPS Experiment No.No. of SPS LTPP Sections
GPS-1(Conventional AC pavement)140SPS-1(Structural factors for flexible pavement)207
GPS-2(Full-depth AC pavement)77SPS-2(Structural factors for rigid pavement)166
GPS-3(JPC pavement)120SPS-3(Preventive maintenance of AC pavement)259
GPS-4(JRC pavement)50SPS-4(Preventive maintenance of PCC pavement)72
GPS-5(CRC pavement)64SPS-5(AC overlays on AC pavement)152
GPS-6(AC overlays on AC pavement)169SPS-6(CPR and AC overlays on PCC pavement)103
GPS-7(AC overlays on PCC pavement)55SPS-7(Bonded PCC overlays on PCC pavement)27
GPS-9(Unbonded PCC overlays)24SPS-8(Environmental effects on AC, PCC pavements)47
  SPS-9(SHRP AC mix designs)80

Table 3. Breakdown of test sections by State.

State/ProvinceNo. of LTPP SectionsState/ProvinceNo. of LTPP SectionsState/ProvinceNo. of LTPP Sections
Alabama58Michigan62South Dakota27
Arizona81Minnesota68Tennessee25
Arkansas57Mississippi38Texas156
California78Missouri79Utah31
Colorado42Montana36Vermont4
Connecticut7Nebraska40Virginia29
Delaware28Nevada37Washington41
Florida46New Hampshire1West Virginia5
Georgia28New Jersey23Wisconsin53
Idaho22New Mexico33Wyoming21
Illinois36New York7Alberta16
Indiana35North Carolina39British Columbia4
Iowa60North Dakota16Manitoba20
Kansas56Ohio41New Brunswick3
Kentucky15Oklahoma55Newfoundland2
Louisiana13Pennsylvania30Ontario12
Maine17Rhode Island1Quebec11
Maryland21South Carolina7Saskatchewan17
Massachusetts3    

Chapter 4. Development of LTPP-Based Smoothness Index Relationships

Introduction

Based on a comprehensive review of past model development research, the following procedure was utilized in developing LTPP-based PI-to-PI0.0 and PI-to-IRI relationships:

  1. Perform preliminary evaluation of the assembled database, including a detailed check of data quality, appropriate data cleaning, and development of comprehensive scatter plots.
  2. Select the most appropriate model form for the smoothness indices relationships. Selection will be based on trends observed from the preliminary data analysis and past research.
  3. Analyze the results of the preliminary data analysis (bivariate plots) and conduct an analysis of variance (ANOVA) to determine the groupings of pavement types, climatic regions, and other factors with similar smoothness indices relationships (e.g., no significant differences in slopes for linear relationships).
  4. Develop tentative models for the smoothness indices relationships.
  5. Assess tentative models for reasonableness (e.g., assess model diagnostic statistics, such as correlation coefficient [R2] and the standard error of the estimate [SEE]).
  6. Select final models.

The steps outlined for model development are summarized in the flow chart shown in figure 14 and are explained in greater detail in the sections that follow. This approach has been used in previous research studies and has been improved to provide practical and accurate models.

Figure 14. Flow chart for developing pavement smoothness models.

Figure 14. Flow chart for developing pavement smoothness models. Step 1: Preliminary Evaluation, Step 2: Select Appropriate Model Form, Step 3: Group Data with Similar Trends and Smoothness Relations, Step 4: Develop Tentative Models, Step 5: Assess Tentative Models for Reasonableness, Step 6: Select Final Models.

Step 1 -- Preliminary Evaluation

In step 1 of model development, the assembled database was examined to determine its general properties and to identify possible data anomalies (i.e., outliers, missing or erroneous data). The data were "cleaned" as appropriate and then sorted to allow for the development of various PI- PI0.0 and PI-IRI scatter plots for use in model development.

Data Quality Evaluation

Basic statistics, such as the mean and range of data, were used to identify possible gaps in the data and to determine whether the database was representative of the expected inference space. Of specific interest in this process were the following:

Figures 15 through 18 present histograms showing the distribution of IRI and PI5-mm for all AC- and PCC-surfaced pavements. A detailed summary of the information depicted in the plots (categorized by pavement type and climatic region) is provided in table 4. It is clear from these exhibits that the data used for analysis (i.e., the cleaned data), and for developing PI-PI0.0 and PI-IRI relationships, fully cover the ranges of smoothness typical of new construction and AC overlays (i.e., IRI between 800 and 2,000 mm/km [50 and 125 inches per mile], PI5-mm between 0 and 235 mm/km [0 and 15 inches per mile]).

Development of Scatter Plots

As summarized in table 5, 111 scatter plots of IRI versus PI5-mm, PI2.5-mm, and PI0.0, and 111 scatter plots of PI0.0 versus PI5-mm and PI2.5-mm were produced to aid the model development process. The scatter plots represent various combinations of climatic zone and pavement type. Complete sets of the scatter plots developed in the study are provided in appendixes A and B.

At the broadest level, over 14,000 asphalt pavement smoothness data points (representing the average roughness of right and left wheelpaths) and over 8,000 concrete pavement data points representing all four climatic zones were available for plotting and model development. Figure 19 shows the PI0.0-IRI scatter plot for all AC pavements, and figure 20 shows the PI5-mm-PI0.0 scatter plot for all PCC pavements. These plots, which are typical of most of the scatter plots, show reasonably strong (R2 > 0.75) and virtually linear relationships between the smoothness indices. They also, however, illustrate the considerable amount of variation due in large part to the inherent differences in the way the smoothness indices process different surface wavelengths.

Examples of the effects of pavement type and climatic zone on the smoothness relationships can be seen in figures 21 and 22. In the case of the PI0.0-IRI trends for different AC pavements (figure 21), the differences are almost negligible. Slightly more distinct differences, however, are discernible among the PI5-mm-PI0.0 trends representing different climatic zones (figure 22).

Figure 15. Histogram showing the distribution of IRI data used in model development (all AC pavements).

Figure 15. Histogram showing the distribution of IRI data used in model development (all AC pavements). The graph shows IRI (millimeters per kilometer) on the horizontal axis and Frequency on the vertical axis. Frequencies between 1000 and 1200 are seen for IRI's of 1000 and 1500. At an IRI of 2000, the frequency is just under 4000 and the remaining IRIs have frequencies less than 2000. The cumulative curve indicates that 80% have IRIs of less than 1500.

Figure 16. Histogram showing the distribution of IRI data used in model development (all PCC pavements).

Figure 16. Histogram showing the distribution of IRI data used in model development (all PCC pavements). The graph shows IRI (millimeters per kilometer) on the horizontal axis and Frequency on the vertical axis. At IRIs of 1000, 1500, 2000, and 2500, frequencies are about 2000, 7300, 6000, and 2500, respectively. At IRIs of greater than 2500, frequencies are less than or equal to 1000. At IRIs less than 1000, frequencies are near zero. The cumulative curve indicates that less than 80% have IRIs of 2000 or less.

Figure 17. Histogram showing the distribution of PI5-mm data used in model development (all AC pavements).

Figure 17. Histogram showing the distribution of PI (5-millimeter) data used in model development (all AC pavements). The graph shows PI (5.0 millimeters blanking band), millimeters per kilometer, on the horizontal axis and Frequency on the vertical axis. At PIs of 30, 90, 150, 210, frequencies are about 11000, 7000, 4000, and 2000, respectively. At PIs greater than 210, frequencies are below 2000. The cumulative curve indicates that 80% have PIs of 150 or less.

Figure 18. Histogram showing the distribution of PI5-mm data used in model development (all PCC pavements).

Figure 18. Histogram showing the distribution of PI (5-millimeter) data used in model development (all PCC pavements). The graph shows PI (5.0 millimeters blanking band), millimeters per kilometer, on the horizontal axis and Frequency on the vertical axis. At PIs of 30, 90, 150, 210, 270, 330, and 390, frequencies are about 4500, 3500, 2200, 1700, 1200, 1200, and 700, respectively. At PIs greater than 400, frequencies are between 250 and 500. The cumulative curve indicates that 70% have PIs of 210 or less and 50% have PIs less than 90.

Table 4. Summary of basic statistics of data used in model development.

Pavement TypeClimateNIRI MeanIRI Std. Dev.PI0.0 MeanPI0.0 Std. Dev.PI2.5-mm MeanPI2.5-mm Std. Dev.PI5-mm MeanPI5-mm Std. Dev.
ACDF2,7201,252.5671.5373.8216.9190.3187.891.0137.6
ACDNF1,7401,031.4518.7297.7179.1142.0139.463.889.9
ACWF6,5021,330.3661.2450.8238.7254.2215.1131.8163.4
ACWNF4,0461,186.0492.6370.9181.9193.5165.092.5122.4
AC/ACDF1,8561,397.6629.0412.3218.2220.4187.3106.4130.8
AC/ACDNF1,5021,011.1422.2274.6141.9106.5103.040.163.4
AC/ACWF3,8321,135.8423.9342.2159.6174.4140.579.598.3
AC/ACWNF1,4261,125.6491.2346.6192.3181.9158.891.0110.4
AC/PCDF901,072.4196.9336.488.2152.8115.363.272.7
AC/PCDNF0
-
-
-
-
-
-
-
-
AC/PCWF3,7741,208.5444.5387.1167.7181.0138.274.389.6
AC/PCWNF3761,280.6461.8358.4140.3163.0130.168.4100.5
JPCaDF2,1541,536.8545.2475.2210.6226.4195.899.9139.5
JPCaDNF1,2701,464.9500.1394.8175.1162.1168.368.9117.8
JPCaWF6,5421,639.8703.4572.3294.8334.2286.5180.4236.1
JPCaWNF2,1961,737.3612.7594.1228.3337.7216.0161.5174.1
JRCaDF0
-
-
-
-
-
-
-
-
JRCaDNF0
-
-
-
-
-
-
-
-
JRCaWF1,9501,955.7508.0780.0233.1531.2231.2321.9197.4
JRCaWNF3492,053.8349.0785.4144.4546.3142.8328.9129.2
CRCaDF391,330.354.0508.825.8336.355.3160.829.0
CRCaDNF1201,275.2397.6395.0207.2180.3200.798.0142.2
CRCaWF7221,575.6478.0541.7202.2332.9204.0181.7166.7
CRCaWNF3581,620.7457.5563.4193.3343.6188.6189.2153.7
Notes: - = No data available; a = New construction only.
Table 5. Matrix of scatter plots created for model development.

Climatic ZoneModelAll ACACAC/ACAC/PCCAll PCCJPCJRCCRC
Dry-FreezeIRI vs. PI0.0YesYesYesYesYesYes-Yes
Dry-FreezeIRI vs. PI2.5-mmYesYesYesYesYesYes-Yes
Dry-FreezeIRI vs. PI5-mmYesYesYesYesYesYes-Yes
Dry-NonfreezeIRI vs. PI0.0YesYesYes-YesYes-Yes
Dry-NonfreezeIRI vs. PI2.5-mmYesYesYes-YesYes-Yes
Dry-NonfreezeIRI vs. PI5-mmYesYesYes-YesYes-Yes
Wet-FreezeIRI vs. PI0.0YesYesYesYesYesYesYesYes
Wet-FreezeIRI vs. PI2.5-mmYesYesYesYesYesYesYesYes
Wet-FreezeIRI vs. PI5-mmYesYesYesYesYesYesYesYes
Wet-NonfreezeIRI vs. PI0.0YesYesYesYesYesYesYesYes
Wet-NonfreezeIRI vs. PI2.5-mmYesYesYesYesYesYesYesYes
Wet-NonfreezeIRI vs. PI5-mmYesYesYesYesYesYesYesYes
AllIRI vs. PI0.0YesYesYesYesYesYesYesYes
AllIRI vs. PI2.5-mmYesYesYesYesYesYesYesYes
AllIRI vs. PI5-mmYesYesYesYesYesYesYesYes
Dry-FreezePI0.0 vs. PI5-mmYesYesYesYesYesYes-Yes
Dry-FreezePI0.0 vs. PI2.5-mmYesYesYesYesYesYes-Yes
Dry-FreezePI2.5-mm vs. PI5-mmYesYesYesYesYesYes-Yes
Dry-NonfreezePI0.0 vs. PI5-mmYesYesYes-YesYes-Yes
Dry-NonfreezePI0.0 vs. PI2.5-mmYesYesYes-YesYes-Yes
Dry-NonfreezePI2.5-mm vs. PI5-mmYesYesYes-YesYes-Yes
Wet-FreezePI0.0 vs. PI5-mmYesYesYesYesYesYesYesYes
Wet-FreezePI0.0 vs. PI2.5-mmYesYesYesYesYesYesYesYes
Wet-FreezePI2.5-mm vs. PI5-mmYesYesYesYesYesYesYesYes
Wet-NonfreezePI0.0 vs. PI5-mmYesYesYesYesYesYesYesYes
Wet-NonfreezePI0.0 vs. PI2.5-mmYesYesYesYesYesYesYesYes
Wet-NonfreezePI2.5-mm vs. PI5-mmYesYesYesYesYesYesYesYes
AllPI0.0 vs. PI5-mmYesYesYesYesYesYesYesYes
AllPI0.0 vs. PI2.5-mmYesYesYesYesYesYesYesYes
AllPI2.5-mm vs. PI5-mmYesYesYesYesYesYesYesYes

Note: - = No data available.

Figure 19. IRI vs. PI0.0 for all AC pavements and climates.

Figure 19. IRI vs. PI (0.0) for all AC pavements and climates. The graph shows Simulated PI (0.0), meters per kilometer, on the horizontal axis and IRI, meters per kilometer, on the vertical axis. The line of regression starts at an IRI of 0.3 (0.0 PI) and ends at an IRI of 5.2 (1.8 PI).

Figure 20. PI0.0 vs. PI5-mm for all PCC pavements and climates.

Figure 20. PI (0.0) vs. PI (5-millimeter) for all PCC pavements and climates. The graph shows Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis and Simulated PI (0.0), millimeters per kilometer, on the vertical axis. The line of regression starts at a PI (0.0) of 0.47 (PI (5-millimeter) of 0.0) and ends at a PI (0.0) of 1.7 (PI (5-millimeter) of 1.2).

Figure 21. IRI vs. PI0.0 by AC pavement type for all climates.

Figure 21. IRI vs. PI (0.0) by AC pavement type for all climates. The graph shows Simulated PI (0.0), meters per kilometer, on the horizontal axis and IRI, meters per kilometer, on the vertical axis. Regression lines are shown for AC, All AC, AC/AC, and AC/PCC pavements. The lines for AC, All AC, and AC/AC are nearly identical, starting at an IRI of 0.2 (0.0 PI) and going through an IRI of 3.4 (PI 1.2). The line of regression of AC/PCC is very similar, starting at an IRI of 0.2 (0.0 PI), but going through an IRI of 3.2 at 1.2 PI.

Figure 22. PI0.0 vs. PI5-mm by climate for all PCC pavement types.

Figure 22. PI (0.0) vs. PI (5-millimeter) by climate for all PCC pavement types. The graph shows Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis and Simulated PI (0.0), meters per kilometer, on the vertical axis. The lines of regression for Wet-Freeze and Non-Wet Freeze at nearly identical, starting at a PI (0.0) of 0.4 (PI (5-millimeter) of 0.0) and going through a PI (0.0) of 1.6 (PI (5-millimeter) of 1.0). The line of regression for Dry-Freeze Pavements is slightly steeper, starting at a PI (0.0) of 0.3 (PI (5-millimeter) of 0.0) and going through a PI (0.0) of 1.2 (PI (5-millimeter) of 0.6).

Figures 23 through 27 provide for a direct visual comparison of the smoothness relationships developed in past studies with the LTPP-derived relationships. In each figure, a bandwidth envelope centered one standard deviation around the LTPP-derived regression line has been transposed over the individual regression lines of the past documented smoothness studies. Though the LTPP relationships represent a wide range of smoothness, only the levels typical of new construction (IRI < 2.0 m/km [127 inches per mile]) are illustrated in figures 23 through 27.

As can be seen, in most instances, the LTPP regression envelope covers the individual PI-IRI relationships. In the case of the PI5-mm-IRI relationships for asphalt (figure 23), the PTI relationship and one of the Florida relationships (IRI using ultrasonic profiler) extended outside the LTPP envelope. Equipment is likely a contributing factor with respect to the Florida relationship, as ultrasonic sensors were used as opposed to the infrared sensors used in the LTPP program). And, as noted in the figure, the PTI relationship was based on measurements for both AC and PCC pavements.

In the PI5-mm-IRI relationships for concrete (figure 23), the Arizona relationship contrasted sharply with the LTPP relationship. The fact that the Arizona relationship was based on measurements from only 12 concrete pavement sections may help explain this departure. However, other factors, such as sensor type (Arizona used optical sensors), are likely to have also contributed to this phenomenon.

Figure 23. Graphical comparison of PI5-mm-IRI smoothness relationships for AC pavements.

