EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  a

Exploratory Advanced 

Research Program 

Research Associates 

Program 2021

 
b  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

bNucleation of ettringite mineral in the interfacial transition zone.

Notice

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

of Transportation in the interest of information exchange. The U.S. Government 

assumes no liability for the use of the information contained in this document. 

This report does not constitute a standard, specification, or regulation.

The U.S. Government does not endorse products or manufacturers. Trademarks 

or manufacturers’ names appear in this document only because they are 

considered essential to the objective of the document.

All photos: Source: FHWA, unless otherwise noted.

Quality Assurance Statement

The Federal Highway Administration (FHWA) provides high-quality information 

to serve Government, industry, and the public in a manner that promotes public 

understanding. Standards and policies are used to ensure and maximize the 

quality, objectivity, utility, and integrity of its information. FHWA periodically 

reviews quality issues and adjusts its programs and processes to ensure 

continuous quality improvement.

Cover photos

Left: A simulation input illustrates former EAR Program research associate Nopadon 

Kronprasert’s work on alternative intersection and interchange designs.

Right: Image showing the nucleation of ettringite mineral in the interfacial transition 

zone, part of a research objective to develop inorganic curing compounds for 

addressing the shortcomings of current organic membrane-forming curing compounds 

in pavement construction.
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  1

Contents

The Research Associateship Program 3

Breakthrough Concepts in Materials Science 4

 Development and Evaluation of Innovative Structural Systems 

with UHPC and Resilient Connections: From Analyses and 

Experiments to Design Guidelines 4

Integrating Lifecycle Thinking into Current Pavement Practices 5

Novel Applications of UHPC in Bridge Structures 7

Ultra-High Performance Concrete: A Pathway to Resilient 

Infrastructure Systems through Material Characterization 

 and Structural Design 8

Shear Performance of Full-Scale Pretensioned UHPC Bridge Girders 9

Modeling of Pavement Response Under Traffic Speed 

 Deflection Devices for Pavement Management Application 10

Providing a Performance-Based Asphalt Mixture Design 

Framework through Fatigue and Thermal Cracking 

Index Parameters 12

Developing Frameworks of Performance-Based Asphalt Mix Design 14

Tensile Response of Ultra-High Performance Concrete: 

Validation of Characterization Methods 15

Performance of Geosynthetic-Reinforced Soils at the 

Service Limit State 16

Developing New Vehicle–Tire and Contact Friction Models 17

Use of Inorganic Coatings as Curing Compounds 19

Comprehension and Development of Nano-Additives to Judicially 

Improve the Interfacial Region in Concrete and Asphalt 20

Connected Highway and Vehicle System Concepts 21

Design and Implementation of an MPC-Based Framework 

 for Vehicle Platooning 21

Toward Safer and Efficient Implementation of Automated Driving 

 Systems: Performance Measurements and Evaluation 22

Implement Hardware-in-the-loop in More Complex and 

Realistic Way with Artificial Intelligence 23

Initiation of an Effective Highway Performance Management 

 Strategy by Integrating Multiple Transportation Data Sets 23

 Developing Automated Driving Systems and Predicting 

 Highway Wide Impacts 24

Cost-Benefit Analysis of Connected and Automated 

Vehicle Operations 25

Knowledge-Based Signal Timing and Optimization Expert 

 System for Advanced Urban Signal Control 26

Development of an Eco-Cooperative Adaptive Cruise 

 Control to Optimize Vehicle Performance for 

 Environment and Mobility Benefits 27

Developing and Implementing Dynamic Junction Control 

 System in the United States 28
2  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

Contents (continued)

Human Behavior and Travel Choices 29

Using Naturalistic Driving Study Data to Analyze Behavior 

 at Signalized Intersections 29

Driving the Highway Safety Manual to Perform Better: 

 A Fourfold Research 30

 Effectiveness of High-Visibility Crosswalks in Improving 

 Pedestrian Safety 31

Data-Driven Space-Time Dependent Traffic Condition 

 Estimation and Management 32

Operational and Safety Analyses of Alternative I

ntersection/Interchange Designs 34

Integrating Driving Simulation and Other Behavioral Data: 

Assessment of Driver Behavior and Performance 36

Operational and Safety Analyses of Alternative 

 Intersection/Interchange Designs 37

Utilizing Naturalistic Driving Data and Highway Safety 

 Information System to Advance Highway Crash Data 

Modeling Concepts and Methods 39

Technology for Assessing Performance 41

Artificial Intelligence-Aided Bridge Condition Assessment 

 System Using Deep Learning Approaches 41

Integration of Machine Learning into Long Term Pavement 

 Performance Prediction Models 41

Developing Probabilistic Bridge Deterioration Models Based 

on Nondestructive Evaluation of Concrete Bridge Decks 

 Using Multiple NDE Technologie 42

Numerical and experimental study of air-coupled 

 impact-echo and ultrasonic surface waves for in situ 

 condition monitoring of concrete structures 43

Networks for Interpretation of Nondestructive 

 Evaluation of Bridges 44

Air-Coupled Acoustic and Ultrasonic Arrays for 

 Concrete Nondestructive Test Methods 45

Prediction of Pavement Temperature Profiles Using 

 Surface Temperatures: An Analytical Approach 

 With Model Validation Based on Long-Term 

 Pavement Performance Data 46
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  3

Since 1954, the National Research Council (NRC) has conducted the Research Associateship 

Program (RAP) in cooperation with sponsoring Federal laboratories and other approved 

participating research organizations. RAP provides highly skilled and exceedingly promising 

postdoctoral and senior scientists and engineers with opportunities to research problems that are 

compatible with the interests of sponsoring laboratories. RAP offers recent doctoral graduates 

opportunities for concentrated research with selected members of permanent, professional, 

laboratory staff and allows them to contribute to the overall efforts of the laboratories.

The Federal Highway Administration (FHWA) has participated in RAP since 1992. To supplement the 

expertise of permanent staff, FHWA’s Turner–Fairbank Highway Research Center (TFHRC), through its 

Exploratory Advanced Research (EAR) Program, invites researchers with appropriate backgrounds to 

investigate specific problems on a short-term basis across a wide range of topics and disciplines.

NRC provides a process for selecting candidates on a competitive merit basis and, subsequently, for 

administration of the resident fellows during their tenures at FHWA. The process begins with a 

prospective FHWA adviser developing a proposed research opportunity. The adviser then coordinates 

with FHWA leadership to approve the opportunity and forward the proposed research to NRC. All 

research opportunities require an abstract that relates to exploratory advanced research and is of 

specific relevance to the FHWA research program. One of the significant benefits of this process is that 

it encourages interaction between government researchers and new researchers who are using 

cutting-edge approaches and research tools in their work.

RAP provides opportunities for FHWA’s EAR Program to advance research methods used at TFHRC. 

Over the years, associates have researched topics as diverse as cost-benefit analysis of connected 

and automated vehicle operations, nano-additives for concrete and asphalt, alternative intersection 

and interchange design, and modeling to predict collisions based on driver behavior and 

environmental conditions.

The following pages contain summary descriptions of some of the research projects that the resident 

fellows have been involved in during their respective tenures at FHWA.

The EAR Program sponsors longer term, higher risk research, leveraging cutting-edge science 

and engineering as well as top-notch expertise to create breakthrough solutions to highway 

transportation-related issues.

EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  3

The Research Associateship Program

 
4  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

Breakthrough Concepts in Materials Science Breakthrough Concepts in Materials Science

PROJECT: Development and Evaluation of Innovative Structural Systems with UHPC and Resilient Connections: From Analyses and 

Experiments to Design Guidelines

ASSOCIATE: Alireza Mohebbi

SCHOOL: University of Nevada, Reno 

PERIOD: April 2018–September 2021

OBJECTIVE: To investigate the time-dependent properties of ultra-high performance concrete (UHPC).

ADVISER: Ben Graybeal, FHWA Office of Infrastructure Research and Development

SUMMARY: Alireza Mohebbi investigated the time-dependent 

properties of UHPC and conducted small-scale and large-scale 

testing in the FHWA-TFHRC Concrete and Structures laboratories. 

He developed new predictive models for creep coefficient and 

shrinkage strain of UHPC-class materials. Mohebbi also 

investigated and developed a prestress loss model for 

pretensioned UHPC girder. The predictive models were included 

in the UHPC structural design guide draft submitted to the 

AASHTO-T10 Concrete Design Technical Committee of the 

Subcommittee on Bridges and Structures for adoption in 

AASHTO LRFD Bridge Design Specifications.

RESOURCES: Several publications and papers resulted from this 

RAP research. They are outlined below.

Mohebbi, A., Z. Haber, and B. Graybeal. 2019. “Evaluation of 

AASHTO Provisions for Creep and Shrinkage of Prestressed 

UHPC Girders.” Presented at the 2nd International Interactive 

Symposium on UHPC. Albany, NY. 

Mohebbi, A., R. El-Helou, and B. Graybeal. 2019. “End Zone Design 

and Behavior of Prestressed UHPC Girders.” Presented at the 

International Accelerated Bridge Construction Conference. 

Miami, FL: Accelerated Bridge Construction University 

Transportation Center.
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  5

Breakthrough Concepts in Materials Science

PROJECT: Integrating Lifecycle Thinking into Current Pavement Practices

ASSOCIATE: Milena Rangelov

SCHOOL: Washington State University

PERIOD: January 2019–June 2021

OBJECTIVE: To develop lifecycle assessment (LCA) for pavements and pavement materials in a manner that supports datadriven decision making and lifecycle thinking. 

ADVISER: Nadarajah Sivaneswaran, FHWA Office of Infrastructure Research and Development

SUMMARY: Milena Rangelov’s research included the development 

and advancement of LCA for pavements and pavement materials 

in a manner that supports data-driven decision making and 

lifecycle thinking. Specific areas of work and clarification of 

projects and contributions are described as follows:

• Integration of LCA into planning and project delivery for 

pavements: This project included collaborative work with 

stakeholders to outline the current pavement design, 

planning process, and decision making and evaluate LCA fit 

in a way that facilitates the reduction of environmental 

impacts. Later phases of the project also included the 

integration with asset management. 

• Use of environmental product declarations to support green 

public procurement (GPP): This study involved a national scan 

of current environmental product declarations and product 

category rules for pavement construction materials and 

investigated their use to support current and future efforts in 

GPP. The results of this study indicate the need for harmonization 

and standardization to provide a solid framework for achieving 

environmental impact reductions. 

• Environmental impacts of the use of secondary materials in 

pavements: Even though the use of secondary and recycled 

materials in pavements is typically considered to be a 

sustainable practice, quantification of environmental impacts is 

necessary to support claims about sustainability. This study 

investigated methodological frameworks and approaches for 

secondary-materials allocation and their benefits and tradeoffs. 

• LCA of asphalt pavements: Two studies done under this 

scope include the study of the use of recycled polyethylene 

in asphalt pavements and the use of ground tire rubber 

(GTR). The first study was focused on the synergies 

between engineering and environmental performance, 

aiming to document what level of performance is needed 

to achieve environmental benefits with recycled 

polyethylene. The second study was performed for the 

Puerto Rico case because the island grapples with the 

problem of excess waste tires. Two levels of analysis, at 

the pavement and system level, showed what drives the 

environmental performance of GTR-modified mixes and 

how much pavements can help alleviate the waste-tire 

problem for Puerto Rico. 

• LCAs of concrete pavements and structures: The first study 

from this domain includes the LCA of UHPC bridge deck 

overlay in comparison to conventional solutions such as 

portland cement concrete and latex-modified concrete from 

a lifecycle perspective. The second study follows the efforts 

of the Mobile Concrete Technology Center. By performing 

LCA for mixture designs collected over the last decade 

across the United States, this study sheds light on 

opportunities for agencies to reduce the environmental 
6  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

Breakthrough Concepts in Materials Science

footprint of concrete pavements.

RESOURCES: Several publications and papers resulted from this 

RAP research. They are outlined below.

Rangelov, M., H. Dylla, A. Mukherjee, and N. Sivaneswaran. 2020. “Use of 

Environmental Product Declarations (EPDs) of Pavement Materials in 

the United States of America (U.S.A.) to Ensure Environmental Impact 

Reductions.” Journal of Cleaner Production 283: 24619.

Rangelov, M., H. Dylla, N. Sivaneswaran, and J. Davis. 2020. “Integration of 

Life Cycle Assessment into Planning And Project Delivery for 

Pavements in the USA.” The International Journal of Life Cycle 

Assessment 25: 1605–1619.

Rangelov, M., S. Nassiri, and K. Englund. 2020. “Life Cycle Assessment of 

Pervious Concrete Pavements Reinforced by Recycled Carbon Fiber 

Composite Elements, Pavement, Roadway, and Bridge Life Cycle 

Assessment.” Presented at the International Symposium on Pavement, 

Roadway, and Bridge Life Cycle Assessment. Sacramento, CA: 

University of California Pavement Research Center and the National 

Center for Sustainable Transportation.

Rangelov, M., R. Spragg, Z. Haber, and H. Dylla. 2020. “Life Cycle 

Assessment of Ultra-High Performance Concrete Bridge Deck 

Overlays, Pavement, Roadway, and Bridge Life Cycle Assessment.” 

Presented at the International Symposium on Pavement, Roadway, 

and Bridge Life  Cycle Assessment. Sacramento, CA: University of 

California Pavement Research Center and the National Center for 

Sustainable Transportation.

Rangelov, M., H. Dylla, and N. Sivaneswaran. 2020. “Using environmental 

product declarations to support pavement green public procurement, 

Pavement, Roadway, and Bridge Life Cycle Assessment.” Presented at 

the International Symposium on Pavement. Roadway, and Bridge Life 

Cycle Assessment. Sacramento, CA: University of California Pavement 

Research Center and the National Center for Sustainable Transportation.
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  7

Breakthrough Concepts in Materials Science

PROJECT: Novel Applications of UHPC in Bridge Structures

ASSOCIATE: Arash E. Zaghi

SCHOOL: University of Nevada, Reno

PERIOD: May 2019–May 2020

OBJECTIVE: Develop novel applications of UHPC in bridge structures. 

ADVISER: Benjamin Graybeal, FHWA Office of Infrastructure Research and Development

SUMMARY: Arash Zaghi, an associate professor at the University 

of Connecticut at the time, refined and optimized the current 

tensile testing method for UHPC material. He developed a finite 

element simulation methodology for structural elements made 

of UHPC material. Zaghi also advanced a novel repair method 

for distortion-induced fatigue in steel bridges and performed 

large-scale experiments to validate the repair concept. In his 

work, Zaghi investigated the applicability of a simplified testing 

method for multimode fracture behavior of UHPC.

RESOURCES: Several publications and papers resulted from this 

RAP research. They are outlined below.

Graybeal, B., E. Brühwiler, B.-S. Kim, F. Toutlemonde, Y. L. Voo, A. Zaghi. 

2020. “International Perspective on UHPC In Bridge Engineering.” 

Journal of Bridge Engineering 25, no. 11.

McMullen, K., and A.E. Zaghi. 2020. “Accelerated Repair of Corroded Steel 

Bridge Girders with Ultra-High Performance Concrete.” Presented at 

99th Annual Meeting of the Transportation Research Board. 

Washington, DC: Transportation Research Board.
8  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

Breakthrough Concepts in Materials Science

PROJECT: Ultra-High Performance Concrete: A Pathway to Resilient Infrastructure Systems through Material Characterization and 

Structural Design

ASSOCIATE: Rafic El-Helou

SCHOOL: Virginia Polytechnic Institute and State University

PERIOD: December 2016–October 2019

OBJECTIVE: To develop material testing standards, construction practices, and design methodologies for UHPC, and to advance 

innovative structural applications that fully use UHPC’s durability and performance characteristics.

ADVISER: Benjamin Graybeal, FHWA Office of Infrastructure Research and Development 

SUMMARY: UHPC has many advantages over conventional 

concrete, including greater strength, ductility, and resistance to 

corrosion, chemicals, and severe environmental conditions. Rafic 

El-Helou’s research aimed to standardize material testing 

protocols, establish design models, and explore the best 

construction practices for UHPC. The nature of UHPC requires 

detailed standards to assess material behaviors like first cracking, 

postcracking behavior in tension, compression, and ductility. 

This standardization minimizes variations in material data and 

foster the development of characteristic design models for 

UHPC. To pursue those goals, El-Helou built a national database 

of UHPC material testing procedures and experimental data, 

performing material tests that explore UHPC characteristics, 

assessing the applicability of current testing methods to UHPC, 

and developing design guides and codes that include material 

models and structural design methods for UHPC. Prototyping of 

pretensioned bridge girders built with UHPC was also part of 

El-Helou’s project. This effort was intended to validate that 

increasing the span range of concrete bridges can be achieved 

with UHPC. 

