EAR PROGRAM RESEARCH RESULTS  |  a

EAR Program 

Research 

Results

Updated through 2021
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.

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: DMask—an identity masking system—exchanges the driver’s head in 

naturalistic driving video data with a computer-generated avatar head that 

preserves key facial landmarks as well as information about head pose, 

facial expression, and direction of gaze. This gives researchers access to 

important facial cues while protecting the identity of volunteer drivers (see 

page 56). © SRI International.

Right: Two-dimensional light detection and ranging, or LIDAR, uses 

satellite-based lasers to provide accurate lane-level information about 

vehicle positioning in urban driving environments. Source: FHWA.
EAR Program Research Results

The Exploratory Advanced Research (EAR) Program addresses 

the need for longer term, higher risk research with the potential for 

transformative improvements to transportation systems. The EAR 

Program seeks to leverage expertise and advances in science and 

engineering to create breakthrough solutions to critical 

transportation issues. 

Broad scientific participation and extensive coverage of advanced 

ideas and new technologies are secured by engaging stakeholders 

throughout the EAR Program’s processes—not only in identifying 

and scoping topics but also in ensuring the technical quality of 

sponsored research through expert panels and in communicating 

research results.

This catalog of results documents the output of that effort, a 

critical link in the chain of research, development, and deployment 

of new technology and practices necessary for the United States 

to have the best transportation system in the world for decades to 

come. The EAR Program focuses investments in areas where 

changes in science and engineering can dramatically lead toward 

making the highway system safer, more durable, and more efficient:

• Connected Highway and Vehicle System Concepts.

• Breakthrough Concepts in Materials Science.

• Human Behavior and Travel Choices.

• Technology for Assessing Performance.

• New Technology and Advanced Policies for Energy

and Resource Conservation.

Exploratory Advanced Research . . . 

Next-Generation Transportation Solutions

EAR PROGRAM RESEARCH RESULTS  |  1

The Exploratory Advanced Research Program
2  |  EAR PROGRAM RESEARCH RESULTS

The results of EAR Program-funded projects can lead to new 

fundamental insights into transportation-related issues as well as new 

research methods, models, or data. Such breakthroughs can 

accelerate applied research, new system concepts, or prototypes, 

including laboratory testing and limited field testing. The EAR 

Program does not fund projects through the commercialization or 

deployment stage. Rather, the research community must take up the 

results with the support of other funding sources. The Federal 

Highway Administration (FHWA) is committed to transitioning the 

results of EAR Program-funded projects and actively demonstrates 

results to audiences critical to continuing the research and 

development cycle. Through 12 solicitations, the EAR Program has 

awarded 101 projects (19 of which are ongoing) involving both 

government and academic researchers. These projects represent the 

investment of $99 million in FHWA funds and leverage $28 million in 

matching funds. The following pages contain summary descriptions 

of the results of selected, recently completed research investigations.

The Exploratory Advanced Research Program
EAR PROGRAM RESEARCH RESULTS  |  3

Introduction 6

Connected Highway and Vehicle System Concepts 

Truck Platooning and Connectivity 7

Heavy Truck Cooperative Adaptive Cruise Control 9

Partial Automation for Truck Platooning 10

Cooperative Adaptive Cruise Control (CACC) Human Factors Study 11

Advanced Vehicle Tracking Technologies: Sensing and Monitoring 

Individual Vehicles in Traffic Flow 13

Using Cooperative Adaptive Cruise Control to Form 

High-Performance Vehicle Systems 14

Simulations of Connected Vehicle (CV) Technologies 16

Building a Hardware-in-the-Loop Simulation Testbed 18

Assistive Technologies for Visually Impaired Persons 20

Intersection Control for Autonomous Vehicles 23

Advanced Traffic Signal Control Algorithms 24

Advanced Freeway Merge Assistance: Harnessing the Potential

of Connected Vehicles 25

Next-Generation Vehicle Positioning in GPS-Degraded 

Environments for Vehicle Safety and Automation Systems 26

Innovative Approaches for Next-Generation Vehicle Positioning 27

Development of Enhanced Safety Systems Based on GPS/INU System 28

Development and Evaluation of Selected Mobility Applications for VII 29

Layered Object Recognition System for Pedestrian Collision Sensing 30

Breakthrough Concepts in Materials Science 

Novel Alternative Cementitious Materials for Development

of the Next Generation of Sustainable Transportation Infrastructure 31

Nanoscale Approaches for Inhibiting Corrosion: Green Advanced

Coatings for Application on Steel Structures and Bridges 32

Inorganic Polymers: Novel Ordinary Portland Cement-Free Binders

for Transportation Infrastructure 33

Novel Development of Bio-Based Binder for Sustainable Construction 35

Mechanisms of Hydration and Setting of Ordinary Portland Cement 

in Simple and Complex Systems 37

Paving the Way for Greener Highways: Extending Concrete’s

Service Life through Multiscale Crack Control 39

Greatly Increased Use of Fly Ash in Hydraulic Cement Concrete

for Pavement Layers and Transportation Structures 41

High-Performance Stress-Relaxing Cementitious Composites

for Crack-Free Pavements and Transportation Structures 42

Human Behavior and Travel Choices

Comparative Effectiveness of Alternative Smartphone-Based

Nudges to Reduce Cellphone Use While Driving 43

Contents
Contents (cont.)

InterchangeSE: A Federated Multimodal Simulation Environment 

for Studying Interactions Between Different Modes of Travel 44

Freight Data Development and Enhancement to Support National 

Freight Transportation Analysis, Modeling, and Forecasting Practices 45

Behavioral-Based (or Agent-Based) National Freight Demand Modeling 45

Developing Connected Simulation to Study Interactions 

Between Drivers, Pedestrians, and Bicyclists 46

Knowledge Discovery in Massive Transportation Datasets 47

Applications of Knowledge Discovery in Massive Transportation Data: 

The Development of a Transportation Research Informatics 

Platform (TRIP) 48

High-Performance Data Fusion for Transportation Safety Analytics 49

Video Analytics Research Projects 49

Machine Learning for Automated Analysis of Large Volumes 

of Highway Video 51

Automated Feature Extraction Projects 52

Automated Identity-Masking Projects 55

Multimodal Connectivity Options for a Future, Seamless, 

Transportation System 57

Agent-Based Approach for Integrated Driver and Traveler 

Behavior Modeling 58

Evolutionary Agent System for Transportation Outlook (VASTO) 59

Design of a Completely New Approach for a National Household-Based,

Long-Distance Travel Survey Instrument 61

Making Driving Simulators More Useful for Behavioral Research 62

Behavioral Sciences Approach to Testing, Validating, and Establishing 

Best Practices for Alternative Highway Revenue Collection 63

Impact of Automated Transit and Pedestrian/Bicycling Facilities 

on Urban Travel Patterns 64

Megaregional Travel 65

Driver Behavior in Traffic 66

Modeling the Urban Continuum in an Integrated Framework:

Location Choice, Activity-Travel Behavior, and Dynamic 

Traffic Patterns 68

Technology for Assessing Performance

Development of Structural Carbon Nanotube-Based Sensing 

Composites for Rehabilitation of Deteriorating and 

Fatigue-Damaged Steel Bridges 69

Virtual Nondestructive Evaluation Laboratory for Highway Structures 70

Self-Sensing Adaptive Material for a New Generation of Multifunctional

Bridge-Bearing Systems 71

Cooperating Camera Platforms for Ultra-High-Resolution 

Traffic Surveillance and Autonomous Event Detection 72

4  |  EAR PROGRAM RESEARCH RESULTS
EAR PROGRAM RESEARCH RESULTS  |  5

Contents (cont.)

Remote, Wireless Camera Systems for Environmental Monitoring

of Transportation Corridors 73

Assessing the Structural Health of America’s Highway Bridges: Effective

Wireless Sensor Systems to Monitor Structural Health 

and Detect Damage 75

Ultra Low-Power Wireless Sensing System 77

Multipurpose Wireless Sensors for Asset Management 

and Health Monitoring of Structures 78

A Remote, Self-Sustained System for Monitoring 

Water Quality Near Highways 79

Nanoscale Sensors for Structural Health 80

Flexible Skin, Areal Shear Stress, and Pressure-Sensing System

for Experimental Bridge Scour Research 82

Development of Stiffness-Measuring Device for Pad Foot 

Roller Compaction 83

New Technology and Advanced Policies for Energy and Resource 

Conservation

Creating Productive Roadways: Developing an Advanced Energy

Production, Storage, and Distribution System 84

Results from Research Associateship Program

Cost-Benefit Analysis of Connected and Automated Vehicle Operations 86
6  |  EAR PROGRAM RESEARCH RESULTS

Introduction

From an origin in the Department of Agriculture’s Office of Public 

Road Inquiry over 120 yr ago, the FHWA has been committed to 

shepherding innovations from theory to application. Over the 

past decade, the FHWA EAR Program has focused on early-stage, 

higher risk research where the Federal government can 

demonstrate the potential of new ideas for improving the safety, 

reliability, and condition of the Nation’s roadways. Examples 

include the following:

• Early vehicle aerodynamic and traffic modeling and physical 

testing of technology to control truck spacing in two- and threetruck platoons that showed potential to reduce fuel use.

• The characterization and modeling of new materials that can 

supplement and substitute the use of portland cement, providing 

more choices for building and reconstructing the structures and 

pavements that connect people across the United States.

• The application of experimental economics to daily travel, 

combined with the development of agent-based models, can 

result in improved travel time reliability at a system level.

• New sensor systems that monitor conditions on and off the 

roadway, from identifying cracks in structures before they are 

visible to aiding the movement of wildlife under and 

over roadways.

With the rapid change of communications, machine learning, 

automation, and other technologies, having a program that 

leverages cutting-edge concepts to make travel safer, easier, and 

more cost effective is increasingly important.

Kelly Regal, Ph.D.

Associate Administrator for Research, Development, and Technology

Federal Highway Administration

EAR PROGRAM RESEARCH RESULTS  |  6
EAR PROGRAM RESEARCH RESULTS  |  7

Connected Highway and Vehicle System Concepts

Research projects in this focus area emphasize long-term needs for reaching 

critical safety and mobility goals by developing theory for and assessing the 

feasibility of systems that leapfrog current technological approaches for 

linking infrastructure with future vehicle- and personal mobility technology. 

While people may update mobile devices every 2 yr, the average age of 

private motor vehicles is now over 10 yr. Roadway signals, infrastructure 

sensors, truck trailers, and other elements of the highway system have even 

longer lifecycles before being replaced. 

Accordingly, new systems need to work with existing equipment while 

anticipating future technologies. Connected highway and vehicle system 

research needs to consider the open nature of transportation and legacy 

components and processes as well as the distributed nature of asset 

ownership and operations.

Truck Platooning and Connectivity

Fuel costs make the movement of freight over long distances an increasingly 

costly venture. Even small improvements in highway efficiency could reduce 

the costs per mile significantly, so new technologies and strategies that foster 

such efficiency would be economically beneficial. One such approach is 

incorporating CACC into Class 8 tractor-trailers, the kind typically used in 

freight transportation. CACC consists of radar, Global Positioning System 

(GPS) applications, video cameras, and data exchange operating within a 

dedicated short-range communication (DSRC) system. It allows multivehicle 

“platoons” of trucks to communicate with each other so they can 

automatically adjust engine and brake usage to maintain speed and 

separation distance. The EAR Program funded two research projects that 

explored the use of CACC in freight trucks.

RESOURCES: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/17045/index.cfm.

 Bevly, D., C. Murray, A. Lim, R. Turochy, et al. 2015. Heavy Truck 

Cooperative Adaptive Cruise Control: Evaluation, Testing, and 

Stakeholder Engagement for Near Term Deployment: Phase 

One Final Report. Washington, DC: 
8  |  EAR PROGRAM RESEARCH RESULTS

Connected Highway and Vehicle System Concepts

Federal Highway Administration. http://eng.auburn.

edu/~dmbevly/FHWA_AU_TRUCK_EAR/FHWA_AuburnDATP_

Phase1FinalReport, last accessed November 1, 2021.

 Bevly, D., C. Murray, A. Lim, R. Turochy, et al. 2017. Heavy Truck 

Cooperative Adaptive Cruise Control: Evaluation, Testing, and 

Stakeholder Engagement for Near Term Deployment: Phase 

Two Final Report. Washington, DC: Federal Highway 

Administration. http://eng.auburn.edu/~dmbevly/FHWA_AU_

TRUCK_EAR/FHWA_AuburnDATP_Phase2FinalReport, 

last accessed November 1, 2021.

 Yang, S., S. E. Shladover, X. -Y. Lu, J. Spring, et al. 2018. A First 

Investigation of Truck Drivers’ On-the-Road Experience Using 

Cooperative Adaptive Cruise Control. Berkley, CA: University of 

California, Berkley. https://escholarship.org/uc/item/92359572, 

last accessed November 1, 2021. 

 Ramezani, H., S. E. Shladover, X. -Y. Lu, and O. D. Altan. 2018. 

“Micro-Simulation of Truck Platooning with Cooperative 

Adaptive Cruise Control: Model Development and a Case 

Study.” Journal of Transportation Research Board 2672, 

no. 19: 55–65. http://dx.doi.org/10.1177/0361198118793257. 

 Bishop, R., Bevly, D., Humphreys, L., Boyd, S., et al. 2018 

“Evaluation and Testing of Driver-Assistive Truck Platooning: 

Phase 2 Final Results.” TRR, Journal of Transportation Research 

Board 2615, no. 1: 11–18. http://dx.doi.org/10.3141/2615-02.

IMPACT: By using platooning algorithms with CACC devices for these two 

projects, researchers demonstrated fuel savings at highway speeds. They also 

concluded that CACC could improve traffic flow once deployment of the 

technology achieves sufficient market penetration in freight trucks. In 

addition to cutting fuel costs, this greater efficiency could curtail emissions 

and reduce the workload for both drivers and vehicles. It would enhance the 

adaptive cruise control currently available in many tractor-trailers.
EAR PROGRAM RESEARCH RESULTS  |  9

Connected Highway and Vehicle System Concepts

PROJECT: Heavy Truck Cooperative Adaptive Cruise Control

INSTITUTIONS: Auburn University, American Transportation Research Institute, 

Meritor, Inc., Peloton Technology, and Peterbilt Truck 

COMPLETED: 2019 

OBJECTIVE: To quantify the system performance of CACC in a two-truck 

platoon and evaluate the potential fuel savings that could be 

achieved by implementing the technology.

RESULTS: This team’s research analyzed the business case, vehicle aerodynamics, 

and traffic modeling for CACC-equipped truck platoons by conducting on-road 

tests with two-truck platoons at the Transportation Research Center, Inc., track in 

Ohio. With CACC controlling the distance between the two trucks, the research 

showed peak fuel savings of 5 percent for the lead truck, 10 percent for the trailing 

truck, and 7 percent at peak for the platoon. When the trailing truck stayed 50 ft 

behind the lead truck (a more realistic distance based on surveys that assessed 

driver comfort), the trailing truck saved more than 10 percent in fuel. Fleets that 

average more than 500 mi per trip would yield the highest return on investment 

in CACC. Researchers found that private and large, over-the-roadline truck fleets 

would most likely adopt CACC first. Market penetration in truck platoons would 

need to reach 60 percent to improve overall traffic flow along specific routes.

CACC incorporates video cameras, a DSRC system for intervehicle data 

exchange, and GPS. © n.d. Auburn University, College of Engineering.
10  |  EAR PROGRAM RESEARCH RESULTS

Connected Highway and Vehicle System Concepts

PROJECT: Partial Automation for Truck Platooning

INSTITUTIONS: University of California, Berkeley, Partners for Advanced 

Transportation Technology, Cambridge Systematics, and Volvo 

Technologies of America

COMPLETED: 2018 

OBJECTIVE: To develop and implement the technology for a three-truck 

platooning system using vehicle-to-vehicle communications 

and radar/vision-based sensors.

