Final 

Intelligent Asphalt 

Compaction Analyzer

Highways for LIFE, Technology Partnerships 

Program, Federal Highway Administration

Final Report 

Assistance Agreement DTFH61-08-G-00002

Performance Period October 2007 - December 2009

2011

12/1/2011
ii

TECHNICAL REPORT DOCUMENTATION PAGE

1. REPORT NO. FHWA-HIF-12-019 2. GOVERNMENT ACCESSION NO. 3. RECIPIENT’S CATALOG NO.

4. TITLE AND SUBTITLE 5. REPORT DATE

Intelligent Asphalt Compaction Analyzer Updated December 2011

6. PERFORMING ORGANIZATION CODE

DUNS No. 122592439

7. Report Submitted by 8. Report Prepared by

Bob Lemon

President, Haskell Lemon Construction Company

Sesh Commuri

Devon Energy Hall, 110 W. Boyd St., #432

University of Oklahoma, Norman, OK 73019

(405) 325-4302 (tel); (405) 325-7066 (fax); 

scommuri@ou.edu

9. PERFORMING ORGANIZATION NAME AND ADDRESS 10. WORK UNIT NO.

Haskell Lemon Construction Company

3800 SW 10th Street,

Oklahoma City, OK 73108-2047

11. CONTRACT OR GRANT NO.

DTFH61-08-G-00002

12. SPONSORING AGENCY NAME AND ADDRESS 13. TYPE OF REPORT AND PERIOD COVERED

Highways for LIFE Technology Partnerships Program 

Federal Highway Administration 

Office of Acquisition Mgmt. (HAAM) 

1200 New Jersey Ave., SE, 

Washington, DC 20590

Final Report

14. SPONSOR CONTACT

Ms. Julie Zirlin

Program Manager

(202) 366-9105 (tel); Julie.Zirlin@dot.gov 

15. SUPPLEMENTARY NOTES

16. ABSTRACT A

This report describes the evaluation of the Intelligent Asphalt Compaction Analyzer (IACA) during the 

compaction of Asphalt Pavements. The IACA consists of sensors to measure the location and vibrations of the 

roller, an infrared sensor to monitor the mat temperature, and a display to provide the roller operator the 

estimated pavement density in real-time. The IACA also has built-in features to display vital compaction 

information like coverage and as-built density for the operator to monitor the progress during compaction. 

During the report period (2008-2010), independent contractors evaluated the IACA during the construction of 

both full-depth and overlays of asphalt pavements. A test protocol was developed to determine the short 

term, as well as the long term performance of the IACA. The evaluation was carried out by seven (7) 

participating contractors during the construction/remediation of the asphalt pavements across the United 

States. Roadway cores were extracted at randomly selected locations on the finished pavement and the 

density of the cores was measured using the AASHTO T-166 method. The validation of the IACA performance 

was performed by the comparison of the IACA estimated density with the density of the roadway cores at 

these random locations. 

The measurements from 180 roadway cores over the duration of the project showed that the IACA was able 

to estimate the density of the compacted pavement with a mean error of 0.1% (of the Theoretical Maximum 

Density) and a standard deviation of 0.8. Further, the estimation error had a 95% Confidence Interval of 

[-1.2 1.2], thereby indicating that the IACA is suitable for use as a contractor Quality/process Control tool

during the construction of Asphalt Pavements.

17. KEY WORDS 18. DISTRIBUTION STATEMENT

Intelligent Compaction, Compaction Analyzer, Neural 

Network, Vibration Analysis

Unrestricted.

19. SECURITY CLASSIF. (OF THIS REPORT) 20. SECURITY CLASSIF. 

(OF THIS PAGE) 

21. NO. OF 

PAGES

22. 

PRICE
1.0 Executive Summary

The Intelligent Asphalt Compaction Analyzer (IACA) is a roller mountable system that is capable 

of estimating the level of compaction of an asphalt pavement during its construction for contractors 

as part of their quality/process control operations. The IACA uses a neural network to compare the 

vibrations of the vibratory compactor with known patterns of the vibrations estimate the 

density/stiffness of the pavement. The IACA technology was developed during the years 2003-2007 

and was adapted for field use in 2008 with funding from the Federal Highway Administration (FHWA) 

under the Highways for LIFE Technology Partnerships Program and Volvo Construction Engineering. 

Prototype units were assembled in 2008 and their use during the compaction of Hot Mix Asphalt 

(HMA) pavements was demonstrated in 2009. The results of the field validation of the IACA are 

discussed in this report. 

The chief objective of the project funded under the assistance agreement with the FHWA was 

the refinement of the IACA technology to enable its early commercialization. The following goals 

were defined in order to meet this objective.

G1. Develop a rugged IACA module that could be easily installed on vibratory compactors for use

during the construction of asphalt pavements. 

G2. Develop user manuals and calibration procedures for simplified operation.

G3. Verify the functioning of the IACA during the construction of both full-depth asphalt 

pavements, as well as overlays of asphalt pavements. 

G4. Verify the ability of the IACA to detect over/under compaction of asphalt pavements.

Goal G1 was accomplished by demonstrating that the IACA unit can be installed on vibratory 

compactors and used for extended periods of time in harsh construction environment.

Goal G2 was accomplished by demonstrating that the IACA can be used by roller operators and 

other semi-skilled construction workers after proper training. 

Goal G3 was achieved through the selection of construction projects across the United States 

involving the construction of multiple layers of asphalt pavements, both full-depth asphalt as well as 

remediation of existing pavements. 

Goals G4 was demonstrated through the construction of as-built compaction maps and the 

verification of the compaction values by in-situ measurements taken on the completed pavement. 

Throughout this report, the term 'level of compaction' of an asphalt pavement implies the 

'density' of the pavement at the specified location. Moreover, the density is reported as a ratio of the 

measured density to the maximum theoretical density (MTD) for the mix. Thus, a density of 93.6% 

implies that the pavement is compacted 93.6% of the maximum theoretical density of the asphalt 

mix. The IACA has been developed as a contractor’s tool but not used by the agencies as part of 

their acceptance programs.

1.1 Outcomes of the Study

The field evaluations reported in this study was carried out by the asphalt contractor using the 

equipment that they would normally utilize during the construction. Further, the IACA was used 
iv

primarily to evaluate the compaction process. The contractor was not required to adopt new 

compaction strategies and the IACA output was not used to alter the compaction process. The 

research team trained the roller operator and the construction crew on the installation and the use 

of the IACA but did not play a role in the selection of the test locations for validation of the IACA 

readings or the extraction of cores and the measurement of their density. 

• The IACA was implemented using rugged, off-the-shelf components running on Windows XP 

platform. The components selected were off-the-shelf and readily available through several 

vendors.

• Installation kits including sensors and wiring harnesses were developed. The total installation 

time is typically less than 30 minutes. The IACA module was successfully tested on several 

types of Volvo (Ingersoll Rand) dual drum vibratory compactors (on IR-DD110, IR-DD118, IRDD132, IR-DD138HF, IR-DD158).

• The calibration of the IACA was performed by the operator using menu options in the IACA's 

Graphical User Interface (GUI). 

• In all the tests conducted as part of the study, the training and calibration of the IACA was 

realized in less than 2 minutes.

• Over 180 cores extracted from the completed pavement (Full depth as well as overlays) were 

used to verify the density estimated by the IACA.

At the beginning of the project, contractors were contacted through FHWA and through the 

Volvo Dealer network to solicit their participation in the study. Information on the construction 

schedules, type of construction, compaction equipment, and site location were used to determine 

the schedule for the validation study (Table A1.1 in the Appendix). 

R2 = 0.7086

88.00

89.00

90.00

91.00

92.00

93.00

94.00

95.00

96.00

97.00

98.00

88.00 89.00 90.00 91.00 92.00 93.00 94.00 95.00 96.00 97.00

IACA Estimated Density (% MTD)

Core Density (%MTD)

Overall Compaction Results

Figure 1.1 Overall compaction results
The evaluations show that the accuracy of the density estimates is within 1.5% of the actual 

density in 95% of the cases, thereby meeting one of the stated goals of the project. These results 

demonstrate that the IACA can be used for determining the quality of the asphalt pavement during 

its compaction. Further, the accuracy of the estimated density makes it suitable for use as a quality 

control tool for the contractor.

The comparison of the density of the roadway cores from the compacted pavement with the 

IACA output at the location of the cores is shown in Table 1.3. It is seen from these results that the 

overall compaction that was achieved during asphalt overlay was significantly higher than that 

achieved during the construction of full-depth asphalt pavements (mean density of 93.05% versus a 

mean density of 92.3%). Further, significant variation in the compaction was observed in the Asphalt 

Concrete (AC) base layers, both for full depth as well as for asphalt overlays (standard deviations of 

1.62 and 1.53 respectively). Also, low compaction and high variability was seen during the 

construction of Full Depth Pavements. 

In all, 180 roadway cores were extracted at random from the completed pavements at the test 

sites selected for this study and were measured using the AASHTO T-166 method1

: “Procedure for 

the determination of the bulk specific gravity of compacted specimens (Gmb) from pavement cores.”

The mean density of the cores was 93.13 (standard deviation of 1.36) corresponding to a mean inplace air void level of 6.87%. The IACA estimations at these locations show a mean density of 93.08 

(standard deviation of 1.47). Null hypothesis testing showed that there is no significant statistical 

difference between the density measurements from the cores and the level of compaction estimated 

by the IACA. 

Quality analysis performed using roadways cores extracted after the completion of the 

construction on Interstate I-86 near Hornell, NY showed that 100 percent of the compacted 

pavement was compacted to a density level between 92-96% of the theoretical maximum density. 

Actual compaction data recorded by the IACA showed that 86% of the roadway was compacted to 

density levels between 93-96% while 12% of the roadway was compacted to density levels between 

92-93% of the theoretical maximum density. The IACA also detected that 1% of the completed 

pavement was under compacted (<92%) while another 1% was over compacted (> 96%).

1.2 Major findings of the study

The primary goal of the project described in this report is the development of a commercial 

prototype of the IACA technology to enable its early adoption into the market. The prototype 

developed in this study was shown to be rugged, easily installable on any vibratory compactor, and 

able to estimate the density in real-time with accuracy is suitable for its use as a quality control 

device during the construction of asphalt pavements. While the technology is maturing, there has to 

be a significant education of the workforce before the technology can find widespread use. The 

following are the major findings of the study.

• The IACA estimates reflect the level of compaction of asphalt pavements during their 

construction.

• The IACA is suitable for use as a quality control tool during the compaction of asphalt pavements.

• The IACA can reduce quality control personnel making spot checks behind the break down roller 

during the compaction process. This would have tremendous consequence on the work place 

safety and will be likely to increase the productivity of the crew.
vi

• While the technology has been successfully demonstrated, the research team found reluctance 

on the part of the contractor crew to take on the responsibility of data collection and analysis. 

Significant education of the contractor and DOT personnel is required before Intelligent 

Compaction technologies can find wide spread use.

• The results reported in this study substantiate the ability of the IACA technology to provide 

continuous estimates of the density during the compaction of asphalt pavements. This 

technology is targeted for use by the contractor during the construction process and is not meant 

to replace any existing specifications or agency acceptance criteria. Further, this technology was 

not evaluated by any DOT personnel nor was it demonstrated to replace agency acceptance 

programs. 
The contents of this report reflect the views of the author and of Haskell Lemon Construction 

Company who are responsible for the facts and the accuracy of the data presented herein. The 

contents do not reflect the views of the Federal Highway Administration or the Oklahoma 

Department of Transportation (ODOT). This report does not constitute a standard, specification, or 

regulation. Trade names mentioned in this report are not intended as an endorsement of any 

machine, contractor, process or product.
viii

SI (METRIC) CONVERSION FACTORS

Approximate Conversions to SI Units Approximate Conversions from SI Units

Symbol When you know Multiply by To Find Symbol Symbol When you know Multiply by To Find Symbol

LENGTH LENGTH

In inches 25.40 millimeters mm mm millimeters 0.0394 inches in

Ft feet 0.3048 meters m m meters 3.281 feet ft

Yd yards 0.9144 meters m m meters 1.094 yards yds

Mi miles 1.609 kilometers km km kilometers 0.6214 miles mi

AREA AREA

in2 square inches 645.2 square millimeters mm2 mm2

square 

millimeters 0.00155 square inches in2

ft2 square feet 0.0929 square meters m2 m2 square meters 10.764 square feet ft2

yd2 square yards 0.8361 square meters m2 m2 square meters 1.196 square yards yd2

Ac acres 0.4047 hectares ha ha hectares 2.471 acres ac

mi2 square miles 2.590 square kilometers km2 km2 square kilometers 0.3861 square miles mi2

VOLUME VOLUME

fl oz fluid ounces 29.57 milliliters ml ml milliliters 0.0338 fluid ounces fl oz

gal gallon 3.785 liters L L liters 0.2642 gallon gal

ft3 cubic feet 0.0283 cubic meters m3 m3 cubic meters 35.315 cubic feet ft3

yd3 cubic yards 0.7645 cubic meters m3 m3 cubic meters 1.308 cubic yards yd3

MASS MASS

Oz ounces 28.35 grams g g grams 0.0353 ounces oz

Lb pounds 0.4536 kilograms kg kg kilograms 2.205 pounds lb

T 

short tons (2000 

lb) 0.907 MegaGrams

(metric Ton)

Mg

(T)

Mg

(T)

MegaGrams

(metric Ton)

1.1023 short tons (2000 lb) Mg

(T)

TEMPERATURE (exact) TEMPERATURE (exact)

°F degrees (°F-32)/1.8 degrees °C °C degrees 9/5(°C)+32 degrees °F

Fahrenheit Celsius Fahrenheit Celsius

FORCE and PRESURE or STRESS FORCE and PRESURE or STRESS

lbf Pound-force 4.448 Newtons N N Newtons 0.2248 Pound-force lbf

lbf/in2 Pound-force 6.895 kilopascals kPa kPa kilopascals 0.1450 Pound-force lbf/in2

per square inch per square inch
Table of Contents

1.0 Executive Summary .................................................................................................................... iii

1.1 Outcomes of the Study ..................................................................................................... iii

1.2 Major findings of the study................................................................................................ v 

2.0 Introduction................................................................................................................................. 1 

2.1 Need Statement................................................................................................................. 1 

2.2 Background ........................................................................................................................ 2 

2.3 Goals of the Highways for LIFE Technology Partnerships Program................................... 2 

2.4 Organization of the Report................................................................................................ 3 

3.0 Project Description and Work Plan ............................................................................................. 4 

3.1 Phase 0 - Refinement of Research Prototype (September – December 2007) ................. 4 

3.2 Phase 1 - Development of Commercial Prototype (February – November 2008)............. 5 

3.3 Phase 2 - Field Validation of the Commercial Prototype (January - December 2009) ...... 6 

 A. Selection of users and test sites for Phase II IACA testing............................................. 7 

 B. Installation and operability testing of the IACA (Short term testing)............................ 7 

 C. Long term performance of the IACA during compaction operations............................ 7 

4.0 Background and Operational Principle of the IACA .................................................................... 9 

4.1 Functional Requirements of the IACA................................................................................ 9 

 4.1.1 Sensing Requirements ...........................................................................................................10

 4.1.2 Operational Requirements.....................................................................................................10

 4.1.3 Calibration Requirements..................................................................................................