Figure 23. Graphical comparison of PI (5-millimeter)-IRI smoothness relationships for AC pavements. The figure shows a graph with PI (5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The following lines are graphed: 1996 FLDOT (AC, laser IRI), 1996 TTI (ACOL, computer-simulated PI), 1988 PTI (AC and PCC, computerized PI), 1996 FLDOT (AC, ultrasonic IRI), 1988 PTI (AC and PCC, manual PI, 2000 ILDOT (Bridges, computer-simulated PI), and 2001 LTPP (All AC). The Band Width Envelope on the LTPP Regression Line has a lower limit of 0.70 IRI (PI 0.00) to 1.50 IRI (PI 0.24) and an upper limit of 1.10 IRI (PI 0.00) to 2.00 IRI (PI 0.24).

Figure 24. Graphical comparison of PI5-mm-IRI smoothness relationships for PCC pavements.

Figure 24. Graphical comparison of PI (5-millimeter)-IRI smoothness relationships for PCC pavements. The figure shows a graph with PI (5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The following lines are graphed: 1992 AZDOT (PCC), 1988 PTI (AC and PCC, manual PI), 2000 ILDOT (Bridges, computer-simulated PI), 1992 Univ. of Texas (PCC), 1988 PTI (AC and PCC, computerized PI), and 2001 LTPP (All PCC). The Band Width Envelope on the LTPP Regression Line has a lower limit of 0.90 IRI (PI 0.00) to 1.32 IRI (PI 0.24) and an upper limit of 1.50 IRI (PI 0.00) to 2.30 IRI (PI 0.24).

Figure 25. Graphical comparison of PI2.5-mm-IRI smoothness relationships for AC pavements.

Figure 25. Graphical comparison of PI (2.5-millimeter)-IRI smoothness relationships for AC pavements. The figure shows a graph with PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The following lines are graphed: 1996 FLDOT (AC, laser IRI), 1996 FLDOT (AC, ultrasonic IRI), 2001 LTPP (All PCC). The graph of the 1996 FLDOT (AC, laser IRI) starts at 0.50 IRI (0.00 PI) and ends at 1.50 IRI (0.37 PI). The Band Width Envelope on the LTPP Regression Line has a lower limit of 0.50 IRI (PI 0.00) to 1.60 IRI (PI 0.24) and an upper limit of 0.90 IRI (PI 0.00) to 2.00 IRI (PI 0.24).

Figure 26. Graphical comparison of PI0.0-IRI smoothness relationships for AC pavements.

Figure 26. Graphical comparison of PI (0.0)-IRI smoothness relationships for AC pavements. The figure shows a graph with PI (0.0), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The following lines are graphed: 1996 FLDOT (AC, laser IRI), 1996 TTI (ACOL, computer-simulated PI), 1996 FLDOT (AC, ultrasonic IRI), and 2001 LTPP (All AC). The Band Width Envelope on the LTPP Regression Line has a lower limit of 0.10 IRI (PI 0.00) to 1.32 IRI (PI 0.50) and an upper limit of 0.45 IRI (PI 0.00) to 1.70 IRI (PI 0.50).

Figure 27. Graphical comparison of PI0.0-IRI smoothness relationships for PCC pavements.

Figure 27. Graphical comparison of PI (0.0)-IRI smoothness relationships for PCC pavements. The figure shows a graph with PI (0.0), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The following lines are graphed: 1999 KDOT (PCC), 1999 KDOT (PCC, sim. PI, ltwt profiler 1), 1999 KDOT (PCC, sim. PI, full profiler), 1999 KDOT (PCC, sim. PI, ltwt profiler 2), and 2001 LTPP (All PCC). The Band Width Envelope on the LTPP Regression Line has a lower limit of 0.25 IRI (PI 0.00) to 1.30 IRI (PI 0.50) and an upper limit of 0.70 IRI (PI 0.00) to 1.80 IRI (PI 0.50).

Step 2 -- Selection of Appropriate Model Form

Model development began with the selection of the most suitable functional form that best describes the relationship between IRI and PI. As indicated by the scatter plots presented in figures A-1 through A-37 and B-1 to B-37 in appendixes A and B, the PI-IRI relationship is virtually linear and, thus, a linear function with IRI as the dependent variable and PI as the independent variable was adopted.

A similar functional form was selected for developing the PI0.0 versus PI models, as indicated by the corresponding scatter plots in appendixes A and B. The linear relationship as shown in the figures was true for both AC and PCC surface pavements. The magnitude of the slope, however, varied according to pavement type (AC vs. PCC, or Jointed Plain Concrete (JPC) vs. Continuosly Reinforced Concrete (CRC)) and the climatic region in which the pavement was located. The model form selected is shown as equation 1.

IRI = alpha + beta*PIX, Eq. 1

where:
IRI = International roughness index, mm/km.
PIX = Profile index for blanking band X (X = 0.0, 2.5, or 5.0 mm).
alpha, beta = regression constants.

Step 3 -- Group Data into Sets with Similar Smoothness Relations

Ideally, a single model could be developed to relate the various smoothness indices (e.g., IRI versus PI0.0 for all pavement types, climatic regions). However, unless the influences of different climatic zones and pavement types were statistically insignificant, this would result in the development of models with low prediction capabilities and the introduction of significant levels of error in predicted indices.

On the other hand, developing models for all the different combinations of pavement types (e.g., AC, AC/AC, JPC, CRC) would result in the development of a minimum of 144 models, as illustrated in table 6. So many models is not only impractical from a user's point of view, but could not be developed with the level of accuracy required, due to the lack of sufficient amounts of data in some of the cells in table 6.

For this study, it was deemed important to merge cells within the two main blocks (AC- and PCC-surfaced pavements) in table 6 with similar relationships between the different smoothness indices. Models were developed for a total of six combinations of smoothness indices as follows:

Table 6. Factorial of cells used for model development.

BlockPavement TypeClimatic RegionIRI vs PI (0.0)IRI vs PI (2.5-mm)IRI vs PI (5-mm)PI (0.0) vs PI (2.5-mm)PI (0.0) vs PI (5-mm)PI (2.5-mm) vs PI (5-mm)
Block 1(AC-surfaced pavements)ACDF123456
Block 1(AC-surfaced pavements)ACDNF789101112
Block 1(AC-surfaced pavements)ACWF131415161718
Block 1(AC-surfaced pavements)ACWNF192021222324
Block 1(AC-surfaced pavements)AC/ACDF252627282930
Block 1(AC-surfaced pavements)AC/ACDNF313233343536
Block 1(AC-surfaced pavements)AC/ACWF373839404142
Block 1(AC-surfaced pavements)AC/ACWNF434445464748
Block 1(AC-surfaced pavements)AC/PCDF495051525354
Block 1(AC-surfaced pavements)AC/PCDNF555657585960
Block 1(AC-surfaced pavements)AC/PCWF616263646566
Block 1(AC-surfaced pavements)AC/PCWNF676869707172
Block 2(PCC-surfaced pavements)JPCDF737475767778
Block 2(PCC-surfaced pavements)JPCDNF798081828384
Block 2(PCC-surfaced pavements)JPCWF858687888990
Block 2(PCC-surfaced pavements)JPCWNF919293949596
Block 2(PCC-surfaced pavements)JRCDF979899100101102
Block 2(PCC-surfaced pavements)JRCDNF103104105106107108
Block 2(PCC-surfaced pavements)JRCWF109110111112113114
Block 2(PCC-surfaced pavements)JRCWNF115116117118119120
Block 2(PCC-surfaced pavements)CRCDF121122123124125126
Block 2(PCC-surfaced pavements)CRCDNF127128129130131132
Block 2(PCC-surfaced pavements)CRCWF133134135136137138
Block 2(PCC-surfaced pavements)CRCWNF139140141142143144

  • IRI versus PI0.0.
  • IRI versus PI2.5-mm.
  • IRI versus PI5.0-mm.
  • PI0.0 versus PI5.0-mm.
  • PI0.0 versus PI2.5-mm.
  • PI2.5-mm versus PI5.0-mm.

Similar relationships between the smoothness indices listed above was defined as cells with the same surface type with statistically insignificant differences in mean slope or gradient of a linear model developed relating the two given indices. This is shown conceptually in figure 28.

Thus, cells with similar PI-IRI or PI-PI relationships were merged for model development, so as to limit the number of models. As shown in table 6, cells were defined according to pavement type (e.g., AC, AC/PCC, Jointed Reinforced Concrete (JRC)) and climatic region. For PCC pavements, the categories of surface type were limited to JPC, JRC, and CRC because there were an insufficient number of PCC overlays (e.g., JPC/JPC) to perform a detailed and thorough analysis.

The procedures used to compute mean slopes for the smoothness index relationships for each cell in table 6 are as follows:

  • Develop linear models for each pavement section (with multiple test data within a uniform construction event) for the specific smoothness indices. (e.g., for cell 1 in table 6, the model form IRI = alpha + beta*PI would be used).
  • Develop database with all the beta's for each of the cells.
  • Compute mean slope (mean values of beta) and other relevant statistics, such as standard deviation, for each cell.

Figures 29 through 32 show, for both AC- and PCC-surfaced pavements, examples of the distribution of slopes for IRI versus PI0.0 and PI0.0 versus PI5-mm.

The next step involved testing for similarities or differences in the mean slopes (beta) among cells. This analysis was limited to cells within each pavement category, as it was assumed that there were differences in slopes between AC and PCC pavements. To determine potential similarities or differences among cells, analysis of variance (ANOVA) was performed at the following two levels:

  • Level 1 -- Checks for differences in mean slopes for cells within the two blocks.
  • Level 2 -- Merging together statistically similar cells.

Figure 28. Conceptual plot showing relationships of smoothness indices within and between cells.

Figure 28. Conceptual plot showing relationships of smoothness indices within and between cells. The figure shows a graph with PI (0.0), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The mean slopes for cell 2, IRI = alpha (2) + beta (2)*PI (0.0) and cell 1, IRI = alpha (1) + beta (1)*PI (0.0) are graphed. The conceptual plots of the mean slope for each cell is a straight line that starts at the origin, with the slope for cell 2 being much steeper than for cell 1. Cell 1 and 2 may be merged if beta (1) and beta (2) are not significantly different.

Figure 29. Histogram showing the distribution of slope for IRI versus PI0.0 (for cells in block 1, AC-surfaced pavements).

Figure 29. Histogram showing the distribution of slope for IRI versus PI (0.0) (for cells in block 1, AC-surfaced pavements). The figure shows a bar graph with Slope of IRI vs PI (0.0-millimeter) Linear Relationship on the horizontal axis, and Frequency on the vertical axis. For slopes of 0.25, 0.75, 1.25, 1.75, 2.25, 2.75, 3.25, 3.75, 4.25, 4.75, 5.25, and greater than 5.25 the respective frequencies are about 80, 75, 120, 140, 190, 150, 105, 70, 40, 20, 20, and 25.

Figure 30. Histogram showing the distribution of slope for IRI versus PI0.0 (for cells in block 2, PCC-surfaced pavements).

Figure 30. Histogram showing the distribution of slope for IRI versus PI (0.0) (for cells in block 2, PCC-surfaced pavements). The figure shows a bar graph with Slope of IRI vs PI (0.0-millimeter) Linear Relationship on the horizontal axis, and Frequency on the vertical axis. For slopes of 0.25, 0.75, 1.25, 1.75, 2.25, 2.75, 3.25, 3.75, 4.25, 4.75, 5.25, and greater than 5.25 the respective frequencies are about 55, 25, 55, 90, 83, 73, 55, 32, 31, 13, 9, and 9.

Figure 31. Histogram showing the distribution of slope for PI0.0 versus PI5-mm (for cells in block 1, AC-surfaced pavements).

Figure 31. Histogram showing the distribution of slope for PI (0.0) versus PI (5-millimeter) (for cells in block 1, AC-surfaced pavements). The figure shows a bar graph with Slope of PI (0.0-millimeter) vs PI (5.0-millimeter) Linear Relationship on the horizontal axis, and Frequency on the vertical axis. For slopes of 0.25, 0.75, 1.25, 1.75, 2.25, 2.75, 3.25, 3.75, 4.25, 4.75, 5.25, and greater than 5.25 the respective frequencies are about 155, 100, 200, 220, 140, 80, 55, 30, 25, 20, 10, and 40.

Figure 32. Histogram showing the distribution of slope for PI0.0 versus PI5-mm (for cells in block 2, PCC-surfaced pavements).

Figure 32. Histogram showing the distribution of slope for PI (0.0) versus PI (5-millimeter) (for cells in block 2, PCC-surfaced pavements). The figure shows a bar graph with Slope of PI (0.0-millimeter) vs PI (5.0-millimeter) Linear Relationship on the horizontal axis, and Frequency on the vertical axis. For slopes of 0.25, 0.75, 1.25, 1.75, 2.25, 2.75, 3.25, 3.75, 4.25, 4.75, 5.25, and greater than 5.25 the respective frequencies are about 50, 60, 145, 125, 58, 30, 10, 18, 10, 9, 8, and 21.

Level 1 Analysis

Level 1 analysis involved the following tasks:

The data used in level 1 analysis were as follows:

The basic ANOVA type I statistical model was used in analysis. Like other basic regression models, it was a linear statistical relation between the independent variables and the dependent variable. The model is presented as follows:

Beta = gamma(1) + gamma(2)*CLIMATE + gamma(3)*PVMT, Eq. 2

where:
Beta = Slope of PI-IRI or PI-PI linear model.
CLIMATE = Test pavement climate location.
PVMT = Pavement type.
gamma(1), gamma(2), gamma(3) = Regression constants.

The following hypothesis was tested under the level 1 analysis:

Acceptance or rejection of the null hypothesis was accomplished by computing the level of significance (p-value) for each of the independent classification variables in equation 2 and comparing it to a pre-determined level of significance. For this study, a 95 percent level of significance (p-value = 5 percent) was used. Thus, a computed p-value of 0.05 or less would cause the null hypothesis to be rejected, whereas a p-value greater than 0.05 would confirm the null hypothesis.

The results of the ANOVA are presented in tables 7 and 8 for AC and PCC pavements, respectively. The results show that both pavement type and climate had a significant effect on the PI-IRI and PI-PI relationships. That is, the ANOVA F-test results indicated that one or more of the mean slopes for the different cells in the matrix presented in table 6 were significantly different.

Table 7. ANOVA results on the effect of pavement type and climate on PI-IRI relationship for AC pavements.

Dependent VariableaGrouping VariablebNF-Statistic ValueProbability > F (p-value)
Slope of PI0.0-IRI linear relationshipPavement Type2,3952.240.1061c
Slope of PI0.0-IRI linear relationshipClimate2,3957.610.0001d
Slope of PI2.5-mm-IRI linear relationshipPavement Type2,3955.910.0028d
Slope of PI2.5-mm-IRI linear relationshipClimate2,3953.870.0089d
Slope of PI5-mm-IRI linear relationshipPavement Type2,3950.720.4870e
Slope of PI5-mm-IRI linear relationshipClimate2,3950.950.4177e

Notes:
a Computed for each wheelpath within a given pavement section within a uniform construction period.
b Pavement type considered -- AC, AC/AC, and AC/PCC and climate types -- DF, DNF, WF, and WNF.
c Borderline significance at the 10 percent significance level.
d Significant at the 5 percent significance level.
e Not significant.

Table 8. ANOVA results on the effect of pavement type and climate on PI-IRI relationship for PCC pavements.

Dependent VariableaGrouping VariablebNF-Statistic ValueProbability > F (p-value)
Slope of PI0.0-IRI linear relationshipPavement Type1,1233.440.0630d
Slope of PI0.0-IRI linear relationshipClimate1,1234.820.0024d
Slope of PI2.5-mm-IRI linear relationshipPavement Type1,1235.510.0190d
Slope of PI2.5-mm-IRI linear relationshipClimate1,12313.680.0001d
Slope of PI5-mm-IRI linear relationshipPavement Type1,1192.960.0850c
Slope of PI5-mm-IRI linear relationshipClimate1,11912.460.00014

Notes:
a Computed for each wheelpath within a given pavement section within a uniform construction period.
b Pavement type considered -- AC, AC/AC, and AC/PCC and climate types -- DF, DNF, WF, and WNF.
c Borderline significance at the 10 percent significance level.
d Significant at the 5 percent significance level.
e Not significant.

Level 2 Analysis

Although the ANOVA F-test results listed in tables 7 and 8 indicate significant differences in mean slope for the various cells evaluated, they do not show which cells were similar or how the cells differed from each other. This information is required in order to merge cells that have similar slopes or trends in their PI-IRI and PI-PI relationships, so as to optimize and reduce the number of models to be developed.

Duncan's multiple comparison method in ANOVA was used to group cells with similarities among their mean slopes at a 95 percent significance level. Table 9 provides a summary of the grouping based on the Duncan's multiple comparison tests. The final groupings were based not only on the results of the statistical analysis, but also on the practicality of the groupings and engineering judgment.