RESULTS: University of California, Berkeley researchers tested CACC in threetruck platoons that were operated in real California highway traffic. The driver of 

the lead truck operated it either manually or with partially automated adaptive 

cruise control, while the two trailing trucks featured fully automated CACC. 

Signals from a DSRC system operated at 5.9 GHz synchronized the platoon using 

a “constant time gap” strategy that separated the trucks proportionally based on 

their actual speed. The technology made it possible for the third truck to “see” 

the lead truck and for the platoon to respond in near-zero time to maintain the 

specified gaps between trucks. In addition to testing how the trucks in the platoon 

interacted with each other, researchers gauged how they responded to other 

vehicles changing lanes and getting between two trucks in the platoon. When 

that happened, the system automatically designated a new lead vehicle for the 

platoon, and it adjusted the following gap and strategy.

Three Class 8 trucks equipped with CACC during field test. 

© University of California, Berkeley.
EAR PROGRAM RESEARCH RESULTS  |  11

Connected Highway and Vehicle System Concepts

PROJECT: Cooperative Adaptive Cruise Control (CACC) Human 

Factors Study 

INSTITUTIONS: Leidos, Inc.

COMPLETED: 2017

OBJECTIVE: To examine how using a CACC affected drivers’ workload, 

propensity to distraction, level of physiological arousal, ability 

to avoid a crash, merging abilities, and trust in the system 

through four experiments.

RESOURCES: Summary report of all four experiments at https://www.fhwa.

dot.gov/publications/research/safety/17025/index.cfm.

 Report for Cooperative Adaptive Cruise Control Human Factors 

Study: Experiment 1—Workload, Distraction, Arousal, and Trust

https://www.fhwa.dot.gov/publications/research/safety/16056/

index.cfm.

 Report for Cooperative Adaptive Cruise Control Human Factors 

Study: Experiment 2—Merging Behavior at https://www.fhwa.

dot.gov/publications/research/safety/16057/index.cfm.

 Report for Cooperative Adaptive Cruise Control Human Factors 

Study: Experiment 3—The Role of Automated Braking and 

Auditory Alert in Collision Avoidance Response at https://www.

fhwa.dot.gov/publications/research/safety/16058/index.cfm.

 Report for Cooperative Adaptive Cruise Control Human Factors 

Study: Experiment 4—Preferred Following Distance and 

Performance in An Emergency Event at https://www.fhwa.dot.

gov/publications/research/safety/17024/index.cfm.

RESULTS: The results of experiment 1 and experiment 3 suggest that CACC could 

provide a substantial safety benefit as long as a salient alarm is triggered when 

the driver needs to intervene. Such an alarm is advisable even if CACC is 

implemented with full braking authority because the driver might want to steer 

rather than brake in some crash-imminent circumstances.
12  |  EAR PROGRAM RESEARCH RESULTS

Connected Highway and Vehicle System Concepts

Experiment 2 results strongly suggest that CACC should be accompanied with 

merge or steering assist to allow drivers to comfortably and safely merge into the 

smaller gaps between vehicles. Although most drivers in experiment 3 eventually 

learned how to adjust their speed to merge into smaller gaps, the learning curve 

included more collisions than would be desirable.

Experiment 4 results suggest that drivers’ preferences for following distance 

(gap) do not affect driver performance relative to an automated gap. Drivers 

adjust their performance appropriately for the actual gap, and designers do not 

need to be concerned about individual gap preferences related to driving 

performance.

Experiments 1, 3, and 4 assessed driver workload with and without CACC. In all 

three experiments, CACC was perceived to reduce driver workload.

The research suggests that CACC can reduce driver workload while enhancing 

safety. However, CACC is only one of many vehicle automation technologies in 

development or early deployment. The role of the driver will be in flux for years 

to come as putative safety and convenience automation technologies proliferate. 

Human factors research will need to focus on the ever-changing role of the driver 

and the resulting effects on the performance of these driver-vehicle systems

IMPACT: CACC has the potential to improve traffic flow, increase driver confidence, 

and make shorter vehicle-following distances possible. These experiments help 

understand how drivers interact with CACC, advancing its transition to 

real-world deployment.
EAR PROGRAM RESEARCH RESULTS  |  13

Connected Highway and Vehicle System Concepts

PROJECT: Advanced Vehicle Tracking Technologies: Sensing and 

Monitoring Individual Vehicles in Traffic Flow

INSTITUTIONS: Honeywell Corporation, University of Minnesota, and 

Time Domain Holdings 

COMPLETED: 2017 

OBJECTIVE: To develop a traffic-monitoring system that can recognize and 

track individual vehicles rather than aggregated vehicle 

patterns, without relying on vehicle-based technology that 

provides information about location or movement.

RESOURCE: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/17051/index.cfm. 

RESULTS: Researchers developed an Advanced Vehicle Tracking System (AVTS) 

that uses ultrawide band (UWB) radar to identify and track individual vehicles as 

they move through traffic. The system consists of four-radar units, a tracking 

computer, software that recognizes vehicle targets, and a user interface display. 

The four radars in each unit are arranged as rectangles, with each one capable of 

receiving its own reflected UWB signal and the signals of the other three. The 

radars in each unit fire sequentially as vehicles pass, transmitting a combined 200 

scans/s to a tracking computer and the software, which is called a vehicle 

recognition engine. The software identifies each vehicle by size, direction, and 

speed as a unique track on the user display, and it shares key information with 

adjacent radar rectangles as vehicles 

move through the AVTS. Initial 

testing showed that the radar units, 

which are housed in weatherproof 

enclosures, are most effective when 

mounted on poles 20 ft high and with 

an antenna angle of 15 degrees.

IMPACT: The AVTS enhances the 

collection of complex traffic data by 

focusing on individual vehicles rather 

than aggregated vehicle patterns, 

and it does not rely on vehicle-based technology. The UWB radar at the core of 

the system offers a potential solution to the shortcomings of three other 

vehicle-sensing technologies—inductive loop detectors, microwave radar 

sensors, and video imaging systems.

Battery-powered AVTS radar housed in 

weatherproof case on adjustable-height 

tower. Source: FHWA.
14  |  EAR PROGRAM RESEARCH RESULTS

Connected Highway and Vehicle System Concepts

PROJECT: Using Cooperative Adaptive Cruise Control to Form 

High-Performance Vehicle Systems 

INSTITUTIONS: University of California, Berkeley, California Partners for 

Advanced Transportation Technology and Technical 

University of Delft, Netherlands 

COMPLETED: 2017

OBJECTIVE: To overcome the key technical challenges to implementing 

cooperative adaptive cruise control, clearing the way for 

operational field tests that will be needed to enable 

commercialization of the technology. 

RESOURCES: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/16044/16044.pdf. 

 Liu, H., X. Kan, S. E. Shladover, X.-Y., Lu, et al. 2018. “Modeling 

Impacts of Cooperative Adaptive Cruise Control on Mixed 

Traffic Flow in Multi-Lane Freeway Facilities.” Transp. Res. Part 

C Emerg.Technol. 95: 261–279. 

http://dx.doi.org/10.1016/j.trc.2018.07.027.

 Liu, H., L. Xiao, X. Kan, S. E. Shladover, et al. 2018. Using 

Cooperative Adaptive Cruise Control (CACC) to Form HighPerformance Vehicle Streams. Final Report. Washington, DC: 

Federal Highway Administration. https://escholarship.org/uc/

item/8pw857gb, last accessed November 16, 2021.

 Kan, X., H. Liu, S. E. Shladover, and X. -Y. Lu. 2018. Using 

Cooperative Adaptive Cruise Control (CACC) to Form HighPerformance Vehicle Streams. Microscopic Traffic Model 

Calibration and Validation. Berkeley, CA: University of 

California, Berkeley. https://escholarship.org/uc/item/5jx899dv, 

last access November 16, 2021.

RESULTS: To bridge gaps in knowledge about cooperative adaptive cruise 

control (CACC), researchers for this project identified various operational 

concepts, developed simulation models to test those concepts, and analyzed 

the results to inform future vehicle experiments. The concepts encompassed 

multiple strategies for operating CACC platoons. Created with a new program 

called Microscopic Open Traffic (MOTUS) and the commercially available 
EAR PROGRAM RESEARCH RESULTS  |  15

Connected Highway and Vehicle System Concepts

Aimsun system, the team’s simulation models represented different realworld road conditions (urban, rural, highways, and arterial) and rates of 

traffic. Researchers at both the University of California at Berkeley and the 

Technical University of Delft in the Netherlands used the simulation models to 

assess how various ways of deploying CACC impacted traffic flow and fuel 

consumption. The flow assessments included increases achieved in traffic 

capacity per highway lane, reductions in traffic disturbances, and savings in 

travel times along arterial roadways. Splitting the simulation tests between 

the two university teams enabled them to validate each other’s work. 

Researchers also tested their simulation models at FHWA’s Saxton 

Transportation Operations Laboratory in McLean, VA.

IMPACT: Researchers used data from 

this project and two generations of 

tests at California Partners for 

Advanced Transportation Technology 

to verify the feasibility of various 

CACC strategies. Their work also 

expanded understanding of how 

drivers choose to use CACC and 

clarified the safety implications of the 

technology. Their simulations 

advanced efforts to test and evaluate 

CACC on the road, the next step 

toward deploying the technology in 

the real world. FHWA test vehicles 

simulate a “platoon” of vehicles using 

cooperative adaptive cruise control. FHWA test vehicles simulate a “platoon” 

of vehicles using CACC. Source: FHWA.
16  |  EAR PROGRAM RESEARCH RESULTS

Connected Highway and Vehicle System Concepts

Simulations of Connected Vehicle (CV) Technologies

CV technologies that make it possible for vehicles and roadway infrastructure 

like traffic signals to “talk” to each other can enhance safety, improve 

mobility, shorten travel time, and reduce the environmental impact of traffic. 

To achieve those goals, the engineers who are developing CV applications 

need a reliable, standardized way to test the technologies in various 

simulated conditions. These software simulations consider vehicle speed, 

traffic volume, road conditions, signal timing, and other details at every stage 

of traffic flow. They also show how a change to any one simulated element 

affects the other elements in the scenario. To foster further study of CV 

technologies, the EAR Program funded two research projects that 

incorporated actual vehicle performance data into modeling and 

simulation platforms.

RESOURCES: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/17044/index.cfm.

 Zulkefi, M. A. M., P. Mukherjee, Z. Sun, J. Zheng, et al. 2017. 

“Hardware-in-the-Loop Testbed for Evaluating Connected 

Vehicle Applications.” Transp. Res. Part C Emerg. Technol. 78: 

50–62. https://doi.org/10.1016/j.trc.2017.02.019.

 Songchitruksa, P., S. Sunkari, I. Ugalde, J. Rosca, et al. 2018. 

“Interlinking Vissim and ns-3 for Connected Vehicle Simulation: 

Case Study of Intelligent Dilemma Zone Avoidance.” Journal of 

the Transportation Research Board 2619, no. 1: 36–43. 

http://dx.doi.org/10.3141/2619-04.

IMPACT: The insights gained from these in-the-loop simulations will enhance 

the ability of traffic engineers to accurately and quickly model complex traffic 

environments. This realistic modeling in turn will foster the development of 

CV applications and their future deployment in real traffic.
EAR PROGRAM RESEARCH RESULTS  |  17

Connected Highway and Vehicle System Concepts

PROJECT: New Approaches for Testing Connected Highway and 

Vehicle Systems

INSTITUTIONS: Texas A&M University Transportation Institute (TTI), Battelle 

Memorial Institute, and Siemens Corporation 

COMPLETED: 2017

OBJECTIVE: To develop a simulation environment that incorporates data 

from a connected vehicle and signals in a roadway network 

into a simulation. 

RESULTS: : Researchers demonstrated a simulation platform called Connected 

Vehicle Assessment Simulation (CONVAS) that merges features of the VISSIM 

traffic simulation software with features of ns-3, an open-source wireless 

communications simulation. CONVAS integrates data from actual operating 

roadway elements at a TTI highway test facility and the Connected Vehicle 

Testbed at the Turner–Fairbank Highway Research Center (TFHRC). Novel 

“hardware-in-the-loop” features of the platform send this data into a 

simulation model. CONVAS then shows how real and simulated elements like 

vehicle speed, traffic volume, road conditions, and signal timing interact in 

real time. The platform can model interactions for many CV scenarios, 

including a disruption in the wireless communications needed to keep the 

various elements in the CV environment talking to each other. 

CONVAS incorporates data from actual connected vehicles and traffic signals (left) into 

a simulation that displays the interaction among the vehicles and infrastructure. 

© Texas A&M Transportation Institute.
18  |  EAR PROGRAM RESEARCH RESULTS

Connected Highway and Vehicle System Concepts

PROJECT: Building a Hardware-in-the-Loop Simulation Testbed

INSTITUTIONS: University of Michigan and University of Minnesota 

COMPLETED: 2017

OBJECTIVE: To develop a hardware-in-the-loop system that simulates a 

vehicle engine in the lab for various connected and 

autonomous vehicles (CAV) operation scenarios and precisely 

measures the fuel consumption, and to use sophisticated 

measuring devices in the lab. 

RESULTS: For CV technologies to fulfill their potential, engineers must be able 

to run simulations that can realistically measure vehicle fuel economy and 

emissions. Researchers for this project developed a hardware-in-the-loop 

system that uses a real engine in the lab, which is exactly the same type as the 

engine used in the CAV at TFHRC, and the traffic simulation software VISSIM 

to achieve that goal. There are four key parts in the system—a gas engine, a 

hydrostatic dynamometer, VISSIM, and a laboratory-housed hardware testbed. 

The dynamometer controls the engine’s load and output to a powertrain 

model, while the software transmits the road and traffic conditions and the 

vehicle-specific performance data that researchers select. The data is sent over 

the Internet to the hardware testbed, which precisely measures actual 

emissions and fuel consumption. This in-the-loop simulation system is a 

simpler and less costly form of analysis than equipping multiple test vehicles 

with large precision measurement devices. 

RESOURCES: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/17044/index.cfm. 

 Xiao, J., S. L. Joseph, X. Zhang, B. Li, et al. 2015. “An Assistive 

Navigation Framework for the Visually Impaired.” IEEE 

Transactions on Human-Machine Systems 45, no. 99: 635–640. 

 Joseph S. L., J. Xiao, X. Zhang, B. Chawda, et al. 2015. “Being 

Aware of the World: Toward Using Social Media to Support the 

Blind With Navigation.” IEEE Transactions on Human-Machine 

Systems 45, no. 3: 399–405. 

 Tian, L., C. Yi, and Y. Tian. 2015. “Detecting Good Quality 

Frames in Videos from Mobile Camera for Blind Navigation.” 

Journal of Computer Vision and Image Processing 5, no. 10. 
EAR PROGRAM RESEARCH RESULTS  |  19

Connected Highway and Vehicle System Concepts

IMPACT: The research demonstrated the potential of hardware-in-the-loop for 

cooperative driving automation making it faster and safer to test physical 

components in complex scenarios. Hardware-in-the-loop now is integrated in 

the CARMA platform used by FHWA, academic institutions, and privatesector researchers.

The in-lab testbed ensures that the engine has the same load as the engine running in 

the field-test CAV with an onboard unit (OBU) under various operation scenarios. The 

engine’s emission and fuel consumption are precisely measured by the lab’s powerful 

devices. Source: FHWA.
20  |  EAR PROGRAM RESEARCH RESULTS

Connected Highway and Vehicle System Concepts

Assistive Technologies for Visually Impaired Persons

For roughly 2 million American adults with impaired vision, independent 

travel and active interactions with the surrounding environment present 

significant daily challenges. The EAR Program funded three research projects 

to examine new technology to:

 • Help visually impaired persons identify important objects, movements, 

and text information in the environment.

 • Develop solutions to help visually impaired people find their way through 

indoor and outdoor environments.