IMPACT: El-Helou took part in FHWA efforts to develop and 

deliver a draft on UHPC for the American Association of State 

Highway and Transportation Officials (AASHTO) Load and 

Resistance Factor Design (LRFD) Bridge Design and Construction 

Guide Specifications. This work will support AASHTO’s interest 

in producing a national UHPC standard through its Committee 

on Bridges and Structures, Subcommittee T-10. El-Helou’s 

research on material testing standards, design methodologies, 

and construction practices will encourage simplicity, speed, and 

creativity in designing and implementing UHPC. His investigation 

also provides suggestions on optimal use of UHPC in innovative 

highway applications.

RESOURCES: Several publications and papers resulted from this 

RAP research. They are outlined below. 

Haber, Z. B., I. De La Varga, B. Graybeal, B. Nakashoji, and R. El-Helou. 

2018. Properties and Behavior of UHPC-Class Materials. Report No. 

FHWA-HRT-18-036. Washington, DC: Federal Highway Administration. 

Graybeal, B., and R. G. El-Helou. 2018. “AASHTO LRFD design and 

Construction Guide Specification For Ultra-High Performance 

Concrete, FHWA-TFHRC Plan Towards Development and Delivery.” 

Presented at the AASHTO Committee on Bridges and Structures (CBS) 

T-10 Committee Meeting. Burlington, VT: American Association of 

State Highway and Transportation Officials. 

El-Helou, R. G., and B. Graybeal. 2018. “Towards Ultra-High Performance 

Concrete Design Guidance In The United States.” Presented at the 

American Concrete Institute Spring 2018 Convention. Salt Lake City, 

UT: American Concrete Institute. 

El-Helou, R. G., and B. Graybeal, B. 2017. “AASHTO LRFD Design and 

Construction Guide Specification For Ultra-High Performance 

Concrete, Models and Design Concepts: Compression, Tension, Flexure, 

And 300 Ft Pretensioned Girder.” Presented at the Transportation 

Pooled Fund Solicitation TFP-5(366) Kickoff Meeting. Ames, IA: 

Federal Highway Administration. 

Graybeal, B., and R. G. El-Helou. 2017. “AASHTO LRFD Design and 

Construction Guide Specification for Ultra-High Performance Concrete, 

FHWA-TFHRC Plan Towards Development And Delivery.” Presented at 

the AASHTO Subcommittee on Bridges and Structures (SCOBS) T-10 

Committee Meeting, Cleveland, OH: American Association of State 

Highway and Transportation Officials. 

These images illustrate the process for 

developing and evaluating UHPC 

bridge design methods. Source: 

FHWA.
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  9

Breakthrough Concepts in Materials Science

PROJECT: Shear Performance of Full-Scale Pretensioned UHPC Bridge Girders

ASSOCIATE: Gary Greene

SCHOOL: Missouri University of Science and Technology

PERIOD: May 2019–August 2019

OBJECTIVE: To apply engineering research to advance the state-of-the-art in concrete highway bridges.

ADVISER: Benjamin Graybeal, FHWA Office of Infrastructure Research and Development

SUMMARY: Gary Greene, a professor at Trine University at the 

time, led the setup and execution of large-scale structural tests 

on concrete bridge girders within the FHWA Structural Testing 

Laboratory. He employed his extensive experimentalist skills to 

complete a novel testing program that investigated the next 

generation of concrete, UHPC, under unique loading conditions 

for primary structural behaviors.
10  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

Breakthrough Concepts in Materials Science

PROJECT: Modeling of Pavement Response Under Traffic Speed Deflection Devices for Pavement Management Application

ASSOCIATE: Seyyedmahdi Nasimifar

SCHOOL: University of Nevada–Reno

PERIOD: April 2016–January 2019 

OBJECTIVE: To develop robust methods to relate traffic speed deflection device (TSDD) measurements to pavement structural 

responses for assessing pavement structural condition and rate of deterioration. 

ADVISER: Nadarajah Sivaneswaran, FHWA Office of Infrastructure Research and Development

SUMMARY: Seyyedmahdi “Mahdi” Nasimifar developed an 

analytical approach that is designed to advance the incorporation 

of TSDDs, specifically the Rolling Wheel Deflectometer (RWD) 

and the Traffic Speed Deflectometer (TSD), into pavement 

management applications. To help achieve his research objective, 

he used 3D-Move, a software tool developed under an FHWA 

research effort, which models loads as they move across 

pavements and computes the resulting pavement responses. 

Nasimifar’s current project is an outgrowth of his previous work 

with 3D-Move as a member of a team that carried out an FHWAsponsored project evaluating the RWD and TSD through field 

trials at the Minnesota Road Research Facility and analytical 

modeling. Nasimifar used data collected at the field trials and TSD 

data collected on pavement sections in several States that 

participated in an FHWA-led transportation pooled-fund study to 

calibrate his analytical model. With the calibrated model, he 

developed correlations that related critical pavement responses 

such as tensile strains at the bottom of the asphalt layer (fatigue) 

and compressive strains at the top of subgrade (rutting) to TSDD 

measurements and pavement layer properties. He also conducted 

sensitivity analyses to identify the best correlations between 

TSDD measurements and pavement responses. The final step was 

validating the results from the new model against the field 

measurements to illustrate that it can be applied at a system-wide 

level. Nasimifar thoroughly investigated all parameters that could 

affect the analytical model, from the viscoelastic properties of the 

asphalt-concrete layer to moving-load properties and unbound 

pavement layer properties. In addition, he developed a robust and 

practical method to adjust the surface curvature index from TSD 

data to a reference temperature and proposed a method to use 

TSD data to estimate the effective structural number. This can be 

used to determine remaining structural life and rank pavement 

sections for improvements, maintenance, and rehabilitation.

IMPACT: Building upon previous FHWA-sponsored research into 

TSDDs, Nasimifar is working toward better methods for 

evaluating pavement structural condition and the rate at which 

it deteriorates. Studies have shown that incorporating pavement 

structural condition into the decisionmaking process for 

pavement management leads to better-informed decisions and 

more cost-effective pavement rehabilitation and preservation 

strategies. Nasimifar’s effort will enable State highway agencies 

to incorporate pavement structural condition into their pavement 

management systems to predict how traffic and environmental 

loads will affect their pavement networks over time and better 

plan treatment types and timing to optimize investment 

decisions. The Virginia Tech Transportation Institute, the research 

team for a new transportation pooled-fund study, is using a tool 

that incorporates Nasimifar’s research for analyzing the TSD 

data collected as part of the project.

ONGOING RESEARCH: With the development of TSDDs, networklevel assessment of pavement structural condition has become 

practical. The application of structural condition data in pavement 

management systems can increase the robustness of structural 

deterioration models. A comprehensive study on improving the 

pavement deterioration models that include structural condition 

The traffic speed 

deflectometer is a trailer 

truck that measures 

pavement dynamic 

responses while traveling 

at traffic speed. © 2018 

Seyyedmahdi Nasimifar.
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  11

Breakthrough Concepts in Materials Science

is under investigation. The results of this study will enable State 

highway agencies to use enhanced pavement deterioration models 

that will foster more informed treatment selections and timing and 

will maximize the benefits from the investments being made.

RESOURCES: Several publications and papers resulted from this 

RAP research. They are outlined below.

Nasimifar, M., Thyagarajan, S., & Sivaneswaran, N. (2018). Computation of 

pavement vertical surface deflections from traffic speed deflectometer 

data—Evaluation of current methods. Journal of Transportation 

Engineering, Part B: Pavements, 144(1), 04018001.

Nasimifar, M., Thyagarajan, S., & Sivaneswaran, N. (2017). Backcalculation 

of flexible pavement layer moduli from traffic speed deflectometer 

data. Transportation Research Record: Journal of the Transportation 

Research Board, 2641, 66–74.

Nasimifar, M., Thyagarajan, S., & Sivaneswaran, N. (2017). Comparison of 

the methodologies to compute pavement surface deflections from 

traffic speed deflectometer data. Presented at the World Conference 

on Pavement and Asset Management, Milan, Italy.

Nasimifar, M., Thyagarajan, S., Chaudhari, S., & Sivaneswaran, N. (2018). 

Evaluation of temperature correction models for deflection index from 

falling weight deflectometer and traffic speed deflectometer. Presented 

at the 97th Transportation Research Board Annual Meeting, 

Washington, DC.

Nasimifar, M., Thyagarajan, S., & Sivaneswaran, N. (2017). Backcalculation 

of flexible pavement layer moduli from traffic speed deflectometer 

data. Presented at the 96th Transportation Research Board Annual 

Meeting, Washington, DC.

Nasimifar, M. (2016). Using traffic speed deflectometer data to backcalculate pavement layer moduli. Presented at the Falling Weight 

Deflectometer Users Group, San Jose, CA.

Internal pavement response measure 

instrumentation of the Traffic Speed Deflectometer. 

© 2018 Seyyedmahdi Nasimifar.
12  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

Breakthrough Concepts in Materials Science

PROJECT: Providing a Performance-Based Asphalt Mixture Design Framework through Fatigue and Thermal Cracking Index 

Parameters

ASSOCIATE: David Mensching

SCHOOL: University of New Hampshire

PERIOD: May 2015–August 2016

OBJECTIVE: To develop index parameters to relate material and structural parameters, identifying whether a mixture is prone to 

fatigue or thermal cracking. 

ADVISER: Nelson Gibson, FHWA Office of Infrastructure Research and Development

SUMMARY: The premature distress and failure of highways cost 

money in the form of repairs and time in the form of increased 

congestion while repairs are being made. One way to alleviate 

these effects is to improve the science behind pavement design, 

including the proportion of asphalt, additives, and aggregates 

for creating performance-based mixtures. David Mensching’s 

research explored ways to revise, enhance, and expand the index 

parameters for informing the design decisions of highway 

departments and contractors. An index parameter compares a 

specialized value (or index) to a critical threshold for failure of a 

material. In this case, Mensching used index parameters to 

gauge the impact of content, gradation, and air voids on asphalt 

mixtures, with an eye toward impeding thermal and fatigue 

cracking. The project consisted of testing various asphalts in the 

field and developing a database to monitor degradation and 

volumetric changes in pavement over time. The field methods 

included dynamic modulus testing to develop a framework for 

creating Black Space diagrams, a physics tool for evaluating the 

elasticity and stiffness of materials, and direct tension fatigue 

tests using the simplified viscoelastic continuum damage model. 

Mensching used FHWA’s Accelerated Loading Facility at the 

TFHRC and the Asphalt Mixture Performance Tester to monitor 

performance. To develop a materials database that could reflect 

regional differences in pavement materials and predict their 

performance, he collected information from WesTrack in Nevada 

and from departments of transportation. 

This beta-gamma plot compares conventional, short-term oven aging 

(STOA) for asphalt with loose-mix, long-term oven aging (LTOA) and 

extended, high-temperature oven aging (EHTOA). Varying amounts of 

re-refined engine oil bottoms (REOB) are used. Cracking resistance is 

expected to decrease as beta/gamma decreases and gamma increases. 

The plot shows that EHTOA is more extreme than LTOA and that 15 

percent REOB is in a less crack-resistant location than the other mixtures.

From: Mensching, D., A. Andriescu, C. DeCarlo, et al. 2017. “Effect of 

Extended Aging on Asphalt Materials Containing Re-Refined Engine 

Oil Bottoms.” Transportation Research Record 2632, no. 1: 10. copyright 

© 2017 by David Mensching. Reprinted by permission of SAGE 

Publications, Inc.
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  13

Breakthrough Concepts in Materials Science

RESOURCES: Several publications and papers resulted from this 

RAP research. They are outlined below.

Mensching, D. J. (2016). Testing for fatigue cracking in the asphalt mixture 

performance tester, Report No. FHWA-HIF-16-027, Federal Highway 

Administration, Office of Asset Management, Pavement, and 

Construction, Washington, DC.

 Mensching, D. J., Rahbar-Rastegar, R., Underwood, B. S., & Daniel, J. S. 

(2016). Identifying indicators for fatigue cracking in hot mix asphalt 

pavements using viscoelastic continuum damage principles. 

Transportation Research Record: Journal of the Transportation 

Research Board, 2576, DOI: 10.3141/2576-04.

 Jeong, M. M., & Mensching, D. J. (2017). Testing and acceptance procedures 

for as-constructed asphalt mixtures related to thermal fracture. Journal 

of Transportation Engineering: Part B, Pavements, 143(4).

 Mensching, D. J., Andriescu, A., DeCarlo, C., Li, X., & Youtcheff, J. S. (2017). 

Effect of extended aging on asphalt materials containing re-refined 

engine oil bottoms. Transportation Research Record: Journal of the 

Transportation Research Board, 2632, DOI: 10.3141/2632-07.

 Li, X., Mensching, D. J., & Gibson, N. H. (2017). A practical method to 

determine the strain level for cyclic direct tension fatigue testing in the 

AMPT. Transportation Research Record: Journal of the Transportation 

Research Board, 2631, DOI: 10.3141/2631-15.

 Mensching, D. J., Jeong, M. M., & McCarthy, L. M. (2016). Relative 

comparison of complex dynamic modulus predictive models for nonconventional asphalt concrete mixes. Journal of Testing and Evaluation, 46(1).

 Mensching, D. J., Gibson, N. H., Andriescu, A., Rowe, G. M., & Daniel, J. S. 

(2016). Assessing the applicability of rheological parameters to 

evaluate modified binders. Presented at the International Society for 

Asphalt Pavements Symposium, Jackson Hole, WY.

 Mensching, D. J., Gibson, N. H., Rowe, G. M., & Daniel, J. S. (2016). Using 

mixture-based rheology to evaluate cracking performance of modified 

asphalt pavements. Presented at the International Society for Asphalt 

Pavements Symposium, Jackson Hole, WY.

IMPACT: Mensching’s research benefitted FHWA’s initiative on 

performance-based asphalt designs in multiple ways. His 

research work showed how different asphalts perform based on 

temperature changes and fatigue stresses. His study also 

expanded national data about asphalt materials and soil 

structures for future research as well as the usefulness of Black 

Space diagrams to gauge the performance of asphalt mixtures 

and monitor pavement degradation. He generated a report to 

help highway departments and contractors adjust asphalt 

designs based on temperature, fatigue, and rutting performance. 
14  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

Breakthrough Concepts in Materials Science

PROJECT: Developing Frameworks of Performance-Based Asphalt Mix Design

ASSOCIATE: Jong-Sub Lee

SCHOOL: North Carolina State University

PERIOD: September 2014–April 2016

OBJECTIVE: To investigate use of mechanistic models to evaluate voids in mineral aggregate (VMA), design air void content, and 

in-place air void content as parameters for reliably predicting field performance of various asphalt mix designs.

ADVISER: Katherine Petros, FHWA Office of Infrastructure Research and Development

SUMMARY: Performance-related specifications (PRS) will offer 

engineers, contractors, and funding agencies a way to assess 

future performance, maintenance requirements, and lifecycle 

costs for highway construction projects. PRS can be thought of as 

a set of quality assurance specifications that describe the desired 

levels of key materials and construction-acceptance quality 

characteristics that correlate with fundamental engineering 

properties that predict performance. PRS will rely on models that 

objectively assess performance based on observed constructionquality characteristics related to fundamental engineering 

properties and will:

• Utilize testing that focuses on key measureable characteristics 

related to performance.

• Use pavement design assumptions as a basis for 

construction performance.

• Incorporate incentives and disincentives based on 

modeled performance.

• Allow contractors to innovate and be competitive.

• Reduce long-term monitoring and management.

When fully developed, PRS will employ the quantified relationships 

containing the characteristics to predict as-constructed pavement 

performance. Thus, PRS will provide the basis for rational 

acceptance and pay-adjustment decisions related to highway 

construction projects.

Jong-Sub Lee’s research helped develop a testing and modeling 

framework for performance-based asphalt mix design. The goal 

was to identify the effect of volumetric mix design targets 

(design VMA and design air void) and compaction level (in-place 

air density) on fatigue characteristics and performance. The 

project investigated asphalt mixtures based on the Superpave® 

mix design system (developed through the Strategic Highway 

Research Program) using mechanistic analyses based on the 

viscoelastic continuum damage (VECD) analyses and 

mechanistic–empirical pavement analysis using the 

AASHTOWare Pavement ME Design® program. The analyses 

included the simplified VECD model at the material level and 

two structural models: (a) layered viscoelastic analysis and (b) 

layered viscoelastic pavement analysis for critical distresses.

Key performance-related findings of the research include:

• The damage state at failure is increased (i.e., better fatigue 

performance) with an increase in the design VMA and a decrease 

in the in-place air void and design air void content. The design 

VMA is more sensitive than the others.

• Fatigue life was found to improve when the value of the design 

VMA was increased and the in-place air void content and design 

air void content was decreased in rank of sensitivity.

• Superpave® mix design parameter of design VMA was the most 

sensitive parameter that significantly affected the linear 

viscoelastic property, damage characteristic, and fatigue life in 

the mechanistic analysis.

• The effect of the design air void on mechanistic fatigue life was 

diminished as the pavement thickness increased.

• Increasing the design VMA content caused the least amount of 

fatigue cracking area at the thin pavement.

IMPACT: Data gathered through this research will contribute to the 

development of testing and modeling protocols that can be used to 

develop PRS for asphalt mix design.