Steps 4 and 5 -- Develop Tentative Models and Assess Models for Reasonableness

Linear regression models for all of the groupings (merged cells) in table 9 were developed and are presented in tables 10 through 13. Each model was verified for accuracy and reasonableness by evaluating diagnostic statistics, such as the standard estimate of the error (SEE), coefficient of determination (R2), and the number of data points used in model development.

In general, the models appeared to be reasonable. For AC-surfaced pavement models, R2 was typically greater than 70 percent, with only 3 out of 33 models having reported R2 values less than 70 percent. SEE ranged from 178 to 308 mm/km (11.2 to 19.5 inches per mile) for IRI and 21 to 79 mm/km (1.3 to 5.0 inches per mile) for PI. These models contained the largest number of data points to date for modeling the PI-IRI relationships, ranging from 1,800 to 14,170 data points per model.

Table 9. Summary of groupings (merged cells) used for model development.

BlockPavement TypeClimatic RegionIRI vs PI0.0IRI vs PI2.5-mmIRI vs PI5-mmPI0.0 vs PI2.5-mmPI0.0 vs PI5-mmPI2.5-mm vs PI5-mm
Block 1 (AC-surfaced pavements)ACDF123456
Block 1 (AC-surfaced pavements)ACDNF123789
Block 1 (AC-surfaced pavements)ACWF123456
Block 1 (AC-surfaced pavements)ACWNF123789
Block 1 (AC-surfaced pavements)AC/ACDF101112131415
Block 1 (AC-surfaced pavements)AC/ACDNF161718192021
Block 1 (AC-surfaced pavements)AC/ACWF222324252627
Block 1 (AC-surfaced pavements)AC/ACWNF222324252627
Block 1 (AC-surfaced pavements)AC/PCDF282930313233
Block 1 (AC-surfaced pavements)AC/PCDNF282930313233
Block 1 (AC-surfaced pavements)AC/PCWF282930313233
Block 1 (AC-surfaced pavements)AC/PCWNF282930313233
Block 2 (PCC-surfaced pavements)JPCDF343536373839
Block 2 (PCC-surfaced pavements)JPCDNF404142434445
Block 2 (PCC-surfaced pavements)JPCWF343536464748
Block 2 (PCC-surfaced pavements)JPCWNF495051525354
Block 2 (PCC-surfaced pavements)JRCDF343536373839
Block 2 (PCC-surfaced pavements)JRCDNF404142434445
Block 2 (PCC-surfaced pavements)JRCWF343536464748
Block 2 (PCC-surfaced pavements)JRCWNF495051525354
Block 2 (PCC-surfaced pavements)CRCDF343536373839
Block 2 (PCC-surfaced pavements)CRCDNF404142434445
Block 2 (PCC-surfaced pavements)CRCWF343536464748
Block 2 (PCC-surfaced pavements)CRCWNF495051525354

Note: Cells with the same numbers share the same model.

Table 10. PI-to-IRI index conversion equations and variability indices for AC pavements.

Pavement TypeClimateaBlanking Band (mm)Correlation Equation (IRI = mm/km, PI = mm/km)NSEER2
AC1,2,3,40.0IRI = 2.66543*PI0.0 + 213.0114,170200.170.89
AC1,2,3,42.5IRI = 2.97059*PI2.5-mm + 638.7414,160231.690.86
AC1,2,3,45.0IRI = 3.78601*PI5-mm + 887.5113,775292.260.77
AC/AC10.0IRI = 2.74599*PI0.0 + 265.421,854191.970.91
AC/AC20.0IRI = 2.68169*PI0.0 + 274.671,494184.640.81
AC/AC3,40.0IRI = 2.42295*PI0.0 + 301.905,126178.810.84
AC/AC12.5IRI = 3.12622*PI2.5-mm + 708.561,854230.030.87
AC/AC22.5IRI = 3.33564*PI2.5-mm + 655.671,494246.640.66
AC/AC3,42.5IRI = 2.68324*PI2.5-mm + 660.345,126216.980.76
AC/AC15.0IRI = 4.25316*PI5-mm + 957.801,824288.170.79
AC/AC25.0IRI = 4.39478*PI5-mm + 883.201,345308.230.45
AC/AC3,45.0IRI = 3.42671*PI5-mm + 876.804,906265.850.63
AC/PCC1,2,3,40.0IRI = 2.40300*PI0.0 + 292.934,156205.580.79
AC/PCC1,2,3,42.5IRI = 2.78217*PI2.5-mm + 716.874,156229.680.73
AC/PCC1,2,3,45.0IRI = 3.94665*PI5-mm + 939.224,052259.580.65

a Climatic zones: 1=DF, 2=DNF, 3=WF, 4=WNF.

Table 11. PI-to-PI index conversion equations and variability indices for AC pavements.

Pavement TypeClimateaCorrelation Equation (PI = mm/km)NSEER2
AC1,3PI0.0 = 1.08722*PI2.5-mm + 174.425,74447.730.96
AC1,3PI0.0 = 1.35776*PI5-mm + 275.485,68483.580.88
AC1,3PI2.5-mm = 1.28213*PI5-mm + 87.795,68446.620.95
AC2,4PI0.0 = 1.12338*PI2.5-mm + 152.848,41845.230.95
AC2,4PI0.0 = 1.46417*PI5-mm + 240.098,09371.730.86
AC2,4PI2.5-mm = 1.34055*PI5-mm + 73.138,09338.640.95
AC/AC1PI0.0 = 1.14153*PI2.5-mm + 160.701,85643.410.96
AC/AC1PI0.0 = 1.56038*PI5-mm + 250.891,82673.740.88
AC/AC1PI2.5-mm = 1.39462*PI5-mm + 75.551,82640.470.95
AC/AC2PI0.0 = 1.28067*PI2.5-mm + 138.151,49652.260.86
AC/AC2PI0.0 = 1.75837*PI5-mm + 222.841,34779.320.66
AC/AC2PI2.5-mm = 1.52523*PI5-mm + 56.601,34734.140.89
AC/AC3,4PI0.0 = 1.11926*PI2.5-mm + 145.855,12844.860.93
AC/AC3,4PI0.0 = 1.45876*PI5-mm + 233.594,90871.530.81
AC/AC3,4PI2.5-mm = 1.36739*PI5-mm + 71.174,90838.120.93
AC/PCC1,2,3,4PI0.0 = 1.15412*PI2.5-mm + 177.084,15844.460.93
AC/PCC1,2,3,4PI0.0 = 1.61123*PI5-mm + 271.114,05471.070.81
AC/PCC1,2,3,4PI2.5-mm = 1.44895*PI5-mm + 76.834,05436.990.93

a Climatic zones: 1=DF, 2=DNF, 3=WF, 4=WNF.

Table 12. PI-to-IRI index conversion equations and variability indices for PCC pavements.

Pavement TypeClimateaBlanking Band (mm)Correlation Equation (IRI = mm/km, PI = mm/km)NSEER2
PCC1,30.0IRI = 2.12173*PI0.0 + 439.7612,039259.630.84
PCC20.0IRI = 2.58454*PI0.0 + 423.091,448176.540.88
PCC40.0IRI = 2.3582*PI0.0 + 317.192,888236.510.84
PCC1,32.5IRI = 2.15316*PI2.5-mm + 947.0512,039278.690.81
PCC22.5IRI = 2.5921*PI2.5-mm + 1024.731,448226.530.80
PCC42.5IRI = 2.40731*PI2.5-mm + 888.102,888264.460.79
PCC1,35.0IRI = 2.62558*PI5-mm + 1205.7311,946305.960.77
PCC25.0IRI = 3.51673*PI5-mm + 1226.351,364268.700.72
PCC45.0IRI = 2.87407*PI5-mm + 1229.632,885297.370.74

a Climatic zones: 1=DF, 2=DNF, 3=WF, 4=WNF.

Table 13. PI-to-PI index conversion equations and variability indices for PCC pavements.

Pavement TypeClimateaCorrelation Equation (PI = mm/km)NSEER2
PCC1PI0.0 = 1.39512*PI5-mm + 343.082,18271.190.87
PCC2PI0.0 = 1.36715*PI5-mm + 313.251,36666.420.86
PCC3PI0.0 = 1.20723*PI5-mm + 367.919,76486.730.91
PCC4PI0.0 = 1.19909*PI5-mm + 390.492,88585.190.85
PCC1PI0.0 = 1.04364*PI2.5-mm + 238.132,23746.910.95
PCC2PI0.0 = 1.02028*PI2.5-mm + 229.781,44844.340.94
PCC3PI0.0 = 1.01255*PI2.5-mm + 238.659,80049.980.97
PCC4PI0.0 = 1.01320*PI2.5-mm + 244.812,88856.940.94
PCC1PI2.5-mm = 1.36458*PI5-mm + 96.462,18043.270.95
PCC2PI2.5-mm = 1.38376*PI5-mm + 74.901,36439.840.95
PCC3PI2.5-mm = 1.20990*PI5-mm + 123.959,76453.620.96
PCC4PI2.5-mm = 1.212677*PI5-mm + 138.432,88542.990.96

a Climatic zones: 1=DF, 2=DNF, 3=WF, 4=WNF.

All of the PCC-surfaced pavement models had R2 greater than 70 percent. SEE ranged from 177 to 306 mm/km (11.2 to 19.4 inches per mile) for IRI and 21 to 79 mm/km (1.3 to 5.0 inches per mile) for PI. These models contain the largest number of data points to date for modeling the PI-IRI relationships, ranging from 1,366 to 12,039 data points per model.

Step 6 -- Select Final Models

Fifteen models were developed for the PI-IRI relationships and 18 models were developed for the PI-PI relationships for AC-surfaced pavements. For PCC-surfaced pavements, 9 and 12 models were developed for PI-IRI and PI-PI relationships, respectively. The models were developed using a database that represented a reasonable inference space (IRI ranged from 300 to 4,000 mm/km [19 to 253 inches per mile] and PI ranged from 0 to 1,700 mm/km [0 to 108 inches per mile] for all blanking bands). The number of data points used in model development ranged from 1,300 to 14,000.

In general, the models developed were adequate and predicted IRI and PI well. An evaluation of diagnostic statistics, such as SEE and R2, showed that there was a good correlation between the measured and predicted smoothness indices from the models (R2 was typically > 70 percent) with a reasonable level of error (ranged from 34 to 86.7 mm/km [2.1 to 5.5 inches per mile] for PI and 177 to 308 [11.2 to 19.5 inches per mile] for IRI).

The models presented in tables 10 through 13 predict the mean smoothness index (IRI or PI) for the sample LTPP data used in model development. In this case, the sample means are probably a reasonable estimate of means of the population of pavements within the limits of the reference data. However, they do not necessarily indicate the range of values within which the true population means lies.

The range of values within which the true population mean lies can be obtained by computing a confidence interval around the predicted sample mean. The confidence interval for the mean provides a range of values around the mean where one can expect the "true" (population) mean to be located (with a given level of certainty). Confidence interval can be computed using the following equation:

CI = mean ± talpha/2sigma, Eq. 3

where:
CI = Confidence interval.
mean = Predicted smoothness index.
t = Value of t-statistic at a given significance level.
alpha = Significance level (usually 90 or 95 percent).
sigma = Model standard error of estimate (SEE).

For example, if the predicted mean IRI (computed using models based on the LTPP data sample) is 1,000 mm/km (63.4 inches per mile), and the lower and upper limits at a significance level of 95 percent are 900 and 1,100 mm/km (57.0 and 69.7 inches per mile) respectively, then it can be concluded that there is a 95 percent probability that the population mean is between 900 and 1,100 mm/km (57.0 and 69.7 inches per mile). If the significance level is set to a smaller value (say 99 percent), then the interval would become wider thereby increasing the certainty of the estimate, and vice versa.

In essence, the larger the sample size, the more reliable will be its mean, and the larger the variation (SEE), the less reliable will be the mean. Sample size used for development of both the LTPP PI-IRI and PI-PI models ranged from 1,347 to 14,170 data points. These numbers are greater than the generally required minimum of 100 and should provide reliable results.

The SEE values associated with the PI-IRI models in tables 10 and 12 ranged from 179 to 292 mm/km (11.3 to 18 inches per mile). The SEE values associated with the PI-PI models in tables 11 and 13 ranged from 25 to 58 mm/km (1.6 to 3.7 inches per mile). These SEE values are reasonable, considering the inherent differences in the way surface wavelengths are processed for IRI and PI.

Chapter 5. Adaptation of LTPP-Based Models to Current State Smoothness Specifications

Introduction

The vast majority of U.S. highway agencies use smoothness specifications to ensure an adequate level of initial smoothness for newly constructed and resurfaced pavements. Smoothness specifications typically define the type of equipment and testing procedures to be used to measure initial smoothness, the method of identifying significant bumps to be removed, the type of smoothness statistics to be computed and reported, and the levels of smoothness required for full pay, bonuses, penalties, and corrective work.

As discussed in chapter 1, most specifications are based on the PI smoothness statistic, as measured using a profilograph. Although these specifications differ primarily in terms of PI limits for acceptable smoothness and pay adjustment provisions, there are also differences in testing procedures and equipment. For instance, the length, location, and timeframe specified for testing may be different, as might the responsibility (i.e., contractor vs. agency) for testing. Also, there are various makes and models of profilographs (Ames, Cox, and McCracken California-type profilographs, Rainhart-type profilograph, and manual or computerized trace reduction), and different filters (3rd order Butterworth, 1st order Cox, and moving average), and blanking band sizes (0, 2.5, and 5 mm [0, 0.1, 0.2 inches]) that can be applied to compute PI.

This chapter provides a summary of States' current AC and PCC smoothness specifications and presents the results of an effort to develop recommended IRI smoothness limits that correspond to existing specified PI limits. The recommended IRI limits were derived using the PI-IRI conversion models developed and reported in chapter 4.

Overview of State Smoothness Specifications

In the last 10 years, at least five different national surveys have been conducted to show the status of State smoothness specifications. In each of these surveys, about half of the responding agencies use a California- or Rainhart-type profilograph for testing new AC pavements, whereas slightly more than three-fourths of the agencies use profilographs for new PCC.

Usage of response-type testing devices (e.g., Mays meter) on AC pavements declined slightly during this time, from about 15 percent in the mid 1990s to about 10 percent now. In contrast, the use of inertial profilers on AC pavements increased appreciably, from about 6 percent in the early 1990s to about 24 percent now. For testing of PCC pavements, the use of response-type systems stayed the same (about 2 percent), while the use of inertial profilers increased from about 6 percent in 1992 to about 10 percent now.

Tables 14 and 15 list some of the key aspects of current State smoothness specifications, including the type of equipment and smoothness index used, the testing interval, and the smoothness ranges specified for acceptance, correction, bonus, and penalty. The information contained in these tables is based largely on data compiled by the FHWA in 2000 (Rizzo) and on inquiries made to selected State agencies.

As can be seen in table 14, 26 of the 50 States and Puerto Rico have a PI-based smoothness specification for asphalt pavements. Of these 26 agencies, 21 use the 5-mm (0.2-inch) blanking band, 1 uses the 2.5-mm (0.1-inch) blanking band, and 4 use the zero blanking band. Collectively, the ranges for full pay are as follows:

For concrete pavements (table 15), 42 of the 50 States and Puerto Rico have a PI-based smoothness specification. Of these 42 agencies, 1 uses a 7.5-mm (0.3-inch) blanking band, 31 use the 5-mm (0.2-inch) blanking band, 4 use the 2.5-mm (0.1-inch) blanking band, and 6 use the zero blanking band. The collective ranges for full pay are as follows:

Development of Recommended Initial IRI and PI0.0 Levels

To assist agencies in transitioning from their existing PI-type specification to a PI0.0 or IRI specification, the LTPP-based correlation models developed and presented in chapter 4 were applied to the full-pay PI limits given in tables 14 and 15. For each State with a PI specification, the respective correlation model was used to develop best estimates of the full-pay PI0.0 and IRI limits for new AC, new PCC, AC overlays on AC, and AC overlays on PCC.

The results of this effort are summarized in tables 16 through 19. Each table lists, for a given State, its currently reported PI5-mm, PI2.5-mm, or PI0.0 full-pay smoothness limits, its different climate types, and the estimated equivalent PI0.0 and IRI values, computed using the PI-IRI model reflective of the State's predominant climate (highlighted in column 3). These estimated equivalent PI0.0 and IRI values can be used as a starting point for developing specifications based on one of these two indices.

Because the IRI and PI indices are not exactly correlated, tables 16 through 19 include a 90 percent standard error of the estimate range for the projected specification limit. This error rating should assist specification writers in defining their limits. It also can be used as a basis for refining the specification on an ongoing basis.

Table 14. State agency smoothness specifications for asphalt pavements.