 • Extend navigation guidance for visually impaired travelers in areas where 

GPS data is not reliable.

COMPLETED: 2016 

RESOURCES: Fact sheet at http://www.fhwa.dot.gov/publications/research/

ear/15040/index.cfm.

 Details at http://www.its.dot.gov/research_archives/attri/index.htm.

 Tian, L., C. Yi, and Y. Tian. 2015. “Detecting Good Quality Frames in 

Videos from Mobile Camera for Blind Navigation.” Journal of 

Computer Vision and Image Processing 5 no.10.

 Pierce, J. D., and D. M. Bevly. 2015.“A Centralized Approach to 

Pedestrian Localization Using Multiple Odometry Sources.” 

Presented at the 2015 International Technical Meeting of The 

Institute of Navigation. Dana Point, CA: Institute of Navigation.

 Shao, Y., M. Azrin, M. Zulkefli, S. Zongxuan, et al. 2019. “Evaluating 

Connected and Autonomous Vehicles Using a Hardware-In-TheLoop Testbed and a Living Lab.” Transportation Research Part C: 

Emerging Technologies 102: 121–135. https://doi.org/10.1016/j.

trc.2019.03.010.

IMPACT: These projects demonstrated the potential for advances in mobile 

sensors, computing, and communications to aid people that are blind or have 

visual impairments with outdoor and indoor navigation and wayfinding. Since the 

completion of the projects, there has been continued investment increasing the 

technological maturity and the range of environments—from airport concourses 

to signalized pedestrian crossings—where travelers can benefit.
EAR PROGRAM RESEARCH RESULTS  |  21

Connected Highway and Vehicle System Concepts

PROJECT: Intelligent Situation Awareness and Navigation Aid 

for Visually Impaired Persons

INSTITUTION: City College of the City University of New York 

COMPLETED: 2016 

OBJECTIVE: To develop technologies that detect and track stationary and 

moving objects, read signs, and monitor movement to support 

wayfinding and navigation of visually impaired people through 

indoor and outdoor environments. 

RESULTS: : Researchers for this project focused on exploring and developing 

awareness and navigation technologies that can recognize stationary objects; 

read and recognize important text and signage; and detect, track, and 

represent moving objects and other dynamic changes. The system includes a 

wearable device with integrated sensors, such as cameras, three-dimensional 

orientation sensors and pedometers, and a unit that will provide auditory and 

tactile guidance. Ultimately, this system will provide the user with a 

navigation map, register landmarks on the map, and generate a verbal 

description or tactile feedback for blind users to obtain a global perception 

of their environment.

Researchers demonstrate the Intelligent Situation Awareness Navigation Aid at U.S. Department of Transportation headquarters. 

Source: FHWA.
22  |  EAR PROGRAM RESEARCH RESULTS

Connected Highway and Vehicle System Concepts

PROJECT: Navigation Guidance for People with Vision Impairment

INSTITUTION: TRX Systems, Inc. 

COMPLETED: 2016 

OBJECTIVE: To develop navigational technologies that will localize, track, 

and plan a route for visually impaired users anywhere, including 

areas without access to GPS information. 

RESULTS: Key elements of this research include 

developing a navigational aid that can localize and 

track the location of a blind person anywhere, 

including indoors or in urban areas where GPS data is 

not available or not reliable; planning and adaptively 

updating a route that allows a visually impaired 

person to get to a destination; providing guidance 

through tactile information instead of relying solely 

on auditory instructions; using computer vision 

techniques to find stairs, elevators, hallways, and 

doors to help with navigation; and verifying that the 

user has reached the correct destination.

PROJECT: Extended Event Horizon Navigation and Wayfinding for Blind 

and Visually Impaired Pedestrians in Unstructured Environments

INSTITUTION: Auburn University 

OBJECTIVE: To develop a navigation system that can fill the gaps where GPS 

data is not sufficient and present information to visually impaired

users when it is needed, whether they are indoors or outdoors. 

RESOURCES: Project details at https://highways.dot.gov/research/projects/

extended-event-horizon-navigation-wayfinding-blind-visuallyimpaired-pedestrians-unstructured.

RESULTS: Researchers for this project demonstrated the utility of a specialized 

pedestrian navigation device that integrates GPS, inertial measurement units, 

visual odometry, and stored and updated map data to accurately capture the 

movements of a pedestrian user in environments such as parks, airports, 

intersections, and general pedestrian zones. Where GPS is not available, the 

inertial measurement and odometry units can continue to provide accurate 

positioning and navigation information. The device communicates with the user 

through a system that combines vibration and tactile sensations with an iPhone 

app to indicate path and navigation information.

The navigation aid 

developed by 

TRX Systems. 

© TRX Systems, Inc.
EAR PROGRAM RESEARCH RESULTS  |  23

Connected Highway and Vehicle System Concepts

PROJECT: Intersection Control for Autonomous Vehicles

INSTITUTION: University of Texas at Austin

COMPLETED: 2013

OBJECTIVE: To develop, test, and evaluate (in simulation with a full-sized 

robotic vehicle) traffic-control algorithms for autonomous 

intersection management (AIM) and autonomous vehicles. 

RESOURCES: Research reports and simulation videos at 

http://www.cs.utexas.edu/~aim/.

RESULTS: The project team demonstrated 

that AIM, in conjunction with autonomous 

vehicles communicating with each other 

and with roadside equipment, can 

dramatically improve intersection 

efficiency, reduce traffic delays, and 

alleviate traffic congestion. The research 

team developed and tested traffic control 

algorithms for autonomous vehicles and 

evaluated them first in simulation only 

and then in simulation integrated with a 

full-size robotic vehicle. Among several 

important project innovations are 

the following:

• Parameters for an autonomous vehicle to safely cross an intersection in an 

AIM system.

• A setpoint-scheduling algorithm to control arrival time, velocity, and position 

of an autonomous vehicle by sending control parameters to its brake and 

throttle actuators.

• Prioritization schemes to allocate intersection access and keep traffic moving. 

• A preemptive, fail-safe protocol to prevent collisions when mechanical 

failures occur.

IMPACT: As automated vehicles come onto the market, results from this project 

have the potential to provide a safe system for improving traffic flow and 

dramatically reducing fuel use and mobile-source emissions at intersections.

An AIM simulation, which shows virtual 

and real vehicles at an intersection. 

White vehicles have a reservation to 

enter the intersection; yellow vehicles 

do not. The green vehicle is a proxy, 

representing the real-world location of 

the autonomous vehicle. Source: FHWA. 
24  |  EAR PROGRAM RESEARCH RESULTS

Connected Highway and Vehicle System Concepts

PROJECT: Advanced Traffic Signal Control Algorithms 

INSTITUTIONS: California Department of Transportation; California PATH, 

University of California, Berkeley; Center for Environmental 

Research and Technology, University of California, Riverside; 

and BMW Group 

COMPLETED: 2013

OBJECTIVE: To develop advanced signal control strategies based on 

connected vehicle data; that is, real-time information on a 

vehicle’s location, speed, and characteristics, as well as 

communication to the signal control infrastructure.

RESOURCES: Project details at https://highways.dot.gov/research/projects/

advanced-traffic-signal-control-algorithms. 

 Technical report at https://www.ocf.berkeley.edu/~xuanyg/doc/

Argote_Christofa_Xuan_Skabardonis_2012_TRB.pdf.

 Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/11044/11044.pdf.

RESULTS: The research team developed and tested several signal control 

applications, including strategies to minimize the occurrence of red-light running. 

The team’s prediction algorithm for DARE (dynamic all-red extension when a 

high probability of collision exists) achieved a correct detection and activation 

rate over 95 percent. Strategies to reduce arrival flow during the yellow interval, 

which influences red-light running in coordinated arterials, were also effective. To 

minimize fuel consumption, the team developed an in-vehicle speed advisory 

system that achieved fuel savings of over 13 percent in field tests. The team also 

proposed new methods for estimating common arterial measures of effectiveness 

for different penetration rates of connected vehicles. In one example, the team 

found that to accurately estimate intersection queue length in lighter traffic 

conditions, 80 percent of vehicles need to have connectivity, but in oversaturated 

conditions, only 10 percent need to be equipped. This finding indicates that 

connective traffic control strategies may be possible in the most congested 

networks before connected vehicles are ubiquitous. 

IMPACT: The project results show great potential to advance real-time signal 

control strategies in some cases, with low levels of new technology adoption. 

Improved efficiency will reduce travel time, frequency and length of stops, fuel 

consumption, and harmful emissions.
EAR PROGRAM RESEARCH RESULTS  |  25

Connected Highway and Vehicle System Concepts

PROJECT: Advanced Freeway Merge Assistance: 

Harnessing the Potential of Connected Vehicles

INSTITUTION: University of Virginia Center for Transportation Studies 

COMPLETED: 2012

OBJECTIVE: To develop and evaluate candidate freeway merge-assistance 

systems that might improve the efficiency and safety of freeway 

merges in a connected vehicle environment. 

RESOURCE: Project details and final report at https://highways.dot.gov/

research/projects/advanced-freeway-merge-assistanceharnessing-potential-connected-vehicles.

RESULTS: The project team developed four algorithms that use connected-vehicle 

data to improve freeway merging strategies: lane-level variable speed limit, lanechanging advisory, gap-responsive on-ramp signal, and merging control. The 

team evaluated the algorithms within a connected vehicle simulation environment 

that simulates both vehicle movement and communications. The lane-level 

variable speed limit approach, lane-changing advisory, and gap-responsive 

onramp signal algorithms did not produce statistically significant improvement, 

although they showed potential. The merge-control algorithm, however, 

generated statistically significant benefits in average speed (23.6 percent 

increase), travel time (11.5 percent decrease), delays (17.9 percent decrease), and 

miles traveled (2.4 percent increase) within the connected vehicle environment. A 

sensitivity analysis of market penetration rates revealed that significant system 

improvements occur when 50 percent or more vehicles have connective capabilities.

IMPACT: These results will 

help transportation agencies 

understand the value of 

connected vehicle 

technology as it emerges 

and may eventually lead to 

freeway merge areas with 

greater capacity and 

fewer crashes. Freeway merge control example. Within the 

merging area, the acceleration of the vehicles 

is controlled: leading (green, no change), 

entering (blue, acceleration), and following (red, 

deceleration). Source: FHWA.
26  |  EAR PROGRAM RESEARCH RESULTS

Connected Highway and Vehicle System Concepts

PROJECT: Next-Generation Vehicle Positioning in GPS-Degraded 

Environments for Vehicle Safety and Automation Systems

INSTITUTIONS: Auburn University, Kapsch TrafficCom, Pennsylvania State 

University, and Stanford Research Institute

COMPLETED: 2012

OBJECTIVE: To provide ubiquitous, precise positioning in regard to vehicle 

safety and automation in the presence of GPS degradation. 

RESOURCES: Final report, presentations, and video at http://www.eng.

auburn.edu/~dmbevly/FHWA_AU_EAR2/.

 Project details at https://highways.dot.gov/research/projects/

next-generation-vehicle-positioning-global-positioningsystem-gps-degraded-environments-vehicle.

RESULTS: The project team developed an integrated vehicle positioning system 

in which subsystems with complementary 

strengths are fused to provide precise 

positioning data in environments where 

one or more of the subsystems could fail. 

The subsystems assessed were GPS; inertial 

navigation systems (INS); camera and light 

detection and ranging (LIDAR) lane 

departure warning systems; a dedicated, 

short-range communications, distanceestimation system; visual odometry; and a 

road fingerprinting system. The accuracy and robustness of integrated systems 

were evaluated in test track and roadway scenarios under various weather 

conditions and at various speeds. The subsystems helped to improve lane-level 

accuracy. In live tests, GPS/INS integration provided improved results over 

standalone GPS, particularly in heavy foliage and urban canyon environments, 

and the full system of sensors performed best overall.

IMPACT: New algorithms, data fusion techniques, and ways of handling GPS data 

discovered in the project can support major improvements in vehicle positioning 

performance. Data fusion techniques can produce low-cost, precise positioning, 

allowing for a range of safety and mobility applications that currently would 

require high-cost equipment.

Camera and LIDAR equipment 

mounted on the roof of the test 

vehicle. Source: FHWA.
EAR PROGRAM RESEARCH RESULTS  |  27

Connected Highway and Vehicle System Concepts

PROJECT: Innovative Approaches for Next-Generation Vehicle Positioning 

INSTITUTION: University of California, Riverside 

COMPLETED: 2012

OBJECTIVE: To investigate and test a range of approaches that could provide 

lane-level positioning accuracy in diverse driving environments. 

RESOURCE: Project details at https://highways.dot.gov/research/projects/

next-generation-vehicle-positioning-global-positioningsystem-gps-degraded-environments-vehicle. 

 Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/13059/index.cfm. 

RESULTS: No single positioning technology can meet the requirements for lanelevel positioning across diverse driving environments—each has performance 

limitations. Researchers for this project explored the most promising technologies 

for improving the accuracy, availability, and reliability of vehicle positioning by 

augmenting Global Navigation Satellite System/INS technology. After evaluating 

the performance of aiding technologies (i.e., LIDAR, radar, computer vision, and 

DSRC), the research team developed and tested prototype systems that integrate 

a variety of sensors. The team found that LIDAR and radar technology integrate 

with the quickest processing and response, while terrestrial radio navigation and 

DSRC methods require more time. Radio and DSRC-based methods show great 

promise because implementation costs are relatively low but require further 

development to improve accuracy. The performance of vision-based aiding 

improves with increased sensor cost; however, implementation requires the 

development of onboard feature mapping.

IMPACT: This project’s 

theoretical and experimentally 

demonstrated results will 

facilitate continued rapid 

advancement in vehicle 

positioning technology, 

providing opportunities for 

new safety, mobility, and 

eco-drive applications.

Typical use of two-dimensional LIDAR to aid 

positioning in urban areas. Source: FHWA.
28  |  EAR PROGRAM RESEARCH RESULTS

Connected Highway and Vehicle System Concepts

PROJECT: Development of Enhanced Safety Systems Based on 

GPS/INU System

INSTITUTIONS: Ohio State University, University of Virginia, 

and GNSS Solutions, LLC

COMPLETED: 2012

OBJECTIVE: To test emerging navigation technologies in a simulation 

environment that could lead to better assessment of future 

navigation technology and improved methods for roadway design. 

RESOURCES: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/13065/13065.pdf.

 Dedes, G., G. -B. Dorota, D. Guenther, G. Heydinger, K. Mouskos, 

et al. 2011.“Integrated GNSS/INU, Vehicle Dynamics, and 

Microscopic Traffic Flow Simulator for Automotive Safety.” 

Presented at the 14th International IEEE Conference on 

Intelligent Transportation Systems. Washington, DC: Institute 

of Electrical and Electronics Engineers.

RESULTS: The project team developed an integrated simulation platform to 

evaluate the impact of emerging vehicle positioning and communications 

technologies that provide level positioning at less than 3.9 inches and allow 

connected vehicles and infrastructure to monitor and share safety related 

information. To estimate how system errors, communication delays, and 

communication interruptions affect the timing of warnings, driver perceptions/

reactions, networkwide delays, and safety, the team 

simulated warning scenarios for eight sensor system 

combinations. The team found that error- and delayfree driver warnings reduced the number of conflicts in 

the range of 28 percent to 50 percent. The project 

compared different positioning approaches for overall 

accuracy and for providing the fewest false and 

missing warnings.

IMPACT: Use of the integrated simulation environment

to assess connected vehicle technologies and improve

roadway design can reduce the risk of crashes, 

prevent travel delays, and reduce fuel consumption as 

new systems are implemented. 

CarSim is a vehicle 

simulator utilized by 

Ohio State University 

to develop realistic 

vehicle trajectories.