 4.1.4 Display and Recording Requirements................................................................................

4.2 Principle of operation of the IACA ................................................................................

 4.2.2 Implementation of the IACA ..............................................................................................

 4.2.3 Training of the Neural Network .........................................................................................

 4.2.4 Calibration of the Analyzer ................................................................................................

 4.2.5 Validation of the Analyzer..................................................................................................

 4.2.6 Procedure for calibrating the IACA during the compaction of an asphalt pavement........

5.0 Results of Field Demonstrations .......................................................................................

5.1 Accuracy of IACA Measurements..................................................................................

5.2 Quality Analysis of Pavement Construction..................................................................

5.3 Ease of IACA installation and calibration ......................................................................

6.0 Field Demonstrations of the Intelligent Asphalt Compaction Analyzer............................

6.1 Field Demonstration - Reading, Pennsylvania (June 01 - 05, 2009)..............................

 6.1.1 Discussion of Results ........................................................................................................

6.2 Field Demonstration - Tecumseh Road, Norman, OK (March 02, 2009) ......................

 6.2.1 Discussion of Results ........................................................................................................

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...11

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...17

...21

...25

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... 30

....32

...33

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x 

6.3 Field Demonstration - US-65, Carollton, MO (September 02, 2009)...............................36

 6.3.1 Discussion of Results ............................................................................................................36

6.4 Field Demonstration - I-40, Hinton, OK (June 10- July 10, 2009).....................................38

 

 

 

 

6.4.1 Discussion of Results ............................................................................................................41

6.5 Field Demonstration - I-86, Howard, NY (July 22-24, 2009) ............................................43

 6.5.1 Discussion of Results ............................................................................................................44

6.6 Field Demonstration - HWY 386, Cohocton, NY (August 12-17, 2009)............................45

6.6.1 Discussion of Results ............................................................................................................45

6.7 Field Demonstration - I-35, Norman, OK (June 17, 2009 - April 21, 2010)......................47

6.7.1 Discussion of Results ............................................................................................................48

6.8 Field Demonstration - I-35, Ardmore, OK (July 01 - 31, 2009).........................................49

6.8.1 Discussion of Results ............................................................................................................50

6.9 Field Demonstration - US-69, Muskogee, OK (April 2009) ..............................................50

7.0 Conclusions and Scope of Future Work .................................................................................... 51

7.1 Partnership for Success....................................................................................................52

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7.2 Opportunities for Wide-Scale Implementation and Challenges...

References....................................................................................................

Appendix ............................................................

Appendix A1 .......................................................

Appendix A2 .......................................................

A2.1 Protocol for short run field tests...........

A2.2 Protocol for extended run field tests ....

Appendix A3 .......................................................

 
ACKNOWLEDGEMENTS

The author would like to express their sincere appreciation to the Federal Highway

Administration (FHWA) and Oklahoma Department of Transportation (ODOT) and Volvo Construction 

Equipment Company for providing the funds to support the work presented in this report. Special 

thanks and appreciation are due to Mr. Eric Weaver, Civil Engineer, FHWA Turner-Fairbank Highway 

Research Center, Mr. Victor (Lee) Gallivan, Asphalt Pavement Engineer, FHWA, and Mr. William "Bill" 

King, Jr., LTRC Asphalt Research Engineer, for their assistance throughout this project. 

The results presented in this report would not have been possible without the substantial help of 

the following organizations: A. L. Blades & Sons, Inc; Kinsley Construction; Silver Star Construction; 

Haskell Lemon Construction Company; APAC Construction; Journagan Construction; and Glover 

Construction. The author would like to thank these contractors for their willingness to work with the 

research team and their flexibility in accommodating the needs of the team

The author would also like to Haskell Lemon Construction Company, EST Inc., and Volvo 

Construction Equipment Company for their assistance at every stage of the project.
LIST OF PARTICIPATING ORGANIZATIONS
 

xii 

S. No Contractor/ Contact Address 

1 A. L. Blades & Sons, Inc 7610 County Route 65, P. O. Box 590, Horn ell, NY 

14843 

(607) 324-3636 

2 Kinsley Construction 2700 Water Street, York, PA 17405 

(717) 741-3841 

3 Haskell Lemon 

Construction Co. 

3800 South West 10th, Oklahoma City, OK 73108 

(405) 947-6069 

4 Silver Star Construction

(2 crews) 

2401 S Broadway St, Moore, OK 73160 

(405) 793-1725 

5 APAC Construction 

(Dale Williams, MoDoT) 

Missouri 

(573) 526-4353; (573) 442-0146 

 

6 Journagan Construction 

(Dale Williams, MoDoT) 

Missouri 

(573) 526-4353; (417) 839 217 

7 Glover Construction Tulsa, Oklahoma 

 (918 -686-8081) 
1 

2.0 Introduction

The Intelligent Asphalt Compaction Analyzer (IACA) 15

is a device has been demonstrated to assist 

contractors during the construction of an asphalt pavement continuously in real-time, over the entire 

length of the pavement during its construction. Quality control techniques currently used in the field 

involve the measurement of density at several locations on the completed pavement or the 

extraction of roadway cores. These methods are usually time consuming and do not reveal the 

overall quality of the construction. Furthermore, any compaction issues that are identified cannot be 

easily remedied after the asphalt mat has cooled down. The ability of the IACA to estimate the level 

of compaction of the asphalt pavement during its construction will enable the roller operator to 

identify and remedy under-compaction of the pavement while avoiding over-compaction.

In recent years, several Intelligent Compaction (IC) technologies have been introduced by 

manufacturers of vibratory compactors4,8,11,19,28,32-34,45

. Uniform compaction of both soil and 

aggregate bases is achieved through the variation of the machine parameters (amplitude and 

frequency of vibrations, vectoring of the thrust, etc.). Dynamic control of the machine parameters 

allows for the application of the vibratory energy only to under-compacted areas and thereby 

preventing over-compaction and ensuring uniform compaction of the soil/aggregate base

33-35

. These 

IC techniques hold promise for the future and their performance is being evaluated by several 

agencies, including the Federal Highway Administration (FHWA)21. 

In contrast to the IC technologies being offered in the market place today, the IACA is a 

measurement device that does not control any aspect of the machine behavior. Further, the IACA is a 

standalone device that can be retrofitted on any existing vibratory compactor. The main utility of the 

IACA is in providing real-time estimates of the density of the asphalt mat at each location on the 

pavement under construction. This information can then be utilized by the roller operator to ensure 

uniform compaction, address under-compaction, as well as minimize the over-compaction of the 

pavement. 

2.1 Need Statement

Improper compaction of an asphalt mat during construction is a leading cause for the early 

degradation of asphalt pavements36. Excessive rutting, cracking, potholes etc., that are signs of 

failure of asphalt pavements can be avoided by using good quality control tools during the 

compaction process and through the adoption of better construction practices. The most reliable 

method of measuring pavement density in the quality assurance process is the extraction of field 

cores at several locations and conducting air voids tests in the laboratory as specified in AASHTO T166: “Bulk specific gravity of compacted bituminous mixtures using saturated surface-dry 

specimens.” This method of testing, however, is time consuming, costly, and a destructive process. 

Alternative methods for in-place measurement of density of hot mix asphalt (HMA) layers include 

both nuclear density gauges and non-nuclear density gauges2,37-39. The nuclear-based devices tend to 

have problems associated with licensing, equipment handling, and storage. All of these technologies 

allow only point-wise measurements of density during the construction of an asphalt pavement. This 

manual process of measurement is time consuming and results in avoidable delays in the 
2 

construction while not reflecting the overall quality of the pavement. Thus, there is a need for 

integrating new technology into vibratory rollers and to develop automated processes that can 

provide real-time data that can be used to achieve the target levels of compaction. Such a device 

would not only result in better quality and longer lasting pavements, but will also result in increased 

productivity of the construction crew, shorter construction times, and reduced construction costs.

2.2 Background

The IACA technology was developed at the University of Oklahoma, Norman during the years 

2003-2006 under a research grant from the Oklahoma Center for Advancement of Science and 

Technology (OCAST) 12

. Several tests were first conducted to characterize the compaction process in 

the laboratory and the data gathered was analyzed to design and develop the prototype IACA. The 

performance of the prototype was verified through tests in the laboratory using an Asphalt Vibratory 

Compactor

13

. The results indicate that the compacted specimen reached a mean density of 92.7% 

with a standard deviation of 0.304. The 95% confidence interval for the first set of tests obtained 

using the Student’s t-distribution is [ ] 92.7 0.38 ± , i.e. [92.32, 93.08]. Similarly when the specified 

target density is 94%, the compacted specimen was found to have reached a mean density of 93.9% 

with a standard deviation of 0.313. The 95% confidence interval in this case was [93.48, 94.25]. The 

results indicate that in both the cases, there is a 95% confidence that the achieved density is within 

1.25% of the target density. This compares very favorably with hand held density gauges currently 

used for quality control in the field

13

. 

The performance of the IACA prototype was validated during compaction under a controlled set 

of conditions. These limited tests demonstrated that the research prototype was capable of 

estimating the compaction of an asphalt pavement during its construction with accuracy acceptable 

for use as a quality control tool17. However, the use of the technology was limited due the need for 

manual calibration of the IACA. Further, the IACA was implemented on a computational platform 

that was primarily designed for testing in the laboratory. The use of the IACA technology in the field 

would require the porting of the IACA application to a rugged embedded hardware that is capable of 

withstanding extreme vibrations and the harsh environment typically found at construction sites. The 

development of automated, simple to use calibration techniques, and the validation of the 

performance during exhaustive field testing were necessary for the IACA technology to gain 

acceptance. 

2.3 Goals of the Highways for LIFE Technology Partnerships Program

The refinement of the IACA technology and the development of a commercial prototype were

accomplished between October 2007 - December 2009 under the assistance agreement DTFH61-08-

G-00002, Highways for LIFE Technology Partnerships Program, Federal Highway Administration. The 

prototype of the Intelligent Asphalt Compaction Analyzer (IACA) was developed during the Phase 1 of 

the project and its testing under real-world conditions was accomplished during the Phase II of this 

award. The ability of the IACA to continuously estimate the density of the asphalt pavement was 

demonstrated at several different sites across the country. The IACA provides the roller operator 

tools to address the targeted level of compaction during the construction process. During this study, 

the IACA was also shown to be helpful in determining the uniformity of compaction and in detecting

over-compaction of pavements during construction. The results of the study carried out under this 

agreement are presented in this report.
3 

"The purpose of Highways for LIFE (HfL) is to advance Longer–lasting highway 

infrastructure using Innovations to accomplish the Fast construction of Efficient and safe 

highways and bridges." †

The IACA aids the asphalt contractor in the construction of well compacted asphalt pavements. 

Ensuring adequate compaction and the prevention of over compaction of these pavements is critical 

to their longevity. Further, nondestructive evaluation of the pavements will eliminate the need for 

the extraction of roadway cores and thereby reduce the occurrence of pot holes and other forms of 

early degradation of the pavement. The compaction maps that are generated can be used to 

document the quality of the infrastructure right after the construction and can provide insight into 

factors affecting the performance of the pavement over time. The ability of the IACA to automatically 

estimate the density of the pavement will also reduce the need for the test personnel to take spot 

measurements of the density during the construction of the pavement, thus improving the 

workplace safety. Therefore, the IACA innovation will directly advance the HfL's goals of improving 

workplace safety and the improvement in the quality of the highway infrastructure. 

2.4 Organization of the Report

This report documents the activities designed to meet the project goals and the results achieved 

during the three phases of the project. The tasks for Phase 0, Phase I, and Phase II of the project and 

the milestones in the development process are first discussed in Section 3. The background of the 

IACA technology and the scope of the development proposed in this study are discussed in Section 4. 

The results of the field demonstrations are presented in Section 5. The detailed descriptions of the 

field evaluations are presented in Section 6. The opportunities and challenges for the IACA 

technology and the conclusions of this study are presented in Section 7. Protocols for the tests 

conducted during the course of this study, data from the field tests, and the interim reports for each 

of the project phases are given in the Appendix.

† Highways for LIFE, US Department of Transportation, Federal Highway Administration, 

http://www.fhwa.dot.gov/HfL/ (last accessed on October 17, 2010)
4 

3.0 Project Description and Work Plan

The development of a prototype IACA and its systematic testing during the construction of fulldepth pavements as well as overlays of asphalt pavements, were carried out under the Phase 0 and 

Phase 1 activity of this project24,25

. Prior to the start of this project, the IACA training and calibration 

techniques were performed manually, thereby limiting the utility of the IACA. Further, the IACA was 

implemented on a computational platform that was primarily designed for testing in the laboratory. 

During the course of this project (Phase I), the IACA application was ported to a rugged embedded 

hardware that is capable of withstanding extreme vibrations and the environment encountered 

during the construction of asphalt pavements. Automated, calibration techniques were also 

developed and the performance of the IACA was verified during field testing conducted by the 

University of Oklahoma (OU) research team. 

In the Phase 2 of the project, tests were conducted by independent users in order to study both 

the short term, as well as the long term use of IACA during the construction of asphalt pavements. In 

order to accomplish this objective, five (5) IACA prototypes were developed for installation on 

vibratory rollers. In addition, the installation kits including wiring harness, mounting brackets, and 

procedures for installation onto and removal from a roller were also developed. Test protocols were 

developed to study the factors (subgrade, underlying asphalt layers, calibration, etc) that affect the 

performance of the IACA, the effect of site (subgrade, compaction of underlying asphalt layers) on 

the calibration, and the use of the IACA to estimate the mean and variance of the density readings 

over the entire compacted pavement. The study was limited to the use of vibratory rollers and did 

not cover the use of oscillatory rollers. The detailed work plan23 is attached in the Appendix.