RESOURCES: The following reports resulted from this RAP 

research and are outlined below.

Lee, J., Norouzi, A., & Kim, Y. R. (2016). Determining specimen geometry of 

cylindrical specimens for direct tension fatigue testing of asphalt 

concrete. Journal of Testing and Evaluation, 45(2).

Lee, J-S., Gibson, N., & Kim, Y. R. (2015). Use of mechanistic models to 

investigate fatigue performance of asphalt mixtures: effects of asphalt 

mix design targets and compaction. Transportation Research Record, 

Journal of the Transportation Research Board, 2507.

Lee, J-S., & Kim, Y. (2014). Performance-based moisture susceptibility 

evaluation of warm-mix asphalt concrete through laboratory tests. 

Transportation Research Record, Journal of the Transportation 

Research Board, 2446.

Balis, J., & Platte, K. (n.d.). Performance specifications to speed 

construction, reduce oversight, and encourage innovative approaches: 

Performance specifications for rapid renewal (R07). SHRP2 Solutions.
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  15

Breakthrough Concepts in Materials Science

PROJECT: Tensile Response of Ultra-High Performance Concrete: Validation of Characterization Methods

ASSOCIATE: Luis Felipe Maya Duque

SCHOOL: Polytechnic University of Madrid 

PERIOD: June 2013–April 2016

OBJECTIVE: To critically assess the applicability of a recently proposed tensile-test method for ultra-high performance, fiberreinforced concrete. 

ADVISER: Benjamin Graybeal, FHWA Office of Infrastructure Research and Development

SUMMARY: Concrete is the most widely used construction material 

and has played a fundamental role in the development of 

infrastructure since the Romans. Advances in fiber-reinforced 

concretes over the last 50 years have enabled the development of 

an entirely new generation of cement-based composite materials. 

Ultra-high performance concrete (UHPC) represents a class of 

cement composites with high compressive strength and whose 

tensile response is characterized by high-strain capacity 

accompanied by multiple microcracking. To take full advantage of 

the tensile behavior of these UHPC materials, it is necessary to 

develop tensile-test methods and guidelines to be incorporated 

into codes and recommendations. Luis Felipe Maya Duque’s 

research project focused on the assessment of proposed test 

methods designed to provide a reliable assessment of UHPC 

tensile behavior, not only in a research environment, but also for 

quality-control purposes in a production environment. Maya 

Duque assessed a singular direct tensile-test method that has 

already been the subject of FHWA research to establish 

advantages and drawbacks compared with existing methods. 

Maya Duque also conducted a critical review of the state of the art 

in tensile-test methods for UHPC. The research project included 

an extensive experimental campaign to properly assess the 

performance of the proposed tensile-test method. Furthermore, 

Maya Duque also considered the suitability of the direct tension 

test method to accurately reflect the influence of the fiber 

distribution and orientation in structural elements.

IMPACT: This research allows for the development and 

implementation of a quality control test method for UHPC in a 

production environment. Broader use of UHPC could lead to more 

durable and longer lasting highway structures, reducing the cost 

and risks associated with reconstruction.

ONGOING RESEARCH: FHWA conducted over 120 direct tension 

tests on both mold-cast and sawed specimens to assess the 

influence of flow conditions, as well as fiber orientation and fiber 

distribution on the tensile response of UHPC. FHWA also 

performed flexural tests on UHPC strips and slabs to correlate the 

results from the material characterization tests with the mechanical 

response of structural elements. Those results will contribute to 

assessing the reliability of the current design approaches as well 

as to improving understanding of the main mechanisms and 

variables to be considered in the development of design codes 

and recommendations. Maya Duque continues to complete the 

assessment of the structural efficiency of fiber reinforcement in 

UHPC structures through an experimental and analytical validation 

process at FHWA. FHWA plans to conduct two full-scale beam 

tests at the TFHRC Structures Laboratory. The results of these 

tests will provide insight for the development of continuity 

connection using UHPC as an alternative to increase the span 

range currently covered by conventional, precast, prestressed 

concrete girders.

RESOURCES: Several publications and papers resulted from this 

RAP research. They are outlined below.

Graybeal, B., & Baby, F. (2013). Development of a direct tension test 

method for ultra-high-performance fiber-reinforced concrete. ACI 

Materials Journal, 110(2), 177–186.

Maya, L. F., Zanuy, C., Albajar, L., Lopez, C., & Portabella, J. (2013). 

Experimental assessment of connections for precast concrete frames 

using ultra high performance fiber reinforced concrete. Construction 

and Building Materials, 48(11), 173–186.

Maya, L. F., Ruiz, M., Muttonni, A., & Foster, S. J. (2012). Punching shear 

strength of steel fiber reinforced concrete slabs. Engineering Structures, 

40, 83–94.

The following website provides insight on the FHWA UHPC research 

portfolio: http://www.fhwa.dot.gov/research/resources/uhpc/

Full-scale flexural test of a beam splice 

connection made of UHPC.

Casting of beam splice connection.
16  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

Breakthrough Concepts in Materials Science

PROJECT: Performance of Geosynthetic-Reinforced Soils at the Service Limit State

ASSOCIATE: Danial Esmaili

SCHOOL: University of Oklahoma

PERIOD: December 2014–October 2015

OBJECTIVE: To analyze large-scale performance test results to evaluate the effect of tensile strength, vertical reinforcement 

spacing, facing elements, and backfill properties on deformations of geosynthetic-reinforced soil under typical 

bridge support service pressures. 

ADVISER: Jennifer E. Nicks, FHWA Office of Infrastructure Research and Development

SUMMARY: Geosynthetic-reinforced soil (GRS) technology 

consists of closely spaced layers of geosynthetic reinforcement 

and compacted granular fill material. This method of using 

geosynthetics to reinforce foundations is a proven alternative to 

the construction of deep foundations, depending on the site 

conditions. GRS is widely used for a variety of earthwork projects, 

particularly in GRS-integrated bridge system (IBS) applications. 

GRS-IBSs are economical and easy to design; they can be built in 

a variety of weather conditions and can be modified to 

accommodate characteristics of varying site conditions. An 

important geotechnical feature of any bridge foundation, 

including GRS bridge elements, is the service limit state (SLS), 

which ensures the durability and serviceability of a bridge and its 

structural components under everyday loads for the design life.

The SLS for GRS abutments primarily includes vertical settlement, 

lateral deformation, and reinforcement strain. Notwithstanding 

their widespread use in construction, the SLSs of GRS abutments 

have not been well defined.

Danial Esmaili’s research project involved analyzing the results of 

a series of 13 large-scale column experiments (also called 

performance tests or minipier tests) conducted to help quantify 

both the SLS and ultimate limit state for GRS. The experiments 

were conducted on GRS piers consisting of different backfill 

materials, geosynthetic reinforcement strengths, and 

reinforcement spacing (the thickness of backfill between 

reinforcement layers). Some test piers were constructed with 

concrete masonry facing; others had no facing. All GRS 

configurations were tested to failure, with the focus of this study 

on the performance at loads of 200 kPa (recommended allowable 

GRS bearing pressure) and 400 kPa (to test performance at 

extreme service loading). Key research findings of these 

experiments are that:

• GRS piers built with higher strength backfill undergo less lateral 

and vertical deformation.

• Settlement and lateral displacement at 200 kPa, depending on 

composition of test columns, ranged from 8.3 mm to 33.9 mm 

and 3.0 mm to 10.1 mm, respectively.

• Reinforcement spacing plays a larger role than does 

reinforcement strength in lateral and vertical deformation.

• Lateral movement of pier walls is greatest in the top third of

the composite.

• Limiting-bearing pressure to 10 percent of the estimated 

bearing resistance of the GRS abutment will limit axial strains to 

within 0.5 percent of the abutment.

IMPACT: Data gathered through these experiments will help 

engineers more reliably design GRS-IBS projects without having 

to conduct complex and expensive laboratory testing.

RESOURCES: Several publications and papers resulted from this 

RAP research. They are outlined below.

Nicks, J. E., Esmaili, D., & Adams, M. T. (2016). Deformations of geosynthetic 

reinforced soil under bridge service loads. Geotextiles and 

Geomembranes, 44(4), 641–653.

Adams, M. T., Ooi, P. S. K., & Nicks, J. E. (2014). Mini-pier testing to estimate 

performance of full-scale geosynthetic reinforced soil bridge 

abutments. Geotechnical Testing Journal, 37(5).

Minipier tests helped quantify SLS for GRS with (left photo) and without (right photo) concrete 

masonry facing. Source: FHWA.
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  17

Breakthrough Concepts in Materials Science

PROJECT: Developing New Vehicle–Tire and Contact Friction Models

ASSOCIATE: Emmanuel Bolarinwa

SCHOOL: University of Birmingham

PERIOD: September 2013–September 2015

OBJECTIVE: To use a model-based approach for investigating the effect of tire–pavement contact friction on the safety 

performance of vehicles.

ADVISER: James A. Sherwood, FHWA Office of Infrastructure Research and Development

SUMMARY: The effective management of critical pavement surface 

characteristics, such as friction and texture, has been shown to 

help prevent or reduce the consequences of rear-end and run-offthe-road crashes. Although high-friction surfaces can lead to 

increased numbers of dry pavement rollovers, they also lead to 

fewer wet pavement run-off-the-road crashes and tend to have 

fewer crashes involving fatalities and serious injuries. For his 

research project, Emmanuel Bolarinwa implemented a modelbased approach to investigate the effect of variations in vehicle– 

and tire–pavement friction on vehicle safety performance, such as 

stopping distances during braking. He considered the interactions 

among key crash causative factors and predicted vehicle 

performance and stability metrics. Bolarinwa examined a vehicle 

simulation package containing various values for pavement 

friction and texture inputs. For model verification, Bolarinwa 

obtained vehicle data and crash information from the Highway 

Safety Information System (HSIS) and the second Strategic 

Highway Research Program’s naturalistic driving study. He then 

used the model to develop theoretical thresholds for pavement 

friction and texture inputs (i.e., the minimum values when crash 

rates have been found to increase at a significantly higher rate). 

Bolarinwa analyzed results from the simulation to extract vehicle 

performance and safety metrics as possible indicators of the 

onset of vehicle crashes for different vehicle types and a variety of 

road sections and geometries.

IMPACT: This research should lead to enhanced road safety, 

ensuring significant savings in cost and human lives by managing 

pavement friction. The research directly contributes to FHWA’s 

strategic safety improvement program by predicting friction 

threshold values to determine conditions when a pavement 

should be investigated for maintenance intervention. Bolarinwa’s 

research will lead to better characterization of the effects of a 

broad range of human, vehicle, and environmental factors on 

crash outcomes. It will also provide a basis for evaluating practices 

related to pavement surface material parameters and roadway 

geometry. FHWA will ultimately use the results of this research to 

develop new vehicle crash models, which will be of value to safety 

engineers working on State highway safety improvement 

programs. In addition, the results could be used to change 

pavement design standards to select the best pavements in terms 

of safety.

ONGOING RESEARCH: Bolarinwa continues research into the 

development of theoretical threshold values for pavement friction 

and development of procedures for predicting stopping distances 

based on the friction of the pavement surface. The long-term goal 

is to reduce fatal and severe (incapacitating injury) crashes, by 

prescribing levels of pavement friction and macrotexture.

A simulation model for 

investigating vehicle behavior 

on a sloped terrain surface. 

Source: FHWA.
18  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

Breakthrough Concepts in Materials Science

RESOURCES: Several publications and papers resulted from this 

RAP research. They are outlined below.

Uzunsoy, E., Bolarinwa, E., Olatunbosun, O., & He, R. (2014). Investigating 

vehicle behavior on a sloped terrain surface. SAE Technical Paper 2014-

01-0857.

Yang, X., Olatunbosun, O., Ramos, D. G. P., & Bolarinwa, E. (2013). 

Experimental investigation of tire dynamic strain characteristics for 

developing strain-based intelligent tire system. SAE International 

Journal of Passenger Cars–Mechanical Systems, 6(1), 97–108.

Bolarinwa, E. O., Mahadevaiah, U., Marzougui, D., & Opiela, K. S. (2012). The 

development of an enhanced finite element tire model for roadside safety

hardware assessment. Proceedings of the Institution of Mechanical 

Engineers, Part K: Journal of Multi-Body Dynamics, 226(3), 206–219.

Bolarinwa, E. O. (2014). Material and geometrical characterization for FE 

tire modeling and simulation. Paper presented at the 2014 Tire 

Technology Expo Conference, Cologne, Germany.

Bolarinwa, E. O. (2013). Development of an FE tire model for vehicle crash 

simulations. Paper presented at the 2013 Tire Technology Expo 

Conference, Cologne, Germany.

Bolarinwa, E. O. (2013). Experimental investigation of vehicle behavior on a 

sloped-terrain surface. Paper presented during the SAE 2013 World 

Congress and Exhibition, Detroit, MI.

Bolarinwa, E. O. (2012). Role of tire testing in efforts to develop improved 

finite element models to support crash simulation. Workshop on 

Improving the Modeling of Tire, Steering and Suspension Systems in Angular

Crashes, FHWA Turner–Fairbank Highway Research Center, McLean, VA.

Bolarinwa, E. O. (2011). The development of an enhanced finite element tire 

model for vehicle crash simulations. Paper presented at the 30th 

Annual Conference on Tire Science and Technology, Akron, OH.

Bolarinwa, E. O. (2011). Role of tire testing in efforts to develop improved 

finite element vehicle models to support crash simulations. Paper 

presented at the 2011 Tire Technology Expo Conference, Cologne, Germany.
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  19

Breakthrough Concepts in Materials Science

PROJECT: Use of Inorganic Coatings as Curing Compounds

ASSOCIATE: Jessica Silva

SCHOOL: University of Wisconsin–Madison

PERIOD: September 2012–December 2013

OBJECTIVE: To develop inorganic curing compounds to address the shortcomings of current organic membrane-forming 

curing compounds. 

ADVISER: Jack S. Youtcheff, FHWA Office of Infrastructure Research and Development

SUMMARY: Proper curing is a vital post-treatment process when 

constructing durable concrete pavements. This is because water 

loss by evaporation through exposed surfaces can result in 

mechanical or chemical deficiencies in the final surface of the 

concrete product. Existing membrane-forming curing compounds 

are widely used to form a physical barrier to prevent the migration 

of water during the first few hours of concrete placement; 

however, these membranes do not always form a continuous 

coating, may degrade after environmental exposure, and provide 

little protection of the concrete section at later stages of the 

pavement’s service life. Jessica Silva’s research project examined 

the use of inorganic curing compounds to address the 

shortcomings of current organic compounds. These inorganic 

curing compounds, prepared from metal-oxide materials, can 

react with the concrete surface to form durable coatings and 

hydration products. The compounds may also impart beneficial 

characteristics to the roadway and provide improvements to the 

pavement long after traditional membranes. Silva examined 

changes occurring to the air and mortar and mortar and aggregate 

interface, in addition to the porosity, density, and chemical 

makeup of the cement paste. Silva also ensured that the inorganic 

curing compounds under development would not adversely 

affect the concrete material. As part of this research project, Silva 

used a traceable element to better understand the effect of the 

compound as it penetrates the concrete.

IMPACT: This research could represent a paradigm shift in the 

world of curing compounds. In addition, if the material developed 

as a result of this research is not ultimately useful as a curing 

compound, it may still prove useful to enhance general concrete 

characteristics.

RESOURCES: Several publications and papers resulted from this 

RAP research. They are outlined below.

Silva, J. M. S., Youtcheff, J., & Arnold, T. (2013). Utilizing sol-gel nanoparticles 

in concrete curing to improve surfaces. National Research Council 

Research Associateship Programs Newsletter, 14–16.

Munoz, J. F., Silva, J. M. S., Perry, L., Youtcheff, Y., & Sobolev, K. (2014). 

Interaction of amorphous nano-aluminosilicates with cement pore 

solution and the effect on the early hydration reaction of portland 

cement. Proceedings of the Fifth International Symposium on 

Nanotechnology in Construction.

Nucleation of ettringite mineral in the interfacial transition zone. 

Source: FHWA.
20  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

Breakthrough Concepts in Materials Science

PROJECT: Comprehension and Development of Nano-Additives to Judicially Improve the Interfacial Region in Concrete and Asphalt

ASSOCIATE: Jose Muñoz

SCHOOL: University of Wisconsin–Madison

PERIOD: April 2010–April 2013 

OBJECTIVE: To investigate how judicially applied coatings on the surface of the aggregates of different nano-additives 

can improve the interfacial region in concrete and asphalt. 

ADVISER: Jack S. Youtcheff, FHWA Office of Infrastructure Research and Development

SUMMARY: Jose Muñoz examined a method to enhance the area 

of contact between cement-paste aggregates and asphalt 

aggregates, known as the interfacial region. This is one of the 

most vulnerable areas of concrete and asphalt, potentially 

affecting the overall performance of pavement. The durability of 

concrete is highly influenced by its pore structure, specifically a 

highly porous area known as the interfacial transition zone (ITZ). 