© Mechanical Simulation Corporation.
EAR PROGRAM RESEARCH RESULTS  |  29

Connected Highway and Vehicle System Concepts

PROJECT: Development and Evaluation of Selected Mobility 

Applications for VII

INSTITUTIONS: California PATH, University of California, Berkeley; and 

California Department of Transportation

COMPLETED: 2011

OBJECTIVE: To develop new strategies to reduce bottlenecks, minimize 

congestion, and maximize throughput by utilizing the capabilities 

of intelligent vehicles and highway infrastructure.

RESOURCES: Liu, H., X. Kan, S. E. Shladover, and R. Ferlis. 2018. “Impact of 

Cooperative Adaptive Cruise Control on Multilane Freeway 

Merge Capacity.” Journal of Intelligent Transportation System

22, no. 3: 263–275.

 Final report at https://dot.ca.gov/-/media/dot-media/

programs/research-innovation-system-information/

documents/task-2138-tsm-a11y.pdf.

RESULTS: The project team modeled, tested, and demonstrated prototype 

wireless communication systems to improve traffic flow by calculating and 

communicating variable speed limits (VSLs) to drivers, achieve higher effective 

lane capacities using CACC, and reduce fuel consumption and increase truck-only 

lane capacity with automated platoons. Their work demonstrated the following:

Variable Speed Limits—In simulation and live tests on I-80, the researchers 

broadcast speeds calculated to prevent traffic flow breakdowns, with promising 

results. VSLs show significant potential to prevent traffic delays.

Cooperative Adaptive Cruise Control—Study results show that CACC could 

substantially increase highway capacity when it reaches moderate to high 

market penetration. Retrofitting non-CACC vehicles with inexpensive “here I am” 

radios could accelerate achievement of these capacity benefits.

Automated Truck Platoon Control—A wireless communications system 

successfully coordinated a platoon of three tractor-trailer trucks traveling at 

53 mi/h and in varied joining and splitting maneuvers. Fuel savings were 

estimated at 10 to 14 percent for the following trucks.

IMPACT: New connected vehicle and highway systems can lead to substantial 

safety, operational, and environmental benefits.
30  |  EAR PROGRAM RESEARCH RESULTS

Connected Highway and Vehicle System Concepts

PROJECT: Layered Object Recognition System for 

Pedestrian Collision Sensing

INSTITUTIONS: Sarnoff Corporation and AutoLiv Electronics America

COMPLETED: 2009

OBJECTIVE: To develop a real-time, in-vehicle, vision-only system to detect 

pedestrians and determine potential collisions with high 

accuracy and minimal false alarms.

RESOURCES: Conference paper at http://onlinepubs.trb.org/onlinepubs/

conferences/2011/RSS/2/Zhang,W.pdf.

 Final report at https://www.fhwa.dot.gov/publications/

research/safety/11056/11056.pdf.

RESULTS: The project team developed an in-vehicle, stereo, vision-based system 

that detects, recognizes, and tracks pedestrians in its field of view. The system uses 

contextual information to reduce false alarms and light-enhancing techniques to 

improve low-visibility detection. Evaluated on publicly available datasets, the 

system matched or exceeded the performance of leading pedestrian detectors, 

tracking pedestrians at vehicle speeds of up to 30 mi/h and distances up to 115 ft 

away under good visibility conditions and up to 82 ft away under reduced visibility, 

with a 90-percent overall positive detection rate. The researchers recommend 

further development to upgrade performance. The feasibility of commercial 

implementation is high since the system uses low-cost components.

IMPACT: Twilight hours are the most dangerous time for pedestrians. Existing 

detection systems, however, have limited effectiveness in low-light conditions. 

New approaches introduced in this study provide superior results in twilight.

Visual output of the pedestrian-detection system as it 

recognizes crossing pedestrians. Source: FHWA.
Breakthrough Concepts in Materials Science

EAR PROGRAM RESEARCH RESULTS  |  31

Advances in instrumentation allow for measuring materials used to construct 

the U.S. highway system at time and length scales previously unknown, 

leading to new insights into fundamental knowledge. Combined with new 

methods for multiscale material modeling, research in this focus area can 

potentially improve the reliability of materials for highway structures and 

pavements.

PROJECT: Novel Alternative Cementitious Materials for Development 

of the Next Generation of Sustainable Transportation 

Infrastructure

INSTITUTIONS: Georgia Institute of Technology, Oklahoma State University, 

Tourney Consulting Group, and U.S. Army Corps of Engineers

COMPLETED: 2019

OBJECTIVE: To increase access to alternative cementitious materials 

(ACMs) as potential replacements for ordinary portland 

cement (OPC) to achieve significant sustainability 

improvements and to take advantage of the special setting 

and durability properties of ACMs.

RESOURCES: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/18031/. 

 Techbrief at https://www.fhwa.dot.gov/publications/research/

ear/16017/index.cfm.

 Project details at https://highways.dot.gov/research/projects/

novel-alternative-cementitious-materials-development-nextgeneration-sustainable-transportation.

RESULTS: Researchers for this three-phase project studied various ACMs as 

potential substitutes for OPC to extend the life of concrete in pavement and bridges. 

The researchers reviewed relevant literature, visited sites to evaluate the long-term 

performance of ACMs, and interviewed producers and users of the materials before 

conducting their own tests of ACMs. Using OPC as a control measure, the researchers 

first looked at nine ACMs—three calcium sulfoaluminate (CSA), one polymermodified CSA, two calcium aluminate (CA), one portland/CA/calcium sulfate 

ternary blend, one chemically activated Class C fly ash (AA1), and one magnesium 

phosphate (MP) binder. For the second phase of work, they narrowed the focus to 

two CSA cements, two CA cements, and AA1 based on the promise they showed for 
Breakthrough Concepts in Materials Science

32  |  EAR PROGRAM RESEARCH RESULTS

use in transportation infrastructure. Tests of those five ACMs within concrete 

gauged their ability to resist physical abrasion, progressive alkali silica reactivity 

deterioration, and other threats. Phase 3 of the project featured more corrosion 

tests, extended lab testing, long-term field exposure studies, and forensic analysis 

of well-aged ACM-based pavements.

IMPACT: ACMs expand the 

options available to designers, 

owners, and contractors of 

concrete-based transportation 

infrastructure. They require 

less energy to create than 

portland cement and generate 

less carbon dioxide, resulting 

in significant sustainability 

improvements, and they may 

be particularly valuable in 

concrete exposed to extreme 

environments. This research 

provides insights that can be used to recommend test methods for ACMs and 

preliminary specifications for their use.

PROJECT: Nanoscale Approaches for Inhibiting Corrosion: Green Advanced

Coatings for Application on Steel Structures and Bridges

INSTITUTION: City College of New York

COMPLETED: 2018

OBJECTIVE: To slow the deterioration of steel infrastructure with safer, 

corrosion-resistant coatings and to develop a model to help 

bridge owners set optimal rehabilitation schedules for 

steel bridges.

RESOURCES: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/13064/index.cfm.

 Project details at https://highways.dot.gov/research/projects/

nanoscale-approaches-inhibiting-corrosion-green-advancedcoatings-application-steel-structures and https://www.fhwa.

dot.gov/publications/research/ear/11034/11034.pdf.

Concrete slump made of an alternative 

cementitious material (calcium sulfoaluminate). 

© College of Engineering, Georgia Institute of 

Technology.
Breakthrough Concepts in Materials Science

EAR PROGRAM RESEARCH RESULTS  |  33

RESULTS: High maintenance and rehabilitation costs are the motivation for 

research into new types of steel coatings that inhibit corrosion, resist scratching, 

and reduce environmental risk. This particular project focused on creating a 

nanotechnology-based coating that meets those requirements at a lower 

lifecycle cost while also being easy to apply, fast to dry, and resistant to 

ultraviolet rays. The first phase of work incorporated nanomaterials into two 

novel coating systems—a polyaniline (PANI) epoxy system with added carbon 

black and a nanoclay-enhanced calcium sulfonate alkyd (CSA) system. 

Researchers compared different concentrations of these coatings with zincrich epoxy primer coatings, which have been common since the 1960s. The 

PANI-epoxy system performed better than the nanoclay-enhanced CSA system 

in corrosion tests, but the latter material had stronger adhesion, dried more 

quickly, and was more resistant to scratching. Phase 2 encompassed tests of 

two alternative additives for the CSA-based system, accelerated testing and 

weathering studies of the PANI and CSA systems, and a 16-mo study of the 

PANI system and the CSA system that performed best.

IMPACT: Nano-enhanced, corrosion-resistant, and environmentally friendly 

coatings for steel could help extend bridge service life and keep the driving 

public safe. By providing insights into the use of nanomaterials in steel coatings, 

this project advanced the lifecycle management of steel bridges. Data from the 

research was used to estimate the lifetime deterioration of structural 

components. The research results could have applications for many steel 

structures besides bridges.

PROJECT: Inorganic Polymers: Novel Ordinary Portland Cement-Free 

Binders for Transportation Infrastructure

INSTITUTIONS: University of California, Los Angeles; University of California, 

Santa Barbara; University of Texas, Austin; and Boral Materials

COMPLETED: 2018

OBJECTIVE: To determine how inorganic polymer binders made from fly 

ash react with certain chemical solutions and improve 

understanding of how those reactions affect binder 

performance and production.

RESOURCES: Gomez-Zamorano, L., M. Balonis, B. Erdemli, N. Neithalath, et 

al. 2017. “C–(N)–S–H and N–A–S–H Gels: Compositions and 
Breakthrough Concepts in Materials Science

34  |  EAR PROGRAM RESEARCH RESULTS

Solubility Data at 25 c and 50 c.” Journal of American Ceramics 

Society 100, no. 6: 2700–2711.

 Kumar, A., Oey, T., Falzone, G., Huang, et al. 2017. “The Filler 

Effect: The Influence of Filler Content and Type on the 

Hydration Rate of Tricalcium Silicate.” Journal of American 

Ceramics Society 100, no. 7: 3316–3328.

 Oey, T., A. Kumar, I. Pignatelli, Y. Yu, et al. 2017 Topological 

Controls on the Dissolution Kinetics of Glassy Aluminosilicates, 

Journal of American Ceramics Society. 100, no. 12: 5521–5527.

 Oey, T., J. Timmons, P. Stutzman, J. W. Bullard, et al. 2017. “An 

Improved Basis for Characterizing the Suitability of Fly Ash as 

a Cement Replacement Agent.” Journal American Ceramics 

Society 100, no. 10: 4785–4800.

 Oey, T., Y. H. Hsiao, E. Callagon, B. Wang, et al. 2017. “Rate 

Controls on Silicate Dissolution in Cementitious Environments.” 

RILEM Tech. Lett. 2: 67–73.

 Krishnan, N. A., B. Wang, G. Falzone, Y. Le Pape, et al. 2016. 

“Confined Water in Layered Silicates: The Origin of Anomalous 

Thermal Expansion Behavior in Calcium-Silicate-Hydrates.” 

ACS Applied Materials & Interfaces 8, no. 51: 35621–35627.

 Oey, T., A. Kumar, G. Falzone, J. Huang, et al. 2016. “The 

Influence of Water Activity on the Hydration Rate of Tricalcium 

Silicate.” Journal of American Ceramics Society 99, 

no. 7: 2481–2492. 

 Pignatelli, I., A. Kumar, M. Bauchy, and G. Sant. 2016. 

“Topological Control on Silicates’ Dissolution Kinetics.” 

Langmuir 32, no. 18: 4434–4439.

RESULTS: Various researchers are striving to develop concrete that uses less 

energy in its manufacture and costs less. This team focused its efforts on 

“cement-free” inorganic polymer binders (IPBs) that could “glue” the raw 

materials in concrete together. They examined fly ash, a byproduct from coalfired power plants, as a potential alternative to ordinary portland cement, the 

traditional binder in concrete. To study how fly ash reacts when introduced 

into certain chemical solutions, researchers developed a molecular design 
Breakthrough Concepts in Materials Science

EAR PROGRAM RESEARCH RESULTS  |  35

strategy. First, they analyzed 

the compositional and physical 

parameters of fly ash to identify 

the desired characteristics for 

producing IPBs. Next, the team 

used solid- and liquid-phase 

nuclear magnetic resonance, 

vertical scanning interferometry, 

and molecular simulations to 

examine at the atomic scale the 

molecular processes and 

products that result when 

cement-free binders react 

under typical conditions. Among other insights, researchers learned how 

chemical species formed in the solutions. In the last phase of research, the 

team used an embedded material properties database to study the evolution 

of IPBs throughout a reaction.

IMPACT: This project contributed to the understanding of how cement-free 

binders made from fly ash may perform in highway infrastructure. Researchers 

developed tools and methodologies that could improve the ability to 

manufacture IPBs and help the construction industry integrate industrial 

byproducts into building materials.

PROJECT: Novel Development of Bio-Based Binder 

for Sustainable Construction

INSTITUTIONS: Washington State University and Pavement 

Preservation Systems

COMPLETED: 2018

OBJECTIVE: To produce a bio-based substance that is comparable or 

superior in performance to petroleum-based asphalt binders 

for use in constructing roads and other similar projects.

RESOURCES: Project details at https://cms7.fhwa.dot.gov/research/projects/

novel-development-bio-based-binder-sustainableconstruction.

 Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/18030/index.cfm.

A three-dimensional image acquired using 

vertical scanning interferometry that shows a 

cluster of fly ash particles. © Henry Samueli 

School of Engineering and Applied Science, 

University of California, Los Angeles.
Breakthrough Concepts in Materials Science

36  |  EAR PROGRAM RESEARCH RESULTS

Researchers created a rotary reactor to simulate the production of the hot-mix 

bio-binder through mixing aggregates with bioasphalt. © 2017 Department of Civil 

and Environmental Engineering, Washington State University.

RESULTS: Researchers for this project mixed waste cooking oil with lignin, a 

byproduct of the paper pulping process, to create a bio-based asphalt binder. To 

develop the binder, the researchers first mixed the waste cooking oil with maleic 

anhydride at 365°F and used iodine as a catalyst. This initiated a chemical reaction 

in the oil to boost its molecular weight, a process known as polymerization. Next, 

the team put the lignin through chemical processes to create an epoxy. Because it 

is more stable at high temperatures, the lignin-derived epoxy makes roads built 

with the bio-based asphalt binder more resistant to rutting, well-worn depressions, 

and grooves. Researchers then preblended the polymerized waste cooking oil and 

lignin, and they mixed that substance with asphalt aggregates in a hot drum to 

create a “bioasphalt.” After curing the mixture for 2 hr, they packed the bioasphalt 

in a gyratory compactor. The goal of the research was to create a substance that 

provides as much or more resistance to fatigue, rutting, thermal cracking, and 

moisture as petroleum-based asphalt.

IMPACT: Successfully producing a bio-based asphalt binder that equals or 

exceeds the performance of traditional asphalt could reduce the reliance on 

petrochemicals in road networks. The results of this project could contribute to 

future research into bioasphalt, including its ability to withstand various traffic 

loads and weather conditions based on the degrees of the binder’s 

polymerization.
Breakthrough Concepts in Materials Science

EAR PROGRAM RESEARCH RESULTS  |  37

PROJECT: Mechanisms of Hydration and Setting of Ordinary Portland 

Cement in Simple and Complex Systems

INSTITUTIONS: Princeton University; National Institute of Standards 

and Technology (NIST); Oklahoma State University; Rice 

University; University of California, Santa Barbara; and W.R. 

Grace and Company

COMPLETED: 2017

OBJECTIVE: To develop advanced hydration models that will improve the 

setting, strength, and durability of concrete and provide 

guidance on a pavement’s expected performance based on the 

composition of cement, supplementary cementitious materials, 

admixtures, and temperature.

RESOURCES: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/15084/index.cfm.

 Fonseca, P. C., and G. W. Scherer. 2015. “An Image Analysis 

Procedure to Quantify the Air Void System of Mortar and 

Concrete.” Materials and Structures 48: 3087–3098.

 Stoian, J., T. Oey, J. W. Bullard, J. Huang, et al. 2015. “New 

Insights into the Prehydration of Cement and its Mitigation.” 