3.1 Phase 0 - Refinement of Research Prototype (September – December 2007)

As noted earlier, the IACA has been developed as a research prototype and has been validated to 

a limited extent in the field. Research was carried out in Phase 0 of this study to automate the 

training and calibration process. Automation steps were first developed in the laboratory using 

vibration data collected during field compaction. This vibration data was first used to train the neural 

network in the IACA. The densities measured from the roadway cores extracted after the 

construction of the pavement were then used to calibrate the output of the neural network for 

corresponding densities24. The validation of the calibration process involved the verification of the 

data at three different construction sites. During this phase of activity, automated calibration 

procedures using measurements obtained from a nuclear density gauge, as well as a non-nuclear 

density gauge were also developed. At each of these sites, the IACA was then was calibrated using 

density measurements from roadway cores and the performance was validated by comparing the 

IACA estimations against core densities. 

The following were the goals for this phase of the project. 

a. Develop a procedure to automatically train and calibrate the IACA using measurements of 

the roller vibrations during compaction. 

b. Validate the training procedure under laboratory setting using real field data.

c. Demonstrate the training and calibration procedure during preliminary field experiments.
5 

The following are the summary results of this phase of the project:

a. A low cost WAAS GPS receiver, Trimble ProXT35

, capable measuring position with sub-meter 

accuracy, was integrated with the IACA and automatic calibration procedures were 

developed. The calibration and training procedures developed were verified using 

construction data from prior research. 

b. Preliminary studies were conducted during the construction of a full-depth pavement at 

three sites (base, intermediate layers and shoulder) and the calibration procedure was 

validated. Test results show that the density estimated by the IACA compares well with the 

density measured from roadway cores. Results from the 14 core locations indicate that the 

mean error between the IACA estimations and the actual density as measured from the core 

is less than 1 pcf (pound-per-cubic-feet) with a 95% confidence interval of less than 3 pcf. 

The results of the Phase 0 of the project indicate that the IACA can estimate the density of the 

asphalt pavement with an accuracy that is suitable for quality control during the construction of the 

asphalt pavement. The integration of low-cost GPS sensor also improves the commercial feasibility of 

the technology. Based on the results of Phase 0, the project team commenced the next phase of the 

project, i.e. the development of a IACA prototype as described in the detailed work plan23. 

3.2 Phase 1 - Development of Commercial Prototype (February – November 2008)

In this phase of the proposed development, the research prototype validated in Phase 0 was 

used to develop a commercializable prototype of the IACA. The first task in this process was the 

selection of an electronic module in a rugged enclosure that was suitable for extended operations in 

the field. The project team coordinated with MathWorks, Inc., and Volvo Construction Equipment to 

determine a target electronic control module (ECM). The IACA application was then ported onto the 

target ECM, and the system was validated during the construction of asphalt pavements. 

Simultaneously, additional sensors to record properties (e.g., temperature) of the asphalt mat were 

incorporated into the system. Construction sites for validating the prototype were identified and the 

testing of the IACA to determine the repeatability and the accuracy of the estimations were

systematically carried out. This constituted the Milestone M2 of the project.

The accuracy of the density estimates and their repeatability were then investigated over a 

period of 9 months (March-December 2008). Sites with different mix designs, construction types, lift 

thicknesses, etc., were identified and the performance of the device was carefully studied. 

Appropriate refinement in the calibration and operation procedures was made to meet the desired 

performance. In addition, User Manuals, and Operator Training and Field Reporting procedures were 

also developed. 

The following were the goals for Phase I of the project: 

a. Determine an electronic platform that is tested to SAE J145527 standard to withstand 

vibrations and temperature variations encountered in heavy duty off-road applications. Port 

the IACA application to this platform and test functionality in the laboratory.

b. Incorporate temperature sensor, odometer, vibration switch, travel direction sensor, GPS 

sensor and test the commercial prototype during compaction in the field.

c. Identify five sites for systematic testing of the IACA. The sites selected will be representative 

of typical construction encountered in the field and will involve full depth construction as 

well as rehabilitation of existing pavements. The sites will also be selected to cover different 
6 

soil types to address varying liquid limit and plasticity indices. A partial list of the test sites 

that have been identified and their characteristics are given in the Appendix.

d. The performance of the IACA will be validated during the construction of the base, 

intermediate, and the surface layers of the asphalt pavement.

The following are the summary results of Phase I of the project:

a. An Electronic Control Module (ECM) (IDAN26 from RTD Embedded Technologies) was selected 

and the IACA algorithm was implemented on this platform. The selected hardware was 

resistant to shock and vibration and was suited for use in off-road applications. The 

associated software drivers and library functions also allowed the easy porting of the existing 

IACA application to the selected IDAN platform.

b. The suitability and performance of the IDAN ECM was verified using vibration data collected 

during compaction on SH-99 at Seminole (see Phase 0 Progress Report24

). 

c. The IDAN prototype was evaluated during the construction of asphalt pavements across 

Oklahoma. Five different construction sites were selected to verify the ability of the IACA to 

estimate the density of the asphalt mat during the compaction operation. The selected sites 

had different geomorphologies and covered a range from the construction of full-depth 

pavements to overlays and the compaction of multiple lifts of asphalt to simple overlay of a 

two inch surface course. The analysis of the densities measured from roadway cores and the 

estimates of the IACA indicate that after calibration, the IACA was able to estimate the 

densities within 1.5% of the maximum theoretical density of the asphalt mix. 

d. A graphical user interface (GUI) and a display monitor were developed that enabled the 

operator to easily calibrate the IACA. The GUI also allows for rapid report generation for the 

project including as-built maps, spatial variation of the compacted density, and core locations 

and density measured from the cores. Pass by pass variations in density can also plotted to 

study the rolling pattern and the compaction quality.

e. Manuals for calibration and evaluation of the IACA were also developed. 

f. Five sets of hardware have been purchased in order to implement five (5) IACA units for 

rigorous field testing during the Phase 2 of the project (January–December 2009). The team 

worked with Volvo Construction Equipment to determine production platform, wiring 

harness, mounting brackets etc. for commercial release of the technology. 

The results of the Phase 1 of the project indicated that the IACA was able to estimate the density

of the asphalt pavement with an accuracy that was suitable for quality control during the 

construction of the asphalt pavement. The prototype was rugged and could be produced at a cost 

that improves the commercial feasibility of the technology. Based on the results of Phase 1, the 

project team commenced the next phase of the project.

3.3 Phase 2 - Field Validation of the Commercial Prototype (January - December 

2009) 

The successful deployment of the technology will involve systematic and rigorous testing of the 

prototype. While the IACA evaluation during the Phase I of the project (2008-2009) was done during 

the construction of different type of asphalt pavements, the testing was done primarily to ascertain 

the ease and accuracy of the calibration process. In the Phase 2 of the project, tests are conducted by 

independent users to study both the short term, as well as the long term use of IACA during the 

construction of asphalt pavements. To accomplish this objective, a total of five prototype units were
7 

developed for installation on Ingersoll-Rand DD138HF or similar vibratory compactors. Operators 

were trained on the calibration and use of the technology. The selection of potential users, the 

protocol for testing, and the performance measures that were studied during these tests are 

discussed in this section. 

A. Selection of users and test sites for Phase II IACA testing

In order to comprehensively study the performance of the IACA, it is necessary to verify the 

functioning during the construction of Full-depth asphalt pavements, as well as overlays on existing 

pavements. It is also necessary to study the ability of the IACA to estimate the compaction of 

different layers of asphalt. At the beginning of the Phase II of the project, the Principal Investigators 

(PIs) coordinated with the FHWA contracting officer's technical representative (COTR) and distributed 

a Call for Participation to several regional Departments of Transportations (DOTs). Simultaneously, 

the PIs also worked through their contacts at Oklahoma Asphalt Pavers Association (OAPA) to 

identify likely users. The construction schedules and details provided by the end users were used to 

establish the test schedule for Phase II of the project. The details of the users and the information of 

the site are provided in Tables A1.1 and A1.2 respectively in the Appendix.

B. Installation and operability testing of the IACA (Short term testing)

The short term tests were structured to obtain feedback from a wide range of users on the 

installation and usage of the IACA. Specifically, these tests are intended to (a) determine the ease 

and effectiveness of the installation procedure, (b) the ease and the accuracy of the calibration and 

validation procedures, and (c) the clarity of the operator training and test procedures. In addition to 

these, the accuracy and verifiability of the density readings provided by the IACA was also studied. 

Prior to the evaluation, the research team worked with each contractor to identify the test location, 

to train the project crew on the test protocol, and the use of the IACA. On the day of the testing, the 

research team installed the IACA on the roller and helped calibrate the device. The contractor was 

allowed to use the IACA for a period of time (between two and four weeks) after which the IACA and 

the test data collected during the evaluation was sent back to the research team. The contractor was 

also asked to provide feedback on the IACA technology to the research team. 

During the compaction, the validation was performed during the construction of each asphalt 

layer (AC base, intermediate, and surface) and the accuracy of the IACA estimated density was 

verified through the density of roadway cores. 

C. Performance of the IACA during compaction operations

The testing of the IACA was designed to provide information on the consistency of the estimated

values during construction. These tests were designed to address the following performance issues:

a. How often should the IACA be calibrated in the field?

b. Does the IACA aid or hinder workplace safety?

c. Can the IACA estimates be used to detect soft spots in the soil subgrades during 

construction?

d. Will the use of the IACA help achieve uniform compaction?

e. Does the use of the IACA affect the productivity?

The data obtained from these tests was used to compare the compaction of different overlays on 

the same stretch of the pavement. The tests also helped determine if the site characteristics warrant 

re-calibration of the IACA during the compaction process and if the calibration can be refined over 

time. The impact of the technology on the productivity of the crew and workplace safety was also 

analyzed.
8 

The following is a summary of the results of this phase of the project.

a. Ten prototype units with associated wiring harness and sensors were developed and tested. 

The functioning of these units was demonstrated on a range of vibratory compactors being 

used by the contractors.

b. The tests conducted in Phase II of the project involved the verification of the calibration and 

accuracy of the IACA as well as its ability to function for extended periods of time. In all the 

IACA was tested during the construction of full depth asphalt pavements (2 sites), 

construction of one asphalt layer on existing asphalt pavement (4 sites), and construction of 

multiple layers of asphalt on AC/PCC base (4 sites). The IACA units were tested at nine 

different sites across the United States. Extended testing of the IACA was conducted at the 

remaining three sites. The testing of the IACA was carried out by 7 different contractors.

c. The installation of the IACA on the compactors was accomplished in less than 15 minutes. 

The training and calibration of the IACA was also accomplished in less than 2 minutes at each 

of the sites. The entire installation and calibration process was usually completed in less than 

an hour. 

d. The IACA estimated level of compaction was validated through comparison with over 180 

cores extracted at random from the completed pavements. The IACA estimates reflected the 

quality of compaction in the field and were shown to be satisfactory for use as a quality 

control tool in the field.

e. The IACA can map the coverage of the asphalt mat by the roller in real-time during the 

compaction process. This is a valuable tool and can help achieve uniformity in compaction. 

The built in functionality for mapping the surface temperature of the asphalt mat also helps 

in determining if the ‘cessation temperature’ has been reached after which further 

compaction would not be possible. 

f. The ‘as-built’ maps generated by the IACA are useful documentation of the contractors 

quality control of the constructed pavement.

g. In the tests conducted in Phase II of this award, the IACA was calibrated only once for each 

pavement layer at each site. Further calibration was not required at any of the sites where 

the IACA was tested. 

h. The IACA was able to detect the existence of soft spots in the base layers as well as overcompaction of the mix. In addition, the IACA estimate of the pavement quality was 

consistent with the quality estimated using Percent-within-Limits9,10,22,29-31 calculations. 

i. The IACA can reduce the frequency of quality control personnel making spot checks behind 

the break down roller during the compaction process. This would have tremendous 

consequence on the work place safety and will be likely to increase the productivity of the 

crew.
9 

4.0 Background and Operational Principle of the IACA

The Intelligent Asphalt Compaction Analyzer (IACA) is based on the hypothesis that a vibratory 

compactor and the hot mix asphalt (HMA) mat form a coupled system having unique vibration 

properties that can be identified by an analysis of the power spectrum distribution of the vibrations 

of the coupled system during the compaction process. Accelerometer measurements are used to 

extract relevant features from the power spectrum of the vibrations. These features are then 

classified by frequency and signal power and an artificial neural network-based pattern recognition 

approach is used to continuously measure the degree of compaction in real time. 

The primary purpose of the IACA is to estimate the level of compaction of an asphalt pavement 

during its construction. The IACA functions on the hypothesis that the vibratory roller and the 

underlying Hot Mix Asphalt (HMA) pavement form a coupled system. The response of the roller is 

determined by the frequency of its vibratory motors and the natural vibratory modes of this coupled 

system. Compaction of an asphalt mat increases its stiffness and as a consequence, the vibrations of 

the compactor (coupled system) are altered. The knowledge of the properties of the mat and the 

vibration spectrum of the compactor can therefore be used to estimate the stiffness of the mat. At 

this time, since the quality specifications are usually specified as a percentage of the Maximum 

Theoretical Density (MTD) of the asphalt mix, the IACA estimates the level of compaction rather than 

the stiffness of the mixture. Details of the IACA design, calibration, and field validation can be found 

in our earlier published work12-17

. The functional requirements of the IACA are discussed in the 

following section. 

4.1 Functional Requirements of the IACA

The functional requirements of the IACA can be categorized into the following sub-groups: 

Sensing Requirements, Operational Requirements, Calibration Requirements, Display and Recording 

Requirements, and Training and User Documentation. The overall functional model is shown in 

Figure 4.1 and the requirements are discussed in the following sections.