StateTesting DeviceIndexTesting IntervalBonus RangeFull Pay RangePenalty RangeCorrection Range
ALCalifornia-type profilographPI5-mm0.16 kma (0.1 mi)<32 mm/km (<2 inches per mile)32 - 63 mm/km (2 - 3.9 inches per mile)64 - 160 mm/km (4 - 10 inches per mile)>160 mm/km (<10 inches per mile)
AK
--
--
--
--
--
--
--
AZGM-type profilerMRN0.16 kma (0.1 mi)<520 mm/kma (<33 inches per mile)520 - 710 mm/kma (33 - 45 inches per mile)711 - 1578 mm/kma (46 - 100 inches per mile)<1578 mm/kma (>100 inches per mile)
ARCalifornia-type profilograph, lightweight profilerPI5-mm0.2 km (0.1 mi)</= 45 mm/km (</= 3 inches per mile)46 - 75 mm/km (3.1 - 5 inches per mile)76 - 110 mm/km (5.1 - 7 inches per mile)>110 mm/km (< 7 inches per mile)
CACalifornia-type profilographPI5-mm0.16 km (0.1 mi)a
--
</= 80 mm/km (</= 5 inches per mile)a
--
>80 mm/km (>5 inches per mile)a
COCalifornia-type profilographPI2.5-mm0.15 km (0.095 mi) </= 222 mm/km (</= 14 inches per mile)222.1 - 252 mm/km (14.1 - 16 inches per mile)252.1 - 378 mm/km (16.1 - 24 inches per mile)>378 mm/km (>24 inches per mile)
CTARAN inertial profilerIRI0.16 kma (0.1 mi)>950 mm/kma (<60 inches per mile)950 - 1260 mm/kma (60 - 80 inches per mile)1261 - 1894 mm/kma (80.1 - 120 inches per mile)>1894 mm/kma (>120 inches per mile)
DERolling straightedge
--
--
--
--
--
--
FLRolling straightedge
--
--
--
--
--
--
GAInertial profilerIRI1.6 km(1.0 mi)
--
</= 750 mm/km (</= 47.5 inches per mile)a
--
>750 mm/km (>47.5 inches per mile)a
HI
--
--
--
--
--
--
--
IDCalifornia-type profilographPI5-mm0.1 km (0.1 mi)
--
</= 8 mm/0.1km (</= 0.5 in/0.1mi)
--
>8 mm/0.1km (>0.5 in/0.1 mi)
ILCalifornia-type profilographPI5-mm0.16 km (0.1 mi)</= 8 mm/km (</= 0.5 inches per mile)b9 - 160 mm/km (0.6 - 10 inches per mile)161 - 235 mm/km (10.1 - 15 inches per mile)>235 mm/km (>15 inches per mile)
INCalifornia-type profilographPI5-mm0.16 km (0.1 mi)
--
</= 30 mm/0.16 km (</= 1.2 in/0.1 mi)31 - 38 mm/0.16 km (1.21 - 1.5 in/0.1 mi)>38 mm/0.16 km (>1.5 in/0.1 mi)
IACalifornia-type profilographPI5-mm0.16 km (0.1 mi)</= 48 mm/km (</= 3 inches per mile)49 - 110 mm/km (3.1 - 7 inches per mile)111 - 160 mm/km (7.1 - 10 inches per mile)>160 mm/km (>10 inches per mile)
KSCalifornia-type profilographPI0.00.1 km (0.1 mi)</= 160 mm/km (</= 10 inches per mile)161 - 475 mm/km (10.1 - 30 inches per mile)476 - 630 mm/km (30.1 - 40 inches per mile)c>630 mm/km (>40 inches per mile)
KYInertial profilerRI1.6 kma (1.0 mi)RI >/= 4.053.70 </= RI < 4.053.45 </= RI < 3.70RI < 3.45
LACalifornia-type profilographPI5-mmLot
--
</= 47 mm/km (</= 3 inches per mile)48 - 95 mm/km (3.1 - 6 inches per mile)>95 mm/km (>6 inches per mile)
MERolling dipstick profilerIRI0.2 km (0.12 mi)</= 945 mm/kma (</= 60 inches per mile)946 - 1105 mm/kma (60.1 - 70 inches per mile)1106 - 1260 mm/kma (70.1 - 80 inches per mile)>1260 mm/kma (>80 inches per mile)
MDCalifornia-type profilographPI5-mm0.16 kma (0.1 mi)</= 63 mm/kma (</= 4.0 inches per mile)64 - 110 mm/kma (4.1 - 7 inches per mile)111 - 190 mm/kma (7.1 - 12 inches per mile)>191 mm/kma (>12 inches per mile)
MAInertial ProfilerIRI0.2 km (0.12 mi)a
*
*
*
*
MICalifornia-type profilograph or GM-type inertial profilerPI5-mmRQId0.16 kma (0.1 mi)</= 63 mm/kma (</= 4 inches per mile)or RQI <4564 - 158 mm/kma (4.1 - 10 inches per mile) or 45 </= RQI </= 53
--
>158 mm/kma (>10 inches per mile)or RQI > 53
MNCalifornia-type profilographPI5-mm0.1 km (0.1 mi)</= 38.7 mm/km (</= 2.4 inches per mile)38.8 - 78.9 mm/km (2.5 - 5 inches per mile)79 - 118.3 m/km (5.1 - 7.5 inches per mile)>118.3 mm/km (>7.5 inches per mile)
MSCalifornia-type profilographPI5-mm0.16 kma (0.1 mi)</= 79 mm/kma (</= 5 inches per mile)80 - 110 mm/kma (5.1 - 7 inches per mile)111 - 158 m/kma (7.1 - 10 inches per mile)>158 mm/kma (>10 inches per mile)
MOCalifornia-type profilographPI0.00.1 km (0.1 mi)</= 284 mm/km (</= 18 inches per mile)285 - 395 mm/km (18.1 - 25 inches per mile)396 - 711 m/km (25.1 - 45 inches per mile)>712 mm/km (>45 inches per mile)
MT
--
--
--
--
--
--
--
NECalifornia-type profilographPI5-mm0.2 km (0.1 mi)</= 75 mm/km (</= 5 inches per mile)76 - 110 mm/km (5.1 - 7 inches per mile)111 - 155 mm/km (7.1 - 10 inches per mile)>155 mm/km (>10 inches per mile)
NVCalifornia-type profilographPI5-mm0.1 km (0.1 mi)
--
</= 80 mm/km (</= 5 inches per mile)
--
>80 mm/km (>5 inches per mile)
NHGM-typeinertial profilerRN0.16 kma (0.1 mi)
**
**
**
**
NJRolling straightedge
--
--
--
--
--
--
NMCalifornia-type profilographPI5-mm0.1 km (0.1 mi)</= 65 mm/km (</= 4 inches per mile)66 - 80 mm/km (4.1 - 5 inches per mile)81 - 160 m/km (5.1 - 10 inches per mile)>160 mm/km (>10 inches per mile)
NCHearne straightedgeCSI0.76 km (0.47 mi)CSI=10,20CSI=30,40CSI=11,21,31,41,50,51,60,61
--
ND
--
--
--
--
--
--
--
OHCalifornia-type profilographPI5-mm0.16 kma (0.1 mi)</= 63 mm/kma (</= 4 inches per mile)64 - 110 mm/kma (4.1 - 7 inches per mile)111 - 190 m/kma (7.1 - 12 inches per mile)>190 mm/kma (>12 inches per mile)
OKCalifornia-type profilographPI5-mm0.16 kma (0.1 mi)</= 79 mm/kma (</= 5 inches per mile)80 - 110 mm/kma (5.1 - 7 inches per mile)111 - 190 m/kma (7.1 - 12 inches per mile)>190 mm/kma (>12 inches per mile)
ORCalifornia-type profilographPI5-mm016 kma (0.1 mi)</= 80 mm/kma (</= 5 inches per mile)81 - 110 mm/kma (5.1 - 7 inches per mile)111 - 155 mm/kma (7.1 - 10 inches per mile)>155 mm/kma (>10 inches per mile)
PACalifornia-type profilographPI0.00.16 kma (0.1 mi)</= 442 mm/kma (</= 28 inches per mile)443 - 536 mm/kma (28.1 - 34 inches per mile)537 - 726 mm/kma (34.1 - 46 inches per mile)>726 mm/kma (>46 inches per mile)
PRCalifornia-type profilographPI5-mm0.16 kma (0.1 mi)</= 110 mm/kma (</= 7 inches per mile)111 - 205 mm/kma (7.1 - 13 inches per mile)->205 mm/kma (>13 inches per mile)
RI
--
--
--
--
--
--
--
SCMaysmeterMRN1.6 kma (1.0 mi)</= 552 mm/kma (</= 35 inches per mile)553 - 630 mm/kma (35.1 - 40 inches per mile)631 - 868 mm/kma (40.1 - 55 inches per mile)>868 mm/kma (>55 inches per mile)
SDInertial profilerIRI0.16 kma (0.1 mi)</= 868 mm/kma (</= 55 inches per mile)869 - 1105 mm/kma (55.1 - 70 inches per mile)1106 - 1262 mm/kma (70.1 - 80 inches per mile)>1262 mm/kma (>80 inches per mile)
TNMaysmeterMRN1.6 kma (1.0 mi)</= 315 mm/km a (</= 20 inches per mile)316 - 475 mm/kma (20.1 - 30 inches per mile)476 - 950 mm/kma (30.1 - 60 inches per mile)>950 mm/kma (>60 inches per mile)
TXCalifornia-type profilographPI0.00.16 kma (0.1 mi)</= 237 mm/kma (</= 15 inches per mile)238 - 315 mm/kma (15.1 - 20 inches per mile)316 - 630 m/kma (20.1 - 40 inches per mile)>630 mm/kma (>40 inches per mile)
UTCalifornia-type profilographPI5-mm0.2 km (0.12 mi) a
--
</= 110 mm/km (</=7 inches per mile) a
--
>110 mm/km (>7 inches per mile)a
VTMaysmeterIRI0.32 kma (0.2 mi)<950 mm/kma (<60 inches per mile)950 - 1090 mm/kma (60 - 69 inches per mile)1091 - 1500 mm/kma (70 - 95 inches per mile)>1500 mm/kma (>95 inches per mile)
VASouth Dakota-type profilerIRI0.16 kma (0.1 mi)</= 868 mm/kma (</= 55 inches per mile)869 - 1105 mm/kma (55.1 - 70 inches per mile)1106 - 1578 kma (70.1 - 100 inches per mile)>1578 mm/kma (>100 inches per mile)
WAeLightweight inertial profilerIRI0.1 km (0.1 mi)a</= 946 mm/kma (</= 60 inches per mile)947 - 1500 mm/kma (60.1 - 95 inches per mile)1501 - 1815 mm/kma (95.1 - 115 inches per mile)>1815 mm/kma (>115 inches per mile)
WVMaysmeter or inertial profilerMRN0.16 km (0.1 mi)
--
</= 1000 mm/km (</= 65 inches per mile)1001 - 1500 mm/km (66 - 97.5 inches per mile)>1500 mm/km (>97.5 inches per mile)
WICalifornia-type profilographPI5-mm0.16 kma (0.1 mi)
--
</= 158 mm/kma (</= 10 inches per mile)159 - 237 m/kma (10.1 - 15 inches per mile)>237 mm/kma (>15 inches per mile)
WYInertial profilerIRI0.16 kma (0.1 mi)
***
***
***
***

*Percent Within Limits Specification: Upper Spec Limit = 1500 m/km (95 inches per mile)
**Percent Within Limits Specification: Lower Spec Limit = RN = 4.1
***Statistical Based Specification: Full Pay approximately equal to 868-1105 mm/km (55-70 inches per mile)
a Limits are a direct English-Metric conversion from counterpart limits. Actual limits given by the Agency were not available.
b Based on average profile index for entire project.
c For PI between 476 mm/km (30.1 inches per mile) and 630 mm/km (40 inches per mile), must also grind to 475 mm/km (30 inches per mile) or below.
d RQI: Ride quality index.
e Draft specification.

Table 15. State agency smoothness specifications for concrete pavements.