Cement and Concrete Research 70: 94–103.

 Li, X., Z. C. Grasley, J. W. Bullard, and E. J. Garboczi. 2015. 

“Computing the Time Evolution of the Apparent Viscoelastic/

Viscoplastic Poisson’s Ratio of Hydrating Cement Paste.” 

Cement and Concrete Composites 56:121–133.

 Bullard, J. W., G. W. Scherer, and J. J. Thomas. 2015. “Time 

Dependent Driving Forces and the Kinetics of Tricalcium 

Silicate Hydration.” Cement and Concrete Research 74: 26–34.

 Sangodkar, R. P., B. J. Smith, D. Gajan, A. J. Rossini, et al. 2015. 

“Influences of Dilute Organic Adsorbates on the Hydration of 

Low-Surface-Area Silicates.” Journal of American Chemical 

Society 137: 8096–8112.

 Hu, Q., M. Aboustait, T. Kim, M. T. Ley, et al. 2016. “Direct 

Three-Dimensional Observation of the Microstructure and 

Chemistry of C3S Hydration.” Cement and Concrete Research

88, 157–169. http://dx.doi.org/10.1016/j.cemconres.2016.07.006.
Breakthrough Concepts in Materials Science

38  |  EAR PROGRAM RESEARCH RESULTS

 Bullard, J. W., and G. W. Scherer. 2016. “Solid Solution Model 

for C-S-H” Journal of American. Ceramic Society 99, no.12: 

4137–4145.

 Hu, Q., M. Aboustait, T. Kim, M. T. Ley, et al. “Direct 

Measurements of 3D Structure, Chemistry and Mass Density 

during the Induction Period of C3S Hydration.” Cement and 

Concrete Research 89: 14–26. http://dx.doi.org/10.1016/j.

cemconres.2016.07.008.

 Scherer, G. W., and F. Bellmann. 2018. “Kinetic Analysis of 

C-S-H Growth on Calcite” Cement and. Concrete Research 103: 

226–235. http://dx.doi.org/10.1016/j.cemconres.2016.07.017

 Bellmann, R., and G. W. Scherer. 2018. “Analysis of C-S-H 

Growth Rates in Supersaturated Conditions.” Cement and 

Concrete Research 103: 236–244. http://dx.doi.org/10.1016/j.

cemconres.2017.05.007.

RESULTS: Researchers combined experimental 

measurement techniques with computer modeling 

to observe, measure, and model the hydration 

process in cement at scale. The team conducted 

the research in two phases, with the first focused 

on the mechanisms of cement hydration and the 

second on the impact of organic admixtures. The 

researchers used experimental techniques like 

vertical scanning interferometry, tomographyassisted chemical correlation, and nuclear 

magnetic resonance spectroscopy to identify 

mechanisms to include in their models. Using 

these techniques, the researchers obtained data 

to verify model predictions and validate models at 

nano-, micro-, and macroscopic length scales. 

They also discovered breakthrough techniques 

that allowed them to obtain even more information 

about reaction rates. The studies enabled them to 

identify which chemical reactions occur at the 

early ages of cement, where they occur within the 

Researchers conducted 

x-ray nano-computed 

tomography and 

nano-x-ray fluorescent 

imaging using the 

Beamline 26 x-ray 

nanoprobe at Argonne 

National Laboratory in 

Illinois. © Argonne National 

Laboratory, managed and 

operated by UChicago 

Argonne, LLC, for the 

U.S. Department of Energy.
Breakthrough Concepts in Materials Science

EAR PROGRAM RESEARCH RESULTS  |  39

cement, at what rate, and how they can be modified to make concrete more 

sustainable and durable. These insights will help improve the hydration reaction 

simulation and modeling programs being developed at NIST and other 

institutions. The data has resulted in published technical papers that have 

helped refine the modeling efforts being advanced at NIST, including the 

hydration reactions in a microstructures project (https://www.nist.gov/

programs-projects/hydration-reactions-microstructures-project) and the 

Virtual Cement and Concrete Testing Laboratory software (https://www.nist.

gov/services-resources/software/vcctl-software).

IMPACT: By creating a tool to observe cement at its material length scales, this 

project helped advance the control of hydration in cement. Researchers 

applied their knowledge from the project toward improving NIST’s HydratiCA 

model for simulating hydration and toward developing SimBNG, a boundary 

nucleation and growth model. FHWA will make the research available by 

technique, mineral, additive, and other key words for future experimentation.

PROJECT: Paving the Way for Greener Highways: Extending Concrete’s 

Service Life through Multiscale Crack Control

INSTITUTION: University of California, Berkeley

COMPLETED: 2015

OBJECTIVE: To extend the service life of reinforced concrete structures by 

limiting the spread of cracks, and to reduce the environmental 

impact of concrete by incorporating recycled waste materials.

RESOURCES: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/13079/13079.pdf.

 Details at https://www.asce.org/communities/institutes-andtechnical-groups/engineering-mechanics-institute/researchgroup-profiles/durability-mechanics-at-the-university-ofcalifornia-berkeley.

RESULTS: The research team demonstrated the effectiveness, environmental 

benefit, and cost savings of an approach called deterioration reduction through 

micro and macro crack control (DRMC) that significantly slows the deterioration 

of highways, bridges, and other major concrete structures while reducing the 

environmental costs of concrete construction. The first component of the 
Breakthrough Concepts in Materials Science

40  |  EAR PROGRAM RESEARCH RESULTS

DRMC research—hybrid fiber-reinforced concrete (HyFRC)—evaluated the use 

of a mix of water-soluble polymer microfibers (0.312 inches) and hooked-end 

steel macro fibers (1.170 inch) to limit the development and spread of cracks, 

which reduce concrete’s strength and speed up its deterioration. Compared 

with conventional concrete, HyFRC showed significant improvement in 

corrosion control due mainly to suppression of spreading cracks. The second 

component of DRMC tested a “green” variant of HyFRC that uses fly ash—a 

waste product of burning coal to generate electricity—to replace 50 percent of 

the portland cement in concrete. In addition, the green HyFRC uses recycled 

concrete aggregate, which is commonly sent to landfills, to replace natural 

stone and gravel used in concrete. Tests showed that the green DRMC approach 

achieved both goals—enhanced corrosion resistance and conservation of 

natural resources.

IMPACT: Achieving significant crack and corrosion resistance in concrete that 

incorporates recycled waste material represents an economical and effective 

next-generation approach to major infrastructure construction projects, 

leading to increased service life expectancy and reduced environmental impact. 

Two concrete samples using equivalently reactive 

aggregate. Left, ASR-damaged concrete with cracks 

marked; right, crack-resistant HyFRC for concrete 

strength and stiffness retention. © 2013 Claudia Ostertag.
Breakthrough Concepts in Materials Science

EAR PROGRAM RESEARCH RESULTS  |  41

PROJECT: Greatly Increased Use of Fly Ash in Hydraulic Cement 

Concrete for Pavement Layers and Transportation Structures

INSTITUTIONS: Purdue University, Auburn University, NIST, National Ready 

Mixed Concrete Association, and FHWA’s Chemistry and 

Concrete Laboratories

COMPLETED: 2012

OBJECTIVE: To improve understanding of infrastructure materials, 

specifically, how to use higher amounts of fly ash in concrete 

and obtain the performance needed for long-lasting concrete 

highway pavements and structures.

RESOURCES: Final report at https://www.nrmca.org/wp-content/

uploads/2020/06/Lab_fly_ashFinal_report.pdf.

RESULTS: Large-scale experiments demonstrated 

that high-volume fly ash (HVFA) concrete can be 

produced to have setting times and early-age 

compressive strength development comparable 

to conventional portland cement concrete. In 

experiments with HVFA replacement volumes of 

40 percent and 60 percent, researchers found 

that lower water-to-cementitious materials ratios 

and internal curing (adding pre-wetted, 

lightweight aggregates that release water to the matrix after time of set) improved 

early-age strength and reduced early-age cracking. Other project studies examined 

materials compatibility, prediction methods for property development, improved 

freezing and scaling durability, and activation energy values of cementitious 

materials. Technology transfer activities in the project will guide agencies and 

contractors in using HVFA in concrete mixtures.

IMPACT: The performance data and best practices developed in this project can 

lead to significantly increased use of fly ash in concrete mixtures, resulting in 

transportation infrastructure with a smaller carbon footprint, lower embodied 

energy, and improved long-term performance.

Fly ash with different carbon 

content levels. Source: FHWA.
Breakthrough Concepts in Materials Science

42  |  EAR PROGRAM RESEARCH RESULTS

PROJECT: High-Performance Stress-Relaxing Cementitious Composites

for Crack-Free Pavements and Transportation Structures

INSTITUTION: Texas A&M University Texas Transportation Institute

COMPLETED: 2011

OBJECTIVE: To achieve a durable concrete with enhanced viscoelastic 

properties and high resistance to cracking through the 

utilization of nano inclusions. 

RESOURCES: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/09065.pdf.

 Technical report at http://d2dtl5nnlpfr0r.cloudfront.net/swutc.

tamu.edu/publications/technicalreports/476660-00017-1.pdf.

 Research article at http://www.hindawi.com/journals/

jnm/2012/371927.

RESULTS: Investigators performed a comprehensive 

review of previous work using carbon nanoflaments 

(CNFs) and tubes (CNTs) in cementitious materials to 

improve their mechanical properties and behaviors and 

conducted a detailed study of the common method of 

incorporating CNFs. They developed a novel 

thermodynamic-based dispersion quantification method 

to measure the effect of geometry-dependent clustering 

on CNF dispersion in cement paste. They also developed 

a new method for improving and stabilizing CNF 

dispersion in cement paste using silica fume to 

significantly improve CNF dispersion in a hardened 

cementitious matrix. Finally, experimental investigation of the effect of CNFs on 

the mechanical behavior and properties of hardened cement paste showed that 

CNFs can increase flexural strength and reduce shrinkage cracking. The 

researchers produced an advanced hardened cement paste that is strong and 

resists shrinkage cracking quite well under certain levels of restraint. Next steps 

could include additional exploratory advanced research.

IMPACT: Use of new materials such as CNTs can lead to increased durability of 

pavements and structures as well as to multifunctional materials such as selfsensing pavements. 

Carbon nanofibers 

spanning nano/

micro crack in 

a cementitious 

composite. 

Source: FHWA.
EAR PROGRAM RESEARCH RESULTS  |  43

Human Behavior and Travel Choices

New mobile sensors and computers are creating radical new tools for 

understanding how individuals and groups of people behave in structured 

experiments and natural, everyday life. With advances in automation, there 

also are new demands for understanding how people interact with machines. 

The EAR Program has supported research in this focus area, mining data to 

create new methods of assessing long-distance passenger travel, freight data, 

and safety surrogate measures. The EAR Program also is taking advantage of 

advances in machine learning to increase the automated coding of 

naturalistic driving data. Harnessing technological advancements for 

innovation can result in more effective safety countermeasures, roadway 

designs, and system investments that reflect the future needs of the transit of 

people and goods.

PROJECT: Comparative Effectiveness of Alternative Smartphone-Based 

Nudges to Reduce Cellphone Use While Driving

INSTITUTION: University of Pennsylvania and the Children’s Hospital 

of Philadelphia

COMPLETED: 2021

OBJECTIVE: To examine the issue of distracted driving by applying 

behavioral economics concepts and novel smartphone 

technology.

RESOURCES: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/20013/20013.pdf. 

RESULTS: Two field experiments tested scalable smartphone-based “nudge” 

strategies to reduce cellphone use while driving. The first randomized trial 

tested the effect of policies requiring smartphones to have a “car mode,” akin 

to “airplane mode,” and enhancements for uptake and sustained use via 

potential auto insurance incentives. Specifically, the researchers looked at the 

effect of “opt-out” versus “opt-in” deployment of a smartphone “car mode” 

setting that blocks cellphone use while driving, with and without 

financial incentives.

The second randomized trial compared the effects of social, individual, and 

team-based incentives by employers that could be scaled to reduce cellphone 

use while driving.
44  |  EAR PROGRAM RESEARCH RESULTS

Human Behavior and Travel Choices

IMPACT: The data derived from these scalable smartphone and incentive 

strategies may help develop public safety programs for reducing dangerous 

distracted driving behaviors.

PROJECT: InterchangeSE: A Federated Multimodal Simulation 

Environment for Studying Interactions Between Different 

Modes of Travel

INSTITUTION: Iowa State University

COMPLETED: 2021

OBJECTIVE: To design, develop, and demonstrate a simulation in a realtime environment where a variety of traffic and roadway 

situations can be created, run, and studied.

RESOURCES: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/20014/20014.pdf.

RESULTS: Using multimodal simulation technology called InterchangeSE, the 

researchers examined interactions among several transportation stakeholders 

(i.e., bicyclist, driver, and pedestrian) representing different decision 

perspectives in various traffic/roadway situations. Using a client-server 

network architecture, InterchangeSE connected physical and simulated driving 

agents (i.e., bicyclist and automobile driver) to a traffic simulator application. 

The physical participants interacted with each other using a variety of displays 

including multiple computer monitors, head-mounted virtual reality displays, 

and augmented reality displays. Driving parameters from the physical 

participants, such as position and heading, were network synchronized with 

traffic (i.e., vehicles and pedestrians) and computed by the traffic simulator. 

The computed traffic was relayed back to the physical driving participants, 

who saw them on their screens and adjusted driving responses accordingly, all 

in real time.

IMPACT: This research will help ensure the safe and reliable introduction of new 

technologies, such as cooperative driving automation, into the U.S. highway 

system by allowing more complex and realistic experiments.
EAR PROGRAM RESEARCH RESULTS  |  45

Human Behavior and Travel Choices

PROJECT: Freight Data Development and Enhancement to Support 

National Freight Transportation Analysis, Modeling, and 

Forecasting Practices

INSTITUTION: Research Systems Group, Inc., University of Washington, and 

the University of Toronto

COMPLETED: 2021

OBJECTIVE: To develop a coherent and holistic freight modeling framework 

for tracking vehicles and shipments and for surveying all 

relevant freight agents (e.g., producers, shippers, logistics 

providers, carriers, wholesalers, retailers, end-consumers) with 

considerable time and geographical coverage (national, 

regional/urban, and rural areas).

RESOURCES: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/17122/index.cfm.

RESULTS: The research team gathered and integrated available data to develop 

a national freight model estimation. This research provided the modelingframework foundation for next generation behavioral and agent-based 

predictive tools. These tools will be capable of modeling complex interactions 

that underlie logistics and transport choices and can be applied at various 

geographic levels. 

IMPACT: This study will allow decisionmakers to understand better the factors 

that influence freight movement on scales ranging from interurban commercial 

deliveries to regional and national infrastructure needs.

PROJECT: Behavioral-Based (or Agent-Based) National Freight 

Demand Modeling

INSTITUTION: Massachusetts Institute of Technology

COMPLETED: 2020

OBJECTIVE: To demonstrate novel approaches for the development of a 

national-level, disaggregated, behavioral-based, and 

multimodal freight demand modeling tool.

RESOURCES: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/17122/17122.pdf.
46  |  EAR PROGRAM RESEARCH RESULTS

Human Behavior and Travel Choices

RESULTS: This study built on the national freight model that examines the 

national movement of goods in the United States. The research team evaluated 

the use of innovative communication technologies to collect high-resolution 

and high-frequency data that accurately describe the behavior of choices that 

underpin freight movement. The researchers developed freight logistics survey 

methods that use smartphones, tablets, Global Positioning System loggers, 

radio frequency identification, mobile sensing, and wireless communication 

technologies to collect data that accurately describe what freight transportation 

agents do while minimizing the burden of data reporting and protecting 

sensitive business information. The researchers validated and enhanced this 

trove of observed behavioral data through in-person and web- or tablet-based 

recall surveys to reveal underlying decisionmaking and choice among multiple 

logistics and route variables. The initial results from applying the national 

freight model in this study demonstrated that the model produces reasonable 

estimates of the business relationships and transport logistics required to 

move goods in the United States.