IACA

Accelerometer

Temperature 

Sensor

GPS

RS232 

Travel Direction 

Switch

Vibration Switch

Display

Time, 

Location, Temp, 

Density

Calibration

Data

User Input

Figure 4. 1 Functional Model of the IACA
10

4.1.1 Sensing Requirements

The IACA should be able to record the instantaneous spatial position of the compactor on the 

mat. The IACA should also be able to measure through non-contact means the surface temperature 

of the mat. In addition, the IACA should be able to detect the state of the vibration motors (ON/OFF) 

and the direction of travel of the compactor (FORWARD / REVERSE).

a. GPS Sensor. The GPS sensor should be capable of sub-meter accuracy in measurement and 

be capable of providing updates every second. The communication interface is through the 

use of the standard NEMA string and the IACA should be capable of extracting the Latitude 

and Longitude of the location of the compactor. The interface between IACA and the GPS 

unit is through RS232 or through a wireless Bluetooth connection.

b. Temperature Sensor. A non-contact temperature sensor capable of sensing surface 

temperatures from 0 degrees Fahrenheit ( 0 0 F ) to 350 degrees Fahrenheit ( 0 350 F ) should 

be integrated with the IACA. The temperature should be read in at a minimum once every 

second. The temperature input is typically an analog voltage with a swing between 0 and 5 

volts. Calibration routines should account for the DC bias and conversion factor of the 

sensing device. 

c. Travel Direction Switch Sensor. The IACA should be able to detect the switch status of the 

roller to determine the direction of travel. This input is typically a digital input to the IACA 

having discreet logic level (0 or 1) corresponding to Forward / Reverse.

d. Vibration Switch Sensor. The IACA should be able to detect the switch status of the roller to 

determine when the vibration motors are turned on. This input is typically a digital input to 

the IACA having discreet logic level (0 or 1) corresponding to ON/OFF. 

e. Accelerometer Sensor. The IACA should be capable of reading the acceleration of the drum 

through a tri-axial accelerometer mounted on the frame of the drum. The output of the 

accelerometer is an analog voltage between 0 and 5 volts. The vertical acceleration of the 

drum must be sampled at a 1000 Hz (once every milli-second).

4.1.2 Operational Requirements

The IACA reads in the sensed vibrations of the drum and estimates the corresponding density of 

the mat. The density estimates along with the location of the roller on the mat, the current process 

time, and the mat temperature are to be displayed to the user at least once every second. The error 

in the estimated density and the actual density measured from the roadway core should be within 

limits comparable to point wise density measurement tools in use today (accuracy of PQI 301 is 

within ±1.5 pcf and for nuclear density gauge the accuracy is within ±2.5 pcf ). The density must 

be displayed to the user as a numeric value (1 decimal precision), as well as a slider bar that indicates 

the progress in compaction. 

The IACA electronics must be housed in a rugged enclosure that is tested for vibration and shock, 

as well as environmental variables such as temperature and moisture (SAE J 1445 and SAE/TMSC 

environmental standards). 

4.1.3 Calibration Requirements

The use of the IACA requires detailed procedures for calibrating the output of the IACA to 

minimize the error between the estimates and the density measured off roadway cores. The 

procedure must provide for calibration in the field using measurements from roadway cores, as well 
11

as measurements taken using a non-nuclear density gauge such as PQI 301 or a nuclear density 

gauge like the Troxler 3450 gauge. The procedure must also provide a measure of the calibration 

accuracy. Once the readings from the field are input into the system, the calibration process must be 

automatic and result in the operational parameters (interconnection weights of the Neural Network 

and the calibration constants) being set in the IACA for field use during compaction.

The calibration procedures should be able to account for the location of the temperature sensor 

relative to the ground and provide the user the ability to calibrate the sensor in order to accurately 

record the surface temperature of the mat. 

4.1.4 Display and Recording Requirements

The IACA display should provide the user with real-time information on the location of the 

compactor, the temperature of the mat, and the estimated density at the location. The density 

information should be displayed both in a numeric format as well as a visual indication of the level of 

compaction (e.g. a slider bar). The compaction data (time, latitude, longitude, temperature, density) 

should also be stored as a text file for retrieval and post processing to generate as-built data maps.

The display is crucial to the field validation of the IACA. Validation in the field would require realtime information of the compaction achieved at any location on the pavement. It is anticipated that 

the readout from the IACA would be used to correlate the spatial location on the pavement with the 

estimated densities. This would allow verification with densities measured from roadway cores as 

well as using point-wise density measuring tools.

The display should also include a mechanism for selecting prior calibration data for use during 

the construction. The selection of the appropriate calibration data would involve the knowledge of 

the construction characteristics and the mix information.

4.2 Principle of operation of the IACA 

Compaction of an asphalt mat is achieved through the application of energy and pressure by a 

roller. The asphalt mat and the roller form a coupled system whose response is determined by the 

frequency of the vibratory motors of the roller and the natural vibratory modes of the coupled 

system. Compaction of an asphalt mat increases its stiffness and as a consequence, the vibrations of 

the roller are altered. The knowledge of the properties of the mat and the vibration spectrum of the 

roller can therefore be used to estimate the stiffness of the mat. Since the density and the modulus 

of the asphalt mixture are related, the IACA estimates the compacted density of the pavement rather 

than the stiffness.

A vibratory compactor equipped with IACA is shown in Figure 4.2(a) and the components of the 

IACA are shown in Figure 4.2(b). The sensor module (SM) in the IACA consists of accelerometers for 

measuring the vibrations of the compactor during operation, infrared temperature sensors for 

measuring the surface temperature of the asphalt mat, an user interface for specifying the amplitude 

and frequency of the vibration motors, and for recording the mix type and lift thickness. The feature 

extraction (FE) module computes the Fast Fourier Transform (FFT) of the input signal and extracts the 

features corresponding to vibrations at different salient frequencies. The artificial Neural Network 

(NN) Classifier is a multi-layer Neural Network that is trained to classify the extracted so that each 

class represents a vibration pattern specific to a pre-specified level of compaction. The Compaction 

Analyzer (CA) then post-processes the output of the NN and estimates the degree of compaction in 
12

real time. Details of the IACA and its preferred embodiment are discussed in detail in the IACA patent 15

application . 

(a)

(b)

Measure of 

Compaction

(Density)

Mat 

Properties

Extract salient 

features from the 

vibrations

Use training data 

to classify the 

features

Collect 

vibration 

data

Map the neural 

network output to 

density

Compaction 

Analyzer

Neural 

Network

Feature 

Extractor Sensor 

Module

Roller 

Vibrations

Figure 4. 2 Experimental Setup (a) Instrumentation of the compactor; (b) Functional block 

diagram of the IACA

4.2.2 Implementation of the IACA 

The functional components of the IACA and their operational principles are described in this 

section. 

Sensor Module. In the implementation discussed in this section, the Sensor Module of the IACA 

is comprised of an accelerometer mounted on the frame of a DD-138HFA Ingersoll-Rand vibratory 

compactor, an Intel Pentium based tablet PC to input the mat properties such as the mix type, 

binder, pavement layer, layer thickness, target density, etc., and a real-time data acquisition system. 

18

The accelerometer used was a CXL10HF3 tri-axial accelerometer manufactured by Crossbow , 

capable of measuring 10g acceleration up to a frequency of 10 kHz. The accelerometer measures the 

vibrations of the roller frame during the compaction. The surface temperature of the asphalt mat is 
13

measured using an infrared temperature sensor mounted on the frame below the roller. A Trimble 

Pro XT GPS receiver

35

is used to record the instantaneous location of the roller.

Feature Extractor Module. Analysis of the vibratory response of the roller requires the extraction 

of the frequency components of the vibrations and their amplitudes. These characteristic ‘features’ 

are related to the roller and the underlying pavement layers. As the pavement layer is compacted, 

the vibratory response of the roller changes. These changes are visible in the altered spectrum of the 

roller vibrations as the compaction progresses. The knowledge of these features can then be used to 

estimate the density of the pavement layer during its compaction. 

The feature extractor module of the IACA implements a Fast Fourier Transform to efficiently 

extract the different frequency components of the roller vibrations. The output of the FFT is a vector 

with 256 elements, where each element corresponds to the normalized signal power at the 

corresponding frequency. Since the vibration signal of the roller is sampled at 1 kHz, the frequency 

spectrum is uniformly distributed from 0 and 500 Hz. In order to classify these vibrations, the 200 

elements corresponding to the fundamental frequency of the roller response and its harmonics are 

used as input to the classifier. 

Classifier Module. The artificial Neural Network (NN) classifier implemented in the IACA is a 

three layer NN with 200 inputs, 10 nodes in the input layer, 4 nodes in the hidden layer, and 1 node 

in the output layer. The inputs of the NN correspond to the outputs of the feature extraction module, 

i.e. in this case 200 features in the frequency spectrum. The output corresponds to a signal indicative 

of the level of compaction reached. 

Analyzer Module. The analyzer module uses the mix parameters such as the mix type, binder, 

pavement layer, layer thickness, and the target density, and the calibration data to convert the 

output of the classifier to a value representing the density of the asphalt mat at the current location 

of the roller. The calibration data consists of a slope parameter and an offset parameter that is used 

to convert the output of the neural network, a number between 0 and 4, to a density value between 

0 and 100 (typically between 85 and 96). 

4.2.3 Training of the Neural Network

Central to the functioning of the IACA is the neural network that is used to classify the observed 

vibrations of the compactor into classes representing different levels of compaction. In order to 

accomplish this, the output of the feature extractor module is analyzed over several roller passes 

during the calibration process and the total power content in the vibration signal is calculated at each 

instant in time. Five equally spaced power levels are identified, and the features corresponding to 

these power levels are used to train the Neural Network. During compaction, the NN observes the 

features of the roller vibration and classifies these features as those corresponding to one of the 

levels of compaction. Figure 4.3 shows the features corresponding to five different compaction 

levels, with the lowest level corresponding to the case where the roller is operating with the 

vibration motors turned off and the highest level corresponding to the case where the maximum 

vibrations observed.
14

4.2.4 Calibration of the Analyzer

The calibration of the Analyzer is a two step process. In the first step, ideal compaction is 

assumed with the expectation that the analyzer would encounter ‘Lay Down’ density of the asphalt 

mat during the first roller pass and a density corresponding to the ‘target’ density during the final 

pass of the roller. 

Figure 4.3 Power content of the vibration signal during successive roller passes

Figure 4.4 Spectral features corresponding to five levels of compaction 
15

During the calibration process, a thirty feet section of the road is first identified and the vibration 

data is collected during successive roller passes over this stretch. The features extracted from this 

vibration data (Figure 2.3) are used to train the Neural Network in the Classifier module. After the

completion of the training process, the Classifier can recognize five levels of compaction labeled from 

‘0’ through ‘4’. Level 0 corresponds to the situation when the vibratory motors are turned off. The 

initial calibration assumes that the ‘Level 1’ of the vibrations corresponds to the “lay down” density 

of the mat and the ‘Level 4’ of the vibrations corresponds to the target density specified for the mix. 

This actual density is an indicator of the maximum compaction that is achievable during field 

compaction of the asphalt mix and is selected as the target density for IACA calibration. 

After the compaction of the 'calibration stretch', three roadway cores are extracted from known 

locations on the compacted pavement and their density is measured in the laboratory according to 

AASHTO T-166 method. The offset and slope constants for the compaction analyzer are determined 

to minimize the mean square error between the estimated density and the density measured from 

the cores2

. 

4.2.5 Validation of the Analyzer

In order to validate the functioning of the analyzer, core locations are marked at random on the 

completed pavement and the location of the cores is measured using a GPS sensor. The cores are 

then extracted and their density is determined in the lab. The GPS readings are used to determine 

the density estimated by the IACA at these locations during the final compaction pass of the roller. 

The error between the measured and estimated densities is then studied to determine the statistical 

measures of performance.

4.2.6 Procedure for calibrating the IACA during the compaction of an asphalt pavement

The evaluation described above has been carried out during the construction of the Hot Mix 

Asphalt Pavements. The calibration stretch is shown in Figure 4.5 and the procedure for calibration is 

described below.

i) The vibration data for calibration of the IACA is first acquired during the construction of a 

control strip. The control strip is one hundred feet (33 m) long and twelve feet (4 m) wide. 

A thirty foot (10 m) 'test section' is selected in the middle of the control strip and the GPS 

sensor is used to trigger the collection of the vibration data as the roller compacts this 'test 

section.' 

ii) Using the GPS sensor, the coordinates at the beginning and at the end of the test section is 

obtained by taking measurements at the center of the lane. These coordinates are used to 

automatically start and stop the collection of the vibration signals as the roller passes over 

the test strip.

iii) Three test locations at the center of the lane, five feet (1.6 m), fifteen feet (5 m) and 

twenty five feet (8.33 m) from the beginning of the test section are marked.

iv) Using a device similar to a 3450 Troxler Nuclear Density Gauge or a TransTech PQI 301 nonnuclear density gauge, the density of the pavement is measured after each roller pass at 

each of the test locations marked in step (iii). 
16

Figure 4.5 Selection of core locations after the final pass of the roller

Lane Width

Start

End

Calibration Stretch 30 feet

15 feet

5 feet

Final Roller Pass

5 feet

Cores 

Drum

Width

v) The compaction process is stopped when no appreciable increase in the density is seen 

after the roller pass or when roll over, i.e., reduction in measured density is observed. The 

core locations are marked from the center of the final roller pass at each of the test 

locations in step (iv). The GPS locations of the cores, as well as the density at the core and 

in the immediate vicinity of the core are recorded.

vi) The cores marked in the previous step are extracted and their density is measured in 

accordance with the AASHTO T-166 method.

vii) The density measurements taken after each roller pass and the densities of the extracted 

cores are used to train and calibrate the IACA.
17

5.0 Results of Field Demonstrations

The field evaluations reported in this section were carried out at 9 different construction sites 

operated by 7 contractors between January – December 2009. Of these, short term tests of the IACA 

were conducted at 6 sites and long term tests were conducted at the remaining three sites. The 

results from these sites are discussed in Sections 6.1-6.6 (and Sections 6.7-6.9. In all 14 contractors 

had responded to the invitation sent out by the research team and the FHWA, and of these 7 

contractors were selected for the field evaluations. Field trials at the construction sites of the 

remaining contractors could not be carried out due to either scheduling difficulties or lack or followup by the contractors. The location of the test sites and the relevant details of the construction are 

given in Tables A1.1 and A1.2 in the Appendix.

The installation of the IACA was performed by the research team with the assistance of the 

performing contractors. The cores for calibration and validation of the IACA were marked and 

extracted by the contractor and their density independently was verified either by EST or the 

contractor. The density of the cores was determined by the AASHTO T-166 method which specifies 

the procedure for the determination of the bulk specific gravity of compacted specimens (Gmb) from 

pavement cores. This value is used to estimate the density of the compacted specimen and is used 

for comparison between roadway compaction tests and the IACA estimated level of compaction 

values.