StateTesting DeviceIndexTesting IntervalBonus RangeFull Pay RangePenalty RangeCorrection Range
ALCalifornia-type profilographPI5-mm0.16 km (0.1 mi)<45 mm/km (<3 inches per mile)45 -- 94 mm/km (3 -- 5.9 inches per mile)95 - 160 mm/km (6 - 10 inches per mile)>160 mm/km (>10 inches per mile)
AK
--
--
--
--
--
--
--
AZCalifornia-type profilographPI5-mm0.16 kma(0.1 mi)<110 mm/kma(<7 inches per mile)110 -- 142 mm/kma(7 - 9 inches per mile)
--
>142 mm/kma(>9 inches per mile)
ARCalifornia-typeprofilograph, lightweight profilerPI5-mm0.2 km (0.1 mi)</= 90 mm/km (</= 6 inches per mile)91 - 110 mm/km (6.1 - 7 inches per mile)
--
>110 mm/km (>7 inches per mile)
CACalifornia-type profilographPI5-mm0.1 km (0.06 mi)a
--
</= 110 mm/km (</= 7 inches per mile)a
--
>110 mm/km (>7 inches per mile)a
COCalifornia-type profilographPI2.5-mm0.15 km (0.095 mi)</= 222 mm/kma (</= 14 inches per mile)222.1 - 252 mm/kma (14.1 - 16 inches per mile)252.1 - 378 mm/kma (16.1 - 24 inches per mile)>378 mm/kma (>24 inches per mile)
CTCalifornia-type profilographPI5-mm0.15 km (0.1 mi)a</=160 mm/km (10 inches per mile)a161 - 190 mm/km (10.1 - 12 inches per mile)a191 - 315 mm/km (12.1 - 20 inches per mile)a>315 mm/km (>20 inches per mile)a
DECA profilograph or rolling straightedgePI5-mm0.16 kma(0.1 mi)<50 mm/kma(<3.2 inches per mile)50 - 200 mm/kma(3.2 - 12.7 inches per mile)
--
>200 mm/kma(>12.7 inches per mile)
FLCalifornia-type profilographPI5-mm0.1 km (0.1 mi)</= 80 mm/km (</= 5 inches per mile)81 - 95 mm/km (5.1 - 6 inches per mile)96 - 110 mm/km (6.1 - 7 inches per mile)>110 mm/km (>7 inches per mile)
GARainhart profilographPI2.5-mm0.4 kma(0.25 mi)
--
</= 110 mm/kma(</= 7 inches per mile)
--
>110 mm/kma(>7 inches per mile)
HICalifornia-type profilographPI5-mm0.16 kma(0.1 mi)
--
</= 157 mm/kma(</= 10 inches per mile)158 - 236 mm/kma(10.1 - 15 inches per mile)>236 mm/kma(>15 inches per mile)
IDCalifornia-type profilographPI5-mm0.1 km (0.1 mi)
--
</= 8 mm/0.1 km (</= 0.5 in/0.1mi)
--
>8 mm/0.1 km (>0.5 in/0.1mi)
ILCalifornia-type profilographPI5-mm0.16 km (0.1 mi)</= 67 mm/km (</= 4.25 inches per mile) b68 - 160 mm/km (4.26 - 10 inches per mile)161 - 235 mm/km (10.01 - 15 inches per mile)>235 mm/km (>15 inches per mile)
INCalifornia-type profilographPI5-mm0.16 km (0.1 mi)</= 23mm/0.16 km (</= 0.9 in/0.1mi)23 - 25 mm/0.16km (0.9 - 1.0 in/0.1 mi)
--
>25 mm/0.16 km (>1.0 in/0.1 mi)
IACalifornia-type profilographPI5-mm0.16 km (0.1 mi)</= 48 mm/km (£3 inches per mile)49 - 110 mm/km (3.1 - 7 inches per mile)111 - 160 mm/km (7.1 - 10 inches per mile)>160 mm/km (>10 inches per mile)
KSCalifornia-type profilographPI0.00.1 km (0.1 mi)</= 285 mm/km (</= 18 inches per mile)286 -- 475 mm/km (18.1 -- 30 inches per mile)476 -- 630 mm/km (30.1 -- 40 inches per mile)c>630 mm/km (>40 inches per mile)
KYRainhart profilographand inertial profilerPI2.5-mmRI0.3 kma(0.19 mi)RI >/= 4.05</=125 mm/kma (</= 8 inches per mile)126 - 190 mm/kma(8.1 - 12 inches per mile)>190 mm/kma(>12 inches per mile)
LACalifornia-type profilographPI5-mmLot-£94 mm/km (</= 6 inches per mile)95 - 126 mm/km (6.1 - 8 inches per mile)>126 mm/km (>8 inches per mile)
ME
--
--
--
--
--
--
--
MDCalifornia-type profilographPI5-mm0.16 kma(0.1 mi)</= 63 mm/kma (</= 4.0 inches per mile)64 - 110 mm/kma(4.1 - 7 inches per mile)111 - 190 mm/kma(7.1 - 12 inches per mile)>191 mm/kma(>12 inches per mile)
MA
--
--
--
--
--
--
--
MICalifornia-type profilograph or GM-type inertial profilerPI5-mmRQI d0.16 kma(0.1 mi)</= 63 mm/kma (</= 4 inches per mile)or RQI < 4564 - 158 mm/kma (4.1 - 10 inches per mile)or 45 </=RQI </= 53
--
>158 mm/kma(>10 inches per mile)or RQI > 53
MNCalifornia-type profilographPI5-mm0.16 km (0.1 mi)</= 63 mm/km (</= 4 inches per mile)64 - 94 mm/km (4.1 - 6 inches per mile)95 - 126 m/km (6.1 - 8 inches per mile)>126 mm/km (>8 inches per mile)
MSCalifornia-type profilographPI5-mm0.16 kma(0.1 mi)
--
</= 110 mm/kma(</= 7 inches per mile)111 - 190 m/kma(7.1 - 12 inches per mile)>190 mm/kma(>12 inches per mile)
MOCalifornia-type profilographPI0.00.1 km (0.1 mi)</= 284 mm/km (</= 18 inches per mile)285 - 395 mm/km (18.1 - 25 inches per mile)396 - 711 m/km (25.1 - 45 inches per mile)>712 mm/km (>45 inches per mile)
MTCalifornia-type profilographPI5-mm0.16 kma(0.1 mi)</= 94 mm/kma(£6 inches per mile)95 - 158 mm/kma(6.1 - 10 inches per mile)159 - 237 m/kma (10.1 - 15 inches per mile)>237 mm/kma(>15 inches per mile)
NECalifornia-type profilographPI5-mm0.2 km (0.1 mi)</= 75 mm/km (</= 5 inches per mile)76 - 155 mm/km (5.1 - 10 inches per mile)156 - 230 mm/km (10.1 - 15 inches per mile)>230 mm/km (>15 inches per mile)
NVCalifornia-type profilographPI5-mm0.1 km (0.1 mi)
--
</= 80 mm/km (</= 5 inches per mile)
--
>80 mm/km (>5 inches per mile)
NH
--
--
--
--
--
--
--
NJRolling straightedge
--
--
--
--
--
--
NMCalifornia-type profilographPI5-mm0.1 km (0.1 mi)</= 80 mm/km (</= 5 inches per mile)81 - 110 mm/km (5.1 - 7 inches per mile)111 - 190 m/km (7.1 - 12 inches per mile)>190 mm/km (>12 inches per mile)
NYCalifornia-type profilographPI5-mm0.16 km (0.1 mi)a</= 79 mm/kma(</= 5 inches per mile)80 - 190 mm/kma(5.1 - 12 inches per mile)
--
>190/kma(>12 inches per mile)
NCRainhart profilographPI5-mm0.18 kma(0.11 mi)
--
</= 63 mm/kma(</= 4 inches per mile)
--
>63 mm/kma(>4 inches per mile)
NDCalifornia-type profilographPI5-mm0.16 kma(0.1 mi)<8mm/0.16 kma(<0.3 in/0.1mi)8 - 13 mm/0.16 kma(0.3 - 0.5 in/0.1mi)14 -- 23 mm/0.16 kma(0.51 - 0.9 in/0.1mi)>23 mm/0.16 kma(>0.9 in/0.1mi)
OHCalifornia-type profilographPI5-mm0.16 kma(0.1 mi)</= 78 mm/kma(</= 5 inches per mile)79 - 110 mm/kma(5.1 - 7 inches per mile)111 - 190 m/kma(7.1 - 12 inches per mile)>190 mm/kma(>12 inches per mile)
OKCalifornia-type profilographPI5-mm0.16 kma(0.1 mi)</= 79 mm/kma(</= 5 inches per mile)80 - 110 mm/kma(5.1 - 7 inches per mile)111 - 190 m/kma(7.1 - 12 inches per mile)>190 mm/kma(>12 inches per mile)
ORCalifornia-type profilographPI5-mm0.2 km (0.1 mi)a</= 80 mm/km (</= 5 inches per mile)a81 - 110 mm/km (5.1 - 7 inches per mile)a
--
>110 mm/km (>7 inches per mile)a
PACalifornia-type profilographPI0.00.16a(0.1 mi)</= 568 mm/kma(</= 36 inches per mile)
--
--
>568 mm/kma(>36 inches per mile)
PRCalifornia-type profilographPI5-mm0.16 kma(0.1 mi)</= 110 mm/kma(</= 7 inches per mile)111 - 205 mm/kma(7.1 - 13 inches per mile)
--
>205 mm/kma(>13 inches per mile)
RI
--
--
--
--
--
--
--
SCRainhart profilographPI5-mm0.4 kma(0.25 mi)
--
</= 158 mm/kma(</= 10 inches per mile)
--
>158 mm/kma(>10 inches per mile)
SDCalifornia-type profilographPI0.00.1 km (0.1 mi)</= 395 mm/km (</= 25 inches per mile)396 - 550 mm/km (25.1 - 35 inches per mile)551 - 630 mm/km (35.1 - 40 inches per mile)>630 mm/km (>40 inches per mile)
TNRainhartprofilographPI2.5-mm0.1 km (0.1 mi)
--
</= 160 mm/km (</= 10 inches per mile)161 - 235 mm/km (10.1 - 15 inches per mile)>235 mm/km (>15 inches per mile)
TXCalifornia-type profilographPI0.00.16 kma(0.1 mi)237 mm/kma(</= 15 inches per mile)238 - 315 mm/kma(15.1 - 20 inches per mile)316 -- 630 m/kma(20.1 - 40 inches per mile)>630 mm/kma(>40 inches per mile)
UTCalifornia-type profilographPI5-mm0.2 km (0.12 mi)a
--
</= 110 mm/km (</= 7 inches per mile)a
--
>110 mm/km (>7 inches per mile) a
VT
--
--
--
--
--
--
--
VASouth Dakota-type profilerIRI0.16 kma (0.1 mi)</= 946 mm/kma (</= 60 inches per mile)947 - 1262 mm/kma (60.1 - 80 inches per mile)1263 - 1578 km a(80.1 - 100 inches per mile)>1578 mm/kma (>100 inches per mile)
WACalifornia-type profilographPI7.5-mm0.1 km (0.1 mi) a</= 60 mm/km (</= 3.8 inches per mile)a61 -- 100 mm/km (3.9 - 6.3 inches per mile) a>100 mm/km (>6.3 inches per mile) a,e
--
WVMaysmeter or inertial profilerMRN0.16 km (0.1 mi)
--
</= 1000 mm/km (</= 65 inches per mile)1001 - 1500 mm/km (66 - 97.5 inches per mile)>1500 mm/km (>97.5 inches per mile)
WICalifornia-type profilographPI01-inch0.16 kma (0.1 mi)</= 400 mm/kma (</= 25.3 inches per mile)401 - 700 mm/kma (25.4 - 44.3 inches per mile)701 - 800 m/kma (44.4 - 50.7 inches per mile) f>800 mm/kma (>50.7 inches per mile)
WYCalifornia-type profilographPI5-mm*****

* Perf. Related Spec (PCC thickness, strength, smoothness) >80 mm/km (>5.0 inches per mile).
a Limits are a direct English-Metric conversion from counterpart limits. Actual limits given by the agency were not available.
b Based on average profile index for entire project.
c For PI between 476 mm/km (30.1 inches per mile) and 630 mm/km (40 inches per mile), must also grind to 475 mm/km (30 inches per mile) or below.
d RQI: Ride quality index.
e For PI greater than 100 mm/km (6.3 inches per mile), must also grind to 100 mm/km (6.3 inches per mile) or less.
f For PI greater than 700 mm/km (44.3 inches per mile), must also grind to 700 mm/km (44.3 inches per mile) or less.

Table 16. Estimated equivalent PI0.0 and IRI values for PI-based smoothness specifications for new AC pavement.

PI5-mm Specification:

AgencyExisting Full-Pay Range, mm/kmClimatic ZoneEstimated PI0.0 Full-Pay Range, mm/kmSEE, mm/kma Estimated PI0.0Estimated IRI Full-Pay Range, mm/kmEstimated IRI SEE, mm/kma
AL32 - 63WNF287 - 332721009 - 1126292
AR46 - 75WF,WNF307 - 350721062 - 1171232
CA</= 80DNF,WF,WNF</= 35772</= 1190292
ID</= 80bDF,WF</= 38484</= 1190292
IL9 - 160WF288 - 49384922 - 1493292
IN</= 187cWF</= 52984</= 1595292
IA49 - 110WF342 - 425841073 - 1304292
LA</= 47WNF</= 30972</= 1065292
MD64 - 110WF362 - 425841130 - 1304292
MI64 - 158WF362 - 490841130 - 1486292
MN38.8 - 78.9WF328 - 383841035 - 1187292
MS80 - 110WNF357 - 401721190 - 1304292
NE76 - 110DF,WF379 - 425841175 - 1304292
NV</= 80DF< 38484< 1190292
NM66 - 80DF,DNF337 - 357841137 - 1190292
OH64 - 110WF362 - 425841130 - 1304292
OK80 - 110DF,WF,WNF357 - 401721190 - 1304292
OR81 -110DF,WNF385 - 425841194 - 1304292
PR111 - 205WNF403 - 540721308 - 1664292
UT</= 110DF,WF< 42584< 1304292
WI</= 158WF< 49084< 1486292

PI2.5-mm Specification:

AgencyExisting Full-Pay Range, mm/kmClimatic ZoneEstimated PI0.0 Full-Pay Range, mm/kmSEE, mm/kma Estimated PI0.0Estimated IRI Full-Pay Range, mm/kmEstimated IRI SEE, mm/kma
CO222.1 - 252DF,WF415 - 446481295 - 1381232

PI0.0 Specification:

AgencyExisting Full-Pay Range, mm/kmClimatic ZoneEstimated PI0.0 Full-Pay Range, mm/kmSEE, mm/kma Estimated PI0.0Estimated IRI Full-Pay Range, mm/kmEstimated IRI SEE, mm/kma
KS161 - 475DF,WF  642 - 1479200
MO285 - 395WF  973 - 1266200
PA443 - 536WF  1394 - 1642200
TX238 - 315DF,DNF,WF,WNF  847 - 1053200

a SEE = Standard error of the estimate. Range of values with 90 percent confidence.
b Extrapolated from actual specification, which calls for PI </= 8 mm per 0.1 km.
c Extrapolated from actual specification, which calls for PI </= 30 mm per 0.16 km.

Table 17. Estimated equivalent PI0.0 and IRI values for PI-based smoothness specifications for AC overlays on AC pavement.

PI5-mm Specification:

AgencyExisting Full-Pay Range, mm/kmClimatic ZoneEstimated PI0.0 Full-Pay Range, mm/kmSEE, mm/kma Estimated PI0.0Estimated IRI Full-Pay Range, mm/kmEstimated IRI SEE, mm/kma
AL32 - 63WNF280 - 32572986 - 1093266
AR46 - 75WF,WNF301 - 343721034 - 1134217
CA</= 80DNF,WF,WNF< 36479< 1235308
ID</= 80bDF,WF< 37674< 1298288
IL9 - 160WF247 - 46772908 - 1425266
IN</= 187cWF< 50672< 1518266
IA49 - 110WF305 - 394721045 - 1254266
LA</= 47WNF< 30272< 1038266
MD64 - 110WF327 - 394721096 - 1254266
MI64 - 158WF327 - 464721096 - 1418266
MN38.8 - 78.9WF290 - 349721010 - 1148266
MS80 - 110WNF350 - 394721151 - 1254266
NE76 - 110DF,WF369 - 423741281 - 1426288
NV</= 80DF< 37674< 1298288
NM66 - 80DF,DNF339 - 364791173 - 1235308
OH64 - 110WF327 - 394721096 - 1254266
OK80 - 110DF,WF,WNF350 - 394721151 - 1254266
OR81 -110DF,WNF377 - 423741302 - 1426288
PR111 - 205WNF396 - 533721257 - 1579266
UT</= 110DF,WF< 42374< 1426288
WI</= 158WF< 46472< 1418266

PI2.5-mm Specification:

AgencyExisting Full-Pay Range, mm/kmClimatic ZoneEstimated PI0.0 Full-Pay Range, mm/kmSEE, mm/kma Estimated PI0.0Estimated IRI Full-Pay Range, mm/kmEstimated IRI SEE, mm/kma
CO222.1 - 252DF,WF413 - 446431399 - 1490230

PI0.0 Specification:

AgencyExisting Full-Pay Range, mm/kmClimatic ZoneEstimated PI0.0 Full-Pay Range, mm/kmSEE, mm/kma Estimated PI0.0Estimated IRI Full-Pay Range, mm/kmEstimated IRI SEE, mm/kma
KS161 - 475DF,WF  708 - 1570191
MO285 - 395WF  992 - 1259179
PA443 - 536WF  1375 - 1601179
TX238 - 315DF,DNF,WF,WNF  913 - 1119185

a SEE = Standard error of the estimate. Range of values with 90 percent confidence.
b Extrapolated from actual specification, which calls for PI </= 8 mm per 0.1 km.
c Extrapolated from actual specification, which calls for PI </= 30 mm per 0.16 km.

Table 18. Estimated equivalent PI0.0 and IRI values for PI-based smoothness specifications for AC overlays on PCC pavement.

PI5-mm Specification:

AgencyExisting Full-Pay Range, mm/kmClimatic ZoneEstimated PI0.0 Full-Pay Range, mm/kmSEE, mm/kma Estimated PI0.0Estimated IRI Full-Pay Range, mm/kmEstimated IRI SEE, mm/kma
AL32 - 63WNF323 - 373711066 - 1188260
AR46 - 75WF,WNF345 - 392711121 - 1235260
CA</= 80DNF,WF,WNF< 40071< 1255260
ID</= 80bDF,WF< 400711255260
IL9 - 160WF286 - 52971975 - 1571260
IN</= 187cWF< 57271< 1677260
IA49 - 110WF350 - 448711133 - 1373260
LA</= 47WNF< 34771< 1125260
MD64 - 110WF374 - 448711192 - 1373260
MI64 - 158WF374 - 526711192 - 1563260
MN38.8 - 78.9WF334 - 398711093 - 1251260
MS80 - 110WNF400 - 448711255 - 1373260
NE76 - 110DF,WF394 - 448711239 - 1373260
NV</= 80DF< 40071< 1255260
NM66 - 80DF,DNF377 - 400711200 - 1255260
OH64 - 110WF374 - 448711192 - 1373260
OK80 - 110DF,WF,WNF400 - 448711255 - 1373260
OR81 -110DF,WNF402 - 448711259 - 1373260
PR111 - 205WNF450 - 601711377 - 1748260
UT</= 110DF,WF< 44871< 1373260
WI</= 158WF< 52671< 1563260

PI2.5-mm Specification:

AgencyExisting Full-Pay Range, mm/kmClimatic ZoneEstimated PI0.0 Full-Pay Range, mm/kmSEE, mm/kma Estimated PI0.0Estimated IRI Full-Pay Range, mm/kmEstimated IRI SEE, mm/kma
CO222.1 - 252DF,WF432 - 466451332 - 1412230

PI0.0 Specification:

AgencyExisting Full-Pay Range, mm/kmClimatic ZoneEstimated PI0.0 Full-Pay Range, mm/kmSEE, mm/kma Estimated PI0.0Estimated IRI Full-Pay Range, mm/kmEstimated IRI SEE, mm/kma
KS161 - 475DF,WF  680 - 1434206
MO285 - 395WF  978 - 1242206
PA443 - 536WF  1357 - 1581206
TX238 - 315DF,DNF,WF,WNF  865 - 1050206

a SEE = Standard error of the estimate. Range of values with 90 percent confidence.
b Extrapolated from actual specification, which calls for PI </= 8 mm per 0.1 km.
c Extrapolated from actual specification, which calls for PI </= 30 mm per 0.16 km.

Table 19. Estimated equivalent PI0.0 and IRI values for PI-based smoothness specifications for new PCC pavement and PCC overlays.