IMPACT: The results of this study significantly enhance transportation managers’ 

ability to anticipate and plan freight movement capacity, operation, and 

infrastructure investment.

PROJECT: Developing Connected Simulation to Study Interactions 

Between Drivers, Pedestrians, and Bicyclists

INSTITUTION: University of Iowa

COMPLETED: 2020

OBJECTIVE: To transform simulation technology to enable studies of how 

the expectations, anticipations, and responses of all road users 

are influenced by futuristic vehicle technologies, new 

infrastructure designs, and each other.

RESOURCES: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/20014/index.cfm.

RESULTS: Connected simulation technology offers enormous potential to study 

interactions between drivers, pedestrians, and bicyclists and assess the impact 

of new technologies on safety and mobility. This project researched the 

development of an innovative mixed-mode connected driving, pedestrian, and 
EAR PROGRAM RESEARCH RESULTS  |  47

Human Behavior and Travel Choices

bicycling simulator system. This work incorporated graphical avatars into the 

simulation that represented the live movements of drivers, bicyclists, and 

pedestrians and the development of new methods of scenario control and 

data analysis appropriate for multiparticipant simulation research. The 

experiments examined the interactions between drivers, bicyclists, 

and pedestrians.

IMPACT: This research will help ensure the safe and reliable introduction of new 

technologies, such as cooperative driving automation, into the U.S. highway 

system by allowing more complex and realistic experiments.

Knowledge Discovery in Massive Transportation Datasets

The ability to extract and analyze safety-related information from vast 

datasets about driver behavior, vehicle performance, traffic patterns, weather, 

and infrastructure could help reduce crashes on the Nation’s highways. These 

datasets include FHWA’s Highway Safety Information System (HSIS), which 

features data on accident, roadway, and traffic variables; the naturalistic 

driving study (NDS), a resource from the second Strategic Highway Research 

Program (SHRP 2) that describes more than 3,400 drivers and vehicles 

involved in roughly 36,000 events; and a related SHRP 2 roadway information 

database (RID), which details NDS trips on the most frequently traveled 

roadway sections. Open-source technology that can process these massive 

transportation datasets is needed to enhance knowledge discovery. The EAR 

Program backed two projects designed to develop such technology.

RESOURCES: Hankey, J. M., M. A. Perez, and J. A. McClaferty. 2016. Description of 

the SHRP 2 Naturalistic Database and the Crash, Near-Crash, and 

Baseline Data Sets. Blacksburg, VA: Virginia Tech Transportation 

Institute. https://vtechworks.lib.vt.edu/handle/10919/70850.

IMPACT: The first project will enable researchers to leverage decades of 

information in existing transportation datasets, work with data sources not 

typically considered in the safety domain and broaden their understanding of 

safety countermeasures. The platform the researchers developed also could 

have applications in operations and maintenance if the necessary datasets are 

added to it. Tools developed through the second project will be refined for use 

with similar data-rich traffic information resources.
48  |  EAR PROGRAM RESEARCH RESULTS

Human Behavior and Travel Choices

PROJECT: Applications of Knowledge Discovery in Massive 

Transportation Data: The Development of a Transportation 

Research Informatics Platform (TRIP)

INSTITUTION: CUBRC

COMPLETED: 2018

OBJECTIVE: To manage massive amounts of transportation data and 

provide researchers with an efficient way to conduct analytics 

with big data. 

RESULTS: Researchers at CUBRC developed a tool 

called the Transportation Research Informatics 

Platform (TRIP). Built on a Linux operating system, 

TRIP features open-source tools that consume, 

transform, align, and store massive amounts of 

traffic data that users can mine for patterns related 

to traffic safety. The platform’s versatile dashboard 

makes it possible to visualize streaming data and 

historical information. This information includes 

State road crashes, traffic volumes, and roadway 

characteristics from the HSIS; roadway geometrics 

from the RID; data on historical crashes, traffic 

volumes, weather, traffic laws, safety campaigns, 

and work zones; weather data and roadway surface 

conditions from the Clarus Initiative; and weather information like precipitation, 

temperature, and wind speed from the Iowa Environmental Mesonet. CUBRC 

tested TRIP with sample datasets from the Seattle region.

RESOURCES: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/17117/index.cfm.

IMPACT: The research demonstrated the potential of advanced methods for 

working with diverse and unstructured data. Since the project ended, 

additional government funding continues to advance the maturity of open, 

flexible data tools for developing actionable information for increasing 

transportation safety and mobility.

An illustration of the study 

area being examined in 

TRIP, including 4,277 mi 

of centerline data and 

27 roadway weather 

information stations. 

© 2017 CUBRC.
EAR PROGRAM RESEARCH RESULTS  |  49

Human Behavior and Travel Choices

PROJECT: High Performance Data Fusion for Transportation 

Safety Analytics

INSTITUTION: Palo Alto Research Center, Inc.

COMPLETED: 2018

OBJECTIVE: To combine and analyze data from large datasets in the 

transportation domain, including datasets containing sensitive 

personal and business information.

RESULTS: Researchers at the Palo Alto Research Center, Inc. (PARC) developed 

automated, machine-learning methods to extract, clean, and restructure 

traffic-related data from disparate sources. They used video, radar, and still 

photography information gathered from Chicago intersections. This new 

approach, an improvement upon 

slower, manual methods for 

handling such data, can reveal 

safety issues that might not be 

apparent from examining 

traditional datasets. When the 

SHRP 2 NDS became available, 

PARC started developing a video 

analysis tool. Being tested now, 

this tool processes snippets of 

video and can return the location 

on the video matching the snippet.

RESOURCES: Fact sheet at 

https://www.fhwa.dot.gov/publications/research/ear/

17117/index.cfm.

IMPACT: The research demonstrated the potential of advanced methods for 

working with diverse and unstructured data. Since the project ended, 

additional government funding has continued to advance the maturity of 

open, flexible data tools for developing actionable information for increasing 

transportation safety and mobility.

Video Analytics Research Projects

The NDS conducted by the SHRP 2 of the Transportation Research Board 

collected 1.2 million hr of video from more than 3,400 volunteer drivers and 

Interactive feedback on the examples proposed by PARC’s automated machine-learning method for agile video queries. © Palo 

Alto Research Center, Inc.
50  |  EAR PROGRAM RESEARCH RESULTS

Human Behavior and Travel Choices

their vehicles traveling on U.S. highways over 2 yr. This is one of the largest 

and richest resources for transportation safety researchers.

Each vehicle was equipped with an interface to collect data from the vehicle’s 

onboard systems, video cameras, GPS, and other systems that combined to 

generate more than 2 petabytes of data. The EAR Program funded six 

separate research projects that addressed separate aspects of video 

analytics, aiming to help researchers manage and extract accurate 

information from the large and complex SHRP 2 data set.

RESOURCES: Baragchizadeh, A., Karnowski, T.P., Bolme, D.S., and O’Toole, A.J. 

Evaluation of Automated Identity Masking Method (AIM) in 

Naturalistic Driving Study (NDS), 2017 12th IEEE International Conf. 

on Automatic Face & Gesture Recognition (FG 2017), Washington, 

DC, May 30–June 3, 2017, 378–385. 

 Paone, J., Bolme, D., Ferrell, R., Aykac, D., et al. Baseline Face 

Detection, Head Pose Estimation, and Coarse Direction Detection for 

Facial Data in the SHRP2 Naturalistic Driving Study, 2015 IEEE 

Intelligent Vehicles Symposium (IV), Seoul, South Korea, June 28–

July 1, 2015, 174–179.

 Seshadri, K., Juefei-Xu, F., Pal, D.K., Savvides, M., et al. Driver Cell 

Phone Usage Detection on Strategic Highway Research Program 

(SHRP2) Face View Videos, Proc. 2015 IEEE Conf. on Computer 

Vision and Pattern Recognition Workshops, Boston, MA, June 7–12, 

2015, 35–43.

 Hoang Ngan Le, T., Zheng, Y., Zhu, C., Luu, K., et al. Multiple Scale 

Faster-RCNN Approach to Driver’s Cell-Phone Usage and Hands on 

Steering Wheel Detection, Proc. 2016 IEEE Conf. on Computer Vision 

and Pattern Recognition Workshops, Las Vegas, NV, June 26–July 1, 

2016, 46–53.

 Chu, W. -S., F. de la Torre, and J. Cohn. 2017. “Selective Transfer 

Machine for Personalized Facial Expression Analysis.” IEEE Trans. 

Pattern Anal. Machine Intell. 39, no. 3: 529–545. 

 Zeng, J., W. -S. Chu, F. de la Torre, and Z. Xiong. 2016. “Confidence 

Preserving Machine for Facial Action Unit Detection.” IEEE 

Transactions on Image Processing 25, no. 10: 4753–4767. 
EAR PROGRAM RESEARCH RESULTS  |  51

Human Behavior and Travel Choices

 Seshadri, K., and M. Savvide. 2015. “Towards a Unified Framework 

for Pose, Expression, and Occlusion Tolerant Automatic Facial 

Alignment.” IEEE Transactions on Pattern Analysis and Machine 

Intelligence 38 no. 10: 2110–2122. 

 Radwin, R. G., J. D. Lee, and O. Akkas. 2015. “Are Driver Movement 

Patterns Indicators of Distraction and Engagement?” Presented at 

the Human Factors and Ergonomics Society 59th Annual Meeting. 

Madison, WI: Human Factors and Ergonomics Society. 

 Schwarz, C., T. Brown, J. Lee, J. Gaspar, et al. 2016. “The Detection 

of Visual Distraction Using Vehicle and Driver-Based Sensors” 

presented at the SAE 2016 World Congress and Exhibition. 

Detroit, MI: SAE International. 

 Seshadri, K., F. Juefei-Xu, D. Pal, M. Savvides, et al. 2015. “Driver Cell 

Phone Usage Detection on Strategic Highway Research Program 

(SHRP2) Face View Videos.” Presented at the 2015 IEEE Conference 

on Computer Vision and Pattern Recognition. Boston, MA: Institute 

of Electrical and Electronics Engineers.

PROJECT: Machine Learning for Automated Analysis of Large Volumes of 

Highway Video

INSTITUTION: Carnegie Mellon University

COMPLETED: 2016

OBJECTIVE: To develop a 

prototype tool 

that uses 

computer vision 

and machinelearning 

algorithms to 

identify and 

extract useful 

information 

about roadway 

features from data gathered from forward-looking, 

vehicle-mounted cameras. 

A typical challenging situation for overlapping 

objects (left vehicles) and occluded objects 

(right vehicle) in an urban environment. 

© Carnegie Mellon University.
52  |  EAR PROGRAM RESEARCH RESULTS

Human Behavior and Travel Choices

RESULTS: Researchers evaluated analytical solutions to challenges such as 

identifying multiple roadway features (car and truck detection), differentiating 

among scene context elements (vegetation, sky, and roadway shoulder), and 

identifying traffic signs and status of traffic signals. The researchers also developed 

a simple graphical user interface that enables even novice users to effectively 

employ appropriate algorithms to a range of analytical tasks.

IMPACT: This research demonstrates the effectiveness of applying appropriate 

machine-learning techniques to large, diverse data sets and opens avenues for 

active learning to address challenges such as traffic congestion control, driver 

behavior training, and road safety.

Automated Feature Extraction Projects

The EAR Program sponsored three research projects designed to advance 

efficient and cost-effective methods and tools to analyze the large amounts 

of video-related safety data generated by studies such as the SHRP 2 NDS. 

These projects focused on the driver and the interior of vehicles involved. 

Each project brings different technical strengths and approaches and applies 

the approaches to different features of interest for highway safety. These 

projects are briefly summarized below.

PROJECT: DCode: A Comprehensive, Automated Coding System for 

Driver Behavior Analysis

INSTITUTION: SRI International

COMPLETED: 2016

OBJECTIVE: To develop a 

comprehensive, 

automatic system 

to assist in coding 

of features in 

the SHRP 2 NDS 

data set that 

are relevant to 

traffic and 

roadway safety 

researchers. 

The DCode System will extract driver 

behavior features and recognize various 

actions. It will also track contextual features. 

© SRI International.
EAR PROGRAM RESEARCH RESULTS  |  53

Human Behavior and Travel Choices

RESULTS: Researchers for this project developed software to code contextual 

features such as passengers, radio, navigation, and conditions outside the vehicle. 

The software extracts core and intermediate features to code driver behavior 

features (e.g., hand position and facial expression) and to track driver attention 

(emotional, cognitive, and physiological state). The project identified areas for 

future research, such as image stabilization and improved techniques to extract 

contextual features when the environment is not ideal, such as when seat belts 

are not brightly colored and difficult to detect.

IMPACT: This project demonstrates the effectiveness of a coding system that 

makes it possible to identify and evaluate the actions and behaviors of drivers, 

as well as the context in which they are performed.

PROJECT: DB-SAM: CMU Driver Situational Awareness System

INSTITUTION: Carnegie Mellon University

COMPLETED: 2016 

OBJECTIVE: To develop an 

automated, 

real-time 

method for 

analyzing key 

facial landmarks 

to determine if 

a driver is 

fatigued or 

distracted.

RESULTS: DB-SAM uses Active Appearance Models to analyze facial images 

and Active Shape Models to analyze facial outlines by tracking a variety of 

physical and biological landmarks in videos. This analysis is used to estimate 

driver distraction or fatigue. Researchers also evaluated methods to analyze 

hand position to determine if drivers have their hands on the steering wheel or 

are holding a cell phone to their ear.

IMPACT: This project demonstrates the potential for using real-time video 

analytics to estimate if a driver is in good condition to operate a vehicle.

Examples of how the distance between the 

curves of the eyelids could be used for eye 

openness classification. © Carnegie Mellon 

University.
54  |  EAR PROGRAM RESEARCH RESULTS

Human Behavior and Travel Choices

PROJECT: Quantifying Driver Distraction and Engagement Using 

Video Analytics

INSTITUTION: University of Wisconsin-Madison

COMPLETED: 2016 

OBJECTIVE: To develop an open software system and graphical user 

interface that will enable automated feature extraction and 

behavior characterization using naturalistic driving video.

RESULTS: This research team evaluated automated feature extraction and 

behavior characterization systems to estimate driver distraction and engagement, 

as well as road state. In this system, algorithms segment video into regions of 

interest that include the driver’s head, face, and upper body; steering wheel; and 

roadway. The software tracks facial landmarks to estimate head pose, tracks eye 

and mouth movement to help estimate gaze, and monitors hand activity to 

determine if a driver’s hands are on the steering wheel. The software also 

evaluates features of road state (e.g., traffic signal detection, day or night, in 

traffic or alone on the road). This information is used to help understand 

driver engagement.

IMPACT: This research represents an important advance toward development of 

a reliable, automated, video coding system that can be used with naturalistic or 

driving-simulator video to help understand and prevent driver distraction.

Regions of interest, including the driver’s face, hands, and front view, are monitored by 

the system. © Regents of the University of Wisconsin–Madison.
EAR PROGRAM RESEARCH RESULTS  |  55

Human Behavior and Travel Choices

Automated Identity-Masking Projects

The EAR Program supported two research projects designed to investigate 

automated identity masking that preserves underlying information about 

the driver’s expression (e.g., head pose, mouth, and eye movement) while 

protecting privacy and precluding personal identification. The following 

pages provide a brief summary of these two projects.

PROJECT: Automation of Video Feature Extraction for Road Safety—

Automated Identity-Masking

INSTITUTIONS: Carnegie Mellon University and University of Pittsburgh

COMPLETED: 2016

OBJECTIVE: To develop an automated, facial-masking technique to prevent 

personal identification without eliminating facial behavior. 