5.1 Accuracy of IACA Measurements

The IACA measurements reflected the quality of compaction in the field validations that were 

conducted during this project. In all, 180 roadway cores were extracted at random from the 

completed pavements at the test sites selected for this study and their density measured using the 

AASHTO T-166 method. The comparison of the density of the roadway cores from the compacted 

pavement with the density estimated by the IACA at the location of the cores is shown in Table 5.1. 

The mean density of the cores was 93.13 (standard deviation of 1.36) The IACA measurements at 

these locations show a mean density of 93.08 (standard deviation of 1.47). Null hypothesis testing 

showed that there is no significant statistical difference between the density measurements from the 

cores and the density estimated by the IACA. 

It is seen from Table 5.1 that the overall compaction that was achieved during asphalt overlay 

was significantly higher than that achieved during the construction of full-depth asphalt pavements 

Further, significant variation in the density was observed during the compaction of the Asphalt 

Concrete (AC) base layers, both for full depth as well as for asphalt overlays (standard deviations of 

1.62 and 1.53 respectively). Also, low compaction and high variability was seen during the 

construction of Full Depth Pavements. 

It is to be noted that the vibratory analysis cannot be applied to static rolling. The impact of the 

finish rolling using pneumatic and static rollers on the density is minimal. Our studies indicate that 

under normal conditions the density improves by 0.75-1.0 pcf (pounds per cubic feet) due to finish 

rolling. This is taken into account in the calibration procedure where the density measurements used 

are the values measured after the finish rolling.
18

Table 5.1 Summary of compaction data 

#

Cores

Type Mean

Density* 

(Cores)

Std. 

dev

(Cores)

Mean

Density* 

(IACA)

Std. 

dev

(IACA)

Error

(IACACore)

Std. 

dev

Error†

Max 

Error

(IACA)

R2

25 AC base (Full 

Depth)

92.29 1.62 92.21 1.44 -0.08 0.5 1.7 0.83

27 Intermediate 

(Full Depth)

93.24 0.9 93.12 1.13 -0.08 0.68 -1.3 0.63

15 Surface

(Full Depth)

92.1 0.87 92.07 1.03 -0.03 0.62 -1.2 0.63

49 AC base &

Intermediate

(HMA 

Overlay)

93.05 1.53 92.91 1.56 -0.14 0.65 -1.5 0.83

64 Surface

(HMA 

Overlay)

93.76 1.04 93.83 1.07 0.15 0.77 -2.2 0.54

* Mean density of the cores extracted after the compaction of the pavement

† Error between the measured density and the density estimated by the IACA

Figure 5.1 Comparison of the IACA estimated density with density determined from cores 

extracted from AC base layer (Full Depth construction)
19

Figure 5.2 Comparison of the IACA estimated density with density determined from cores 

extracted from AC intermediate layers (Full Depth construction)

Figure 5.3 Comparison of the IACA estimated density with density determined from cores 

extracted from surface layers (Full Depth construction)
20

Figure 5.4 Comparison of the IACA estimated density with density determined from cores 

extracted from AC base and intermediate layers (HMA overlay)

Figure 5.5 Comparison of the IACA estimated density with density determined from cores 

extracted from surface course (HMA overlay)
21

During the field tests, the performance of the IACA was observed to depend on the type of 

construction as well as the thickness of the pavement layer. While the estimates were close to the 

measured densities for full depth pavements, the IACA estimates had large coefficient of variation for 

thin surface layers used in overlays. 

Further, Figures 5.1 and 5.4 demonstrate that the IACA estimates for the AC base layers and the 

core measurements are strongly correlated (coefficient of determination = 0.83). Figures 5.2 and 5.3 

also indicate that in the case of full depth pavements, the IACA performance is not influenced by the 

asphalt layer (similar mean and variance as the density measured from the core and identical 

coefficient of determination). However, in the case on HMA overlay on exiting pavements, thin 

overlays on existing pavements resulted in larger estimation errors and a lower coefficient of 

determination (0.54) between estimated densities and the density measured from cores.

5.2 Quality Analysis of Pavement Construction 

a. Statistical Quality Analysis. 

The construction of asphalt pavements would typically involve the compaction of multiple lanes over 

several miles of the roadway. Ideally, the compacted density of the entire pavement has to be known 

in order to determine the quality of compaction. However, such a measurement is infeasible both 

from a time and cost standpoint when conventional tools and techniques are used. As a 

consequence, quality determination in the field is usually restricted to taking only a finite number of 

measurements at randomly selected locations. Percent Within Limit (PWL) is a Statistical Quality 

Analysis (SQA) method that can be used to ensure the quality of HMA pavements10,22. PWL technique 

enables the use of a small number of spot tests on the completed pavement to statistically estimate 

the overall quality of the roadway21. 

PWL is based on the assumption that the density of the compacted asphalt pavement is normally 

distributed about a mean density9,10. The variance of the measurements is an indicator of the 

uniformity of the compaction – larger the variance, greater is the variability of the density about the 

mean. For example, if four spot tests of density on a mile of compacted asphalt pavement reveal a 

mean density of 94% (6% air voids) and a standard deviation (σ) of 1%, then it can be construed that 

68% of the pavement has density values between 1 standard deviation of the mean density. In other 

words, about 68% of the pavement is likely to be compacted between 93-95% of the maximum 

theoretical density. PWL is designed to encourage and reward contractors to achieve uniform, 

consistent compaction of HMA pavements. 

According to the New York DOT Materials Bureau30, PWL is the percentage of the lot between the 

lower specification limit (LSL) and the upper specification limit (USL). These limits determine the 

acceptable quality and the corresponding pay factors. During the course of a construction project, 

the PWL is calculated as follows30. 

i. Four core locations are marked at random for every 1000 tons of asphalt that is laid and 

compacted.

ii. The density of each of the cores is measured according to the AASHTO T166 method then the 

mean (μ) and standard deviation (σ) for the days’ production are calculated.
22

iii. The standard deviation (σ) of the four cores is computed as follows:

 where ‘n’ is the total number of cores, and xi is the density

of the i

th core.

iv. The Lower Quality Index (QL) and Upper Quality Index (QU) are computed as follows:

 and 

 where L is the lower specification limit and U is the upper specification limit.

v. PWL between U and L is finally calculated as follows:

 

where PU and PL are determined from Table 1 in Index I30. 

The quality of compaction achieved during the long term testing of the IACA was investigated

during the construction HMA overlays at two different sites: I-86 near Howard, NY; Hwy 383 near 

Cohocton, NY. The details of these constructions are presented in Section 4.5 and 4.6. The 

construction on I-86 involved the overlay of 3.8 miles (6.08 km) of the road using two inches (50.4 

mm) of 19mm asphalt mix. After the placement of the asphalt mat, compaction was achieved using a 

Volvo DD-118HFA vibratory compactor. The construction on I-386 involved the overlay of 3.7 miles 

(5.92 km) of the road using two inches (50.4 mm) of 19mm asphalt mix. After the placement of the 

asphalt mat, compaction was achieved using a Volvo DD-118HFA vibratory compactor. The main 

difference between the two sites was in the preparation of the base layers prior to the construction. 

In the case of I-86, the rehabilitation of the existing pavement was undertaken by milling a removing 

a thin lift (0.6 inches / 15.24mm) of Nova Chip from the existing pavement. On the other hand, 

existing concrete pavement was rubbelized and proof rolled prior to the placement of the asphalt 

mat.

After calibrating the IACA system, the IACA estimated data was collected during the compaction 

at both the sites. Four core locations were marked by the New York Department of Transportation 

NY-DOT) engineer at the end of each day. The contractor recorded the GPS coordinates of these core

locations and then extracted the marked cores as well as companion cores adjacent to the marked 

locations. The density of the companion cores were measured by the contractor while the remaining 

cores were processed by NY-DOT. Performing the PWL analysis based on the density measurements 

from the DOT cores, it was estimated that 100% of the I-86 pavement was compacted between 

density of 93% and 96% (Table 5.3). Likewise, for the construction on Hwy 386, it was estimated that 

100% of the Hwy-386 pavement was compacted between density of 93% and 96% (Table 5.3). On the 

other hand, using the IACA estimated density, one could conclude that 100% of the constructed 

pavement on I-86 and 98% of the constructed pavement on Hwy 386 was between 93% and 96% 

compaction. Table 5.4 shows the actual density estimated during the final roller pass during 

compaction at both these sites. The data presented in this table reflects the actual density achieved 

over the entire extent of the construction. The data reiterates the fact that the majority of the 

construction was of very high quality and less than 1% of the completed pavement was undercompacted.
23

Table 5.2 Estimates of pavement quality using core densities and IACA estimations

Density Range

(DR)

DR ≤ 88

I – 86, H

Using Core

0

oward, NY

Using IACA

0

Hwy 386,

Using Core

0

 Cohocton, NY

Using IACA

0

88 < DR ≤ 89 0 0 0 0

89 < DR ≤ 90 0 0 0 0

90 < DR ≤ 91 0 0 0 0

91 < DR ≤ 92 0 0 0 0

92 < DR ≤ 93 0 0 0 2

93 < DR ≤ 96 100 100 100 98

96 < DR ≤ 97 0 0 0 0

97 < DR ≤ 98 0 0 0 0

98 < DR ≤ 99 0 0 0 0

DR > 99 0 0 0 0

Table 5.3 IACA tabulated final compaction density (percent)

Density Range

(DR)

I – 86

Howard, NY

Hwy 386

Cohocton, NY

DR ≤ 88 0% 0%

88 < DR ≤ 89 0% 0%

89 < DR ≤ 90 0% 0%

90 < DR ≤ 91 0% 0%

91 < DR ≤ 92 1% 1%

92 < DR ≤ 93 12% 14%

93 < DR ≤ 96 86% 80%

96 < DR ≤ 97 1% 5%

97 < DR ≤ 98 0% 0%

98 < DR ≤ 99 0% 0%

DR > 99 0% 0%

b. Detection of variation in the compaction of pavements

During the preparation of the I-86 site, the contractor had noted the existence of soft spots in the AC 

base between stations 13500 and 15500 and between stations 10500 and 11500. This stretch 

corresponded to the section of the highway under a bridge and remediation was not considered 

feasible. Reconstruction of the as-built maps from IACA estimates show that an average density of 

93% was achieved on this stretch in contrast to densities between 94-95% at other locations on the 

completed pavement.
24

(a)

(b)

Figure 5.6 As-built density on two sections with low underlying support on I-86

c. Detection of over-compaction during construction

The rolling pattern for a particular compaction job is established by the contractor in cooperation 

with the agency /DOT representative at the beginning of the job. During the compaction of a test 

pavement, the density achieved after each roller pass is measured using a handheld gauge. 

Compaction is stopped when no further increase in density is observed. Cores are extracted at 

random from the completed pavement and their density was measured in the laboratory to ensure 

that compaction targets are met. Once the rolling pattern is established, the contractor periodically 

verifies the final density but does not usually verify the variations in density after each pass or alter 

the rolling pattern unless necessitated by quality issues. While this process may be adequate to 

obtain passing quality during the compaction of asphalt pavements, it is not ideal for attaining 

optimum quality during compaction.

Comparison of IACA density estimates after each roller pass can be a good indicator of the 

quality and can be used to obtain optimum compaction of the asphalt mat. The density at a test 

location during successive roller passes is shown in Figure 5.7. In this case, two rollers were operated 

in tandem with the first roller providing 5 roller passes and then the second roller compacting the 

pavement with 5 additional roller passes. The variation in density seen during the compaction with 

the second roller indicates that the target density was achieved by the second roller pass. Additional 

roller passes not only resulted in lowered density but also resulted in a loss of uniformity in 

compaction.
25

Figure 5.7 Reduction in density as a result of over-compaction of the asphalt pavement

d. Coverage maps and rolling patterns

The IACA has built in functionality to generate complete as-built maps (Figure 5.8). Any 

measurement data, for example density measured using roadway cores or calibrated gauges, can be 

superimposed on this map to generate a validated quality measure for the entire project. Further, 

such maps can be generated in real time as the roller compacts a stretch of the pavement (Figures 

5.9 and 5.10). The surface temperature of the mat serves as an indicator of the time remaining 

before compactive effort would cease to result in increased density.

5.3 Ease of IACA installation and calibration

During each of the field evaluations, the installation of the IACA on the vibratory compactor was 

completed within 15 minutes by the research team and the training and calibration of the IACA was 

accomplished within 2 minutes of the completion of the calibration stretch. Figures 5.11 and 5.12 

show the IACA installed on a contractor owned Ingersoll Rand DD-90 vibratory compactor and a 

Volvo owned DD118HFA vibratory compactor. At each site, calibration was performed for each layer 

of asphalt. The validation results presented in this report were obtained by comparing the density of 

randomly selected roadway cores with the IACA estimated density at the core locations. 

Recalibration of the IACA was not found to be necessary during the course of the project. 
26

The operator feedback on the ease of installation and calibration was positive. The displayed 

information was also well received. However, the research team found that the roller operator 

primarily paid attention to adhering to the rolling pattern that was established and not to the quality 

of compaction that was being achieved. The roller operator would seldom look at the display or pay 

attention to the density estimates and the as-built density maps. Therefore, it was not possible to 

evaluate the benefits that could result in the uniformity of compaction or the productivity through 

the use of IACA technology.

Figure 5.8 As-built compaction map with verifiable density estimates
27

Figure 5.9 Density map and the surface temperature of a stretch of pavement during compaction

6

8%

3 3

Figure 5.10 Density map for each pass during compaction
28

(a)

(b) (c)

Figure 5.11 Installed view of the IACA on a Ingersoll Rand DD-90 vibratory compactor
29

(a)

(b)

Figure 5.12 (a)Installation of the IACA on a Volvo DD 118HFA roller; (b) IACA in use
30

6.0 Field Demonstrations of the Intelligent Asphalt Compaction Analyzer

6.1 Field Demonstration - Reading, Pennsylvania (June 01 - 05, 2009)

The performance of the IACA was observed during the overlay of asphalt pavement on highway 

US-222 near Reading, PA. Remediation of the existing pavement involved milling and removal of 2.54 

miles of existing pavement and then compacting a two inch lift of 12.5mm asphalt mix on top of the 

jointed plain concrete pavement (JPCP) base. Compaction was achieved using Ingersoll Rand DD110 

dual drum vibratory compactor. Finish rolling was done using a static steel drum roller Ingersoll Rand 

DD110 roller. Quality control in the field was performed using a Troxler 3450 nuclear density gauge

(NDG). The location of the site is shown in Figure 6.1 and the site details are given in Table 6.1. The 

accelerometer sensor was located on the axle of the front drum and the GPS receiver was located on 

the roof of the compactor. The offset in Table 6.1 indicated the lateral separation between the 

accelerometer and the GPS receiver and was used to relate the GPS measurement to the location of 

the drum.