PI5-mm Specification:

AgencyExisting Full-Pay Range, mm/kmClimatic ZoneEstimated PI0.0 Full-Pay Range, mm/kmSEE, mm/kma Estimated PI0.0Estimated IRI Full-Pay Range, mm/kmEstimated IRI SEE, mm/kma
AL45 - 94WNF444 - 503851359 - 1500297
AZ110 - 142DF,DNF464 - 507661613 - 1726269
AR91 - 110WF, WNF500 - 522851491 - 1546297
CA</= 110DNF,WF,WNF</= 46466</= 1613269
CT161 - 190WF562 - 597871628 - 1705306
DE50 - 200WF428 - 609871337 - 1731306
FL81 - 95WNF382 - 587661402 - 1930269
HI</= 157WNF</= 57985</= 1681297
ID</= 80 bDF,WF</= 44571</= 1416306
IL68 - 160WF450 - 561871384 - 1626306
IN144 - 156 cWF542 - 556871584 - 1615306
IA49 - 110WF427 - 501871334 - 1495306
LA</= 94WNF</= 50385</= 1500297
MD64 - 110WF445 - 501871374 - 1495306
MI64 - 158WF445 - 559871374 - 1621306
MN64 - 94WF445 - 481871374 - 1453306
MS</= 110WNF</= 52285</= 1546297
MT95 - 158WF483 - 559871455 - 1621306
NE76 - 155DF,WF449 - 559711405 - 1613306
NV</= 80DF</= 45571</= 1416306
NM81 - 110DF,DNF424 - 464661511 - 1613269
NY80 - 190WF464 - 597871416 - 1705306
NC</= 63WF,WNF</= 46685</= 1411297
ND50 - 81 dDF,WF413 - 456711337 - 1418306
OH79 - 110WF463 - 501871413 - 1495306
OK80 - 110DNF,WF,WNF486 - 522851460 - 1546297
OR81 -110DF,WNF456 - 497711418 - 1495306
PR111 - 205WNF524 - 636851549 - 1819297
SC</= 158WNF</= 58085</= 1684297
UT</= 110DF,WF</= 49771</= 1495306
WY</= 80DF</= 45571</= 1416306

PI2.5-mm Specification:

AgencyExisting Full-Pay Range, mm/kmClimatic ZoneEstimated PI0.0 Full-Pay Range, mm/kmSEE, mm/kma Estimated PI0.0Estimated IRI Full-Pay Range, mm/kmEstimated IRI SEE, mm/kma
CO222.1 - 252DF,WF469 - 499471423 - 1485279
GA</= 110WF,WNF</= 46957</= 1420264
KY</= 125WF</= 36550</= 1216279
TN</= 160WF,WNF</= 40757</= 1273317

PI0.0 Specification:

AgencyExisting Full-Pay Range, mm/kmClimatic ZoneEstimated PI0.0 Full-Pay Range, mm/kmSEE, mm/kma Estimated PI0.0Estimated IRI Full-Pay Range, mm/kmEstimated IRI SEE, mm/kma
KS286 - 475DF,WF  1047 - 1448306
MO285 - 395WF  1044 - 1278306
PA568 eWF  </= 1645306
TX396 - 550DF,DNF,WF,WNF  1038 - 1237269
WI401 - 700WF  1291 - 1925306

a SEE = Standard error of the estimate. Range of values with 90 percent confidence. b Extrapolated from actual specification, which calls for PI </= 8 mm per 0.1 km. c Extrapolated from actual specification, which calls for 23 </= PI </= 25 mm per 0.16 km. d Extrapolated from actual specification, which calls for 8 </= PI </= 13 mm per 0.16 km. e Actual specification calls for incentives for PI</=568 mm/km (36 inches per mile) and correction for PI>568 inches per mile (36 inches per mile).

For example, if Maryland (a wet-freeze climatic zone state) entertained thoughts of switching from PI5-mm to PI0.0, it could refer to table 16 to identify the comparable PI0.0 range for the current PI5-mm full-pay range 64 to 110 mm/km (4 to 7 inches per mile). This range is estimated to be 321 to 403 mm/km (20.3 to 25.5 inches per mile). With a standard error of the estimate (SEE) of 72 mm/km (4.6 inches per mile) for this relationship, the specification writer can assume that variability within the relationship results in a reasonable range for comparable PI0.0 values of 321 to 403 mm/km (20.3 to 25.5 inches per mile).

If, on the other hand, the agency desired to transition to an IRI specification, it could use the comparable IRI range of 1,096 to 1,254 mm/km [70 to 79.5 inches per mile]). The SEE for this relationship is 266 mm/km (16.9 inches per mile).

Direct State-to-State comparisons of derived specification limits may not be appropriate due to individual agencies' implementation practices. Factors that may affect the specification limits for a specific agency include segment length, whether an agency aggregates segments, scope of application (new pavements or overlays, and type facilities), and method of index computation (half-car roughness index, individual wheelpath IRI, or average IRI).

Chapter 6. Conclusions and Recommendations

Conclusions

In the search for reasonable, practical relationships that link IRI with PI5-mm, PI2.5-mm, and PI0.0, and PI0.0 with PI5-mm and PI2.5-mm, a comprehensive evaluation was made of trends documented in past pavement smoothness studies, as well as trends developed in this study from vast amounts of LTPP profile and smoothness data. The background and results of these studies were presented and discussed in previous chapters of this report.

Although past documented PI-IRI relationships were rather limited (particularly with respect to PI2.5-mm-IRI relationships) and showed varying degrees of disparity, factors such as pavement type, equipment characteristics, and filtering methods contributed significantly to these disparities.

A much broader and more controlled evaluation using over 43,000 LTPP smoothness data points showed generally similar PI-IRI trends as the past study trends. The data points consisted of IRI and simulated PI values computed from the same longitudinal profiles measured multiple times for 1,793 LTPP pavement test sections.

Detailed statistical analyses of IRI and simulated PI data indicated a reasonable correlation between IRI and PI (PI5-mm, PI2.5-mm, and PI0.0) and between PI0.0 and PI (PI5-mm and PI2.5-mm). However, it was determined that pavement type (i.e., AC, JPC, AC/PCC) and climatic conditions (i.e., dry-freeze, wet-nonfreeze) are significant factors in the relationship between IRI and PI.

The effects of these variables were taken into consideration in the development of PI-to-IRI and PI-to-PI conversion models. A total of 15 PI-to-IRI models and 18 PI-to-PI models covering all three PI blanking band sizes (5, 2.5, and 0 mm [0.2, 0.1, and 0 in]) and all four climatic zones (dry-freeze, dry-nonfreeze, wet-freeze, and wet-nonfreeze) were developed for AC-surfaced pavements. Similarly, for PCC-surfaced pavements, 9 PI-to-IRI models and 12 PI-to-PI models were developed.

The equations, estimated standard errors, and other relevant statistics for all 54 models are summarized in tables 10 through 13 in chapter 4. These equations can be used to assist highway agency personnel in transitioning smoothness specification limits from PI to IRI or to PI with a tighter blanking band. Chapter 5 of this report illustrated the results of applying these conversion equations to existing State smoothness specifications. Each State's PI5-mm, PI2.5-mm, or PI0.0 full-pay range was converted to an estimated equivalent IRI range, and each State's PI5-mm or PI2.5-mm full-pay range was converted to an estimated equivalent PI0.0. Results of this exercise are summarized in tables 16 through 19 in chapter 5.

Recommendations

The major goal of this research was to develop a practical tool to assist in the transition from PI to PI0.0 or IRI specifications. Correlation and error estimates have been provided to allow agencies to estimate the level of IRI and PI smoothness that is associated with their current specifications. To make this research useful, agencies are asked to:

References

Baus, R., and W. Hong. 1999. "Investigation and Evaluation of Roadway Rideability Equipment and Specifications," Federal Highway Administration/South Carolina Department of Transportation Report FHWA-SC-99-05, Columbia, South Carolina.

Fernando, E.G. 2000. "Evaluation of Relationship Between Profilograph and Profile-Based Roughness Indices," Paper Prepared for the 79th Annual Meeting of the Transportation Research Board, Washington, D.C.

Florida Department of Transportation (FLDOT). 1997. "Comparison of Ride Quality Monitoring Equipment Used for New Construction," Draft Report, Pavement Systems Evaluation Study 97-2, Florida Department of Transportation State Materials Office, Tallahassee, Florida.

Hossain, M., M. Akhter, J. Hancock, and J. Boyer. 2000. "Evaluation of Performance of Lightweight Profilometers," Final Report prepared for Kansas Department of Transportation, Kansas State University, Manhatten, Kansas.

Kombe, E.M. and S.A. Kalevela. 1993. "Evaluation of Initial Pavement Smoothness for the Development of PCCP Construction Specifications," Phase I Final Report, Arizona Department of Transportation, Phoenix, Arizona.

Ksaibati , K., R. McNamera, W. Miley, and J. Armaghani. 1999. "Pavement Roughness Data Collection and Utilization," Transportation Research Record 1655, Transportation Research Board, Washington, D.C.

Kulakowski, B.T. and J.C. Wambold. 1989. "Development of Procedures for the Calibration of Profilographs." Final Report, Pennsylvania Transportation Institute (PTI), Pennsylvania State University, University Park, Pennsylvania.

Rizzo, R. 2000 "Survey of State Smoothness Specifications," Federal Highway Administration, Michigan Division, Lansing, Michigan.

Rufino, D., K. Baraka, and M.I. Darter. 2000. "Development of a Bridge Smoothness Specification for Illinois DOT," Interim Report prepared for Illinois Department of Transportation, Report No. FHWA-IL-UI-279, University of Illinois, Urbana-Champaign, Illinois.

Scofield, L. 1993. "Profilograph Limitations, Correlations, and Calibration Criteria for Effective Performance-Based Specifications," NCHRP Project 20-7 Task 53 Draft Report, Transportation Research Board, Washington, D.C.

Apprendix A. IRI and PI Relationships for AC Pavements

Figure A-1. IRI vs. PI0.0 for all AC pavement types and climatic zones.

Figure A-1. IRI vs. PI (0.0) for all AC pavement types and climatic zones. The figure shows a graph with Simulated PI (0.0), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The linear regression line starts at an IRI of 0.2 (PI 0.0) and ends at an IRI of 5.2 (PI 1.85). The Full-Pay Range (TYP) is shown to be within an IRI of 0.6 - 1.5 and a PI of 0.15 - 0.50.

Figure A-2. IRI vs. PI2.5-millimeter for all AC pavement types and climatic zones.

Figure A-2. IRI vs. PI (2.5-millimeter) for all AC pavement types and climatic zones. The figure shows a graph with Simulated PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The linear regression line starts at an IRI of 0.6 (PI 0.0) and ends at an IRI of 5.3 (PI 1.6). The Full-Pay Range (TYP) is shown to be within an IRI of 1.1 - 2.2 and a PI of 0.15 - 0.50.

Figure A-3. IRI vs. PI5-millimeter for all AC pavement types and climatic zones.

Figure A-3. IRI vs. PI (5-millimeter) for all AC pavement types and climatic zones. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The linear regression line starts at an IRI of 0.9 (PI 0.0) and ends at an IRI of 6.0 (PI 1.33). The Full-Pay Range (TYP) is shown to be within an IRI of 0.8 - 1.8 and a PI of 0.0 - 0.2.

Figure A-4. IRI vs. PI0.0, PI2.5-millimeter, and PI5-millimeter for all AC pavement types and climatic zones.

Figure A-4. IRI vs. PI (0.0), PI (2.5-millimeter), and PI (5-millimeter) for all AC pavement types and climatic zones. The figure shows a graph with Simulated PI, meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The linear regression line for the 5-millimeter Blanking Band is the steepest, starting at an IRI of 1.0 (PI 0.0) and ending at an IRI of 5.8 (PI 1.3). The 2.5-millimeter Blanking Band regression line is the next steepest, starting at an IRI of 0.6 (PI 0.0) and ending at an IRI of 5.2 (PI 1.55). The Zero Blanking Band starts at an IRI of 0.2 (PI 0.0) and ends at an IRI of 5.2 (PI 1.85).

Figure A-5. IRI vs. PI0.0 by AC pavement type for all climatic zones.

Figure A-5. IRI vs. PI (0.0) by AC pavement type for all climatic zones. The figure shows a graph with Simulated PI (0.0), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The slopes of the linear regression lines for AC/AC, AC, and All AC are nearly identical, passing through the points IRI 0.2 (PI 0.0) and IRI 3.6 (PI 1.3). The slope for AC/PCC passes through the same point of origin, but is less steep, with an IRI of 3.4 at a PI of 1.3.

Figure A-6. IRI vs. PI2.5-millimeter by AC pavement type for all climatic zones.

Figure A-6. IRI vs. PI (2.5-millimeter) by AC pavement type for all climatic zones. The figure shows a graph with Simulated PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The slopes of the linear regression lines for AC/AC, All AC, and AC/PCC are nearly identical, passing through the points IRI 0.6 (PI 0.0) and IRI 4.2 (PI 1.2). The line AC only passes through the same point of origin and has a slope that is just slightly steeper.

Figure A-7. IRI vs. PI5-millimeter by AC pavement type for all climatic zones.

Figure A-7. IRI vs. PI (5-millimeter) by AC pavement type for all climatic zones. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The slopes of the linear regression lines for AC/AC, All AC, AC, and AC/PCC are identical, passing through the points IRI 1.0 (PI 0.0) and IRI 4.0 (PI 0.8).

Figure A-8. IRI vs. PI0.0 by climatic zone for AC pavements.

Figure A-8. IRI vs. PI (0.0) by climatic zone for AC pavements. The figure shows a graph with Simulated PI (0.0), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for all climatic zones pass through the point IRI 0.2 (PI 0.0). The slope for Dry-Freeze pavements is the steepest, passing through the point IRI 3.2 (PI 1.0). The slope of Dry-Nonfreeze pavements is just slightly less steep. The slopes of Wet-Freeze and Wet-Nonfreeze are nearly the same, passing through the point IRI 2.8 (PI 1.0).

Figure A-9. IRI vs. PI2.5-millimeter by climatic zone for AC pavements.

Figure A-9. IRI vs. PI (2.5-millimeter) by climatic zone for AC pavements. The figure shows a graph with Simulated PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for all climatic zones pass through the point IRI 0.6 (PI 0.0). The slopes for Dry-Freeze and Dry-Nonfreeze pavements are the steepest passing through the point IRI 3.0 (PI 0.7). The slopes of Wet-Freeze and Wet-Nonfreeze pavements are just slightly less steep, passing through the point IRI 2.6 (PI 1.0).

Figure A-10. IRI vs. PI5-millimeter by climatic zone for AC pavements.

Figure A-10. IRI vs. PI (5-millimeter) by climatic zone for AC pavements. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for all climatic zones pass through the point IRI 0.8 (PI 0.0). The slopes for Dry-Freeze and Dry-Nonfreeze pavements are the steepest passing through the point IRI 3.2 (PI 0.5). The slopes of Wet-Freeze and Wet-Nonfreeze pavements are less steep, passing through the point IRI 2.6 (PI 0.5).

Figure A-11. IRI vs. PI0.0 by climatic zone for AC/AC pavements.

Figure A-11. IRI vs. PI (0.0) by climatic zone for AC/AC pavements. The figure shows a graph with Simulated PI (0.0), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for all climatic zones pass through the point IRI 0.4 (PI 0.05). The slopes for Dry-Freeze and Dry-Nonfreeze pavements are the steepest passing through the point IRI 3.0 (PI 1.0). The slopes of Wet-Freeze and Wet-Nonfreeze pavements are less steep, passing through the point IRI 2.6 (PI 1.0).

Figure A-12. IRI vs. PI2.5-millimeter by climatic zone for AC/AC pavements.

Figure A-12. IRI vs. PI (2.5-millimeter) by climatic zone for AC/AC pavements. The figure shows a graph with Simulated PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for all climatic zones pass through the point IRI 0.6 (PI 0.0). The slopes for Dry-Freeze and Dry-Nonfreeze pavements are the steepest passing through the point IRI 3.0 (PI 0.7). The slope of the Wet-Nonfreeze pavements is the flattest, passing through the point IRI 2.8 (PI 0.7). The slope of the Wet-Freeze pavements is the least steep, passing through the point IRI 2.6 (PI 0.7).

Figure A-13. IRI vs. PI5-millimeter by climatic zone for AC/AC pavements.

Figure A-13. IRI vs. PI (5-millimeter) by climatic zone for AC/AC pavements. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for all climatic zones pass through the point IRI 0.9 (PI 0.0). The slopes for Dry-Freeze and Dry-Nonfreeze pavements are the steepest passing through the point IRI 3.2 (PI 0.5). The slope of the Wet-Nonfreeze pavements is less steep, passing through the point IRI 2.8 (PI 0.5). The slope of the Wet-Freeze pavements is the flattest, passing through the point IRI 2.4 (PI 0.5).

Figure A-14. IRI vs. PI0.0 by climatic zone for AC/PCC pavements.

Figure A-14. IRI vs. PI (0.0) by climatic zone for AC/PCC pavements. The figure shows a graph with Simulated PI (0.0), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for all climatic zones pass through the point IRI 0.6 (PI 0.1). The slope for Wet-Nonfreeze pavements is the steepest passing through the point IRI 2.8 (PI 0.8). The slopes of the Wet-Freeze and Dry-Freeze pavements are less steep, passing through the point IRI 2.2 (PI 0.8).

Figure A-15. IRI vs. PI2.5-millimeter by climatic zone for AC/PCC pavements.

Figure A-15. IRI vs. PI (2.5-millimeter) by climatic zone for AC/PCC pavements. The figure shows a graph with Simulated PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for all climatic zones approximately pass through the point IRI 0.6 (PI 0.0). The slopes for Wet-Nonfreeze and Wet-Freeze pavements are the steepest passing through the point IRI 1.6 (PI 0.3). The slope of the Dry-Freeze pavements is less steep, passing through the point IRI 1.2 (PI 0.3).

Figure A-16. IRI vs. PI5-millimeter by climatic zone for AC/PCC pavements.