RESULTS: The research team for this project developed automated masking 

techniques that protect personal identity while allowing future researchers to 

analyze facial behavior as a tool to help evaluate driving characteristics through 

study of naturalistic driving videos. The central concept employed in this 

research is facial action transfer, which clones a facial action (e.g., forming a 

smile) from one person within a video to another person. This process preserves 

the changing subtle facial movements 

from the person being de-identified. 

The process is nonreversible, ensuring 

that driver identity is protected. 

Researchers have developed an 

automatic graphical user interface 

that can output de-identified video.

IMPACT: This project demonstrates 

the effectiveness of an automated 

system for de-identifying individuals 

in naturalistic driving videos, greatly 

expanding the utility of these videos 

in driver safety and behavior studies. The personalized facial action transfer 

process. Chart: © Carnegie Mellon. Face 

images: © University of Pittsburgh.
56  |  EAR PROGRAM RESEARCH RESULTS

Human Behavior and Travel Choices

PROJECT: DMask: A Reliable, Identity-Masking System for Driver Safety 

Video Data

INSTITUTION: SRI International

COMPLETED: 2016 

OBJECTIVE: To develop an automated facial-masking technique to prevent 

personal identification without eliminating distinctive aspects 

of driver expression.

RESULTS: This research involved exchanging the driver’s head in SHRP 2 video 

data with a computer-generated avatar head. The system preserves key facial 

landmarks as well as information about head pose, facial expression, direction 

of gaze, and the state of the eyes and mouth. This information about facial 

motion is automatically and accurately mapped to the avatar face, giving 

researchers access to important facial cues while protecting individual identity. 

A manual-assist feature allows users to manually correct mis-mapping of the 

eyes, nose, and mouth.

IMPACT: This project helps broaden the research value of data collected in 

naturalistic driving videos, by retaining often subtle but relevant facial 

movements while protecting the identity of volunteer drivers.

A driver’s identity is protected using an avatar to replace their face in all frames. 

©SRI International.
EAR PROGRAM RESEARCH RESULTS  |  57

Human Behavior and Travel Choices

PROJECT: Multimodal Connectivity Options for a Future, Seamless, 

Transportation System

INSTITUTION: University of Southern California 

COMPLETED: 2014

OBJECTIVE: To harness emerging technologies to develop a new type of 

decentralized transportation system based on a market for 

unused transportation capacity.

RESOURCE: Project details at https://highways.dot.gov/research/projects/

multimodal-connectivity-options-future-seamlesstransportation-system.

RESULTS: The research team explored how to bring unused transportation 

capacity (i.e., empty seats in vehicles already making certain types of trips) to a 

novel market that is able to match riders and drivers, negotiate a fair price for 

transport, and efficiently adjust routes so as to preserve benefits for all users. 

The research team explored computational and algorithmic issues related to 

pricing and route allocation in dynamic ridesharing systems, and developed 

important innovations that have been documented in several academic 

publications. Building on their basic research, the team developed open-source 

simulation software that can perform ride matching, routing, and auction pricing. 

The research team also conducted a workshop on car sharing and dynamic 

ridesharing to discuss the state of practice and knowledge in this area.

IMPACT: Understanding and simulating the market mechanisms and dynamics of 

shared-ride transportation based on small financial transactions will support 

continued growth and innovation in this rapidly evolving transportation market. 

The open-source software is freely available so that it can serve as a platform for 

further research in this area.
58  |  EAR PROGRAM RESEARCH RESULTS

Human Behavior and Travel Choices

PROJECT: Agent-Based Approach for Integrated Driver and Traveler 

Behavior Modeling

INSTITUTION: University of Maryland

COMPLETED: 2014

OBJECTIVE: To develop a theoretical framework for agent-based driver and 

traveler behavior modeling.

RESOURCE: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/13080/index.cfm.

RESULTS: The research team developed a theoretical framework for agentbased driver and traveler behavior modeling. The team evaluated traditional 

and emerging data collection methods for ABMS in transportation, evaluated 

alternative implementation platforms for ABMS applications in transportation, 

and developed an agent-based model of en-route and pre-trip route, departure 

time, and mode choices. The model considers five key ABMS components: (1) 

agent characteristics; (2) agent behavior rules; (3) observable agent behavior; 

(4) agent experience; and (5) attributes of the environment. A key factor of the 

integrated model is a learning process that allows cumulative agent experiences 

to lead to changes in certain agent preferences and subsequent decisions. The 

research team demonstrated the concept in the Washington, DC—Baltimore 

region, where additional data was collected for agent-behavior estimation and 

validation. The model was used to evaluate traffic and regional demand 

impacts of Maryland’s Inter-County Connector project and the I-270 multimodal 

corridor traffic management strategies.

IMPACT: The results from this project will help researchers understand future 

travel demands, improve transportation system management and travel 

reliability, and provide valuable investment insight for maintaining urban 

transport systems and services in the Washington, DC–Baltimore region. More 

broadly, the model demonstrates the potential of ABMS for improved 

forecasting accuracy, improved understanding of driver and traveler behavior, 

and modeling of transportation systems management concepts and insights 

for capital investment.
EAR PROGRAM RESEARCH RESULTS  |  59

Human Behavior and Travel Choices

PROJECT: Evolutionary Agent System for Transportation Outlook 

(VASTO)

INSTITUTIONS: University of Arizona and George Mason University

COMPLETED: 2014

OBJECTIVE: To use agent-based modeling and simulation to examine driver 

behavior and interactions between travelers, vehicles, and 

traffic management centers.

RESOURCES: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/12069/12069.pdf.

 Project details at https://highways.dot.gov/research/projects/

vasto-evolutionary-agent-system-transportation-outlook.

RESULTS: The research team used computational and algorithmic advances 

in other areas as an opportunity to improve existing transportation analysis 

capabilities. The team developed a theoretically sound, behaviorally robust, 

and computationally efficient transportation-analysis modeling system that 

seamlessly integrates the concepts of agent-based modeling with existing and 

emerging simulation tools. The team delivered a set of comprehensive 

modeling tools and a revolutionary system for a multiagent modeling system 

framework. The system incorporates innovative agent-based modeling 

concepts to replicate agents such as drivers and traffic management centers. 

This research project provides fundamental knowledge on how agent-based 

modeling and simulation can be useful for transportation system analysis and 

has developed open-source computer programs for other researchers to use. 

IMPACT: This research transforms the understanding and modeling of the 

interactions among heterogeneous agents that represent various groups of a 

transportation system. It advances the ability to realistically mimic various 

behaviors in a computer-simulated transportation network and examine their 

impacts. It will ultimately aid decisionmaking on transportation investments and 

contribute to effective management strategies, leading to a safer, more efficient 

transportation system.
60  |  EAR PROGRAM RESEARCH RESULTS

Human Behavior and Travel Choices

PROJECT: Machine Learning for Automated Analysis of Large Volumes 

of Highway Video

INSTITUTION: Carnegie Mellon University/National Robotics 

Engineering Center 

COMPLETED: 2014

OBJECTIVE: To automate feature extraction from the very large quantities of 

video data produced by the SHRP 2’s NDS.

RESOURCE: Project details at https://cms7.fhwa.dot.gov/research/projects/

machine-learning-automated-analysis-large-volumes-highwayvideo.

RESULTS: Feature extraction from highway video has traditionally been an 

essentially manual process. Technicians scroll through the video files, noting 

where features of interest are identified; however, the data collected by the 

SHRP 2 project totals over 1 million hr of video, rendering manual feature 

extraction unfeasible. In this project, the research team developed a 

multipurpose software framework for the analysis of very large volumes of 

video data and demonstrated several feature-detection and classification 

algorithms for archived on road video datasets. The research team built on 

previous experience using machine learning and image processing to detect 

vehicles and navigate urban and off-road environments. This resulted in the 

development of powerful and flexible methods for analyzing very large 

amounts of video data collected on roads and highways. Combined with 

largescale image processing techniques, the ultimate goal is for researchers to 

automatically search through enormous datasets, such as the SHRP 2 NDS 

data, and identify features of interest to safety researchers. This work also 

identified possible approaches to feature extraction from comparatively poorquality video data. 

IMPACT: This project demonstrates the effectiveness of advanced machinelearning techniques applied to large, diverse datasets. The research lays the 

groundwork for future development of a comprehensive library of data 

processing and analysis tools and will ultimately make it easier and faster to 

study and extract information from large-scale datasets.
EAR PROGRAM RESEARCH RESULTS  |  61

Human Behavior and Travel Choices

PROJECT: Design of a Completely New Approach for a National 

Household-Based, Long-Distance Travel Survey Instrument

INSTITUTIONS: Batelle, The Urban Institute, and University of Maryland

COMPLETED: 2013

OBJECTIVE: To identify and assess novel, innovative techniques and 

methods that can yield improved estimates in future, FHWA, 

long-distance household travel surveys. 

RESOURCE: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/13081/index.cfm.

RESULTS: Researchers for this project investigated alternative ways to capture 

long-distance travel behavior in an accurate, scientifically rigorous, and costeffective manner. The research team developed and tested new smartphone 

and social media applications to passively detect when a survey participant 

had taken a long-distance trip and then prompt that individual for trip-related 

information through an online survey. These applications were successfully 

tested in a pilot study involving over 250 individuals. The research team also 

developed and tested a series of postprocessing methods (based on machinelearning techniques) that estimate trip purpose for long-distance travel as a 

function of available travel survey data and other supplementary data. This 

approach could ultimately impact the design of future long-distance travel 

surveys by reducing the burden placed on collecting data directly from 

respondents through questionnaires.

IMPACT: This project led to several key recommendations for an efficient, 

scientific design, implementation, and processing of the next nationally 

representative travel survey that specifically addresses long-distance 

travel behavior. 
62  |  EAR PROGRAM RESEARCH RESULTS

Human Behavior and Travel Choices

PROJECT: Making Driving Simulators More Useful for Behavioral Research

INSTITUTIONS: University of Iowa/National Advanced Driving Simulator; 

University of Wisconsin; Western Transport Institute, Montana 

State University; Battelle; Entropy Control, Inc.; and William H. 

Levison Associates

COMPLETED: 2013

OBJECTIVE: To develop a mathematical transformation that will allow 

scientists and engineers to better predict the behavior of 

drivers in real environments based on the results of 

experiments conducted in driving simulators.

RESOURCE: Summary report at https://www.fhwa.dot.gov/publications/

research/ear/15016/15016.pdf.

 Project details at https://highways.dot.gov/research/projects/

making-driving-simulators-more-useful-behavioral-research.

RESULTS: The research team identified highway design needs and matched 

them to specific characteristics of driving simulators (e.g., motion, field of 

view, speed, and steering torque) and developed and demonstrated tools to 

characterize how closely responses to simulator characteristics match realworld driving outcomes. In experiments conducted on four different simulator 

platforms, the researchers compared driver judgment of simulator fidelity and 

performance in virtual roadway scenarios and found little effect of motion and 

a moderate effect of visual complexity. The results show that using a highfidelity simulator with attention to accurately rendering the visual complexity 

of the roadway will lead drivers in the simulator to drive at speeds quite 

comparable to those observed on actual roadways.

Actual road data (red points) used in response comparisons for a roundabout scenario. Source: FHWA.
EAR PROGRAM RESEARCH RESULTS  |  63

Human Behavior and Travel Choices

IMPACT: Models developed in this project will enable the driving safety research 

community and highway designers to predict real-world driving behavior 

more accurately from behavior in driving simulators and to integrate the 

results from different simulators more readily. The models also will better 

indicate to researchers when experiments require high-fidelity simulation and 

when lower fidelity approaches are adequate, thereby saving time and funding 

on future studies.

PROJECT: Behavioral Sciences Approach to Testing, Validating, 

and Establishing Best Practices for Alternative Highway 

Revenue Collection

INSTITUTIONS: University of Central Florida and Georgia State University

COMPLETED: 2013

OBJECTIVE: To understand drivers’ behavioral choices between tolled and 

“free” routes and choices of departure time by estimating risk 

attitudes, accuracy of risk perception, and discount rate.

RESOURCES: Fact sheet at http://www.fhwa.dot.gov/advancedresearch/

pubs/congestion/index.cfm.

RESULTS: To improve understanding of when and why drivers choose a tolled 

facility, the research team used experimental economics with a population of 

local drivers and students participating in (1) stylized lotteries to reveal risk 

attitudes; (2) driving simulators to reveal risk attitudes and travel time 

perceptions; and (3) GPS-recorded actual driving choices. More than 550 

drivers with residence and workplace connected by both a toll and a “free” 

route participated in Orlando, Florida, and Atlanta, Georgia. They responded to 

varying road prices in actual driving and simulations to assess their risk 

attitudes and travel time biases in response to monetary incentives. In another 

experiment, 210 college students participated in driving simulations of route 

choices to test whether their behavior could predict field driver behavior. The 

study concluded that risk attitudes are comparable across tasks and regions as 

well as for college students versus field drivers. The researchers found evidence 

of risk aversion as captured both by sensitivity overvalues of route choices and 

by pessimism over likelihoods of congestion. 
64  |  EAR PROGRAM RESEARCH RESULTS

Human Behavior and Travel Choices

IMPACT: Currently, revenue projections for priced roadways are based on 

methods with limited accuracy, which can result in projects with lower-thanexpected revenue. The results of this research confirm the importance of 

accurately incorporating risk attitudes in policy analysis and impact assessment 

of congestion pricing. The use of less costly subject pools and instruments to 

gather behavioral data as demonstrated in the project can increase 

opportunities to investigate driver choices and incorporate more accurate data 

when determining potential revenue.

PROJECT: Impact of Automated Transit and Pedestrian/Bicycling 

Facilities on Urban Travel Patterns

INSTITUTIONS: University of Michigan and University of Illinois at Chicago

COMPLETED: 2013

OBJECTIVE: To evaluate whether innovative pedestrian, bicycle, and transit 

facilities and services will attract travelers and decrease 

passenger-car travel.

RESOURCE: Summary report at https://www.fhwa.dot.gov/publications/

research/ear/15015/index.cfm.

RESULTS: Researchers in this project found that high-frequency shuttle service 

between a neighborhood and a regional rail transit system with available 

capacity can have a significant effect on choice of travel mode. The researchers 

conducted a household survey in four metropolitan Chicago communities to 

assess whether community shuttle service, bike lanes, walkway improvements, 

and other amenities would increase use of rail transit. In each neighborhood, 

they queried 150 residents who lived within 1.5 mi of a rail transit station and 

worked within 3 mi of a station on their current travel patterns and mode 

preferences under the hypothetical improvements. Simulations using a 

combination agent-based/activity-based model predicted that neighborhood 

shuttle service combined with bike lanes would decrease car use from 

36 percent to 22 percent and increase rail transit use from 50 percent to 

67 percent. Predicted shifts to rail were higher in lower density communities 

with lower rail use.
EAR PROGRAM RESEARCH RESULTS  |  65

Human Behavior and Travel Choices

IMPACT: The project’s results support the value of continued research into 

automating high-frequency shuttle services to help reduce traffic congestion, 

fuel consumption, and greenhouse gas emissions.

PROJECT: Megaregional Travel

INSTITUTIONS: University of Maryland, National Center for Smart Growth; 

ECONorthwest; Parsons Brinckerhoff; LEAM Group, University of 

Illinois at Urbana/Champaign; and David Simmonds Consultancy

COMPLETED: 2013

OBJECTIVE: To develop methods and tools that support planning for the 

Nation’s megaregions, integrating multiple disciplines, travel 

modes, and geographic levels. 

RESOURCES: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/12024/12024.pdf.

 Case study at http://www.fhwa.dot.gov/planning/megaregions/

reports/.