Figure 6. 1 Site location on US-222 near Reading, PA
31

Table 6. 1 Machine and Site Information (US-222)

Date June 01, 2009

Location Reading, PA

Construction type Mill & Overlay

Lift 1st 

Mix 12.5 mm

Thickness 50.8mm

Roller Ingersoll Rand DD 110

Calibration (using NDG) 3 

Validation (using NDG) 12

Settings

Accelerometer location front

Offset from GPS receiver (feet) 0 

Drum width (feet) 6.5

Table 6. 2 Validation results from US-222, Reading, PA

Core 

Location

Core Density* 

(NDG) 

Estimated

Density*

(IACA)

Estimation Error* 

(IACA-NDG)

C1 93.60 93.50 -0.10

C2 91.80 93.50 1.70

C3 94.90 93.10 -1.80

M4 93.30 91.30 -2.00

M5 94.50 94.30 -0.20

M6 94.50 92.30 -2.20

M7 93.90 94.00 0.10

M8 93.40 94.20 0.80

M9 92.90 94.30 1.40

M10 92.80 93.90 1.10

M11 91.80 94.00 2.20

M12 91.70 93.90 2.20

M13 91.80 92.90 1.10

M14 92.80 93.30 0.50

M15 93.50 93.50 0.00

* % MTD
32

Figure 6. 2 Roller path and estimated densities at core location C1, US-222, Reading, PA

6.1.1 Discussion of Results

On the day of the validation, the project team installed the IACA on the contractor owned and 

operated IR DD110 compactor. The calibration of the IACA was performed by comparing the IACA 

estimated density with the density measured using the contractor's calibrated nuclear density gauge. 

The IACA estimated density at the calibration location 'CalCore 1' during each roller pass is shown in 

Figure 6.2. In this figure, P1, P2, and P3 represent three consecutive roller passes over the calibration 

location. P1 and P3 denote the forward movement of the roller while P2 indicates the backward 

movement of the roller. For each pass, the starting point is designated by 'S' and the termination of 

the pass is designated by 'E'. For example, P1S represents the starting point for Pass 1 and P1E 

indicates the terminal point of Pass 1. The graph in the lower panel depicts the variation of the IACA 

estimated density in the vicinity of the calibration location. From this figure, the operator can verify 

the increase in density after each roller pass and the uniformity of the compaction at the calibration 

location. 

After the IACA was calibrated, several locations were randomly marked on the compacted 

pavement and the density at each of these locations was measured using the nuclear gauge. The GPS 

coordinates of these locations were also measured and the IACA estimated density was recorded. 

The measured and estimated densities are shown in Table 6.2. The results from these tests indicate 

that the mean estimation error, i.e. mean of the difference between NDG measured density and 

IACA estimated Density is 0.32 with a corresponding standard deviation of 1.425. Further, the 95% 

Confidence Interval for the estimation error is [-0.42, 1.06] which implies that the IACA estimates are 

statistically similar to the measurements obtained using a nuclear density gauge.
33

6.2 Field Demonstration - Tecumseh Road, Norman, OK (March 02, 2009)

The project involved the construction of 1.881 miles of an undivided two lane extension of 

Tecumseh Road between NW 12th Avenue and NE 12th avenue in Norman, Oklahoma (State job # 

14391(04), Project #STPY-014B(378)). The IACA was evaluated during the construction of the surface 

course of a full-depth asphalt pavement. During this evaluation, a three inch (76.2mm) lift comprising 

of 19mm asphalt mix was compacted using an Ingersoll-Rand DD-118 vibratory compactor. The 

accelerometer was affixed on the axle of the front drum and the GPS receiver was mounted on the 

roof of the cab. The longitudinal separation between the GPS receiver and the drum was 4 feet 

(1.13m) (Table 6.3).

Figure 6. 3 Site location on Tecumseh Road, Norman, OK
34

Table 6. 3 Machine and Site Information (Tecumseh Road, Norman, OK)

Date March 02, 2009

Location Tecumseh Road, Norman

Construction type Full depth

Lift Surface

Mix 19 mm (S3)

Thickness 3 inches

Roller Ingersoll Rand DD118

Calibration Cores # 3 

Validation Cores # 4 

Settings

Accelerometer location Front

Offset from GPS receiver (feet) 4 

Drum width (feet) 6.5

6.2.1 Discussion of Results

Prior to using the IACA, the IACA was calibrated by comparing the IACA estimated density with 

the density measured from three roadway cores as described in Section 2. Raw calibration of the 

IACA was first performed by comparing the IACA estimated density with the density measured using 

the target density specified in the mix design sheet. Three cores (Calcore 1, Calcore 2, and Calcore 3 

in Table 6.4) were extracted after the pavement has cooled down and their density was measured 

according to AASHTO T-166 method. The density at these three locations was compared with the 

IACA estimated density and the calibration parameters were recomputed so as to minimize the mean 

square error of the estimation process. After the IACA was calibrated, several locations were 

randomly marked on the compacted pavement and roadway cores were cut and extracted. The 

measured and estimated densities at these locations are shown in Table 6.4. The results from these 

tests indicate that the mean estimation error, i.e. mean of the difference between core density and 

IACA estimated density is -0.46 with a corresponding standard deviation of 0.82. Further, the 95% 

Confidence Interval for the estimation error is [-1.08 0.16] which implies that the IACA estimates are 

statistically similar to the measurements obtained using roadway cores.

The IACA estimated density at the validation location 'M6' during each roller pass is shown in 

Figure 6.2. In this figure, P1, P2, P3, P4 represent four consecutive roller passes over the calibration 

location. P1 and P3 denote the forward movement of the roller while P2 and P4 indicates the 

backward movement of the roller. For each pass, the starting point is designated by 'S' and the 

termination of the pass is designated by 'E'. For example, P1S represents the starting point for Pass 1 

and P1E indicates the terminal point of Pass 1. The graph in the lower panel depicts the variation of 

the IACA estimated density in the vicinity of the calibration location. From this figure, it can be seen 

that the rolling pattern adopted by the in the operator resulted in 4 roller passes at the core location, 

but no appreciable increase in the density was observed. 
35

Figure 6. 4 Roller path and IACA estimated density at test location M6, Tecumseh Road, Norman, OK

Table 6. 4 Validation results from Tecumseh Road, Norman, OK

Core 

Location

Core Density*

(Core)

Estimated

Density* (IACA)

Estimation Error*

(IACA-Core) 

Calcore1 94.30 93.10 -1.20

Calcore2 93.80 92.40 -1.40

Calcore3 93.90 92.70 -1.20

M4 93.80 94.20 0.40

M5 93.80 94.10 0.30

M6 93.50 93.90 0.40

M7 94.60 94.10 -0.50

* % MTD
36

6.3 Field Demonstration - US-65, Carollton, MO (September 02, 2009)

The performance of the IACA was observed during the overlay of asphalt pavement on highway 

US-65 near Carollton, MO. Remediation of the existing pavement involved milling and removal of 1.1 

miles of existing pavement and then compacting a 1.75 inch lift of 12.5mm asphalt mix on top of the 

milled pavement. The mix was trucked to the location by trucks and laid down using a CAT AP10550 

paver. Compaction was achieved using Ingersoll Rand DD158HFA dual drum vibratory compactor. 

Finish rolling was done using an Ingersoll Rand DD130 roller operating in the static mode. 

Figure 6. 5 Site location on HWY 65 at Carollton, MO (near Malta Bend) (1.1 miles from Start to End)

6.3.1 Discussion of Results

Prior to using the IACA, a thirty feet calibration region was first compacted as described in 

Section 2. The calibration of the IACA was performed by comparing the IACA estimated density with 

the density measured from three roadway cores extracted from this calibration region. After the 

IACA was calibrated, several locations were randomly marked on the compacted pavement and 

roadway cores were cut and extracted. The density of the cores at these locations was then 

measured using the AASHTO T-166 method. The GPS coordinates of these locations were also 

measured and the IACA estimated density was recorded. The measured and estimated densities are 

shown in Table 6.5. The results from these tests indicate that the mean estimation error, i.e. mean of 

the difference between core density and IACA estimated Density is 0.2% with a corresponding 

standard deviation of 0.8. Further, the 95% Confidence Interval for the estimation error is [-0.51 

0.91] which implies that the IACA estimates are statistically close to the measurements obtained 

using a roadway cores. 
37

Table 6. 4 Machine and Site Information, HWY 65, Carollton, MO

Information

Date Sep 02, 2009

Location Marshall MO

Construction type Mill and Overlay

Lift Surface

Mix 12.5 mm SP125 09-71 (64-22)

Thickness 1.75"

Roller Ingersoll Rand DD158

Calibration Cores # 3 

Validation Cores # 3 

Settings

Accelerometer location Rear

Offset from GPS receiver (feet) 8 

Drum width (feet) 7 

Table 6. 5 Validation results from US-65, Carollton, MO

Core 

Location

Core Density*

(Core)

Estimated

Density* (IACA)

Estimation Error*

(IACA-Core) 

C1 94.80 94.30 -0.50

C2 95.20 95.40 0.20

C3 95.20 95.40 0.20

W4 93.80 95.30 1.50

W5 93.20 92.80 -0.40

W6 89.70 93.00 †

* % MTD †damaged core
38

6.4 Field Demonstration - I-40, Hinton, OK (June 10- July 10, 2009)

The performance of the IACA was observed during the overlay of asphalt pavement on Interstate 

I-40 near Hinton, OK (Figures 6.6- 6.8). Remediation of the existing pavement involved milling and 

removal of 6.0 miles of existing pavement and then compacting a 3.0 inch lift of 19mm asphalt mix 

followed by a second lift of 2.0 inches using the same mix (Table 6.6). Compaction was achieved 

using a Dynapac and an Ingersoll Rand DD138HF dual drum vibratory compactors operating in 

tandem. Finish rolling was done using Ingersoll Rand DD118 roller operating in static mode. 

Figure 6. 6 Site location on I-40 (West bound) at Hinton, OK
39

Figure 6. 7 Calibration region on East bound I-40 (Hinton, OK)

Figure 6. 8 Validation region on East bound I-40 (Hinton, OK)
40

Table 6. 6 Site and Machine Information, I-40 at Hinton, OK

Date Jun1009 Jun1109 Jun1209

Location Hinton OK Hinton OK Hinton OK

Construction type

Mill & 

Overlay

Mill & 

Overlay Overlay

Lift 1st 1st 2nd

Mix

19 mm

S3 PG-76-28

19mm

S3 PG-76-28

12.5mm

S4 PG-76-28

Thickness 3 inches 3 inches 2 inches

Roller

Ingersoll 

Rand DD138HF

Ingersoll 

Rand DD138HF

Ingersoll 

Rand DD138HF

Calibration Cores # 0 3 0 

Validation Cores # 3 3 6 

Settings

Accelerometer

location front front Front

Offset from GPS 

receiver (feet) 0 0 0 

Drum width (feet) 7 7 7 

Date Jun2609 Jul1009

Location Hinton OK Hinton OK

Construction type Mill & Overlay Mill & Overlay

Lift 2nd 2nd

Mix

12.5mm

S4 PG-76-28

12.5mm

S4 PG-76-28

Thickness 2 inches 2 inches

Roller

Ingersoll Rand 

DD138HF

Ingersoll Rand 

DD138HF

Calibration Cores # 3 0 

Validation Cores # 0 3 

Settings

Accelerometer

location front Front

Offset from GPS 

receiver (feet) 0 0 

Drum width (feet) 7 7 
41

6.4.1 Discussion of Results

The calibration and validation of the IACA was performed for both asphalt layers as described in 

the previous section. Comparison of the density estimated by the IACA and the actual density 

measured from the roadway cores is shown in Table 6.7 and 6.8. The results from these tests indicate 

that in the case of the AC base layer, the mean estimation error, i.e. mean of the difference between 

core density and IACA estimated Density is 0.4% with a corresponding standard deviation of 0.84. 

Further, the 95% Confidence Interval for the estimation error is [-0.19 0.99]. In the case of the 

second asphalt layer, the mean of the difference between core density and IACA estimated Density 

was found to be 0.54% with a corresponding standard deviation of 0.24. Further, the 95% Confidence 

Interval for the estimation error is [0.34 0.74]. These results also indicate that the IACA estimates are 

statistically close to the measurements obtained using a roadway cores. 

The estimated density at core location C3 is shown in Figure 6.9. It can be seen from the figure 

that significant compaction was already achieved during the first pass of the roller. Since the two 

breakdown rollers are operating in tandem, the achieved compaction is higher than in the case 

where only one roller is used. However, it can be seen from the figure that the additional roller 

passes actually have a detrimental effect in the sense that the mix is over-compacted and the final 

compaction that is achieved (92.3%) is far lower than the maximum compaction that was obtained at 

the completion of the second pass (94.6%). Thus, having access to the IACA estimates can avoid over 

compaction of the asphalt pavement and result in better quality of compaction. 

Table 6. 7 Validation results for first lift I-40, Hinton, OK

Core Location

Core Density*

(Core)

Estimated

Density* (IACA)

Estimation Error*

(IACA-Core) 

5210+32 96.23 97.90 1.67

5158+52 94.55 94.00 -0.55

5158+91 93.31 93.40 0.09

Calcore1 95.40 94.70 -0.70

Calcore2 95.10 95.50 0.40

Calcore3 94.50 94.60 0.10

5157+64 95.37 96.50 1.13

5240+86 94.44 95.50 1.06

Table 6. 8 Validation results for second lift I-40, Hinton, OK

Core Location

Core Density*

(Core)

Estimated

Density* (IACA)

Estimation Error*

(IACA-Core) 

Calcore1 95.00 94.40 0.60

Calcore2 94.30 94.60 0.30

CalCore3 94.30 94.60 0.30

5273+61 93.65 93.10 0.55

5262+14 94.92 94.40 0.52

5268+98 94.64 95.60 0.96
42

Figure 6. 9 Roller path and IACA estimated density at test location C3, I-40 at Hinton OK
43

6.5 Field Demonstration - I-86, Howard, NY (July 22-24, 2009)

Field testing of the IACA system was conducted on interstate I-86 near Hornell, New York (Figure 

6.10). The rehabilitation of the pavement was undertaken by first milling and removing a thin lift of 

Nova Chip (0.6 in) from some of the pavement. Then the pavement was paved with a 2.5 in. lift of a 

25mm mix, two 2 in. lifts of 19.0mm, and then a 1.6 in. lift of 9.5mm asphalt mix. The IACA data was 

collected during the construction of the second lift of the 19mm mix. The mix was trucked to the 

location by trucks and laid down using a VOGELE 2219w paver. Compaction was then achieved using 

a HAMM HD-130 HV and a VOLVO DD-118 HFA dual drum vibratory compactors operating in tandem. 