Large fractions of the microcracks occurring in concrete are 

associated with the ITZ; therefore, improving the strength of the 

ITZ could significantly improve concrete durability. Traditional 

approaches to the problem, involving the successive addition of 

different silicon or aluminum-based materials, have been 

inefficient and costly. Muñoz based his research on the theory that 

nanoparticles added as nanoporous films, and when judiciously 

placed on the aggregate surface, can greatly improve the ITZ and 

thereby the performance of the concrete. He investigated changes 

triggered by nanoporous thin films in the chemistry and 

morphology of the hydration products located at the aggregate–

cement-paste interface. Muñoz developed a model to determine 

two-dimensional spatial distribution of cement hydration phases 

and to study the aggregate–cement-paste interface in concrete. 

In addition, Muñoz developed a new sol-gel synthesis (a method 

for producing solid materials from small molecules) to produce 

“nano-aluminosilicate” gels with a controlled silicon-to-aluminum 

ratio. Muñoz also studied the effect of these nano-aluminosilicate 

gels with different silicon-to-aluminum ratios on the hydration 

reaction of portland cement.

IMPACT: The development of new nano-additives, together with a 

new method for applying them in concrete, is expected to help 

create materials with less water and chloride penetrability and 

higher mechanical strength and resistance to cracking. This is 

expected to lead to the creation of construction materials with 

improved characteristics and less energy demand for maintenance 

operations. The application of nanoparticles in concrete and asphalt, 

using dip- or spray-coating methods, offers several advantages 

when compared with the traditional addition of nanoparticles as 

powder additives. It is an easier and safer application method—

fewer additives are required, which reduces costs—and the 

technology is already available. In addition, this technology can have 

a positive impact in locations with limited or marginal-quality 

aggregate sources. For example, these nano-additives can be used 

to improve performance of currently marginal aggregates, such as 

natural aggregate with significant contents of clay minerals strongly 

adhered to their surface.

ONGOING RESEARCH: Muñoz continues to study the effect of the 

nanoparticles in concrete pore solution at early stages of 

hydration. In addition, he also performed research with the U.S. 

Army Engineer Research and Development Center to characterize 

the ITZ modified with nanoparticles.

RESOURCES: Several publications and papers resulted from this 

RAP research. They are outlined below.

Muñoz, J. F., Meininger, R. C., & Youtcheff, J. (2010). New possibilities and 

future pathways of nanoporous thin film technology to improve 

concrete performance. Transportation Research Record, Journal of the 

Transportation Research Board, 2142, 34–41.

Muñoz, J. F., Yao, Y., Youtcheff, J., & Arnold, T. (2011). Nanotechnology to 

improve aggregate performance. National Research Council, Research 

Associateship Program Newsletter.

Muñoz, J. F., Yao, Y., Arnold, T., & Youtcheff, J. (2013). Mixtures of silicon 

and aluminum oxides to optimize the performance of nanoporous thin 

films in concrete. Cement and Concrete Composites, 48.

Munoz, J. F., Silva, J. M. S., Perry, L., Youtcheff, Y., & Sobolev, K. (2014). 

Interaction of amorphous nano-aluminosilicates with cement pore 

solution and the effect on the early hydration reaction of Portland 

cement. Proceedings of the Fifth International Symposium on Nanotechnology in Construction.

Balachandran, C., Muñoz, J. F., Arnold, T., & Youtcheff, J. (2014). Potential 

application of surface enhanced Raman spectroscopy as a tool to 

study cementitious materials. Proceedings of the Fifth International 

Symposium on Nanotechnology in Construction.
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  21

Connected Highway and Vehicle System Concepts Connected Highway and Vehicle System Concepts

PROJECT: Design and Implementation of an MPC-Based Framework for Vehicle Platooning

ASSOCIATE: Mohammad Goli

SCHOOL: The George Washington University

PERIOD: January 2019–October 2020

OBJECTIVE: To develop the cooperative automated vehicle control and the vehicle platooning framework for a cooperationenabled ADS to support CARMA.

ADVISER: Taylor William Paul Lochrane, FHWA Office of Operation Research and Development

SUMMARY: Mohammad Goli’s research work involved 

several areas:

• Vehicle localization using EKF: Vehicle localization is the 

science of estimating the position and orientation of cars in a 

predefined frame using one or more sensors such as GPS, 

IMU, LiDAR, and radar. To this end, he and his colleagues 

chose to implement the EKF algorithm, which is a technique 

dealing with uncertain information coming from the 

measurement system and a model that describes the motion 

of the vehicle at each time step, again with a degree of 

uncertainty, to estimate the pose of the vehicle. He and his 

colleagues were able to simulate an EKF algorithm that brings 

in information from sensors such as GPS and IMU and 

combines it with the information coming from the motion 

model to estimate the vehicle’s position with respect to a 

predefined inertial frame.

• Platooning framework and platooning process design: A 

platooning framework is intended to provide an understanding 

of how different levels of task decisions are structured for 

vehicle platooning. Goli and his colleagues proposed a 

structure that organizes different activities into two layers 

called the mission layer and the behavior layer. In each 

layer, different modules are defined to formalize the 

decision-making process by assigning different decisions 

to different modules. The overall goal of all modules in the 

two proposed layers is to break down the driving task in a 

platoon into different subtasks that can be encoded into 

finite state machines. 

• Mission layer: The mission layer has two modules named 

journey manager and destination manager. The goal of the 

mission layer is to make high-level decisions regarding the 

sequence of major destinations as well as the sequence of 

route segments.

• Behavior layer: The behavior layer includes three different 

modules, which are mainly concerned with the factors that 

affect the autonomous driving behavior of each vehicle in 

the platoon: 

• Route segment manager.

• Driving behavior planner.

• Maneuver planner.

• Platooning process design: In this part of Goli’s work, he and his 

colleagues aimed at proposing a high-level platooning 

process design which describes how an individual vehicle 

would request to join a platoon, initiate the matching process, 

negotiate formation, follow in the platoon (i.e., maintain the 

platoon), and eventually dissolve or leave the platoon.

• CARMA 1tenth initiative :The goal of the CARMA 1tenth project 

is to enable the development and testing of CARMA features 

on a much lower-cost, scaled down robotic platform so that a 

much larger research community could get involved in the 

CARMA developments without compromising or limiting the 

functionality of any aspects of it. Goli worked with others to 

build and test three scaled-down vehicles at TFHRC. The 

vehicles are equipped with computing boards, a LiDAR , a 

stereo camera, IMU, and some other devices to facilitate ADS 

and cooperative driving automation testing.
22  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

Connected Highway and Vehicle System Concepts

PROJECT: Toward Safer and Efficient Implementation of Automated Driving Systems: Performance Measurements 

 and Evaluation

ASSOCIATE: Mohamed Ahmed

SCHOOL: University of Wisconsin-Milwaukee

PERIOD: September 2019–September 2020

OBJECTIVE: To improve safety and operation research in ADS.

ADVISER: Shyuan-Ren (Clayton) Chen, FHWA Office of Safety Research and Development

SUMMARY: Highly automated vehicles (AV) have been progressively tested on public roads for many years; however, there is no 

subjective and systematic way to evaluate their safety. Due to 

the proprietary nature of AV manufacturers, trajectory-level 

crash and near-crash precursors data are missing. Transportation agencies will need to find a mechanism to acquire or substitute such data.

Mohamed Ahmed’s research work investigated five methodologies that have been proposed as potential methods to assess the 

safety of ADS, including field testing, microsimulation, driving 

simulators, hardware-software-in-the-loop simulation, and naturalistic driving studies.

He found that preliminary research, literature review, and interaction with various stakeholders have shown that all these approaches are needed, and they complement one another. According to Ahmed, a new naturalistic driving study is needed to 

assess commercially available level 1 and 2 AVs, which could be 

extended to level 3 as some AV manufacturers are claiming to 

have it in the near future.

RESOURCES: Several publications resulted from this RAP 

research. They are outlined below.

Khoda, A., A. Gaweesh, and M. Ahmed. 2021. “The Safety Performance of 

Connected Vehicles on Slippery Horizontal Curves through Enhancing 

Truck Drivers’ Situational Awareness: A Driving Simulator Experiment.” 

Transportation Research Part F: Traffic Psychology and Behaviour 79, 

no. 2: 118–138.

Khan, N., M. Ahmed. 2021. “Weather and Surface Condition Detection 

Using Road-Side Webcams: Application of Pre-trained Convolutional 

Neural Network.” International Journal of Transportation Science and 

Technology. https://doi.org/10.1016/j.ijtst.2021.06.003. 

Khan, N., M. Ahmed. 2021. “WeatherNet: Development of a Novel 

Convolutional Neural Network Architecture for Trajectory-Level 

Weather Detection Using SHRP2 Naturalistic Driving Data.” 

Transportation Research Record: Journal of the Transportation Research 

Board 2675, no. 9: 1016–1030.

Ahmed, I., and M. Ahmed. 2021. “Injury Severity Analysis of Adverse Vs. 

Non-Adverse Weather Condition Crashes in Rural Two-Lane Two-Way 

Highways—A Random Intercept Bayesian Approach.” Presented at the 

100th Annual Meeting of the Transportation Research Board. 

Washington DC: Transportation Research Board.
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  23

Connected Highway and Vehicle System Concepts

PROJECT: Implement Hardware-in-the-loop in More Complex and Realistic Way with Artificial Intelligence

ASSOCIATE: Yu Cui

SCHOOL: University of Buffalo

PERIOD: April 2019–March 2020

OBJECTIVE: TTo investigate AI methodology related to hardware-in-the-loop.

ADVISER: Peter Huang, FHWA Office of Operations Research and Development

SUMMARY: Yu Cui worked on using loop signatures extracted 

from inductance loop detectors. Yu Cui also employed artificial 

intelligent methodologies to match loop signatures from an 

identical vehicle. 

Yu Cui conducted a literature review about artificial intelligent 

methodologies in traffic signal timing optimization area. The 

methods are mainly focused on fuzzy logic, deep learning, and 

reinforcement learning.

PROJECT: Initiation of an Effective Highway Performance Management Strategy by Integrating Multiple Transportation Data Sets

ASSOCIATE: Zhuo Yang

SCHOOL: George Mason University

PERIOD: January 2019–December 2019

ADVISER: Tianjia Tang, FHWA Office of Office of Highway Policy Information

SUMMARY: During his RAP tenure, Zhuo Yang accomplished the 

following:

• Conducted a highway performance study based on the national 

performance management research data set.

• Conducted a traffic pattern identification study based on the 

travel monitoring analysis system data.
24  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

Connected Highway and Vehicle System Concepts

PROJECT: Developing Automated Driving Systems and Predicting Highway Wide Impacts

ASSOCIATE: Pavle Bujanovic

SCHOOL: The University of Texas at Austin

PERIOD: August 2018–August 2019

OBJECTIVE: To develop and advance current vehicle platooning concepts on CARMASM and using simulation tools to predict the 

impact of cooperation-enabled automated driving systems (ADS) on highways. 

ADVISER: Taylor William Paul Lochrane, FHWA Office of Operation Research and Development

SUMMARY: Pavle Bujanovic worked on four main areas:

• Localization solution.

• Platooning framework.

• Lane detection algorithm.

• Global Positioning System (GPS) signal limitations. 

In localization, the purpose is to find a subdecimeter-level location to allow a vehicle to know almost exactly where it is, which 

is especially important with connected vehicles (CVs). CVs rely 

on receiving accurate information from other vehicles in order to 

determine how to execute their own upcoming maneuvers with 

the most efficiency; to implement a localization solution, Bujanovic and his colleagues used an Extended Kalman Filter (EKF) 

that updates beliefs about where the vehicle thinks it is based on 

a dynamic motion model with current sensor readings. In simulation, he implemented an EKF that used a radar and light detection and ranging (LiDAR) to identify the location of other vehicles with respect to the subject vehicle. Bujanovic and his 

colleagues began using GPS, inertial measurement unit (IMU), 

and odometry sensors to help a subject vehicle locate itself with 

respect to a fixed map frame. 

In addition, he worked on developing a platooning framework. 

The framework is divided into different layers, each of which is 

responsible for helping a platoon move from origin to destination. The mission layer is the uppermost layer, and it exists to 

allow vehicles to determine if they should get together to form a 

platoon based on their destinations, and if so, where and when 

they should join and later split. Within the mission layer are the 

behavior planning and maneuvers planning layers. These layers 

allow the platoon to decide what behavior it needs to execute 

(e.g., pass a slow vehicle in front), what maneuvers make up that 

behavior, and how these maneuvers should be executed. In his 

work with vehicle cameras, he also developed a lane detection 

algorithm. The algorithm works by processing each frame and 

applying various filters, such as the Sobel filter, to detect lane 

lines and then determining how the vehicle needs to move in 

order to be in the middle of the lane. The algorithm has been 

tested successfully on video captured in typical driving conditions and will continue to undergo further tests and development for more complex scenarios. Lastly, he spent time studying 

GPS signals. He helped discover several different issues that limit or obstruct GPS signals when equipment is installed on vehicles. For example, loose cables or exposed cables/wires from 

other equipment can interfere with the GPS signal, causing the 

GPS antennas to completely miss it.

RESOURCES: Khoda, A., and M. Ahmed. 2021.“A Note on Random Forest 

Visualization Tools in Post-Hoc Interpretation of Nonparametric RealTime Risk Assessment Models.” Presented at the 100th Annual Meeting 

of the Transportation Research Board. Washington DC: Transportation 

Research Board.
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  25

Connected Highway and Vehicle System Concepts

PROJECT: Cost-Benefit Analysis of Connected and Automated Vehicle Operations

ASSOCIATE: Mehdi Zamanipour

SCHOOL: University of Arizona

PERIOD: September 2016–November 2019

OBJECTIVE: To study the costs and benefits of deploying connected and automated vehicle (CAV) technology along signalized 

corridors and develop a tool to analyze the mobility and environmental benefits of deploying these systems.

ADVISER: Govindarajan Vadakpat, FHWA Office of Safety Research and Development

SUMMARY: Mehdi Zamanipour evaluated the costs and benefits 

of deploying CAV technologies along signalized traffic corridors. 

His research examined two specific wireless communications 

applications—Multi-Modal Intelligent Traffic Signal Systems 

(MMITSS) and GlidePath. Developed under U.S. Department of 

Transportation (USDOT) programs, both systems get technologically advanced vehicles “talking” to each other and to computerized roadside infrastructure. MMITSS uses the data generated 

in such communications to optimize the movements of transit 

and freight traffic, emergency vehicles, and pedestrians, while 

GlidePath is designed to maximize fuel efficiency as vehicles 

move through traffic signals. Zamanipour developed a simulation environment for analyzing these technologies. The elements 

of the simulator include the CAV Message Distributor application, containerization technology to run MMITSS and GlidePath, 

and traffic flow software. This package collects information from 

CAVs, broadcasts messages to roadside infrastructure, sets an 

emission model, and controls driving behaviors like speed and 

acceleration for each vehicle. Zamanipour used the USDOT-sponsored Research Data Exchange to calibrate baseline software 

models for traffic demand and signal time based on U.S. Environmental Protection Agency guidelines.

IMPACT: Although the simulation environment in this project was 

created to analyze MMITSS and GlidePath, it could be used to 

study other dynamic mobility applications such as cooperative 

adaptive cruise control. State and local transportation agencies 

could incorporate the tool into a larger, overall analysis 

framework to justify investments into CAVs. The results of the 

research also can help demonstrate the relationship between 

CAV market penetration and lower fuel consumption. 

RESOURCES: Several publications and papers resulted from this 

RAP research. They are outlined below.

Beak, B., Zamanipour, M., Head, L., & Leonard, B. (2018). Peer-to-peer 

priority signal control strategy in a connected vehicle environment. 

Transportation Research Record: Journal of the Transportation Research

Board. Available online: https://doi.org/10.1177/0361198118773567.

Zamanipour, M., Head, K. L., Feng, Y., & Khoshmagham, S. (2016). Efficient 

priority control model for multimodal traffic signals. Transportation 

Research Record: Journal of the Transportation Research Board, 2557, 

86–99. Available online: http://dx.doi.org/10.3141/2557-09.

Feng, Y., Zamanipour, M., Head, K. L., & Khoshmagham, S. (2016). 

Connected vehicle-based adaptive signal control and applications. 

Transportation Research Record: Journal of the Transportation Research

Board, 2558, 1–13. Available online: http://dx.doi.org/10.3141/2558-02.

Khoshmagham, S., Head, K. L., Feng, Y., & Zamanipour, M. (2016). 

Multimodal data analytics comparative visualization tool: Case study 

of pedestrian crossing design. Transportation Research Record: Journal 

of the Transportation Research Board, 2557, 44–54. Available online: 

http://dx.doi.org/10.3141/2557-05.

Feng, Y., Head, L., Khoshmagham, S., & Zamanipour, M. (2015). A real-time 

adaptive signal phase allocation algorithm in a connected vehicle 

environment. Transportation Research Part C: Emerging Technologies, 

55, 460–473.