Figure A-16. IRI vs. PI (5-millimeter) by climatic zone for AC/PCC pavements. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for all climatic zones approximately pass through the point IRI 1.0 (PI 0.0). The slope of the Wet-Freeze pavements is the steepest, passing through the point IRI 3.0 (PI 0.5). The slope of the Wet-Nonfreeze pavements is less steep, passing through the point IRI 2.6 (PI 0.5). The slope of the Dry-Freeze pavements is the flattest, passing through the point IRI 1.2 (PI 0.1).

Figure A-17. IRI vs. PI0.0 by climatic zone for all AC pavement types.

Figure A-17. IRI vs. PI (0.0) by climatic zone for all AC pavement types. The figure shows a graph with Simulated PI (0.0), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for all climatic zones pass through the point IRI 0.4 (PI 0.0). The slopes of the Dry-Freeze and Dry-Nonfreeze pavements are the steepest, passing through the point IRI 2.8 (PI 0.9). The slopes of the Wet-Nonfreeze and Wet-Freeze pavements are the flattest, passing through the point IRI 2.6 (PI 0.9).

Figure A-18. IRI vs. PI2.5-millimeter by climatic zone for all AC pavement types.

Figure A-18. IRI vs. PI (2.5-millimeter) by climatic zone for all AC pavement types. The figure shows a graph with Simulated PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for all climatic zones pass through the point IRI 0.6 (PI 0.0). The slopes of the Dry-Freeze and Dry-Nonfreeze pavements are the steepest, passing through the point IRI 4.0 (PI 1.0). The slopes of the Wet-Nonfreeze and Wet-Freeze pavements are the flattest, passing through the point IRI 3.5 (PI 1.0).

Figure A-19. IRI vs. PI5-millimeter by climatic zone for all AC pavement types.

Figure A-19. IRI vs. PI (5-millimeter) by climatic zone for all AC pavement types. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for all climatic zones pass through the point IRI 0.9 (PI 0.0). The slopes of the Dry-Freeze and Dry-Nonfreeze pavements are the steepest, passing through the point IRI 4.5 (PI 0.8). The slopes of the Wet-Nonfreeze and Wet-Freeze pavements are the flattest, passing through the point IRI 3.8 (PI 0.5).

Figure A-20. PI0.0 vs. PI5-millimeter for all AC pavement types and climatic zones.

Figure A-20. PI (0.0) vs. PI (5-millimeter) for all AC pavement types and climatic zones. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression line originates at 0.5/0.0 for PI (0.0)/PI (5-millimeter) and ends at 2.0/1.2. The Full-Pay Range (TYP) is from 0.5/0.0 - 0.6/0.2.

Figure A-21. PI0.0 vs. PI2.5-millimeter for all AC pavement types and climatic zones.

Figure A-21. PI (0.0) vs. PI (2.5-millimeter) for all AC pavement types and climatic zones. The figure shows a graph with Simulated PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression line originates at 0.2/0.0 for PI (0.0)/PI (2.5-millimeter) and ends at 1.9/1.6. The Full-Pay Range (TYP) is from 0.3/0.5 - 0.65/0.45.

Figure A-22. PI2.5-millimeter vs. PI5-millimeter for all AC pavement types and climatic zones.

Figure A-22. PI (2.5-millimeter) vs. PI (5-millimeter) for all AC pavement types and climatic zones. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (2.5-millimeter), meters per kilometer, on the vertical axis. The regression line originates at 0.1/0.0 for PI (2.5-millimeter)/PI (5-millimeter) and ends at 1.8/1.3. The Full-Pay Range (TYP) is from 0.1/0.0 - 0.3/0.2.

Figure A-23. PI0.0 vs. PI5-millimeter by AC pavement type for all climatic zones.

Figure A-23. PI (0.0) vs. PI (5-millimeter) by AC pavement type for all climatic zones. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression lines for all pavement types pass through the point 0.25/0.0 for PI (0.0)/PI (5-millimeter). The slope of the AC/PCC pavements is the steepest, passing through the point 1.1/0.5. The slope of AC/AC pavements is slightly flatter, passing through the point 1.0/0.5. AC pavements have the flattest slope, passing through the point 0.95/0.5.

Figure A-24. PI0.0 vs. PI2.5-millimeter by AC pavement type for all climatic zones.

Figure A-24. PI (0.0) vs. PI (2.5-millimeter) by AC pavement type for all climatic zones. The figure shows a graph with Simulated PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression lines for all pavement types pass through the point 0.25/0.0 for PI (0.0)/PI (5-millimeter). The slope of the AC/PCC pavements is the steepest, passing through the point 1.1/0.5. The slope of AC/AC pavements is slightly flatter, passing through the point 1.0/0.5. AC pavements have the flattest slope, passing through the point 0.95/0.5.

Figure A-25. PI2.5-millimeter vs. PI5-millimeter by AC pavement type for all climatic zones.

Figure A-25. PI (2.5-millimeter) vs. PI (5-millimeter) by AC pavement type for all climatic zones. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (2.5-millimeter), meters per kilometer, on the vertical axis. The regression lines for pavement types AC/PCC, AC/AC, and AC are all very similar, originating at 0.1/0.0 and passing through the point 0.9/0.6 (approximately).

Figure A-26. PI0.0 vs. PI5-millimeter by climatic zone for all AC pavement types.

Figure A-26. PI (0.0) vs. PI (5-millimeter) by climatic zone for all AC pavement types. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression lines for all climatic zones originate at about 0.2/0.0 for PI (0.0)/PI (5-millimeter). The slope of the line for Dry-Nonfreeze pavements is the steepest, passing through the point 1.1/0.5. The slope for Dry-Freeze pavements is only slightly flatter, passing through the point 1.05/0.5. The slopes for Wet-Freeze and Wet-Nonfreeze pavements are the flattest, passing through the point 1.0/0.5.

Figure A-27. PI0.0 vs. PI2.5-millimeter by climatic zone for all AC pavement types.

Figure A-27. PI (0.0) vs. PI (2.5-millimeter) by climatic zone for all AC pavement types. The figure shows a graph with Simulated PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression lines for all climatic zones (Dry-Nonfreeze, Dry-Freeze, Wet-Freeze, and Wet-Nonfreeze) are very similar, originating at about 0.2/0.0 for PI (0.0)/PI (2.5-millimeter) and passing through the point 1.3/1.0.

Figure A-28. PI2.5-millimeter vs. PI5-millimeter by climatic zone for all AC pavement types.

Figure A-28. PI (2.5-millimeter) vs. PI (5-millimeter) by climatic zone for all AC pavement types. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (2.5-millimeter), meters per kilometer, on the vertical axis. The regression lines for all climatic zones originate at about 0.1/0.0 for PI (2.5-millimeter/PI (5-millimeter). The slope of the line for Dry-Nonfreeze pavements is the steepest, passing through the point 0.8/0.5. The slopes for Dry-Freeze, Wet-Freeze, Wet-Nonfreeze pavements are only slightly flatter, passing approximately through the point 0.7/0.5.

Figure A-29. PI0.0 vs. PI5-millimeter by climatic zone for AC pavements.

Figure A-29. PI (0.0) vs. PI (5-millimeter) by climatic zone for AC pavements. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression lines for all climatic zones originate at about 0.25/0.0 for PI (0.0)/PI (5-millimeter). The slope of the line for Dry-Nonfreeze pavements is the steepest, passing through the point 1.1/0.5. The slope for Dry-Freeze pavements in slightly flatter, passing through the point 1.0/0.5. The slopes for Wet-Freeze and Wet-Nonfreeze pavements are only slightly flatter, passing approximately through the point 0.8/0.5.

Figure A-30. PI0.0 vs. PI2.5-millimeter by climatic zone for AC pavements.

Figure A-30. PI (0.0) vs. PI (2.5-millimeter) by climatic zone for AC pavements. The figure shows a graph with Simulated PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression lines for all climatic zones (Dry-Nonfreeze, Dry-Freeze, Wet-Freeze, and Wet-Nonfreeze) are very similar, originating at about 0.2/0.0 for PI (0.0)/PI (2.5-millimeter) and passing through the point 1.0/0.7.

Figure A-31. PI2.5-millimeter vs. PI5-millimeter by climatic zone for AC pavements.

Figure A-31. PI (2.5-millimeter) vs. PI (5-millimeter) by climatic zone for AC pavements. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (2.5-millimeter), meters per kilometer, on the vertical axis. The regression lines for all climatic zones originate at 0.1/0.0 for PI (2.5-millimeter)/PI (5-millimeter). The slope for Dry-Nonfreeze pavements is the steepest, passing through the point 0.8/0.5. The slopes for Dry-Freeze, Wet-Freeze, and Wet-Nonfreeze are slightly flatter, passing through the point 0.7/0.5.

Figure A-32. PI0.0 vs. PI5-millimeter by climatic zone for AC/AC pavements.

Figure A-32. PI (0.0) vs. PI (5-millimeter) by climatic zone for AC/AC pavements. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression lines for all climatic zones originate at 0.3/0.0 for PI (0.0)/PI (5-millimeter). The slope for Dry-Nonfreeze pavements is steepest, passing through the point 0.8/0.3. The slopes for Dry-Freeze and Wet-Nonfreeze are slightly flatter, passing through the point 1.1/0.6. The slope for Wet-Freeze pavements is the flattest, passing through the point 1.0/0.6.

Figure A-33. PI0.0 vs. PI2.5-millimeter by climatic zone for AC/AC pavements.

Figure A-33. PI (0.0) vs. PI (2.5-millimeter) by climatic zone for AC/AC pavements. The figure shows a graph with Simulated PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression lines for all climatic zones (Dry-Nonfreeze, Dry-Freeze, Wet-Nonfreeze, and Wet-Freeze) are nearly the same, originating at 0.2/0.0 for PI (0.0)/PI (2.5-millimeter) and passing around the point 0.7/0.5.

Figure A-34. PI2.5-millimeter vs. PI5-millimeter by climatic zone for AC/AC pavements.

Figure A-34. PI (2.5-millimeter) vs. PI (5-millimeter) by climatic zone for AC/AC pavements. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (2.5-millimeter), meters per kilometer, on the vertical axis. The regression lines for all climatic zones originate at 0.1/0.0 for PI (2.5-millimeter)/PI (5-millimeter). The slope for Dry-Nonfreeze pavements is the steepest, passing through the point 0.6/0.3. The slopes for Dry-Freeze, Wet-Nonfreeze, and Wet-Freeze pavements are slightly flatter, passing through the point 0.5/0.3.

Figure A-35. PI0.0 vs. PI5-millimeter by climatic zone for AC/PCC pavements.

Figure A-35. PI (0.0) vs. PI (5-millimeter) by climatic zone for AC/PCC pavements. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression lines for all climatic zones originate at 0.3/0.0 for PI (0.0)/PI (5-millimeter). The slope for Wet-Freeze pavements is the steepest, passing through the point 1.3/0.6. The slopes for Dry-Freeze and Wet-Nonfreeze are flatter, passing through the point 1.0/0.6.

Figure A-36. PI0.0 vs. PI2.5-millimeter by climatic zone for AC/PCC pavements.

Figure A-36. PI (0.0) vs. PI (2.5-millimeter) by climatic zone for AC/PCC pavements. The figure shows a graph with Simulated PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression line for Wet-Freeze pavements originates at 0.2/0.0 for PI (0.0)/PI (2.5-millimeter) and passes through the point 1.3/0.9. The regression line for Wet-Nonfreeze pavements has the same slope as for Wet-Freeze pavements, but originates at 0.1/0.0 and passes through the point 0.8/0.6. The regression line for Dry-Freeze pavements is flatter, originating at the point 0.3/0.0 and passing through the point 0.5/0.4.

Figure A-37. PI2.5-millimeter vs. PI5-millimeter by climatic zone for AC/PCC pavements.

Figure A-37. PI (2.5-millimeter) vs. PI (5-millimeter) by climatic zone for AC/PCC pavements. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (2.5-millimeter), meters per kilometer, on the vertical axis. The regression lines for all climatic zones originate at 0.1/0.0 for PI (2.5-millimeter)/PI (5-millimeter). The slope for Wet-Freeze pavements is the steepest, passing through the point 0.9/0.6. The slopes for Dry-Freeze and Wet-Nonfreeze are flatter, passing through the point 0.8/0.6.

Appendix B. IRI and PI Relationships for PCC Pavements

Figure B-1. IRI vs. PI0.0 for all PCC pavement types and climatic zones.

Figure B-1. IRI vs. PI (0.0) for all PCC pavement types and climatic zones. The figure shows a graph with Simulated PI (0.0), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression line runs from 0.8/0.15 for IRI/PI (0.0) to 4.4/1.85. The full pay range (TYP) is 0.8/0.15 - 1.6/0.55.

Figure B-2. IRI vs. PI2.5-millimeter for all PCC pavement types and climatic zones.

Figure B-2. IRI vs. PI (2.5-millimeter) for all PCC pavement types and climatic zones. The figure shows a graph with Simulated PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression line runs from 1.1/0.0 for IRI/PI (2.5-millimeter) to 4.4/1.55. The full pay range (TYP) is 1.0/0.0 - 1.4/0.25.

Figure B-3. IRI vs. PI5-millimeter for all PCC pavement types and climatic zones.

Figure B-3. IRI vs. PI (5-millimeter) for all PCC pavement types and climatic zones. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression line runs from 1.2/0.0 for IRI/PI (5-millimeter) to 4.6/1.2. The full pay range (TYP) is 1.2/0.0 - 1.8/2.0.

Figure B-4. IRI vs. PI0.0, PI2.5-millimeter, and PI5-millimeter for all PCC pavement types and climatic zones.

Figure B-4. IRI vs. PI (0.0), PI (2.5-millimeter), and PI (5-millimeter) for all PCC pavement types and climatic zones. The figure shows a graph with Simulated PI, meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression line for the 5-millimeter blanking band runs from 1.2/0.0 for IRI/PI to 4.6/1.25. The regression line for the 2.5-millimeter blanking band runs from 1.0/0.0 to 4.4/1.55. The regression line for the zero blanking band runs from 0.8/0.15 to 4.4/1.85.

Figure B-5. IRI vs. PI0.0 by PCC pavement type for all climatic zones.

Figure B-5. IRI vs. PI (0.0) by PCC pavement type for all climatic zones. The figure shows a graph with Simulated PI (0.0), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for all pavement types originate at 1.8/0.15 for IRI/PI (0.0). The line for JPC pavements has the steepest slope, passing through the point 3.6/1.4. The line for All PCC pavements is the next steepest, passing through the point 3.5/1.4. The slope of the line for CRC is slightly flatter, passing through the point 2.8/1.1. The line for JRC is the flattest, passing through the point 3.0/1.4.

Figure B-6. IRI vs. PI2.5-millimeter by PCC pavement type for all climatic zones.

Figure B-6. IRI vs. PI (2.5-millimeter) by PCC pavement type for all climatic zones. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for all pavement types originate at 1.2/0.0 for IRI/PI (5-millimeter). The regression lines for JPC pavements has the steepest slope, passing through the point 3.0/0.9, followed by All PCC which passes through the point 2.9/0.9, CRC passing through 2.8/0.9, and JRC passing through 2.7/0.9.

Figure B-7. IRI vs. PI5-millimeter by PCC pavement type for all climatic zones.

Figure B-7. IRI vs. PI (5-millimeter) by PCC pavement type for all climatic zones. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for all pavement types originate at 1.2/0.0 for IRI/PI (5-millimeter). The regression lines for JPC pavements has the steepest slope, passing through the point 3.8/0.9, followed by All PCC which passes through the point 3.6/0.9, CRC passing through 2.8/0.7, and JRC passing through 3.2/0.9.

Figure B-8. IRI vs. PI0.0 by climatic zone for CRC pavements.

Figure B-8. IRI vs. PI (0.0) by climatic zone for CRC pavements. The figure shows a graph with Simulated PI (0.0), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for Dry-Nonfreeze, Wet-Nonfreeze, and Wet-Freeze have nearly identical slopes, originating around 0.8/0.2 for IRI/PI (0.0) and passing through the point 2.2/0.9. The regression line for Dry-Freeze pavements is very short and nearly flat, ranging from 1.2/0.50 to 1.4/0.55.

Figure B-9. IRI vs. PI2.5-millimeter by climatic zone for CRC pavements.

Figure B-9. IRI vs. PI (2.5-millimeter) by climatic zone for CRC pavements. The figure shows a graph with Simulated PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression line for Wet-Nonfreeze is the steepest, originating at 0.8/0.0 for IRI/PI (2.5-millimeter) and passing through the point 2.4/0.7. The regression lines for Dry-Nonfreeze and Wet-Freeze are nearly identical, originating at the point 1.0/0.0 and passing through the point 2.3/0.7. The regression line for Dry-Freeze pavements is very short and nearly flat, ranging from 1.2/0.30 to 1.3/0.35.