Finish rolling was done using the same VOLVO roller but operating in static mode (see Table 6.9). 

Figure 6. 10 Site location on I86 near Howard, NY (3.8 miles)
44

Table 6. 9 Site and Machine Information, I-86 near Howard, NY

Date July 22,2009

Location Howard, NY

Construction type Mill & Overlay

Lift Top

Mix 19mm PG 64-22

Thickness 2 inches

Roller DD118HFA

Calibration Cores # 3 

Validation Cores # 7 

Settings

Accelerometer location Front

Offset from the GPS receiver (feet) 0 

Drum width (feet) 6.5

6.5.1 Discussion of Results

The calibration and validation of the IACA was performed as described in the previous section. 

Comparison of the density estimated by the IACA and the actual density measured from the roadway 

cores is shown in Table 6.12. The results from these tests indicate that the mean estimation error, i.e. 

mean of the difference between core density and IACA estimated Density is 0.13% with a 

corresponding standard deviation of 0.85. Further, the 95% Confidence Interval for the estimation 

error is [-0.41 0.66]. 

Table 6. 10 Validation results from I-86, Howard, NY

Core 

Location

Core Density* 

(Core)

Estimated

Density*

(IACA)

Estimation Error* 

(IACA-Core) 

Calcore1 94.90 93.50 -1.40

Calcore2 94.30 94.80 0.50

Calcore3 94.10 94.50 0.40

WC4 94.45 95.10 0.65

WC5 94.35 93.40 -0.95

WC6 95.25 94.60 -0.65

F1 94.30 94.40 0.10

F2 94.55 95.60 1.05

F3 95.85 96.30 0.45

F4 94.30 95.40 1.10

* % MTD
45

6.6 Field Demonstration - HWY 386, Cohocton, NY (August 12-17, 2009)

Field testing of the IACA system was conducted on interstate HWY 386 near Cohocton, New York

(Figure 6.11). The rehabilitation of the pavement was undertaken by first milling and removing a thin 

lift of Nova Chip (0.6 in) from some of the pavement. The rest was the existing, very faulted, concrete 

pavement. The concrete pavement was rubbelized and then proof rolled. Any soft areas were 

undercut by excavating the pavement and offending sub-base and then replacing it with screened 

gravel and a lift of 25mm mix. Then the pavement (either rubbelized or undercut) was paved with a 

2.5 in. lift of a 25mm mix, two 2 in. lifts of 19.0mm, and then a 1.6 in. lift of 9.5mm asphalt mix. The 

IACA data was collected during the construction of the second lift of the 19mm mix. The mix was 

trucked to the location by trucks and laid down using a VOGELE 2219w paver. Compaction was then 

achieved using a HAMM HD-130 HV and a VOLVO DD-118 HFA dual drum vibratory compactors 

operating in tandem. Finish rolling was done using the same VOLVO roller but operating in static 

mode. 

Figure 6. 11 Site location on HWY 386 near Cohocton, NY (3.7 miles)

6.6.1 Discussion of Results

The calibration and validation of the IACA was performed as described in the previous section. 

Comparison of the density estimated by the IACA and the actual density measured from the roadway 

cores is shown in Table 6.13. The results from these tests indicate that the mean estimation error, i.e. 

mean of the difference between core density and IACA estimated Density is 0.01% with a 

corresponding standard deviation of 0.94. Further, the 95% Confidence Interval for the estimation 

error is [-0.42 0.44]. 

S

E
46

Table 6. 11 Validation results from HWY 386, Cohocton, NY

Core Location

Core Density*

(Core)

Estimated

Density* (IACA)

Estimation Error*

(IACA-Core) 

Calcore1 94.70 94.00 -0.70

Calcore2 94.00 93.40 -0.60

CalCore3 93.40 94.50 1.10

C1 95.05 93.30 -1.75

C2 94.40 93.40 -1.00

C3 94.55 93.90 -0.65

C4 91.90 93.80 1.90

C5 93.50 94.00 0.50

C6 93.40 94.50 1.10

C7 93.50 92.80 -0.70

Calcore1 94.30 93.70 -0.60

Calcore2 93.70 93.60 -0.10

CalCore3 92.60 93.40 0.80

C4 92.70 93.90 1.20

C5 92.75 93.40 0.65

C7 93.35 92.70 -0.65

C2 94.50 93.80 -0.70

C3 92.80 92.90 0.10

C4 92.20 92.50 0.30

* % MTD
47

6.7 Field Demonstration - I-35, Norman, OK (June 17, 2009 - April 21, 2010)

The use of the IACA in estimating the stiffness of a multi layer HMA pavement was investigated 

during the construction of Interstate I-35 in Norman, OK (Figure 6.12). This project involved the 

expansion of the existing highway, stabilizing the subgrade to a depth of 200 mm using 10% cement 

kiln dust (CKD), followed by 200 mm thick aggregate base. The asphalt concrete base layer consisted 

of 100 mm thick asphalt layer of 19 mm Nominal Maximum Aggregate Size (NMAS) S3 (64-22 OK), 

while the second and third layers were constructed with 19 mm NMAS S3 (76-28 OK) of 100 mm and 

75 mm thickness, respectively. A 50 mm surface course of 12.5mm NMAS S4 (76-28 OK) was 

compacted on top of the three asphalt layers. During the course of the project, the project team had 

installed the IACA on a contractor owned and operated Ingersoll Rand DD110 roller. The research 

team helped calibrate the IACA for each pavement layer by verifying the IACA estimated density 

against 3 calibration cores extracted from the finished pavement. The contractor was allowed to use 

the IACA instrumented roller and validate the performance of the device.

Figure 6. 12 Site location on I-35 in Norman, OK

E

nd
48

Table 6. 12 Site and Machine Information, I-35 in Norman, OK

Date 6/17/09 6/18/09 6/22/09 3/15/10

Location I 35 Norman I 35 Norman I 35 Norman I 35 Norman

Construction type Full depth Full depth Full depth Full depth

Lift AC base 2nd 3nd 4th

Mix S3 64-22 OK S3 76-28 OK S3 76-28 OK S4 76-28 OK

Thickness 4" 3" 3" 2"

Roller

Ingersoll Rand 

DD110

Ingersoll Rand 

DD110

Ingersoll Rand 

DD110

Ingersoll Rand 

DD110

Calibration Cores # 3 3 3 3 

Validation Cores # 2 3 6 15

Settings

Accelerometer location front front front front

Offset from GPS receiver

(feet) 0 0 0 0 

Drum width (feet) 6.5 6.5 6.5 6.5

6.7.1 Discussion of Results

The calibration and validation of the IACA was performed as described in the previous section. 

For the AC base layer, the tests indicate that the mean estimation error, i.e. mean of the difference 

between core density and IACA estimated Density is -0.18% with a corresponding standard deviation 

of 0.36. Further, the 95% Confidence Interval for the estimation error is [-0.5 0.14]. 

For the second layer of the asphalt pavement, the tests indicate that the mean estimation error 

is -1.03% with a corresponding standard deviation of 1.22. Further, the 95% Confidence Interval for 

the estimation error is [-2.03 -0.04].

For the third layer of the asphalt pavement, the tests indicate that the mean estimation error is -

0.74% with a corresponding standard deviation of 0.81. Further, the 95% Confidence Interval for the 

estimation error is [-1.28, -0.21].

For the final layer of the asphalt pavement, the tests indicate that the mean estimation error is 

0.11% with a corresponding standard deviation of 0.76. Further, the 95% Confidence Interval for the 

estimation error is [0.06 0.4].
49

6.8 Field Demonstration - I-35, Ardmore, OK (July 01 - 31, 2009)

The performance of the IACA was observed during the overlay of asphalt pavement on Interstate 

I-35 near Ardmore, OK (Figures 6.13- 6.14). Remediation of the existing pavement involved milling 

and removal of 6.0 miles of existing pavement and then compacting a 2.0 inch lift of 19mm asphalt 

mix followed by a second lift of 1.75 inches using the same mix. Compaction was achieved using an 

Ingersoll Rand DD90 dual drum vibratory compactor. Finish rolling was done using Ingersoll Rand 

DD90 roller operating in static mode. 

Figure 6. 13 Site location on I-35 near Ardmore, OK (July 01, 2009)

Figure 6. 14 Site location on I-35near Ardmore, OK (July 07, 2009)
50

6.8.1 Discussion of Results

Table 6. 13 Validation results from I-35 near Ardmore, OK

Layer 

Thickness Core Location

Core Density*

(Core)

Estimated

Density* (IACA)

Estimation Error*

(IACA-Core)

2.5"

Calcore1 92.50 93.00 -0.50

Calcore2 92.70 92.90 -0.20

CalCore3 92.80 91.60 1.20

W4 94.10 90.70 3.40

W5 94.60 92.80 1.80

1.75"

Calcore1 94.00 93.50 0.50

Calcore2 93.60 93.90 -0.30

CalCore3 93.80 94.00 -0.20

T4 94.30 92.60 1.70

T5 93.10 90.70 2.40

* % MTD

The project team installed the IACA on the contractor owned Ingersoll Rand DD90 vibratory 

compactor and trained the operator on the operation of the IACA and its installation/removal each 

day after its use. The calibration and validation of the IACA for each of the asphalt layers was 

accomplished by the crew. The IACA device was provided to the contractor for a period of two 

months (duration of the project). During this time, the operator diligently used the IACA each day 

during the compaction of the pavement. However, the roller operator did not mark any validation 

cores on the completed pavement. Therefore, the validation of the IACA was accomplished only at 

the locations marked by the research team at the beginning of the project (Table 6.13).

6.9 Field Demonstration - US-69, Muskogee, OK (April 2009)

The performance of the IACA could not be conclusively determined during the field trials at US69 near Muskogee, OK. At this site, a 1.5 inch asphalt overlay was carried out using a 12.5 mm 

asphalt mix on a concrete subgrade that had cracked in several locations. In this project, the research 

team was not allowed to extract any roadway cores. The calibration and validation of the IACA was 

performed using measurements taken by a Nuclear Density Gauge (NDG). NDG readings were taken 

at three locations for calibrating the IACA and the IACA estimates were investigated at ten random 

locations by comparing it with the NDG recorded density readings at these locations. At this site, a 

mean measurement error of 3.0% with a standard deviation of 1.7 was recorded. 
51

7.0 Conclusions and Scope of Future Work

The development of a commercial prototype of the Intelligent Asphalt Compaction Analyzer was 

addressed in this study. Automation procedures were first developed (Phase 0) to simplify the 

calibration of the IACA during the construction of asphalt pavements. A rugged electronic 

computational platform was selected and the IACA application was ported to this computer. A sensor 

suite and the associated wiring harness were also developed. Installation procedures for retrofitting 

vibratory compactors with the IACA were demonstrated on a variety of vibratory asphalt compactors. 

The accuracy and repeatability of the IACA in estimating the density was demonstrated during the 

construction of asphalt pavements at five different sites in the Phase 1 of the project. Independent 

testing of the IACA was carried out by independent contractors at nine different sites in Phase II of 

the project. The main findings of the study carried out under the assistance agreement with FHWA 

Highways for LIFE Technology Partnerships Program are stated below.

• Low cost rugged sensors and computational platform were selected that resulted in cost 

savings of over 80% compared to the research prototype that was used prior to this 

study.

• The commercial prototype that was developed was shown to be rugged, easy to use, and 

of accuracy necessary for its use as a contractor’s quality control tool in the compaction 

of asphalt pavements.

• The IACA prototype was shown to be a drop in replacement for retrofitting existing 

vibratory compactors.

• The software utilities that were developed for the analysis can be used on the IACA 

platform in 'off line' mode or on any desktop computer operating on Windows XP or 

Windows 7 Operating Systems. The transition between 'on line' density measurement 

mode and 'off line' analysis mode is intuitive and seamless.

• Several utilities for analyzing the quality of the compaction were implemented in the 

IACA software. These utilities directly aid the contractor in obtaining uniformity in 

compaction and increasing the productivity. Specifically, the built in features allow the 

operator to: check coverage and rolling patterns; investigate pass-by-pass variations in 

density; monitor the temperature profile of surface of the asphalt mat; and generate asbuilt maps and statistical estimates of the overall compaction. 

• The IACA technology requires the entire project crew has to take on the responsibility for 

the quality of the pavement. The roller operator has to take care not to over/under 

compact the pavement. The operator also has to make sure that the pavement receives 

adequate coverage through vibratory passes of the roller. The project manager has to 

ensure that the overall quality of the roadway is not compromised and make the 

necessary adjustments based on the site characteristics and the day to day production 

from the plant. 

• The IACA estimated density reports are a good indicator of the quality of the asphalt 

pavement. 

• A migration path for the evolution of the technology and for integration of additional 

functionality is in place and has already been demonstrated to the sponsors.
52

7.1 Partnership for Success

The results achieved in this project demonstrate the importance of teamwork and successful 

collaborations in the developing innovative solutions to mitigate long standing quality issues during 

the construction of asphalt pavements. The project team benefited from the close technical 

cooperation with the Federal Highway Administration and its Field Engineers. Having access to the 

technical expertise at Volvo Construction Equipment (VCE) Company enabled the team to put 

together reliable, production ready solutions in a cost effective manner. Further, having access to the 

dealer network has enabled the team to identify a wider cross section of likely users for testing the 

IACA. Having ready access to construction sites (Haskell Lemon Construction Company) and material 

testing facilities (EST Inc) has enabled the rigorous testing of the IACA and contributed to the 

development of a 'fail safe' and rugged IACA prototype. 

The successful partnership between VCE, Haskell Lemon Construction Company, and the 

University of Oklahoma (OU) has resulted in extending the IACA technology to estimate the stiffness 

(dynamic modulus) of pavement layers during their construction. This technology is currently being 

tested during the construction of full depth pavements and asphalt overlays on asphalt/concrete 

pavements. OU has licensed the IACA technology to VCE and the Stiffness measurements will be 

available to the users in 2013. Research is currently underway to extend the IACA technology for use 

during the compaction of soil subgrades. 