Zamanipour, M., Hu, J., Vadakpat, G., Bared, J., & Curtis, D. (2018). A design 

of cooperation between traffic signal and connected automated 

vehicle. Presented at the 97th Transportation Research Board Annual 

Meeting, Washington, DC.

Beak, B., Zamanipour, M., Head, L., & Leonard, B. (2018). Peer-to-peer 

priority signal control strategy in connected vehicle environment. 

Presented at the 97th Transportation Research Board Annual Meeting, 

Washington, DC.

The proposed integrated signal and trajectory control optimization framework. 

© Mehdi Zamanipour.
26  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

Connected Highway and Vehicle System Concepts

PROJECT: Knowledge-Based Signal Timing and Optimization Expert System for Advanced Urban Signal Control

ASSOCIATE: Yi Zhao

SCHOOL: Beijing Jiaotong University

PERIOD: December 2015–June 2018

OBJECTIVE: To develop a knowledge-based signal timing and optimization expert system and employ a robust evaluation 

methodology to test its applicability. 

ADVISER: Peter Huang, FHWA Office of Safety Research and Development

SUMMARY: The limitations of adaptive traffic control systems as 

a tool to optimize signal timing posed an opportunity for Yi 

Zhao to develop a knowledge-based expert system to improve 

existing signal-control systems. Knowledge-based expert 

systems are an artificial intelligence (AI) technique to help 

people analyze and solve problems. Zhao also applied artificial 

neural network technology for traffic-demand prediction.

His project consisted of five major tasks:

• Designing a system framework.

• Developing a hybrid origin–destination (OD) model to estimate 

traffic demand.

• Developing a system to generate plans and select the appropriate

options from the plans, based on real-time traffic data.

• Optimizing the signal timing plan by using this system. 

For his hybrid OD estimation model, Zhao integrated different 

types of traffic data (time of day, day of week, and average daily 

traffic count), pulling data from various sources (wireless traffic 

sensors, link-based traffic sensors, and national survey data). He 

used AI to estimate each small-area OD, which can be used to 

generate any size of scalable ODs to support advanced signal 

operations. A unique feature of Zhao’s work is assembling an OD 

table from many small-area ODs, which is just like assembling a 

puzzle from small pieces. In this way, a scalable OD can be made 

to provide much improved, timely demand data for more 

effective signal timing.

IMPACT: Traffic engineers will benefit from Zhao’s research as 

they work to improve the efficiency of U.S. traffic signals. The 

software package he developed will help them optimize signal 

timing practices based on AI technology. This advanced system 

is working on the basis of more accurate traffic-demand data, 

and it can become “smarter over time” on the basis of 

accumulated knowledge in the expert system and machinelearning technique.

RESOURCES: One publication and several papers resulted from 

this RAP research. They are outlined below.

Zhao, Y., James, R., Xiao, L., & Bared, J. (2018). A capacity estimation 

model for a contraflow left-turn pocket lane at signalized intersections. 

Transportation Research Record: Journal of the Transportation Research Board. 

Available online: http://journals.sagepub.com/doi/10.1177/0361198118787978.

Zhao, Y., Huang, P., Xiao, L., Ma, J., Hu, J., & Wang, Y. (2017). A scalable 

short-term origin-destination estimation approach based on modularized 

network with connected vehicle technology. Presented at the 96th 

Transportation Research Board Annual Meeting, Washington, DC.

Wolfgram, J., Huang, P., Zhao, Y., & Christofa, E. (2018). A quick and reliable 

traffic incident detection methodology using connected vehicle data. 

Presented at the 97th Transportation Research Board Annual Meeting, 

Washington, DC.

Wang, Y., Zhao, Y., Zhang, W., Bared, J., & Huang, P. (2017). Signal timing 

strategies for Georgia’s first in-house designed DDI, 5th Urban Street 

Symposium, Raleigh, NC.

Xiao, L., Wang, Y., Hu, J., & Zhao, Y. (2017). Responsive signal control with 

active connected vehicles. Presented at the 96th Transportation Research 

Board Annual Meeting, Washington, DC.

Zhao, Y., James, R., Xiao, L., & Bared, J. (2018). A capacity estimation model 

for a contraflow left-turn lane at signalized intersections. Presented at the 

97th Transportation Research Board Annual Meeting, Washington, DC.

Wang, Y., Zhao, Y., Zhang, W., Bared, J., & Huang, P. (2017). Signal timing 

strategies for Georgia’s first in-house designed DDI. Presented at the 5th 

Urban Street Symposium, Raleigh, NC.

Zhao, Y., James, R., Xiao, L., & Bared, J. (2017). A capacity estimation model 

for a contraflow left-turn lane at signalized intersections. Presented at the 

5th Urban Street Symposium, Raleigh, NC.
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  27

Connected Highway and Vehicle System Concepts

PROJECT: Development of an Eco-Cooperative Adaptive Cruise Control to Optimize Vehicle Performance for Environment and 

Mobility Benefits

ASSOCIATE: Jia Hu

SCHOOL: University of Virginia

PERIOD: October 2014–July 2017

OBJECTIVE: To develop an algorithm for eco-cooperative adaptive cruise control (ECACC) that accounts for road topography 

to minimize fuel consumption and emissions while maximizing mobility. 

ADVISER: Joe Bared, FHWA Office of Operations Research and Development

SUMMARY: Eco-driving systems improve fuel efficiency by 

keeping equipped vehicles within a range of speeds in 

mountainous terrain rather than at a fixed speed like conventional 

cruise control. However, the algorithms that these systems use 

do not gauge their impact on mobility. Jia Hu sought to develop 

a framework for ECACC that could minimize a vehicle’s fuel 

consumption while maximizing its mobility. His research also 

evaluated how speed changes within the ECACC framework 

could affect vehicle safety performance. Hu reviewed literature 

on three topics—state-of-the-art ECACC, fuel consumption 

models that consider variables like vehicle speed and roadway 

grade, and car-following models. In the next phase of work, he 

developed an algorithm for ECACC in three stages. Using 

simulation tools, Hu initially designed the algorithm to optimize 

both fuel economy and mobility for a single vehicle. Next, he 

expanded the algorithm to traffic scenarios that mixed one 

ECACC-equipped vehicle with human-driven vehicles. The third 

phase of algorithm development envisioned multiple vehicles 

using ECACC. Hu finished the project by testing the algorithm 

and evaluating the results. To complete this testing, Hu had to 

identify several stretches of highways with different topographies 

to serve as the prototype for a simulation test bed. The tests 

considered average grade and grade changes in the road, vehicle 

weight, target speed range, and other factors when gauging the 

performance of the algorithm. Hu compared the fuel efficiency, 

emissions, speed, vehicle spacing, throughput, and number of 

conflicts that occurred in multiple ECACC simulations.

IMPACT: Hu’s project is expected to generate an ECACC 

framework that can maximize fuel efficiency and minimize the 

technology’s impact on mobility, regardless of the road 

topography the vehicle is traveling. The framework should work 

for either a lone ECACC-equipped vehicle or a platoon of them. 

As a secondary benefit, the research could demonstrate 

improved safety performance for vehicles with ECACC. 

RESOURCES: Several publications and papers resulted from this 

RAP research. They are outlined below.

Hu, J., Shao, Y., Sun, Z., & Bared, J. (2017). Integrated vehicle and powertrain 

optimization for passenger vehicles with vehicle-infrastructure 

communication. Transportation Research Part C: Emerging 

Technologies, 79, 85–102.

Jiang, H., Hu, J., An, S., Wang, M., & Park, B. B. (2017). Eco approach at an 

isolated signalized intersection under partially connected and 

automated vehicle environment. Transportation Research Part C: 

Emerging Technologies, 79, 290–307.

Zhang, L., Zhang, L., Hale, D., Hu, J., & Huang, Z. (2017). A cycle-based 

variable speed limit methodology for improved freeway merging. IET 

Intelligent Transport Systems, 11, DOI: 10.1049/iet-its.2017.0017. 

Hu, J., Shao, Y., Sun, Z., Wang, M., Bared, J., & Huang, P. (2016). Integrated 

optimal eco-driving on rolling terrain for hybrid electric vehicle with 

vehicle-infrastructure communication. Transportation Research Part C: 

Emerging Technologies, 68, 228–244. 

Ma, J., Hu, J., Hale, D., & Bared, J. (2016). Dynamic hard shoulder running 

for traffic incident management. Transportation Research Record: 

Journal of the Transportation Research Board, 2554, 120–128.

Hu’s research shows that an eco-CACC with a connected powertrain can bring additional fuel 

savings of 15 to 25 percent, compared with mere speed optimization. © Jia Hu
28  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

Connected Highway and Vehicle System Concepts

PROJECT: Developing and Implementing Dynamic Junction Control System in the United States

ASSOCIATE: Ximiao Jiang

SCHOOL: University of Tennessee, Knoxville

PERIOD: October 2013–May 2015

OBJECTIVE: To investigate the efficiency of dynamic merge control (DMC) strategy at freeway merge areas.

ADVISER: Joe Bared, FHWA Office of Operations Research and Development

SUMMARY: DMC is a traffic management strategy that can be 

used to dynamically monitor and control traffic flow at freeway 

on- or off-ramps or where multiple-lane freeways merge—for 

example, where a 2-lane freeway merges with a 3-lane freeway 

into 4 lanes. DMC minimizes disruption that can occur, for 

example, when traffic volume on an on-ramp is significantly 

higher than on the freeway. In this case, ramp traffic must find 

gaps in lower volume freeway traffic, resulting in hesitation and 

delay and increasing the possibility of rear-end collisions. DMC 

strategy, now being used in Germany and the Netherlands, 

assigns priority to the high-volume traffic stream. In the example 

above, DMC could close the right lane of the main freeway and 

allow ramp traffic free access at the merge. DMC has not been 

implemented anywhere in the United States, and knowledge of 

the strategy is still experimental here.

Ximiao Jiang’s research project used an analytical technique 

called microsimulation to examine the effectiveness of DMC on 

several road and traffic configurations. Microsimulation can 

effectively model the behavior of many individual vehicles within 

specified traffic environments, including merge queuing and 

congested road networks, to the point of gridlock. Jiang 

simulated DMC lane-closing strategy on two traffic configurations: 

the first, two 2-lane freeways merging into 3 lanes, and the 

second, a 3-lane freeway merging with a 2-lane freeway into 4 

lanes. Simulations included traffic demands ranging from 1,000 

vehicles per hour (vph) to 4,600 vph on 3 lanes and 2,500 vph 

to 6,500 vph on 2 lanes. In the simulations, signals notify drivers 

of lane closure 2,500 ft upstream of the lane closing and close 

the lane 1,000 ft upstream of the merge. The simulation assumed 

that drivers would be 100-percent compliant with lane closure. 

Fifteen runs were simulated for each scenario. Key findings of 

the simulations are:

• Implementing DMC strategy produced benefits in vehicle delay 

and speed at almost all demand combinations.

• When traffic demand on the minor roadway reached 1,900 

vph per lane, DMC benefits became statistically and 

practically significant.

• DMC reduced lane changing in the merge area, thereby increasing 

capacity and delaying the formation of bottlenecks.

IMPACT: This research represents an important first step in 

evaluating the DMC strategy as an effective approach to reducing 

delays and congestion at freeway merge areas.

ONGOING RESEARCH: The next phase of DMC microsimulation 

will investigate varying closing locations and varying distances 

at which drivers are warned. The next phase also will investigate 

various closed-lane compliance ratios.

RESOURCES: Several publications resulted from this RAP 

research. They are outlined below.

Jiang, X., Gan, Q., Bared, J., Mannes, M., & Hale, D. (2015). Traffic 

performance analysis of dynamic merge control using microsimulation. Transportation Research Record, Journal of the 

Transportation Research Board, 2484.

Zhang, Y., Jiang, X., Haghani, A., & Huang, B. (2015). Exploring nonlinear 

effects of traffic crash determinants using a novel poisson-mixed 

multivariate adaptive regression splines model. Transportation 

Research Record, Journal of the Transportation Research Board, 2515.

Microsimulation studies evaluated dynamic merge control in configurations such as a 2-lane freeway 

merging with a 3-lane freeway to form four traffic lanes.

From Jiang, X., J. Bared, M. Maness, and D. Hale. Traffic Performance Analysis of Dynamic Merge 

Control Using Microsimulation. Transportation Research Record: Journal of the Transportation 

Research Board, No. 2484, Figure 1, p. 24, 2015. Reproduced with permission of the Transportation 

Research Board.
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  29

Human Behavior and Travel Choices Human Behavior and Travel Choices

PROJECT: Using Naturalistic Driving Study Data to Analyze Behavior at Signalized Intersections

ASSOCIATE: Chenhui Liu

SCHOOL: Iowa State University

PERIOD: August 2018–October 2020

OBJECTIVE: Analyze behavior at signalized intersections with NDS data.

ADVISER: Wei Zhang, FHWA Office of Safety Research and Development

SUMMARY: Chenhui Liu’s research involved sifting through and 

analyzing the raw SHRP 2 reduced intersection dataset from the 

Virginia Tech Transportation Institute. The dataset is invaluable 

for studying driver behaviors at intersections. However, due to 

the privacy issue and high costs, the dataset has been unavailable 

to most researchers until now. Liu’s work lays a solid foundation 

for researchers to continue naturalistic driver behavior analysis 

in the future.

RESOURCES: Several publications and papers resulted from this 

RAP research. They are outlined below.

Yu, S., L. Wang, G. Wang, C. Liu, and L. Yang. 2020. “Estimation and 

Inference for Generalized Geoadditive Models.” Journal of the 

American Statistical Association 115, no. 530: 761–774.

Zhao, S., K. Wang, C. Liu, and E. Jackson. 2019. “Investigating the Effects 

of Monthly Weather Variations on Freeway Crash Experience.” Journal 

of Safety Research 71: 153–162

Li, X., C. Liu, J. Jia. 2019. “Ownership and Usage Analysis of Alternative 

Fuel Vehicles in the United States with the 2017 National Household 

Travel Survey Data.” Sustainability 11, no. 8: 2262–2277.

Liu, C., C. Lu, S. Wang, A. Sharma, and J. Shaw. 2019. “A Longitudinal 

Analysis of the Effectiveness of California’s Ban on Cellphone Use 

While Driving.” Transportation Research Part A 124: 456–467.

Liu, C., and A. Sharma. 2019. “Are You Going to Get A Ticket or A Warning 

for Speeding? An Autologistic Regression Analysis in Burlington, VT.” 

Transportation Research Interdisciplinary Perspectives 1: 100001.

Lu, C., Dong, J., L. Hu, and C. Liu. 2019. “An Ecological Adaptive Cruise 

Control for Mixed Traffic and Its Stabilization Effect.” IEEE Access 7, 

no.1: 81246–81256.

Zhang, W., C. Liu, and L. Xiao. 2019. “Predicting Vulnerable Road User 

Crashes Based on Seasonable Pattern.” Presented at the International 

Conference on Transportation and Development. Alexandria, VA: 

American Society of Civil Engineers.
30  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

Human Behavior and Travel Choices

PROJECT: Driving the Highway Safety Manual to Perform Better: A Fourfold Research

ASSOCIATE: Seyedehsan Dadvar

SCHOOL: Morgan State University

PERIOD: June 2019–July 2020

OBJECTIVE: To improve tools for data-driven safety analysis.

ADVISER: Shyuan-Ren (Clayton) Chen, FHWA Office of Safety Research and Development

SUMMARY: Seyedehsan Dadvar participated in ongoing Geometric Design Lab activities, in particular testing and reviewing the 

Interactive Highway Safety Design Model development and support (e.g., IHSDM 2019 (version 15.0.0) and IHSDM 2020 (version 

16.0)). Dadvar calibrated the severity distribution functions of 

the Highway Safety Manual (HSM) using data from Maryland for 

freeway segment model.

Dadvar conducted a literature catalog and review on “HSM”-related publications (830+ records), including an online summary 

table of the HSM Part C Crash Modification Factors (CMF) or 

Adjustment Factors (AF), “NDS”-related publications (2,300+ 

records), and AV (levels 2 and 3) owner manuals for active auto 

manufacturers (40+ records) and digitized and geocoded California Department of Motor Vehicle AV crash reports (2014–

present: 259 crash reports).

RESOURCES: Several publications and papers resulted from this 

RAP research. They are outlined below.

Dadvar, S., Y.-J. Lee, and H.-S. Shin. 2020. “Improving Crash Predictability 

of the Highway Safety Manual through Optimizing Local Calibration 

Process” Accident Analysis and Prevention 136. https://doi.

org/10.1016/j.aap.2019.105393.