Figure B-10. IRI vs. PI5-millimeter by climatic zone for CRC pavements.

Figure B-10. IRI vs. PI (5-millimeter) by climatic zone for CRC pavements. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The line for Wet-Nonfreeze pavements is the steepest, originating at about 1.0/0.0 for IRI/PI (5-millimeter) and passing through the point 2.6/0.5. The regression lines for Dry-Nonfreeze and Wet-Freeze are nearly identical, originating at about 1.0/0.0 and passing through the point 2.4/0.5. The regression line for Dry-Freeze pavements is very short and nearly flat, ranging from 0.1/1.3 - 0.1/0.15.

Figure B-11. IRI vs. PI0.0 by climatic zone for JPC pavements.

Figure B-11. IRI vs. PI (0.0) by climatic zone for JPC pavements. The figure shows a graph with Simulated PI (0.0), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for all climate types originate at about 0.8/0.15 for IRI/PI (0.0). The line for Dry-Nonfreeze pavements has the steepest slope, passing through the point 2.8/0.9. The regression lines for Dry-Nonfreeze and Wet-Nonfreeze are nearly identical, passing through the point 2.6/0.9. The regression line for Wet-Freeze pavements has the flattest slope, passing through the point 2.4/0.9.

Figure B-12. IRI vs. PI2.5-millimeter by climatic zone for JPC pavements.

Figure B-12. IRI vs. PI (2.5-millimeter) by climatic zone for JPC pavements. The figure shows a graph with Simulated PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for all climate types originate at about 1.0/0.0 for IRI/PI (2.5-millimeter). The line for Dry-Freeze pavements has the steepest slope, passing through the point 3.0/0.7. The regression lines for Dry-Nonfreeze and Wet-Nonfreeze are nearly identical, passing through the point 2.6/0.7. The regression line for Wet-Freeze pavements has the flattest slope, passing through the point 2.4/0.7.

Figure B-13. IRI vs. PI5-millimeter by climatic zone for JPC pavements.

Figure B-13. IRI vs. PI (5-millimeter) by climatic zone for JPC pavements. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for all climate types originate at about 1.2/0.0 for IRI/PI (5-millimeter). The line for Dry-Nonfreeze pavements has the steepest slope, passing through the point 3.2/0.5. The regression lines for Dry-Freeze pavements is slightly flatter and passes through the point 2.8/0.5. The line for Wet-Nonfreeze pavements passes through the point 2.7/0.5. The regression line for Wet-Freeze pavements has the flattest slope, passing through the point 2.6/0.5.

Figure B-14. IRI vs. PI0.0 by climatic zone for JRC pavements.

Figure B-14. IRI vs. PI (0.0) by climatic zone for JRC pavements. The figure shows a graph with Simulated PI (0.0), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for both climate types have the same slope. For Wet-Nonfreeze pavements, the regression line begins at 1.0/0.2, for IRI/PI (0.0), and ends at 2.6/1.05. The line for Wet-Freeze pavements begins at 0.8/0.2 and ends at 3.3/1.5.

Figure B-15. IRI vs. PI2.5-millimeter by climatic zone for JRC pavements.

Figure B-15. IRI vs. PI (2.5-millimeter) by climatic zone for JRC pavements. The figure shows a graph with Simulated PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for Wet-Non-Freeze and Wet-Freeze pavements have nearly the same slope. Both lines originate near the point 1.0/0.0, for IRI/PI (0.0), and pass through the point 2.6/0.8.

Figure B-16. IRI vs. PI5-millimeter by climatic zone for JRC pavements.

Figure B-16. IRI vs. PI (5-millimeter) by climatic zone for JRC pavements. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression line for Wet-Freeze pavements has the steepest slopes, originating at 1.2/0.0 for IRI/PI (5-millimeter) and passing through the point 2.6/0.6. The line for Wet-Nonfreeze pavements has a slightly flatter slope, originating at 1.4/0.0 and passing through 2.6/0.6.

Figure B-17. IRI vs. PI0.0 by climatic zone for all PCC pavement types.

Figure B-17. IRI vs. PI (0.0) by climatic zone for all PCC pavement types. The figure shows a graph with Simulated PI (0.0), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for all climatic types originate at about 0.8/0.15 for IRI/PI (0.0). The line for Dry-Nonfreeze pavements has the steepest slope, passing through the point 2.8/0.9. The next steepest slope belongs to Dry-Freeze pavements, passing through 2.5/0.9. The slope for Wet-Nonfreeze pavements is slightly flatter, passing through the point 2.4/0.9. The flattest slope corresponds to Wet-Freeze pavements, passing through the point 2.3/0.9.

Figure B-18. IRI vs. PI2.5-millimeter by climatic zone for all PCC pavement types.

Figure B-18. IRI vs. PI (2.5-millimeter) by climatic zone for all PCC pavement types. The figure shows a graph with Simulated PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for all climatic types originate at about 1.0/0.0 for IRI/PI (2.5-millimeter). The line for Dry-Nonfreeze pavements has the steepest slope, passing through the point 2.8/0.7. The next steepest slope belongs to Dry-Freeze pavements, passing through 2.6/0.7. The slope for Wet-Nonfreeze pavements is slightly flatter, passing through the point 2.5/0.7. The flattest slope corresponds to Wet-Freeze pavements, passing through the point 2.3/0.7.

Figure B-19. IRI vs. PI5-millimeter by climatic zone for all PCC pavement types.

Figure B-19. IRI vs. PI (5-millimeter) by climatic zone for all PCC pavement types. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and IRI, meters per kilometer, on the vertical axis. The regression lines for all climatic types originate at 1.2/0.0 for IRI/PI (5-millimeter). The line for Dry-Nonfreeze pavements has the steepest slope, passing through the point 3.0/0.5. The next steepest slope belongs to Dry-Freeze pavements, passing through 2.9/0.5. The slope for Wet-Nonfreeze pavements is flatter, passing through the point 2.6/0.5. The flattest slope corresponds to Wet-Freeze pavements, passing through the point 2.4/0.5.

Figure B-20. PI0.0 vs. PI5-millimeter for all PCC pavement types and climatic zones.

Figure B-20. PI (0.0) vs. PI (5-millimeter) for all PCC pavement types and climatic zones. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression line originates at 0.3/0.0 for PI (0.0)/PI (0.5-millimeter) and ends at 1.9/1.2. The Full Pay Range (TYP) begins at 0.3/0.0 and ends at 0.6/0.2.

Figure B-21. PI0.0 vs. PI2.5-millimeter for all PCC pavement types and climatic zones.

Figure B-21. PI (0.0) vs. PI (2.5-millimeter) for all PCC pavement types and climatic zones. The figure shows a graph with Simulated PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression line originates at 0.3/0.0 for PI (0.0)/PI (2.5-millimeter) and ends at 1.8/1.55. The Full Pay Range (TYP) begins at 0.3/0.0 and ends at 0.5/0.25.

Figure B-22. PI2.5-millimeter vs. PI5-millimeter for all PCC pavement types and climatic zones.

Figure B-22. PI (2.5-millimeter) vs. PI (5-millimeter for all PCC pavement types and climatic zones. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (2.5-millimeter), meters per kilometer, on the vertical axis. The regression line originates at 0.1/0.0 for PI (2.5-millimeter)/PI (5-millimeter) and ends at 1.7/1.2. The Full Pay Range (TYP) begins at 0.1/0.0 and ends at 0.35/0.2.

Figure B-23. PI0.0 vs. PI5-millimeter by PCC pavement type for all climatic zones.

Figure B-23. PI (0.0) vs. PI (5-millimeter) by PCC pavement type for all climatic zones. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression line for JPC pavements is the steepest, originating at 0.35/0.0 for PI (0.0)/PI (5-millimeter) and ending at 1.8/1.2. The line for JRC is the next steepest, originating at 0.4/0.0 and ending at 1.4/0.9. The slope or CRC pavements is the flattest, originating at 0.3/0.0 and ending at 1.4/0.7.

Figure B-24. PI0.0 vs. PI2.5-millimeter by PCC pavement type for all climatic zones.

Figure B-24. PI (0.0) vs. PI (2.5-millimeter) by PCC pavement type for all climatic zones. The figure shows a graph with Simulated PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression lines for pavement types JPC, JRC, and CRC have the nearly the same slope, originating at 0.2/0.0 for PI (0.0)/PI (2.5-millimeter) and passing through 1.28/0.9.

Figure B-25. PI2.5-millimeter vs. PI5-millimeter by PCC pavement type for all climatic zones.

Figure B-25. PI (2.5-millimeter) vs. PI (5-millimeter) by PCC pavement type for all climatic zones. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (2.5-millimeter), meters per kilometer, on the vertical axis. The regression lines for pavement types JPC, JRC, and CRC have the nearly the same slope, originating at 0.1/0.0 for PI (2.5-millimeter)/PI (5-millimeter) and passing through the point 1.0/0.8.

Figure B-26. PI0.0 vs. PI5-millimeter by climatic zone for all PCC pavement types.

Figure B-26. PI (0.0) vs. PI (5-millimeter) by climatic zone for all PCC pavement types. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression line for Dry-Freeze pavements has the steepest slope, originating at 0.4/0.0 for PI (0.0)/PI (5-millimeter) and ending at 1.3/0.7. The lines for Wet-Nonfreeze and Wet-Freeze pavements are nearly identical, originating at 0.4/0.2 and passing through the point 1.5/1.0. The slope for Dry-Nonfreeze pavements is the flattest, originating at 0.3/0.0 and ending at 1.0/0.5.

Figure B-27. PI0.0 vs. PI2.5-millimeter by climatic zone for all PCC pavement types.

Figure B-27. PI (0.0) vs. PI (2.5-millimeter) by climatic zone for all PCC pavement types. The figure shows a graph with Simulated PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression lines for all pavement types (Dry-Freeze, Wet-Nonfreeze, Wet-Freeze, and Dry-Nonfreeze) are nearly identical, originating at 0.25/0.0 for PI (0.0)/PI (2.5-millimeter) and passing through the point 1.25/1.0.

Figure B-28. PI2.5-millimeter vs. PI5-millimeter by climatic zone for all PCC pavement types.

Figure B-28. PI (2.5-millimeter) vs. PI (5-millimeter) by climatic zone for all PCC pavement types. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (2.5-millimeter), meters per kilometer, on the vertical axis. The regression line for Dry-Freeze pavements has the steepest slope, originating at 0.1/0.0 for PI (2.5-millimeter)/PI (5-millimeter) and passing through the point 1.1/0.7. The regression lines for Wet-Nonfreeze, Wet-Freeze, and Dry-Nonfreeze pavements are very similar, originating at about 0.15/0.0 and passing through the point 1.0/0.7.

Figure B-29. PI0.0 vs. PI5-millimeter by climatic zone for CRC pavements.

Figure B-29. PI (0.0) vs. PI (5-millimeter) by climatic zone for CRC pavements. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression line for Dry-Nonfreeze pavements has the steepest slope, originating at 0.25/0.0 for PI (0.0)/PI (5-millimeter) and passing through the point 0.8/0.4. The regression line for Wet-Nonfreeze has a flatter slope, originating at 0.35/0.0 and passing through the point 0.8/0.5. The line for Wet-Freeze pavements has a slightly flatter slope, originating at about 0.5/0.2 and passing through the point 1.1/0.7. The line for Dry-Freeze pavements is very flat and short, ranging from 0.5/0.1 to 0.5/0.2.

Figure B-30. PI0.0 vs. PI2.5-millimeter by climatic zone for CRC pavements.

Figure B-30. PI (0.0) vs. PI (2.5-millimeter) by climatic zone for CRC pavements. The figure shows a graph with Simulated PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression lines for Dry-Nonfreeze, Wet-Freeze, and Wet-Nonfreeze pavements are nearly identical, originating at 0.25/0.0 for PI (0.0)/PI (2.5-millimeter) and passing through the point 0.9/0.7. The line for Dry-Freeze pavements is very flat and short, ranging from 0.5/0.3 to 0.5/0.35.

Figure B-31. PI2.5-millimeter vs. PI5-millimeter by climatic zone for CRC pavements.

Figure B-31. PI (2.5-millimeter) vs. PI (5-millimeter) by climatic zone for CRC pavements. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (2.5-millimeter), meters per kilometer, on the vertical axis. The regression line for Dry-Nonfreeze pavements is the steepest, originating at 0.05/0.1 for PI (2.5-millimeter)/PI (5-millimeter) and passing through the point 0.6/0.4. The regression lines for Wet-Freeze, and Wet-Nonfreeze pavements are nearly identical, originating at 0.1/01.0 and passing through 0.8/0.5. The line for Dry-Freeze pavements is very flat and short, ranging from 0.3/0.15 to 0.3/0.2.

Figure B-32. PI0.0 vs. PI5-millimeter by climatic zone for JPC pavements.

Figure B-32. PI (0.0) vs. PI (5-millimeter) by climatic zone for JPC pavements. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression line for Dry-Freeze pavements is the steepest, originating at 0.35/0.0 for PI (0.0)/PI (5-millimeter) and passing through the point 1.3/0.7. The line for Dry-Nonfreeze pavements has nearly the same slope originating at 0.3/0.0 and passing through 1.0/0.5. The regression line for Wet-Nonfreeze pavements is flatter, originating at 0.4/0.0 and passing through 1.25/0.7. The line for Wet-Freeze pavements is slightly flatter, originating at 0.4/0.0 and passing through the point 1.2/0.7.

Figure B-33. PI0.0 vs. PI2.5-millimeter by climatic zone for JPC pavements.

Figure B-33. PI (0.0) vs. PI (2.5-millimeter) by climatic zone for JPC pavements. The figure shows a graph with Simulated PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression lines for Dry-Freeze, Dry-Nonfreeze, Wet-Freeze, and Wet-Nonfreeze all have the same slope. They originate at 0.25/0.0 for PI (0.0)/PI (2.5-millimeter) and pass through the point 0.9/0.7.

Figure B-34. PI2.5-millimeter vs. PI5-millimeter by climatic zone for JPC pavements.

Figure B-34. PI (2.5-millimeter) vs. PI (5-millimeter) by climatic zone for JPC pavements. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (2.5-millimeter), meters per kilometer, on the vertical axis. The regression line for Dry-Nonfreeze pavements is the steepest, originating at 0.04/0.0 for PI (2.5-millimeter)/PI (5-millimeter) and passing through the point 0.5/0.3. The regression line for Dry-Freeze pavements is slightly less steep, originating at 0.05/0.0 and passing through the point 1.1/0.7. The regression lines for Wet-Nonfreeze and Wet-Freeze pavements are slightly flatter and have nearly the same slope, originating at 0.1/0.0 and passing through 1.0/0.7.

Figure B-35. PI0.0 vs. PI5-millimeter by climatic zone for JRC pavements.

Figure B-35. PI (0.0) vs. PI (5-millimeter) by climatic zone for JRC pavements. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression line for Wet-Freeze pavements is the steepest, originating at 0.45/0.0 for PI (0.0)/PI (5-millimeter) and passing through the point 1.1/0.6. The regression line for Wet-Nonfreeze pavements is flatter, originating at 0.45/0.0 and passing through the point 1.05/0.6.

Figure B-36. PI0.0 vs. PI2.5-millimeter by climatic zone for JRC pavements.

Figure B-36. PI (0.0) vs. PI (2.5-millimeter) by climatic zone for JRC pavements. The figure shows a graph with Simulated PI (2.5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (0.0), meters per kilometer, on the vertical axis. The regression lines for Wet-Freeze and Wet-Nonfreeze are nearly the same. They originate at 0.25/0.0 for PI (0.0)/PI (2.5-millimeter) and pass through the point 1.0/0.8.

Figure B-37. PI2.5-millimeter vs. PI5-millimeter by climatic zone for JRC pavements.

Figure B-37. PI (2.5-millimeter) vs. PI (5-millimeter) by climatic zone for JRC pavements. The figure shows a graph with Simulated PI (5-millimeter), meters per kilometer, on the horizontal axis; and Simulated PI (2.5-millimeter), meters per kilometer, on the vertical axis. The regression lines for Wet-Freeze and Wet-Nonfreeze are nearly the same. They originate at 0.2/0.0 for PI (2.5-millimeter)/PI (5-millimeter) and pass through the point 0.9/0.6.


The Federal Highway Administration (FHWA) is a part of the U.S. Department of Transportation and is headquartered in Washington, D.C., with field offices across the United States. is a major agency of the U.S. Department of Transportation (DOT).
The Federal Highway Administration (FHWA) is a part of the U.S. Department of Transportation and is headquartered in Washington, D.C., with field offices across the United States. is a major agency of the U.S. Department of Transportation (DOT). Provide leadership and technology for the delivery of long life pavements that meet our customers needs and are safe, cost effective, and can be effectively maintained. Federal Highway Administration's (FHWA) R&T Web site portal, which provides access to or information about the Agency’s R&T program, projects, partnerships, publications, and results.
FHWA
United States Department of Transportation - Federal Highway Administration