7.2 Opportunities for Wide-Scale Implementation and Challenges

The results of this study and the ongoing demonstration on Intelligent Compaction(IC) 

technology21 clearly demonstrate that the IC technology is mature and can address several of the 

quality issues faced by the contractor during the construction of asphalt pavements. Several of these 

quality issues can be traced back to the lack of adequate tools for quality control during the 

construction process. The IACA technology can not only rectify this problem, but can also provide 

complete documentation the quality of the constructed pavement. This will have the immediate 

effect of increasing the longevity of the pavements and reducing the cost of their maintenance and 

upkeep. While the competing technologies require the purchase of a new vibratory compactor 

equipped with IC technology, the IACA can be retrofitted on any vibratory compactor. The IACA is 

currently in the final stages of production planning and Volvo Construction Equipment is planning on 

market introduction of the IACA technology in early 2012. The initial IACA offering will be in the form 

of optional Intelligent Compaction Technology on new Volvo compactors. However, it is anticipated 

that this technology will be made available to all users in the form of retrofit technology for use on 

existing compactors. The introduction of the technology has been hampered by weak economic 

conditions prevailing across the world since 2009.

While the market has been ready for the IC technology for several years, there are several 

challenges that need to be overcome before the technology can be successfully integrated into the 

workspace. The primary challenges that the research team encountered during the course of this 

study are listed below:

• Lack of clear acceptance specifications. Current acceptance specifications require the 

extraction of roadway cores as a part of the acceptance testing. The pay factors are also 

calculated based on the density measured from the extracted cores. Thus, the asphalt
53

contractor is still bound by existing specifications and does not perceive the need for IC 

based quality testing.

• Lack of incentives for the use of IC technology. While the use of IACA in determining the 

uniformity of compaction and in the prevention of over/under compaction of asphalt 

mats has been demonstrated, the cost savings and the increase in productivity that can 

be obtained have not been adequately recognized by the user community. The primary 

reason is that the roller operators and the supervisors are entirely focused on the 

traditional methods of construction and there is a noticeable averseness to risks 

associated with newer technologies. This can be a significant impediment to the 

integration of IC technologies into construction practices unless the contractors are 

incentivized to use of IC technologies. Need for outreach and education. The research 

team routinely encountered reluctance on part of the user community due to the 

perception that (a) new technology is risky; (b) new technologies require exceptional 

literacy and computer skills and in the long term cause job attritions. While the IC 

demonstrations21 address this aspect to some extent, there is still a need for significant 

outreach and training form the construction crew all the way up to state and federal 

agencies that oversee the construction of this critical infrastructure. 

• Development of incentives for the use of new technology is a process that has been 

successful in the past. IACA at this time has been demonstrated to be an acceptable 

contractor’s quality control tool which both the contractor and agency can benefit from. 
54

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57

Appendix
58

Appendix A1
59

Table A1.1 Location and site details for the IACA validation

Project ID Contractor / Performance 

Period Description Type

Lift

Mix

Type Thickness

US-69

Glover Construction

Muskogee, OK

April 2009

Extent 0.8 mile

# Lanes 2 Resurfacing 1st 1.5 inches 12.5mm

# Lifts 1

US-222

Reading, PA

Kinsley Construction

May 26 -29, 2009

Extent 7.25 miles

# Lanes 2 Overlay on concrete 1st 2 inches 12.5 mm

# Lifts 1

I-35

Norman, OK

Haskell Lemon Const. Co.

June 2009 – April 2010

Extent 1200 feet

Full Depth

AC Base 4 inches 19 mm PG 64-22

# Lanes 2 2nd 4 inches 19 mm PG 64-22

# Lifts 3 3rd 3 inches 19 mm PG 78-28

I-40

Hinton, OK

Haskell Lemon Const. Co.

June – July 2009

Extent 6 miles

Mill & Overlay

1st 3 inches 19 mm PG-76-28

# Lanes 1 (driving lane) 2nd 2 inches 12.5 mm PG-76-28

# Lifts 2

I-86

Hornell, NY

AC Blades and Sons.

June - July 2009

Extent 3.6 miles

Mill & Overlay

1 2 inches 19mm PG-64-22

# Lanes 1

# Lifts 1

I-35

Ardmore, OK

Silver Star Construction

July – August 2009

Extent 6 miles

Mill & Overlay

1st 2 inches 12.5 mm PG 78-28

# Lanes 2

# Lifts 2

HWY 390

Groveland, NY

AC Blades and Sons.

July – August 2009

Extent 3.6 miles

Mill & Overlay

1 3 inches 25mm PG-64-22

# Lanes 2 2 2 inches 19 mm PG 64-22

# Lifts 2

Rte. 65

Carollton, MO

APAC Const.

August 24, 2009

Extent

Mill & Overlay 1st 1.75 inches (on top of 1 

inch leveling course) # Lanes 2 12.5mm

# Lifts 1

Rte. 60

Republic, MO

Journagan Construction

September –October, 2009

Extent

Full Depth

AC Base 3.25 inches 25 mm

# Lanes 2 2 3.25 inches 25 mm

# Lifts 4 3 3.00 inches 19 mm

4 2.00 inches 12.5 mm
60

Table A1. 2 Matrix of field trials with the details of the construction 

Project 

ID Location Description Type

Lift

Mix # 

Cores

Density

Misc.

Type Thickness Mean

density

Std.

dev

Mean

estimate

Std.

dev

Min 

Error

At 

Core

Max 

Error

At 

Core

Mean 

(error)

Stdev 

(error)

I-35 Norman, 

OK

Extent 1200 

feet

Full Depth

AC base 4 inches S3 64-22 5 93.06 0.32 93.08 0.22 0 93.2 0.3 92.5 0.02 0.19

# Lanes 2 2nd 4 inches S3 64-22 6 92 0.73 91.4 0.68 0.2 91.8 1.8 92.3 -0.58 0.82 IR DD110

# Lifts 3 3rd 3 inches S3 78-28 9 92.8 0.37 92.1 0.88 0 92.8 1.9 92.7 -0.69 0.8

I-40 Hinton, 

OK

Extent 6 miles

Mill & 

Overlay

1st 3 inches S3 PG76-28 6 94.55 0.67 94.35 0.46 0.3 94.5 -0.9 95.5 -0.2 0.52

IR 

DD130HF # Lanes

1 

(driving 

lane)

2nd 2 inches S4 PG76-28

# Lifts 2 

I-86 Hornell, 

NY

Extent 3.6 

miles Mill & 

Overlay

1 2 inches 19mm 

PG-64-22 8 94.63 0.6 94.28 0.64 0.05 94.45 -1.35 95.25 -0.34 0.67

Volvo

# Lanes 1 DD118HFA

# Lifts 1 

I-35 Ardmore, 

OK

Extent > 6 

miles Mill & 

Overlay

1st 2 inches 12.5mm 10 93.55 0.73 92.9 1.19 0.1 92.8 1.7 94.3 -1.05 1.04

IR DD110 # Lanes 2 

# Lifts 2 

US-69 Muskogee, 

OK

Extent 0.8 

mile

Resurfacing

1st 1.5 inches 12.5mm 3 93 0.5 93.7 0.7 -0.4 93.5 2 92.5 0.76 1.2

IR DD110 # Lanes 1 

# Lines 1 

Lancaster 

Turnpike

US-222

Reading, 

PA

Extent 2.4 

miles

Mill & 

Overlay

1st 2 inches 12.5 mm 0 93.06* 1.01 96.04 0.77 0 94.5 4.9 91.7 3.0 1.7

IR DD110 # 

Lanes 2 

# Lifts 2
61

Table A1. 3 Matrix of field trials with the details of the construction (contd). 

Project 

ID Location Description Type

Lift

Mix # 

Cores

Density

Misc.

Type Thickness Mean

density

Std.

dev

Mean

estimate

Std.

dev

Min 

Error

At 

Core

Max 

Error

At 

Core

Mean 

(error)

Stdev 

(error)

HWY390 Groveland,

NY

Extent 3.6 

miles Mill & 

Overlay

1st 3 inches 25 mm

PG 64-22 7 94.48 0.45 94.6 0.41 0.05 94.35 0.3 94.0 0.09 0.15

Volvo

# Lanes 2 2nd 4 inches S3 64-22 4 94.29 0.64 94.5 0.67 0.05 93.55 0.75 94.45 0.21 0.50 DD118HFA

# Lifts 2 

Rte. 65 Carrollton,

MO

Extent 3 miles

Mill & 

Overlay

1st

1.75 

inches 

(on top of 

1 inch 

leveling 

course)

12.5mm 

PG-76-28 9 93.73 1.67 94.24 0.88 0.1 93.9 1.5 93.8 0.51 0.51

IR 

DD130HF

# Lanes 2 

# Lifts 1 
62

Appendix A2
63

A2.1 Protocol for short run field tests

The purpose of the short run tests is to (a) determine the ease and effectiveness of the 

installation procedure, (b) Clarity of the operator training and test procedures, (c) ease and accuracy 

of the calibration and validation procedures. In addition these, the following performance issues will 

also be studied: (d) accuracy and verifiability of the density readings provided by the IACA, and (e) 

the usefulness of the mat surface temperature in determining the time for cessation of compaction, 

i.e. the time remaining before the mat cools down to a temperature at which further compaction is 

not possible. The protocol for the field tests is described below.

i) The evaluation of the IACA during the construction of short stretches of an asphalt 

pavement will be undertaken by the participant with limited support from the research 

team. Prior to the start of the evaluation, the participant will identify the site for 

conducting the tests and communicate the construction schedule to the research team. 

A master schedule will be developed and communicated to all the participants by May 

08, 2009. The tests can be conducted on a full-depth asphalt pavement or an overlay. 

ii) A week prior to the scheduled test, the research team will conduct an on the site training 

for the crew during which an overview of the IACA technology and the procedure to 

calibrate and use the device will be presented. The research team will also assist the 

participant with the installation of the device on the roller.

iii) On the day of the test, the IACA is first calibrated. This is done by first selecting a control 

strip of approximately 100 feet (33m) long. A 30 feet (10m) calibration section is marked 

off in middle of this control strip. The start and the end of the calibration section is 

marked by GPS coordinates at the center line of the pavement. The GPS sensor is used to 

trigger the collection of the vibration data as the roller compacts this calibration section. 

iv) Test locations at the center of the lane, five feet, fifteen feet and twenty five feet from 

the beginning of the test section. 

v) After each roller pass, a non-nuclear density gauge is used to measure the density at 

each of the test locations marked in step (iv). 

vi) The compaction process is stopped when no appreciable increase in the density is seen 

after the roller pass. After the final pass of the roller, five core locations are marked as 

shown in Figure 2.4. The GPS locations of the cores, as well as the density at the core and 

in the immediate vicinity of the core are recorded.

vii) The cores marked in the previous step are extracted and their density is measured in 

accordance with the AASHTO T-166 method.

viii) This will allow the research team to investigate the effect of the underlying layers of 

asphalt pavement of the compaction achieved in the overlaid layers of the pavement.
64

A2.2 Protocol for extended run field tests

The long term testing of the IACA was designed to provide information on the consistency of the 

measured values over the entire construction. The following protocol was used for the long term 

testing of the IACA.

a. Selection of test site

The long term performance of the IACA is studied during the construction of a multiple 

layers of an asphalt pavement. The construction site that is selected shall have at least 2 

layers of asphalt concrete with each layer being at least 3 inches (76.2mm) thick. The 

pavement shall be at least 2 miles (3.2 kilometers) long and subsequent layers of the 

pavement must be constructed on the same stretch. A surface course that is at least two 

inches (50.8mm) thick shall be constructed on top of these two layers. The thickness 

recommendations are non-binding and are suggested to facilitate the easy extraction of 

roadway cores and their density measurement using the AASHTO T-166 procedure. Further 

since 4-5 cores are routinely extracted per lane mile, the extraction of 10-12 random cores 

for the validation of the IACA does not constitute undue requirement on the contractor.

The performance of the IACA can be verified on thinner lifts of asphalt if necessary. 

However, if lift thickness prevents the extraction of cores, then the contractor must ensure 

that a calibrated Nuclear Density Gauge (NDG) is used to obtain 10-12 density readings per 

mile in lieu of the cores.

b. Installation and calibration

The IACA has to be installed on the compactor and calibrated prior to its use. The 

installation will be carried out by the research team and the roller operator and the project 

manager will be trained on the use of the device.

c. Operation, data collection, and analysis

The IACA will be used continuously during the production run. After each layer is 

compacted, 3 cores shall be extracted at random from each sub-lot of the asphalt mix 

(typically 10-12 cores are extracted for every 1000 tons of asphalt mix that is laid) and the 

GPS locations of the cores shall be marked. The vibration data and the density reading of the 

IACA shall be collected and stored for subsequent analysis. This data is stored on the IACA 

and shall be downloaded to a laptop/portable memory storage using the download utility 

that is provided with the IACA. 

After the placement of each lot of the asphalt mix (approximately 1 mile long), the asbuilt map of the pavement shall be generated and region of high and low compaction shall 

be identified. Three cores shall be extracted where the density estimates are the highest and 

a further three cores shall be extracted where low density readings are observed. The GPS 

readings at these core locations and the measured density shall be recorded for analysis.

A second identical stretch of pavement shall be constructed without the IACA 

information being available to the roller operator. 12 cores shall be extracted at random for 

measuring the density as per the standard quality control practice. In addition, 3 cores 

representing the highest density achieved and 3 cores representing the lowest density 

achieved shall be extracted. The GPS readings at these core locations shall be recorded.

d. Productivity

During the construction of each layer of the pavement, the project manager shall keep 

track of the total time for the compaction of the layer with and without the use of the IACA. 

Any delays due to plant/production issues shall be accounted for while determining the 

productivity of the crew. The productivity of the crew when using the IACA shall be 

determined and compared to the productivity when the IACA is not in use.
65

The manpower requirements for the project and the necessity for spot check shall also 

be monitored and reported.

e. Project Completion

After the project is complete, the research team will uninstall the IACA from the roller. 

The project manager and the roller operator will have to provide feedback on the usefulness 

of the IACA measured values and the analyzed information. Any issues that are identified 

with respect to the site preparation or calibration of the IACA shall also be reported.
66

Appendix A3