Shin, H.-S., S. Dadvar, S. Bharti, and Y.-J. Lee. 2020. “Results and Lessons 

from Local Calibration Process of the Highway Safety Manual for the 

State of Maryland: Freeway Segments, Speed-Change Lanes, And 

Ramp Terminals.” Journal of Transportation Safety and Security. 

https://doi.org/10.1080/19439962.2020.1786758.
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  31

Human Behavior and Travel Choices

PROJECT: Effectiveness of High-Visibility Crosswalks in Improving Pedestrian Safety

ASSOCIATE: Tawfiq Sarwar

SCHOOL: State University of New York–University at Buffalo

PERIOD: November 2016–September 2018

OBJECTIVE: To analyze crashes and near-crashes using Strategic Highway Research Program 2 (SHRP 2) naturalistic driving 

study (NDS) data and evaluate the effectiveness of high-visibility crosswalks (HVCs) in improving pedestrian safety. 

ADVISER: Carol Tan, FHWA Office of Safety Research and Development

SUMMARY: Tawfiq Sarwar’s exploration of HVCs as a potential tool 

to improve pedestrian safety is an extension of research conducted 

under SHRP 2. The researchers for the initial project analyzed 

video data of driver behavior that was collected in two SHRP 2 

projects—NDS and the roadway information database. The 

researchers used the data to develop statistical models for 

gauging the effectiveness of HVCs at three uncontrolled 

intersections in Erie County, NY, one of six NDS test sites. They 

defined benchmark points before each intersection based on 

predictions of when drivers could see and react to the HVCs. Then 

they examined changes in speed, acceleration, and throttle pedal 

actuation as drivers passed through the intersections, both before 

and after HVCs were installed. Sarwar took that research to the 

next level by developing similar statistical models to analyze data 

from all six NDS test sites. The other five sites are in Florida, 

Indiana, North Carolina, Pennsylvania, and Washington. For more 

efficient and unbiased estimates of speed, acceleration, and 

throttle pedal actuation, Sarwar will develop statistical models 

that take into account correlations for each factor at the 

benchmark and crosswalk points. He plans to develop models for 

gauging the distance from a driver’s first application of the brakes 

to an HVC and the time it takes for the vehicle to slow to a 

minimum speed value.

IMPACT: By incorporating data from all six SHRP 2 test sites, 

Sarwar will create advanced statistical models for gauging how 

different HVC marking types and placements could improve 

pedestrian safety. The broader sampling of data also makes it 

possible to evaluate HVCs based on regional differences in 

driving behavior. Finally, Sarwar’s models can be used to 

pinpoint how far from HVCs to place warning signs as a prompt 

for drivers to slow their speed.

RESOURCES: Several publications and papers resulted from this 

RAP research. They are outlined below.

Sarwar, M. T., Fountas, G., & Anastasopoulos, P. C. (2017). Simultaneous 

estimation of discrete outcome and continuous dependent 

variable equations: A bivariate random effects modeling approach 

with unrestricted instruments. Analytic Methods in Accident 

Research, 16, 23–34.

Sarwar, M. T., Anastasopoulos, P. C., Golshani, N., & Hulme, K. (2017). 

Grouped random parameters bivariate probit analysis of perceived 

and observed aggressive driving behavior: A driving simulation study. 

Analytic Methods in Accident Research, 13, 52–64.

Anastasopoulos, P. C., Fountas, G., Sarwar, M. T., Karlaftis, M., & Sadek, A. 

(2017). Transport habits of travelers using new energy type modes: A 

random parameters hazard-based approach of travel distance. 

Transportation Research Part C: Emerging Technologies, 77, 516–528.

Nahidi, S., Fountas, G., Sarvani, S., Sarwar, M. T., & Anastasopoulos, P. C. 

(2017). Project discrepancies in roadway construction and preservation: 

A statistical analysis of public–private partnership contract types in the 

US. Frontiers in Built Environment, 3, 15, DOI: 10.3389/fbuil.2017.00015.

Sarwar, M. T., Fountas, G., Bentley, C., Anastasopoulos, P. C., Blatt, A., 

Pierowicz, J., Majka, K., & Limoges, R. (2017). Preliminary investigation 

of the effectiveness of high-visibility crosswalks on pedestrian safety 

using crash surrogates. Transportation Research Record: Journal of the 

Transportation Research Board, 2659, DOI:10.3141/2659-20.

Sarwar, M. T., Fountas, G., & Anastasopoulos, P. C. (2017). Analysis of 

stationary and dynamic factors affecting highway accident occurrence: 

A dynamic correlated grouped random parameters binary logit 

approach. Accident Analysis and Prevention, 113, 330–340.

Sarwar, M. T., Fountas, G., Bentley, C., Anastasopoulos, P. C., Blatt, A., 

Pierowicz, J., Majka, K., & Limoges, R. (2017). Preliminary investigation 

of the effectiveness of high-visibility crosswalks on pedestrian safety 

using crash surrogates. Presented at the 96th Transportation Research 

Board Annual Meeting, Washington, DC.

Fountas, G., Sarwar, M. T., & Anastasopoulos, P. C. (2017). Analysis of 

stationary and dynamic factors affecting highway accident occurrence. 

Presented at the 96th Transportation Research Board Annual Meeting, 

Washington, DC.

Golshani, N., Sarwar, M. T., & Anastasopoulos, P. C. (2017). Exploratory 

empirical analysis of measured and perceived aggressive driving 

behavior in a driving simulation environment. Presented at the 96th 

Transportation Research Board Annual Meeting, Washington, DC.
32  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

Human Behavior and Travel Choices

PROJECT: Data-Driven Space-Time Dependent Traffic Condition Estimation and Management

ASSOCIATE: Lin Xiao

SCHOOL: Hong Kong University of Science & Technology

PERIOD: October 2015–June 2018

OBJECTIVE: To analyze the Strategic Highway Research Program 2 (SHRP 2) and other datasets to gain critical insights into the 

spatial, temporal, and causation patterns of traffic crashes; perform targeted analyses to uncover the underlying 

relationships between crashes and level of services in different types of land-use environments; and develop datamining tools for identifying high-crash locations and extracting relevant crash record data for detailed further analysis. 

ADVISER: Wei Zhang, FHWA Office of Safety Research and Development

SUMMARY: Lin Xiao conducted multi-dimensional analyses of 

datasets from SHRP 2, including the Roadway Information 

Database (RID), the Safety Pilot Dataset from Ann Arbor, MI, and 

statewide crash data from Virginia and Texas. The data he analyzed 

from the RID were primarily the geocoded statewide crash data 

from Florida, Indiana, New York, North Carolina, Pennsylvania, and 

Washington. Xiao developed tools for viewing, analyzing, and 

visualizing the large datasets. The most important tool he 

developed is 2-STEP, which reads in statewide crash data. In Step 

1, an entire State is partitioned into grids of 10 mi2

. The grids are 

ranked by crash frequency and crash cost. In Step 2, the selected 

grids are further partitioned into grids of 0.5 mi2

, and the ranking 

process is repeated. The highlighted smaller grids are the ones 

with the highest number or highest cost of crashes. Based on the 

codes written for this tool, Xiao developed over a half-dozen other 

tools. These tools can analyze different types of geolocated data 

(crash, traffic flow, speed, etc.) and make various predictions. 

These additional tools can be used to:

• Identify traffic bottleneck locations and the peak periods.

• Identify the dates on which weather and other large-scale 

events caused significant changes to the daily crash frequency.

• Predict the annual crash frequency of any location based on 

historic, multi-year crash data.

• Merge naturalistic driving data from the Safety Pilot data 

collected in the Ann Arbor, MI, area with crash data to 

investigate the delays caused by different severities of 

crashes.

• Merge crash data with data from permanent traffic-counting 

stations, and assess the impacts of crashes to speed 

distribution (further refinement of this tool can lead to 

effective crash-detection algorithms).

• Predict time series trends.

Xiao contributed to the investigation of the relationship between 

crash severity and the level of traffic service using a neural network/

machine-learning approach. He collaborated with other associates 

on research into connected vehicles and artificial intelligence.

An illustration of the 2-STEP tool at work, counterclockwise from top: Divide the entire region, the 

State of Virginia in this case, into a grid of 10 mi2 and pick one for further analysis (Step 1); subdivide 

the highlighted grid in Step 1 into a grid of 0.5 mi2 (Step 2); and identify a high-crash location. 

Source: FHWA.
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  33

Human Behavior and Travel Choices

IMPACT: Xiao’s research makes it easier for practitioners to 

identify and extract useful information from SHRP 2 and other 

large datasets. These tools can provide the precise “where,” 

“when,” and “why” of traffic crashes in the identified high-crash 

areas, which provide actionable information for decisionmakers. 

Safety projects initiated based on the above information can 

increase the return on investment significantly and improve 

systemwide safety. His work produced the following 

mathematical and technological tools to help achieve those goals: 

• A tool called 2-STEP for identifying high-crash locations based 

on multiyear, statewide (or other types of regional) crash data.

• A big data approach to predicting traffic crashes for any 

location in a State.

• An interactive tool for identifying traffic bottlenecks.

• An interactive tool for identifying the dates of large-scale 

events that significantly altered daily crash patterns.

• A methodology for assessing the relationship between crash 

severity and levels of traffic flow.

• Algorithms for identifying crash events based on permanent 

traffic counter data.

REASOURCES: Several publications and papers resulted from 

this RAP research. They are outlined below. 

Pan, D., C. Silverstein, L. Xiao, A. Caamaño, W. Zhang, and S. Hamdar. 2018. 

“Investigating the Relationship Between Collision Characteristics and 

Traffic Level of Service Through Big Data Analytics: A Case Study in 

the State of Virginia.” Presented at the American Society of Civil 

Engineers’ Transportation and Development International Conference. 

Pittsburgh, PA: American Society of Civil Engineers. 

Zhang, W., and L. Xiao. 2018. “Vulnerable Road User Crash Patterns in 

Orlando.” Presented at the 18th Chinese Overseas Transportation 

Association’s International Conference of Transportation Professionals. 

Beijing, China: Chinese Overseas Transportation Association.

Zhang, W., L. Xiao, Y. Wang, and K. Kelarestaghi. 2018. “Big Data Approach 

of Crash Prediction.” Presented at the 97th Annual Meeting of the 

Transportation Research Board. Washington, DC: Transportation 

Research Board. 

Wang, P., W. Wu, L. Wang, L. Xiao, X. Deng, and M. Li. 2017. “A Novel 

Cooperative Collision Avoidance Model for Connected Vehicles.” 

Transportation Research Record: Journal of the Transportation 

Research Board 2645. https://doi.org/10.3141/2645-16. 

Kelarestaghi, K., W. Zhang, Y. Wang, L. Xiao, K. Hancock, and K. Heaslip. 

2017. “Impacts to crash severity outcome due to adverse weather 

and other causation factors.” Advances in Transportation Studies 

43: 31–42. 

Wang, P., H. Yu, L. Xiao, and L. Wang. 2017. “Online traffic condition 

evaluation method for connected vehicles based on multisource data 

fusion.” Journal of Sensors. 

Qu, X., S. Wang, T. Wang, L. Xiao, W. Yi, and Z. Liu. 2017. “Mixed-integer 

linear programming models for teaching assistant assignment and 

extensions.” Scientific Programming. 

Ren, Y., Y. Wang, G. Yu, H. Liu, and L. Xiao. 2016. “An adaptive signal control 

scheme to prevent intersection traffic blockage.” IEEE Transactions on 

Intelligent Transportation Systems 18, no. 6: 1519–1528. 

Zhao, Y., P. Huang, L. Xiao, J. Ma, J. Hu, and Y. Wang. 2017. “A scalable 

short-term origin-destination estimation approach based on 

modularized network with connected vehicle technology.” Presented 

at the 96th Annual Meeting of the Transportation Research Board. 

Washington, DC: Transportation Research Board. 

Xiao, L., Y. Wang, J. Hu, and Y. Zhao. 2017. “Responsive signal control with 

active connected vehicles.” Presented at the 96th Annual Meeting of 

the Transportation Research Board. Washington, DC: Transportation 

Research Board. 
34  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

Human Behavior and Travel Choices

PROJECT: Operational and Safety Analyses of Alternative Intersection/Interchange Designs

ASSOCIATE: Yubian Wang 

SCHOOL: University of Texas at El Paso 

PERIOD: October 2014–September 2017

OBJECTIVE: TTo conduct analytical and simulation studies to find suitable and implementable methods of analyzing 

innovative alternative intersection and interchange designs. 

ADVISER: Wei Zhang, FHWA Office of Safety Research and Development

SUMMARY: Researchers and practitioners in the United States 

are exploring ways to improve highway safety and address traffic capacity issues in part by implementing innovative designs at 

intersections and interchanges. Yubian Wang spent 3 yr at 

TFHRC researching alternative intersection designs, including 

diverging diamond interchanges (DDIs), continuous-flow intersections (CFIs), and restricted crossing U-turn intersections 

(RCUTs). Alternative intersections/interchanges are designs 

aimed at reducing congestion and improving safety by reducing 

traffic conflicts rather than adding lanes. These designs take advantage of site-specific traffic demand patterns by introducing 

auxiliary intersections at strategic locations and rerouting certain traffic movements. The traffic conflicts at the primary intersection can be reduced by 50 percent or more, and some previously conflicting movements become compatible and can move 

simultaneously. Alternative designs typically eliminate the protected left-turn phase and increase effective green-light time for 

other traffic movements, which usually translate into more capacity with minimal or no increases in the intersections’ right of 

way. In fully developed areas, alternative designs are often the 

only effective and fiscally viable solution to congestion and safety problems that plague the Nation’s roadway network. 

Wang’s work filled some critical gaps in this area and has been 

applied to solve real work problems. She reviewed relevant literature to synthesize best practices for DDI, CFI, and RCUT designs. The review covered operational and safety performance of 

the designs, their challenges and limitations, and lessons learned 

from building and operating them. She also traveled to alternative intersection sites in Haymarket, Norfolk, and Vienna in Virginia to see firsthand how different types of field data are collected and used to assess different performance aspects of 

alternative designs. Wang expanded the research work of a previous postdoctoral fellow and helped deliver critical technical 

assistance to many State and local agencies. In 2015, the Georgia 

Department of Transportation (GDOT) decided to design a future DDI at I–285 and Camp Creek Parkway in Atlanta. Wang 

took a leading role in performing the simulation analysis to evaluate the impacts of different alternative designs and signal-timing strategies. During a period of over 4 mo, the research team 

(including Wang) presented the simulation results in multiple 

online conferences, the GDOT staff provided feedback, and the 

simulation models were refined to make the simulated conditions closer to field conditions. 

Wang thoroughly analyzed the before- and after-crash data of 

more than 150 modern roundabouts in 6 States, and she developed crash-modification factors for single-lane and multilane 

roundabouts converted from previous stop- or signal-controlled 

intersections. This is one of the largest number of roundabouts 

included in a single study. Wang manually examined the satellite 

images of each site by year to verify if the previous type of traffic control device was coded correctly, sorted through the crash 

records and organized them into unified formats, and analyzed 

the data using various statistical models. 

Wang also contributed to big data research in which she helped 

develop models to predict the frequency and economic cost of 

traffic crashes in a region. 
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  35

Human Behavior and Travel Choices

IMPACT: DDIs, CFIs, and RCUTs can reduce the number of traffic 

signal phases and conflict points, but these designs are still 

relatively new to most traffic engineers. Wang’s work helped 

convince practitioners to implement alternative intersection 

designs at more suitable locations. Her work with GDOT provides 

insight into how different geometric designs and signal-timing 

strategies could improve the level of service. A congested signal 

intersection sitting next to a high-capacity DDI would limit the 

capacity utilization of the DDI. Wang helped advance the state 

of the art in solving this class of problem. Her analysis of 

roundabouts filled a critical gap in safety impacts of converting 

existing stop- or signal-controlled intersections into yieldcontrolled modern roundabouts. 

RESOURCES: Several publications and papers resulted from this 

RAP research. They are outlined below. 

Zhang, W., L. Xiao, Y. Wang, and K. Kelarestaghi. 2018. “Big Data Approach 

of Crash Prediction.” Presented at the 97th Annual Meeting of the 

Transportation Research Board. Washington, DC: Transportation 

Research Board. 

Kelarestaghi, K., W. Zhang, Y. Wang, L. Xiao, K. Hancock, and K. Heaslip. 

2017. “Impacts to Crash Severity Outcome Due to Adverse Weather 

and Other Causation Factors.” Advances in Transportation Studies

43: 31–42. 

Wang, Y., Y. Zhao, W. Zhang, J. Bared, and P. Huang. 2017. “Signal Timing 

Strategies for Georgia’s First In-House Designed DDI.” Presented at the 

5th Urban Street Symposium. Raleigh, NC: Transportation Research 

Board and Institute of Transportation Engineers North Carolina Section.

Wang, Y., and R. L. Cheu. 2016. “Operational impacts of implementing 

auxiliary lanes at isolated freeway off-ramps.” ITE Journal 86: 36–41. 

Wang, Y., and W. Zhang. 2016. “Analysis of Roadway and Environmental 

Factors Affecting Traffic Crash Severities.” Transportation Research 

Procedia 25: 2124–2130. 

Hancock, K., W. Zhang, H. Sardar, and Y. Wang. 2016. “A Two-Step GeoGrid Screening Process to Identify Locations for Safety Improvements.” 

Advances in Transportation Studies: An International Journal 2: 89–102. 

Zhang, W., K. Hancock, Y. Wang, and H. Sardar. 2015. “Estimate Economic 

Losses Due to Roadway Crashes.” Presented at the 2015 Road Safety 

and Simulation International Conference. Orlando, FL: University of 

Central Florida and University of Tennessee, Knoxville.

Zhang, W., K. Hancock, Y. Wang, and H. Sardar. 2016. “Prioritize Safety 

Projects with Confidence Using Two-Step Spatial Screening.” 

Presented at the ASCE International Conference on Transportation and 

Development. Houston, TX: American Society for Civil Engineers.
36  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

Human Behavior and Travel Choices

PROJECT: Integrating Driving Simulation and Other Behavioral Data: Assessment of Driver Behavior and Performance

ASSOCIATE: Alicia Romo

SCHOOL: The University of Texas at El Paso

PERIOD: September 2013–July 2015

OBJECTIVE: To develop methods that will use data from various sources, such as driving simulator experiments, crash 

databases, and naturalistic driving studies, to gain comprehensive understanding about road-user behaviors. 

ADVISER: C. Y. David Yang, FHWA Office of Safety Research and Development

SUMMARY: A high percentage of transportation incidents and 

vehicle crashes are caused by human errors. As a result, it is 

important to continue investing in research resources to gain a 

comprehensive understanding of human errors and to try to 

answer the question, “Why do drivers and travelers do what they 

do?” A number of different datasets have recently become 

available to analyze human errors; however, these datasets point 

in different directions within different areas of interaction. Alicia 

Romo’s research project is focused on finding methods to combine 

data from different sources to gain better understanding about 

road-user behavior. During the first year, Romo conducted a 

comprehensive literature review and summarized information 

from more than 100 technical journals and reports about various 

methods to study road-user behavior and types of available 

behavioral data. Based on the information from this literature 

review, Romo has since developed a framework to categorize 

behavior data from various sources, such as crash databases, 

driving simulator experiments, field test vehicle studies, and 

naturalistic driving studies. Romo’s research will show the benefit 

of using information from multiple data sources to study 

behavioral issues instead of relying on just one data source.

IMPACT: This research project demonstrated one or more 

methods of using data from various sources to better understand 

road-user behavior. The concept of combining and using 

behavioral data from multiple sources is relatively new, and this 

work will pave the way for others to follow. Results from this 

project showed many benefits of combining data to better 

understand behavior issues. Integration of human behavior 

collected using different methods could lead to faster design 

and testing of safety countermeasures and new geometric 

designs, resulting in fewer crashes and potentially saved lives. 

The integration of different human behavior data also could 

provide safe and effective methods for studying and testing 

emerging connected-vehicle and automation technologies..

RESOURCES: Several publications resulted from this RAP 

research. They are outlined below.

Romo, A., Mejia, B., & Yang, C. Y. D. (2014). Utilizing various data sources for 

surface transportation human factors research: workshop summary 

report (Publication No. FHWA-HRT-14-077). FHWA Turner–Fairbank 

Highway Research Center, McLean, VA. Available online:

http://www.fhwa.dot.gov/advancedresearch/pubs/14077/index.cfm.

Romo, A., Yang, C. Y. D. (2015). The science and art of putting drivers 

under the microscope. Public Roads, 78(5). Federal Highway 

Administration Pub. No. FHWA-HRT-15-003. Available online:

https://www.fhwa.dot.gov/publications/publicroads/15marapr/04.cfm.

The relationship between research methods and impacting factors. Source: FHWA

Note: There are five empirical factors that can be used to evaluate the quality of data and the 

analysis performed. The five factors are: driving states, risk, level of control, measurements, and 

validity. The five factors presented in this figure explain the similarities, differences, advantages, and 

disadvantages among the different research methods.
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  37

Human Behavior and Travel Choices

PROJECT: Operational and Safety Analyses of Alternative Intersection/Interchange Designs

ASSOCIATE: Nopadon Kronprasert

SCHOOL: Virginia Polytechnic Institute and State University

PERIOD: November 2012–April 2014

OBJECTIVE: To evaluate operational and safety impacts when implementing alternative intersection and interchange designs. 

ADVISER: Wei Zhang, FHWA Office of Safety Research and Development

SUMMARY: Transportation and traffic professionals working on 

today’s highway improvement projects face daunting pressures 

from the needs of different stakeholders to provide safe, 

efficient, and cost-effective intersections and interchanges. 

FHWA recently proposed several alternative intersection and 

interchange designs to improve the safety- and mobility-related 

issues across the Nation. These new intersections and 

interchanges include displaced left-turn, median U-turn, and 

restricted-crossing U-turn intersections, as well as the doublecrossover diamond interchange. It is important to evaluate how 

efficient the new designs will be and to identify the traffic 

conditions that will deliver the best cost–benefit performance. In 

accordance with this objective, Nopadon Kronprasert’s research 

project investigated operational and safety measures and 

evaluation procedures, analyzed proposed designs at different 

evaluation sites, and developed mathematical models for 

evaluating operational and safety measures for different 

intersection and interchange designs. Kronprasert used a 

microscopic trafficsystems simulation of model characteristics 

and behaviors to evaluate the performance of alternative 

designs. This simulation is a cost-effective method to compare 

different designs, predict potential impacts, replicate real-world 

phenomena, and provide valuable insights into the effects on 

operational and safety performance. Kronprasert conducted his 

research based on problems derived from real projects. As part 

of the technical support to State departments of transportation, 

he performed traffic simulation studies of three double-crossover 

diamond interchanges, three restricted-crossing U-turn 

intersections, and six mini-roundabout projects.

A screen capture of an intersection based on Nopadon Kronprasert’s simulation input. © Wei Zhang, 

Nopadon Kronpraset, and Jason Williams.
38  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

Human Behavior and Travel Choices

IMPACT: As of October 2014, at least one restricted-crossing 

U-turn and three mini-roundabouts Kronprasert worked on have 

been constructed and opened to traffic. Many of the performance 

predictions stated in his research are being verified in the field. 

The results will help analysts understand the relationships 

between the features of alternative designs and their operational 

and safety benefits. The research will ultimately help practitioners 

to find the best course of action when implementing alternate 

designs and also will help highway engineers and the public 

understand the benefits and impacts.

RESOURCES: Several publications and papers resulted from this 

RAP research. They are outlined below. 

Krause, C., N. Kronpraset, J. Bared, and W. Zhang. 2015. “Operational 

Advantages of Dynamic Reversible Left-Lane Control of Existing 

Signalized Diamond Interchanges.” Journal of Transportation 

Engineering 141, no. 5. 

Zhang, W., and N. Kronprasert. 2014. “The ABCs of Designing RCUTs.” 

Public Roads 78, no. 2: 9–13. 

Zhang, W., and N. Kronprasert. 2014. “Unlock DDI’s Capacity Potential by 

Implementing Relaxed Bowtie, Superstreet, And Quadrant Road 

Design at Adjacent Signal Intersections.” Presented at the Second 

International Conference on Access Management. Shanghai, China: 

Transportation Research Board. 

Zhang, W., and N. Kronprasert. 2014. “Unlock Diverging Diamond 

Interchange’s Capacity Potential Using Relaxed Bowtie Design at 

Adjacent Signalized Intersection.” Presented at the Transportation 

Research Board’s Alternative Intersections and Interchanges 

Symposium. Salt Lake City, UT: Transportation Research Board. 

Zhang, W., and N. Kronprasert. 2014. “Crash Prediction Models for Rural 

Restricted Crossing U-Turn Intersections.” Presented at the 

Transportation Research Board’s Alternative Intersections and 

Interchanges Symposium. Salt Lake City, UT: Transportation 

Research Board.

Zhang, W., and N. Kronprasert. 2014. “Mini-Roundabout Case Studies.” 

Presented at the Transportation Research Board’s International 

Roundabout Conference. Seattle, WA: Transportation Research Board. 

Zhang, W., N. Kronprasert, and J. Gustaffson. 2014. “Unclog Local Network 

Congestion Using High-Capacity Mini-Roundabouts: A Feasibility 

Study.” Presented at the 93rd Annual Meeting of the Transportation 

Research Board. Washington, DC: Transportation Research Board. 

Lochrane, T., N. Kronprasert, J. Bared, D. Dailey, and W. Zhang. 2014. 

“Determination of Mini-Roundabout Capacity in the United States.” 

Journal of Transportation Engineering 140, no. 10. 

Zhang, W., and N. Kronprasert. 2016. “System intersections—Concepts, 

Simulation Studies, And Potential Applications.” Presented at the 

International Conference on Transportation and Development 2016. 

Houston, TX: American Society of Civil Engineers. 

Zhang, W., and N. Kronprasert. 2014. “Unlock DDI’s Capacity by ReRouting Left-Turns at Nearby Intersections.” Presented at the 

Conference on Access Management Theories and Practices. Shanghai, 

China: Transportation Research Board. https://ascelibrary.org/

doi/10.1061/9780784413869.020.

An aerial view of a two-cloverleaf highway interchange from a simulation video created by Nopadon 

Kronprasert. © Wei Zhang, Nopadon Kronpraset, and Jason Williams.
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  39

Human Behavior and Travel Choices

PROJECT: Utilizing Naturalistic Driving Data and Highway Safety Information System to Advance Highway Crash Data Modeling Concepts and Methods

ASSOCIATE: Kun-Feng Wu

SCHOOL: Pennsylvania State University

PERIOD: July 2012–June 2013 

OBJECTIVE: To advance safety analysis using surrogate safety measures and improve the evaluation of 

intervention effectiveness. 

ADVISER: Craig P. Thor, FHWA Office of Safety Research and Development

SUMMARY: Kun-Feng Wu’s research project builds on 40 years of 

research concerning the development of crash surrogates for 

assessing traffic safety. The term crash surrogate refers to a crash 

or near-crash event, defined in this project by a set of driver or 

event attributes, driving environment, and kinematic variables. 

Researchers use crash surrogates because crashes are rare events, 

making it hard to draw statistically valid conclusions about 

contributing factors. Surrogate event counts can be used to predict 

the expected number of crashes and identify sites with promise for 

improvement by knowing the number of surrogate events at each 

intersection. Wu investigated a sequence of statistical tests with 

the overall goal of validating surrogate events and facilitating their 

use in enhanced safety analyses. Wu used raw naturalistic driving 

data, including vehicle kinematic, video, and location information, 

to produce sets of specific conditions that identify crashes and 

near crashes (i.e., surrogate events). Wu tested the procedure on a 

small, 100-car naturalistic driving study dataset, conducted by the 

Virginia Tech Transportation Institute, with successful results. A 

second validation procedure compared these results with the 

number of crashes observed in HSIS data, a multistate database 

that contains crash, roadway inventory, and traffic volume data for 

a select group of States. Wu’s research extends research already 

completed in the joint use of crash events and surrogate events in 

a structured framework. His research project specifically compared 

surrogate analyses of countermeasure effectiveness and sites with 

improvement potential to comparable HSIS studies. Wu applied 

the same methods to evaluate the Integrated Vehicle-Based Safety 

System dataset (an initiative designed to develop and field test an 

integrated safety system on light vehicles and commercial trucks). 

In addition, Wu expanded the procedures to include diagnostic 

analytical techniques borrowed from medical science. These 

statistical methods allow for a more accurate assessment of the 

presence of surrogate events.
40  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

Human Behavior and Travel Choices

IMPACT: Specific conditions for defining surrogate events could be 

further tested and studied through driving performance 

assessment and may ultimately lead to improved understanding of 

inappropriate driving behaviors, driver responses, roadway design, 

and operational deficiencies. In addition, crash surrogate studies 

could ultimately reduce the time needed to develop a sufficient 

sample size for analysis. These studies would enable researchers to 

develop models with greater prediction precision and understand 

the factors that contribute to crashes. Decreasing the time and 

increasing the precision of factors that contribute to crashes allow 

faster development and implementation of better countermeasures, 

thereby reducing crashes and potentially saving lives.

RESOURCES: The papers that resulted from this RAP research are 

outlined below.

Wu, K. F., Thor, C., & Ardiansyah, M. N. (2016). Identify sequence of events 

likely to result in severe crash outcomes. Accident; Analysis and 

Prevention, 96:198–207.

Wu, K. F., & Thor, C. (2015). Method for the use of naturalistic driving 

study data to analyze rear-end crash sequences. Transportation 

Research Record, Journal of the Transportation Research Board, 

2518(2518):27–36.

 

A schematic that relates the crash progression process to the etiological process of disease progression. © Kun-Feng Wu
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  41

Technology for Assessing Performance Technology for Assessing Performance

PROJECT: Artificial Intelligence-Aided Bridge Condition Assessment System Using Deep Learning Approaches

ASSOCIATE: Heng Liu 

SCHOOL: University of Maryland

PERIOD: January 2019–November 2021

ADVISER: Jean Nehme, FHWA Office of Infrastructure Research and Development

SUMMARY: During his RAP tenure, Heng Liu developed two 

condition forecast models for the FHWA Long-Term Bridge 

Performance InfoBridgeTM web portal. He also published one 

peer-reviewed journal paper and made several presentations at 

the Transportation Research Board annual meeting and various 

FHWA meetings and webinars.

RESOURCES: His research work resulted in one published peerreviewed journal paper:

Liu, H., J. Nehme, P. Lu. 2021. “An Application of Convolutional Neural 

Network for Deterioration Modeling of Highway Bridge Components 

in the United States.” Structure and Infrastructure Engineering. 

https://doi.org/10.1080/15732479.2021.1979597, last accessed 

November 17, 2021.

PROJECT: Integration of Machine Learning into Long Term Pavement Performance Prediction Models

ASSOCIATE: Adel Rezaei-Tarahomi 

SCHOOL: Iowa State University

PERIOD: June 2019–July 2021 

ADVISER: Jean Nehme, FHWA Office of Infrastructure Research and Development

SUMMARY: During his RAP tenure, Adel Rsaei-Tarahomi did 

the following:

• Leveraged machine learning, artificial neural networks, and 

data analytics to employ unstructured and structured data 

toward pavement performance predictions for saving 

materials and time spent during experimental lab tests.

• Created optimized XGBoost model pipeline in Python by using 

TensorFlow, Keras, and Scikit-learn’s GridSearch that achieved 

98 percent accuracy, which is a 20–30 percent improve ment 

in binder performance prediction accuracy compared to the 

conventional regression models.

• Devised and automated a method for converting 360 degreeimages of the circumference of cylindrical asphalt specimen 

to a 2D flat image by using image-stitching technique, 

OpenCV, Pandas, and NumPy in Python.

• Conceptualized and developed a machine learning-based web 

application by Python, Dash, Flask, HTML, and CSS and 

deployed it to the Heroku cloud platform.

• Developed an analytical PowerBI dashboard to visualize the 

impacts of COVID-19 restrictions on travel speed and collision 

in the state of Maryland.
42  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

Technology for Assessing Performance

PROJECT: Developing Probabilistic Bridge Deterioration Models Based on Nondestructive Evaluation of Concrete Bridge Decks 

 Using Multiple NDE Technologie

ASSOCIATE: Raka Goyal

SCHOOL: University of North Carolina at Charlotte

PERIOD: September 2018–July 2021

OBJECTIVE: To develop a framework for multivariable probabilistic bridge deterioration model. 

ADVISER: Jean Nehme, FHWA Office of Infrastructure Research and Development

SUMMARY: Raka Goyal developed a framework for multivariable 

probabilistic bridge deterioration model development using the 

entire national bridge inventory (NBI) data from 1983 to 2019 for 

more than 6000,000 bridges nationwide. The proportional hazards (PH) bridge deterioration models are based on a combination of survival analysis and Markov-chain theory. She developed 

50-yr forecasts of bridge component condition ratings for all 

bridges and culverts in the NBI using the developed nationwide 

PH bridge deterioration models. Her work enabled implementation of the condition rating forecast dashboard on FHWA InfoBridge web portal. Goyal also developed the PH bridge network 

performance forecast models for bridges nationwide, enabling 

InfoBridge users to develop 50-yr network performance forecasts for selected groups of bridges from the entire NBI. Her 

work enabled the development of the performance forecast 

dashboard of FHWA InfoBridge.

RESOURCES: Several publications and papers resulted from this 

RAP research. They are outlined below.

Goyal, R., Whelan, M., and T. Cavalline. 2020. “A Multivariate Proportional 

Hazards-Based Probabilistic Model for Bridge Deterioration 

Forecasting.” Journal of Infrastructure Systems 26, no. 2: 04020007. 

Goyal, R., Whelan, M. and T. Cavalline. 2019. “Duration-based Forecasting 

of Bridge Condition with Non-Parametric Kaplan-Meier Survival 

Functions.” Presented at the 5th International Conference on Smart 

Monitoring, Assessment and Rehabilitation of Civil Structures. 

Potsdam, Germany: German Society for Non-Destructive Testing.

Goyal, R, and J. A. Nehme. n.d. “Bridge Network Performance—SurvivalBased Models” (web page). https://infobridge.fhwa.dot.gov/Content/

Documents/Models/Bridge_Network_Performance_Forecast_

Survival_Based_Models.pdf, last accessed November 8, 2021.

Goyal, R. n.d. “Bridge Condition Rating Forecast-Survival-Based Models” 

(web page). https://infobridge.fhwa.dot.gov/Content/Documents/

Models/Bridge_Component_Condition_Forecast_Survival_Based_

Models.pdf, last accessed November 8, 2021.

Goyal, R. 2021, “Bridge Condition Forecasting-Survival-Based Models”

100th Annual Meeting of the Transportation Research Board. 

Washington, DC: Transportation Research Board.

Goyal, R. 2020. “Nationwide Survival-Based Bridge Deterioration Models.” 

Presented at the 99th Annual Meeting of the Transportation Research 

Board. Washington, DC: Transportation Research Board.

Goyal, R. 2019. “Proportional Hazards-based Probabilistic Models for 

Bridge Deterioration Forecasting.” Presented at the 98th Annual 

Meeting of the Transportation Research Board. Washington, DC: 

Transportation Research Board.
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  43

Technology for Assessing Performance

PROJECT: Numerical and experimental study of air-coupled impact-echo and ultrasonic surface waves for in situ condition monitoring of concrete structures

ASSOCIATE: Mohammadmehdi Nikirashidi

SCHOOL: Georgia Institute of Technology

PERIOD: August 2018–April 2020

OBJECTIVE: To assess the overall condition of bridge decks using the Jensen-Shannon divergence of nondestructive 

evaluation (NDE) data.

ADVISER: Hoda Azari, FHWA office of Infrastructure Research and Development

SUMMARY: Nikirashidi’s research work involved: 

• Assessing the overall condition of bridge decks using the 

Jensen-Shannon divergence of nondestructive evaluation 

(NDE) data. This research aimed to quantify the differences 

between NDE results represented in the form of probability 

distributions, and use such information to develop a bridge 

deck rating index. To this end, the results from multiple NDE 

technologies on the Haymarket, VA bridge deck were represented in the form of probability distributions. The deviation of these probability distributions from ideal distributions representing an intact condition of the bridge deck, 

was quantified using the square root of the Jensen-Shannon divergence (√JSD). An NDE rating index, in the range of 

0–10, was suggested using √JSD, and it was used to develop 

the deterioration curve of the deck. Results demonstrated 

the effectiveness of this approach for the assessment of the 

overall condition and deterioration modeling of bridge decks.

• Conducting quality control of nondestructive evaluation data 

collected with a robotic-assisted bridge inspection tool 

(RABIT). This research aimed to draw attention to the importance of the data reliability issue during the automated 

nondestructive evaluation of bridge decks. RABIT-collected 

data suffering from the malfunction of the system were 

presented, and a procedure for the improvements of the 

impact-echo results was suggested. For electrical resistivity data, a protocol to investigate the local outliers was 

proposed. It was suggested to include a companion contour map representing the reliability of data with each 

NDE technology.

• Using noise reduction of a multichannel acoustic scanning 

tool (MAST) and developing a signal processing procedure 

for the analysis of acoustic data to overcome the practical 

challenges associated with the traditional acoustic techniques. Special care was taken to minimize the acoustic 

noise and the vibration of components within the device. A 

signal processing procedure was suggested to amplify and 

capture the signal of interest. The performance of MAST on 

a lab-produced reinforced concrete slab and slabs obtained 

from a bridge deck was assessed. The system inspected the 

slabs at a high speed, and it was capable of detecting shallow and deep delamination in concrete slabs. Results suggested great potential for the field application of the system.

• Performing fully noncontact acoustic measurements. In this 

research, a noncontact transducer excited the surface of 

concrete using pulses of a broadband chirp signal (5–55 

kHz), and a micromechanical systems microphone received 

the signal. In the presence of shallow delamination, a clear 

delay in the group velocity of signals with frequencies between 20–30 kHz was observed. Results, interpreted in the 

context of lab wave, suggest mode conversion of surface 

waves in the presence of delamination.

RESOURCES: Several publications and papers resulted from this 

RAP research. They are outlined below.

Rashidi, M., H. Azari, and J. Nehme. 2019. “Assessment of the Overall 

Condition of Bridge Decks Using the Jensen-Shannon Divergence of 

NDE Data.” NDT and E International 110, no. 2020: 102204.

Hoda, A., and R. Mehdi. 2019. “Speeding Up Bridge Deck Evaluations.” 

Public Roads 83, no.3.
44  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

Technology for Assessing Performance

PROJECT: Networks for Interpretation of Nondestructive Evaluation of Bridges

ASSOCIATE: Sattar Dorafshan

SCHOOL: Utah State University

PERIOD: June 2011–May 2013 

OBJECTIVE: To investigate the feasibility of using deep learning models (DLMs) for autonomous subsurface defect detection in 

bridge decks using Impact Echo has been investigated.

ADVISER: Hoda Azari

SUMMARY: Impact echo (IE) is a common NDE method to 

detect subsurface defects in concrete bridge decks. The 

conventional approach for analyzing the IE data requires user 

expertise to define analysis parameters that could hinder broad 

field implementation. In this paper, the feasibility of using deep 

learning models for autonomous subsurface defect detection in 

bridge decks using IE has been investigated. A set of exiting IE 

data from eight laboratory-made reinforced concrete bridge 

specimens with artificial defects, constructed at the FHWA 

Advanced Sensing Technology NDE laboratory, were annotated 

based on the presence and type of subsurface defects. Two 

annotated IE datasets were generated: A total number of 2016 

of IE data from bare specimens, and a total of 1,827 IE data 

from specimens with overlay. Several convolutional neural 

networks based on deep learning, were developed, trained, 

tuned, and tested on the annotated datasets. The most 

successful model was able to produce accuracy of 0.88 by 

classifying 0.70 of the defects and 0.95 of the sound regions 

correctly in the bare specimens. The proposed 1DCNN was 

superior to previous machine learning models that were 

previously used for IE classification. The proposed 1D CNN was 

the most successful in detecting debonding and subsurface 

defects in the overlay dataset; it achieved an average accuracy 

of 0.68 on the cement overlay specimens and 0.58 for asphalt 

overlay specimens. Maps of the defects in decks and defects in 

overlay were generated using the DLMs and were compared to 

the conventional method for analyzing the IE data. The 1D CNN 

produced the most accurate defect maps while successfully 

detected sound, debonded, and defected region. The results of 

this study showed the feasibility and the potentials of the DLMs 

for subsurface defect detection using IE for the first time. 

IMPACT: The models produced in this project were the first 

successful implementation of deep learning for NDE data 

interpretation. The results are promising and showed deep 

learning and AI can be used for full bridge deck evaluation by 

detection of subsurface defects in an autonomous manner. 

RESOURCES: Several publications and papers resulted from this 

RAP research. They are outlined below.

Dorafshan, S., and H. Azari. 2020. “Deep learning models for bridge deck 

evaluation using impact echo.” Construction and Building Materials

263: 120109.

Dorafshan, S., and H. Azari. 2020. “Evaluation of Bridge Decks with 

Overlays Using Impact Echo, a Deep Learning Approach.” Automation 

in Construction 113: 103133.

Dorafshan, S., and H. Azari. 2020 “Artificial Intelligence for IE and GPR 

Data Analysis.” Presented at the 101th Annual Meeting of the 

Transportation Research Board. Washington, DC: Transportation 

Research Board.

Dorafshan, S., and H. Azari. “Federal Highway Administration NDE Program 

Vision for 21st Century Bridge Data.” Presented at the Bridging Big 

Data 2019 Workshop. Lincoln, NE: University of Nebraska-Lincoln.

Dorafshan, S., and H. Azari, H. 2019. “Advanced NDE Data Analysis 

Procedure Including the Use of Deep Learning” Presented at the 19th 

US-Korean Roads Workshop. Washington, DC: Federal Highway 

Administration and Republic of Korea Ministry of Land, Infrastructure 

and Transport.
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  45

Technology for Assessing Performance

PROJECT: Air-Coupled Acoustic and Ultrasonic Arrays for Concrete Nondestructive Test Methods

ASSOCIATE: Hajin Choi

SCHOOL: University of Illinois

PERIOD: January 2017–February 2018

OBJECTIVE: To develop air-coupled acoustic and ultrasonic arrays for non-destructive evaluation of concrete damage or property.

ADVISER: Hoda Azari, FHWA Office of Infrastructure Research and Development

SUMMARY: The large size of concrete structures, the time 

required to adequately inspect them, and the rough texture of 

the material pose challenges to the use of acoustic nondestructive test (NDT) methods for condition assessment of 

highway infrastructure. This research project by Hajin Choi 

aimed to develop an air-coupled acoustic and ultrasonic array 

as a contact-free NDT alternative to the conventional acoustic 

technology. Air-coupled sensors measure leaky Rayleigh 

waves without physical contact on the concrete being tested. 

The research encompassed four tasks. First, Choi developed 

an air-coupled acoustic array for two testing methods, impactecho (IE) and ultrasonic waves (USW). Both methods generate 

stress waves and measure how they reflect off the concrete to 

identify flaws in the material. After developing the air-coupled 

system, Choi evaluated the system by collecting signal data 

from a test sample in FHWA’s specimen library. He evaluated 

the speed of data collection, the signal-to-noise ratio, and the 

accuracy of test results. Next, Choi analyzed USW from the 

hybrid test setup and used the data to develop a linear formula 

for predicting various types of concrete damages. For the final 

task of the project, Choi applied the new air-coupled acoustic 

array and NDT parameters to a robotic platform for inspecting 

bridge decks to evaluate their practical use, and he described 

the tests, results, and analysis in a final report.

IMPACT: The research illustrates the potential of air-coupled 

acoustic arrays to increase the speed of conventional NDT for 

condition assessment of highway infrastructure. The possible 

field uses include IE and USW testing.

RESOURCES: Several publications and papers resulted from this 

RAP research. They are outlined below.

Choi, H., & Azari, H. (2017). Guided wave analysis of air-coupled impact-echo 

in concrete slab. Computers and Concrete, 20(3), 257–262.

Choi, H., Sadegh, S., & Azari, H. (2017). The improvement of impact-echo 

method using hybrid system and guided wave analysis. Proceedings in 

International Conference on Maintenance and Rehabilitation of 

Constructed Infrastructure Facilities.

Choi, H., Sadegh, S., & Azari, H. (2017). NDE application of air-coupled 

array for thickness of concrete slab. Proceedings in International 

Ultrasonics Symposium.

Choi, H., Sadegh, S., & Azari, H. (2017). Application of air-coupled ultrasonic 

array system and f-k domain analysis for delamination-like defect 

detection in bridge deck. Presented at the IEEE International Ultrasonic 

Symposium, Washington, DC.

Choi, H., Sadegh, S., & Azari, H. (2017). The improvement of impact-echo 

method using hybrid system and guided wave analysis. Presented at the 

International Conference on Maintenance and Rehabilitation of 

Constructed Infrastructure Facilities, Seoul, Korea.
46  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

Technology for Assessing Performance

PROJECT: Prediction of Pavement Temperature Profiles Using Surface Temperatures: An Analytical Approach With Model 

Validation Based on Long-Term Pavement Performance Data

ASSOCIATE: Dong Wang

SCHOOL: University of Illinois at Urbana–Champaign

PERIOD: June 2011–May 2013 

OBJECTIVE: To derive and field-validate an easily implementable algorithm for predicting temperature profiles in paving 

materials. 

ADVISER: Yan “Jane” Jiang, FHWA Office of Infrastructure Research and Development

SUMMARY: The mechanical properties of paving materials are 

usually temperature-dependent, but to accurately back-calculate 

the elastic moduli of pavement layers (i.e., the pavement’s 

resistance to being deformed elastically when a force is applied to 

it), time-dependent pavement temperature must be known. 

Knowing the temperature profile allows researchers to better 

characterize the properties of paving materials and predict 

pavement responses under traffic and environmental loadings. 

Dong Wang’s research project investigated a new method for 

predicting time-dependent pavement temperature profiles with 

limited inputs. There are currently three main methods for 

predicting temperature profiles: statistics-based models, 

numerical, and analytical approaches. These existing methods 

require large databases of climatic, meteorological, and 

geographical data and several other inputs to predict temperatures 

for the algorithms to operate effectively. Current pavement-testing 

methods do not easily obtain the required climatic data; thus, 

these algorithms are subsequently limited in their ability to predict 

pavement temperature profiles. Wang focused his research effort 

on infrared pavement surface temperature data that can be easily 

obtained during pavement testing. This improved approach makes 

it possible to develop an entirely new algorithm for predicting a 

time-dependent pavement temperature profile that requires very 

limited inputs when compared with previous algorithms. The only 

inputs needed for this new method are infrared surface 

temperatures, initial pavement temperature profile, pavement 

geometry, and thermal properties of layer materials. Most 

important, unlike previous methods, no climatic data are required. 

To validate the new algorithm, when there are so many different 

types of pavement structures across regions with varied climatic 

conditions, an extremely large temperature dataset is required. To 

meet this requirement, Wang used data from the Long-Term Pavement

Performance (LTPP) Program database for model validation.

IMPACT: Wang’s research is expected to greatly benefit field 

engineers in characterizing pavement temperature for the purpose 

of analyzing and interpreting testing data. In addition, it could lead 

to high savings on pavement evaluation costs.

Histogram of asphalt pavement subsurface temperature difference (predicted (Tp)-measured (Tm) 

temperature difference). Source: FHWA.
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  47

Technology for Assessing Performance

RESOURCES: Several publications and papers resulted from this 

RAP research. They are outlined below.

Wang, D. (2013). Prediction of asphalt pavement temperature profile during

FWD testing: A simplified analytical solution with model validation 

based on LTPP data. Journal of Transportation Engineering, 139(1), 109–113.

Wang, D. (2012). Analytical approach to predict temperature profile in a 

multilayered pavement system based on measured surface temperature 

data. Journal of Transportation Engineering, 138(5), 674–679.

Wang, D. (2013). Simplified analytical approach to predict asphalt pavement 

temperature. Journal of Materials in Civil Engineering, 27(12).

Wang, D. (2013). Prediction of asphalt pavement temperature profile 

during FWD testing: simplified analytical solution with model validation 

based on LTPP data. Journal of Transportation Engineering, 139(1).

Wang, D. (2012, July 5–7). Prediction of time-dependent temperature 

profile in a slab. Paper presented at the Third Advanced Workshop on 

Innovations and Modeling for Sustainable and Resilient Concrete 

Pavements, Quebec, Canada.

Wang, D. (2013, January 13–17). Assessing BELLS3 equation in predicting 

asphalt layer temperature profile based on the latest LTPP FWD 

temperature data. Paper presented at the 92nd Transportation Research 

Board Annual Meeting, Washington, DC.

Wang, D. (2013, January 13–17). Simplified analytical approach to predict 

temperature profile within a PCC slab during FWD testing. Paper 

presented at the 92nd Transportation Research Board Annual 

Meeting, Washington, DC.

Wang, D. (2012, January 22–26). Model validation based on LTPP data to 

predict asphalt temperature profile. Paper presented at the 91st 

Transportation Research Board Annual Meeting, Washington, DC.

Wang, D. (2012, January 22–26). Prediction of temperature profile in a 

multilayered pavement system using measured surface temperature 

data: An analytical approach. Paper presented at the 91st Transportation 

Research Board Annual Meeting, Washington, DC.
48  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM
EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM  |  49

Getting Involved with the EAR Program

To take advantage of a broad variety of scientific and engineering discoveries, the EAR 

Program involves both traditional stakeholders (State department of transportation 

researchers, University Transportation Center researchers, and Transportation Research 

Board committee and panel members) and nontraditional stakeholders (investigators 

from private industry, related disciplines in academia, and research programs in other 

countries) throughout the research process.

Learn More

For more information, see the EAR Program website at https://highways.dot.gov/

research/exploratory-advanced-research. The site features information on research 

solicitations, updates on ongoing research, links to published materials, summaries of 

past EAR Program events, and details on upcoming events.
50  |  EAR PROGRAM—RESEARCH ASSOCIATES PROGRAM

FHWA-HRT-22-024

HRTM-30/12-21(WEB)E

EAR Program Results

The EAR Program strives to develop partnerships with the public and private 

sectors because the very nature of the EAR Program is to apply ideas across 

traditional fields of research and stimulate new approaches to problemsolving. 

The program bridges basic research (e.g., academic work funded by National 

Science Foundation grants) and applied research (e.g., studies funded by State 

departments of transportation). In addition to sponsoring EAR Program 

projects that advance the development of highway infrastructure and 

operations, the EAR Program is committed to promoting cross-fertilization 

with other technical fields, furthering promising lines of research, and 

deepening vital research capacity.

Recommended Citation: Federal Highway Administration, 

Research Associates Program 2021 (Washington, DC: 2021) 

https://doi.org/10.21949/1521709.