RESULTS: Megaregions, large 

agglomerations of metropolitan 

areas, represent a development 

pattern spreading across the 

world and a new planning 

geography. In this project, 

researchers developed and 

demonstrated the megaregion 

market analysis framework, 

which contains a market 

analysis and analytic tools. The 

market analysis focuses on 

defining the megaregion’s 

boundaries, identifying issues it 

must address, and describing 

its characteristics. The analytic 

tools—an economic model 

linked with a travel demand The model components recommended for 

megaregion analysis. © University of Maryland.
66  |  EAR PROGRAM RESEARCH RESULTS

Human Behavior and Travel Choices

model—enable analysis of the intricate effects of economic changes on a 

megaregion’s economy and transportation system. Applying this framework, 

the project defined the Chesapeake megaregion and used existing models and 

data to identify its issues and characteristics. The market analysis illustrates 

the need to broaden the planning perspective beyond local and metropolitan 

areas.

IMPACT: This project provides the framework and tools for policymakers to 

understand issues such as freight and the economy on a megaregional scale 

and demonstrates that analytic tools can be developed with available data and 

at reasonable cost for megaregional analysis.

PROJECT: Driver Behavior in Traffic

INSTITUTIONS: Virginia Polytechnic Institute and State University, 

PTV America, and Virginia Center for Transportation Innovation 

and Research 

COMPLETED: 2012

OBJECTIVE: To characterize driver behavior using naturalistic driving data and 

agent-based modeling techniques for development of effective 

strategies to improve transportation safety and operations.

RESOURCES: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/10070/10070.pdf

RESULTS: This research provides a foundation for agent-based modeling of driver 

behavior based on naturalistic data through an integrated framework for safety 

and operation analysis. Lateral vehicle action was simulated in a microscopic 

traffic-behavior modeling environment, bringing new insights to the modeling of 

driver-maneuvering behavior during safety-critical events. Agents developed and 

evaluated in the VISSIM simulation platform revealed a close resemblance to realdriver data. The project team improved car-following models through 

development of a hybrid model for greater accuracy and flexibility and through 

the addition of the new “passing and hook-following” thresholds. They used the 
EAR PROGRAM RESEARCH RESULTS  |  67

Human Behavior and Travel Choices

model to simulate vehicle actions in safety-critical events, developed agentbased simulation components integrated with the VISSIM simulation package 

through its driver model, and developed and implemented a robust activation 

mechanism for agent-based simulation based on discriminant analysis. The 

investigators also identified key future research issues: adaptability of agents in 

real time and human-factors issues related to warning individual drivers about 

changes in their driving behavior that might lead to safety-critical events.

IMPACT: New behavioral models are necessary to predict the safe and efficient 

use of new, connected-vehicle and roadside technology. This project 

demonstrates the ability of agent-based models based on naturalistic driving 

studies to create new and improved behavioral models.

Example of a sudden lane change. © Rorem, Dreamstime.com.
68  |  EAR PROGRAM RESEARCH RESULTS

Human Behavior and Travel Choices

PROJECT: Modeling the Urban Continuum in an Integrated Framework: 

Location Choice, Activity-Travel Behavior, and Dynamic 

Traffic Patterns

INSTITUTIONS: Arizona State University, University of Arizona, 

and University of Washington

COMPLETED: 2012 

OBJECTIVE: To develop a conceptual framework, integrated prototype, and 

computational tools for modeling interactions between the 

built environment and multimodal transportation systems and 

for modeling urban systems across simulated land use, travel 

demand, and traffic flow.

RESOURCE: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/interurbsys.cfm.

 Project details at https://highways.dot.gov/research/projects/

modeling-urban-continuum-integrated-framework-locationchoice-activity-travel-behavior-dynamic. 

RESULTS: SimTRAVEL, developed in this project, is an integrated modeling 

system that advances land-use and transportation microsimulation by 

providing seamless modeling of longer term choices about location (home, 

work and school) and shorter term choices of activity, travel mode, and route. 

SimTRAVEL integrates the use of UrbanSim (a land-use model), OpenAMOS 

(an activity-based microsimulation model), PopGen (a state-of-the-art 

synthetic population generator), and DynusT/MALTA (a dynamic, trafficassignment and microsimulation model) within a behaviorally robust 

framework. The integrated systems have been fully implemented in a userfriendly software environment with powerful graphical user interfaces and 

visualization dashboards. Open-source software architecture with 

multithreading and parallel-computing capabilities speeds the simulations. 

SimTRAVEL was successfully tested and validated on a 500,000 population 

subregion of Maricopa County, Arizona.

IMPACT: The innovations in this modeling software, which is freely available to 

the modeling community, are expected to have a major impact on transportation 

planning for sustainable futures.
EAR PROGRAM RESEARCH RESULTS  |  69

Technology for Assessing Performance

Advances in science and technology are providing new approaches in signal 

processing and data management. Sensors are continuing to increase in 

number, with many becoming disposable or recyclable and being embedded 

in almost everything sold. Advances in energy scavenging, batteries, and 

efficient spectrum use can increase in orders of magnitude the amount of 

processing that can take place at the source and the amount that can be 

transmitted for post hoc analysis. At the same time, computational models 

are becoming more complex and realistic, providing even more data than 

captured in the physical world. The EAR Program is supporting research in 

this focus area that demonstrates the potential of new approaches that can 

support transportation decisionmakers in finding meaning among increasing 

noise—from determining where damage is occurring on structures before it is 

visible to inspectors to improving the quality of new construction through 

intelligent compaction. 

PROJECT: Development of Structural Carbon Nanotube-Based Sensing 

Composites for Rehabilitation of Deteriorating and FatigueDamaged Steel Bridges

INSTITUTION: University of Delaware

COMPLETED: 2020

OBJECTIVE: To develop a structural sensing composite layer for concrete 

structures that can provide distributed monitoring capability.

RESOURCE: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/17123/17123.pdf. 

RESULTS: During the first phase of the project, the research team developed and 

refined methods for manufacturing and applying adhesive-backed carbon 

nanotube- (CNT) glass fiber reinforced plastic (GFRP) composites to steel and 

insulating the conductive properties of the CNT network against the substrate. 

Next, the researchers gauged the composite’s response to realistic environmental 

conditions on large-scale beam specimens, developing a calibration scheme for 

real bridges and designing hardware and software components for a field-ready 

wireless monitoring system that would use this composite technology. They 

used laboratory validation testing to evaluate how CNT-GFRP composites 

performed in situations mimicking field installations on steel bridges, such as 

exposure to wide temperature variations and high cycle fatigue. Testing included 
Technology for Assessing Performance

70  |  EAR PROGRAM RESEARCH RESULTS

large-scale experiments on prototype steel bridge members with fatigue-prone 

defects and simulated section loss and evaluation of off-the-shelf components 

to minimize costs for an effective monitoring system.

IMPACT: If the technology can be applied successfully in real-life situations, CNTGNRP composites have the potential to extend the lifespan of steel bridges. The 

data gathered from using the technology with structural health monitoring 

systems may enable engineers to assess the performance of bridge repairs and 

provide guidance on how best to retrofit existing bridges and design new ones.

PROJECT: Virtual Nondestructive Evaluation Laboratory for Highway 

Structures

INSTITUTION: Drexel University

COMPLETED: 2020

OBJECTIVE: To develop an online laboratory where inspectors and engineers 

can try out diagnostic tools with the latest in advanced 

technology to study and examine the condition of virtual bridges.

RESOURCE: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/18033/18033.pdf.

RESULTS: To create this laboratory, researchers collected data on real-life bridges. 

That data included high-resolution scans of bridges during different seasons as 

well as the results and observations about the bridges’ condition as gathered 

through nondestructive evaluation (NDE) testing tools and sensor technologies. 

The researchers used these data, plus data supplied by FHWA on other related 

research efforts on bridge condition assessment, to develop two virtual 

components. The first component consisted of data visualization tools that 

would allow laboratory users to explore and interact with the collected data on 

the real-life bridges, including the high-resolution scans and the data garnered 

through NDE testing tools and sensor technologies. 

IMPACT: This online laboratory will allow researchers, engineers, and inspectors 

to test and optimize emerging technologies and tools for assessing 

bridge conditions.
Technology for Assessing Performance

EAR PROGRAM RESEARCH RESULTS  |  71

PROJECT: Self-Sensing Adaptive Material for a New Generation of 

Multifunctional Bridge-Bearing Systems

INSTITUTION: University of Nevada, Reno

COMPLETED: 2017

OBJECTIVE: To develop self-sensing adaptive bridge bearing systems capable

of sensing and redistributing traffic or environmental loads.

RESOURCE: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/17046/index.cfm. 

RESULTS: Part of a three-phase study to identify material composition and 

develop systems responsive to loadings experienced by bridges, this research 

examined the value of magnetorheological elastomers (MREs) as a smart 

material for self-sensing adaptive bridge bearings (SSABs). MREs are polymeric 

solids embedded with iron particles. Their beneficial characteristics include 

piezoresistivity and magnetoresistance; the incorporation of MREs into SSABs 

makes it possible to measure structural loading continually and transmit that 

information to a monitoring system. The first two phases of research involved a 

series of groundbreaking investigations that demonstrated the feasibility of 

using MREs in highway bridge isolation bearings. Through a methodological 

design process, the bearings were developed to accommodate large strain and 

force demands. Experimental evaluations during these two phases showed that 

adaptive features of the bearings in terms of real-time control of apparent shear 

stiffness were attainable. However, further investigation was deemed necessary 

to develop material compositions to realize higher magnetorheological (MR) 

effects. The third phase focused on furthering MRE materials development under 

large strains to improve the MR effects. It characterized the mechanical properties 

of silicone-based and natural rubber-based MREs to improve MR effects under 

large strains. 
Technology for Assessing Performance

72  |  EAR PROGRAM RESEARCH RESULTS

IMPACT: The vibrations caused by wind and traffic are a significant factor in 

bridge performance, and conventional passive bearings, due to their 

predetermined stiffness, are limited in their ability to suppress such vibrations 

and readjust. This research showed that MREs incorporated within SSABs add 

stability to adaptive mechanical properties while withstanding realistic forces. 

The electrical properties of the layers also can be adjusted to measure changes 

in electrical resistance and correlate that to bearing forces.

PROJECT: Cooperating Camera Platforms for Ultra-High-Resolution 

Traffic Surveillance and Autonomous Event Detection

INSTITUTION: University of Maryland

COMPLETED: 2015

OBJECTIVE: To provide continuous, high-resolution, real-time simultaneous 

monitoring, tracking, and analysis of multiple transportation 

events or characteristics.

RESOURCE: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/15068/index.cfm.

RESULTS: The cameras that traditionally monitor 

transportation incidents, infrastructure, and 

congestion often require human monitoring and 

produce low-resolution video. Researchers for this 

project developed a high-resolution system that can 

monitor and analyze multiple incidents or 

characteristics at once and in real time. The cameras 

are synchronized, and their pan, tilt, and zoom 

features enhance the detection of any issues in the 

highway network. The cameras “talk” to each other 

every 50 milliseconds about what they are seeing so 

the system as a whole can track potentially fastmoving vehicles. The reach of the high-resolution 

imagery for highway infrastructure is up to 5 mi. The 

precisely calibrated camera lenses and highperformance gimbals also provide accurate video of 

vehicles at long distances. The system transmits 

footage wirelessly to remote operation centers and to 

Real-time video feature 

extraction (top), and 

cameras that can 

cooperate using precise 

and fast electronic pan, 

tilt, and zoom gimbals for 

event detection (bottom). 

© University of Maryland.
Technology for Assessing Performance

EAR PROGRAM RESEARCH RESULTS  |  73

other network locations at up to 1 gigabit/s, as traffic events dictate. The team 

designed and developed a testbed at the University of Maryland campus and on 

a local state highway. 

IMPACT: The camera system developed in this project offers great promise for 

improved monitoring of transportation infrastructure. It will enhance the quality 

of the video feeds, the speed in which they are delivered to observers, and the 

perspectives and information they provide. The high-bandwidth communications 

network will make it possible for personnel in an operations center to immediately 

detect events and for emergency responders in the field to get situational 

updates instantaneously. The testbed at the University of Maryland can be used 

for subsequent research into high-resolution traffic cameras.

PROJECT: Remote, Wireless Camera Systems for Environmental 

Monitoring of Transportation Corridors

INSTITUTION: University of California, Davis’ Road Ecology Center

COMPLETED: 2017

OBJECTIVE: To develop wireless wildlife camera technology that advances 

the state of the practice in investigating wildlife movement near 

highways, and to create an online interface and database to 

manage images from camera traps.

RESOURCES: Fact sheet at http://www.fhwa.dot.gov/publications/research/

ear/16033/index.cfm. 

 Shilling, F. 2017. “Using Advanced Camera Systems for 

Environmental Monitoring of Transportation Corridors” (web 

page). https://wildlifeobserver.net/files/resources/WEBINAR_

Jan31_ppt.pdf.

 Shilling, F. 2017. “Using Advanced Camera Systems for 

Environmental Monitoring of Transportation Corridors” (web 

page). https://wildlifeobserver.net/files/resources/WEBINAR_

Feb8_ppt.pdf.

 University of California, Davis. n.d. “Questions and Answers 

from Both Advanced Camera Systems Webinars” (web page). 

https://wildlifeobserver.net/files/resources/ChatboxQuestions_

Answers_Webinars1_2_0.pdf.
Technology for Assessing Performance

74  |  EAR PROGRAM RESEARCH RESULTS

Wildlife cameras operated in coordination with the California Department of 

Transportation captured images of two deer (left) and a bear (right) safely using 

wildlife crossings under Interstate 680 and under Interstate 80, respectively. 

© U.C. Davis Road Ecology Center.

RESULTS: The researchers demonstrated the potential for creating affordable, 

accessible remote camera systems for transportation agencies to continuously 

monitor and study wildlife movements in traffic corridors. The approach they 

developed can use commercially available wildlife cameras that have wireless or 

cellular connections to servers and can be incorporated into existing traffic 

camera infrastructure. Using a web interface, the system receives image files 

directly from remote wireless cameras, or transportation agency personnel can 

upload batches of images manually. Uploaded images are automatically 

organized into a database using details like date and time, geographic location, 

and user information. Users can manually add animal type, gender, age, observed 

activity, direction traveled, and any other characteristics to each image file. In the 

next and current phase of the project, researchers are exploring the use of 

software to automatically flag images with no animals and identify common 

wildlife species. State transportation agencies can use the Wildlife Observer 

Network, available at https://wildlifeobserver.net, to collect, manage, analyze, 

and share images. The website includes training materials and webinars 

produced by the research team. Agencies in California, Colorado, South Dakota, 

and Utah helped field test the system.

IMPACT: FHWA and seven other Federal agencies will use the technology 

developed for this project as part of a broader plan to promote ecosystembased environmental mitigation by integrating plans and data across agencies. 

The innovations will help agencies acquire wildlife movement data more easily 

and safely and at less cost than deploying staff periodically to collect images 

from static wildlife cameras mounted near highways.
Technology for Assessing Performance

EAR PROGRAM RESEARCH RESULTS  |  75

Assessing the Structural Health of America’s Highway Bridges: Effective 

Wireless Sensor Systems to Monitor Structural Health and Detect Damage

The ability to monitor the condition of bridges and other civil infrastructure 

systems is of primary interest to all infrastructure owners and operators. The 

development of advanced structural monitoring methods can facilitate the 

early detection of possible structural damage deterioration, with the goal to 

extend the lifespan of structures and increase their safety. Timely information 

gathered from such technologies undoubtedly will help transportation 

agencies in the corrective and urgent decisionmaking process. The 

development of wireless networks has eliminated the need for performing 

the arduous task of stringing connecting cables. The EAR Program supported 

two research projects—battery-powered wireless sensors and wireless 

sensors that operate without batteries—aimed at developing cost-effective 

structure health monitoring.

RESOURCES: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/17043/index.cfm.

 Hasni, H., N. Lajnef, A. H. Alavi, K. Aono, et al. 2018. “Local-Global 

Damage Identification Approach Using Hybrid Network of 

Self-Powered Sensors.” Presented at the 7th World Conference on 

Structural Control and Monitoring, Qingdao, China: Dynamics 

Research Group.

 Hasni, H., P. Jiao, A. H. Alavi, N. Lajnef, et al. 2018. “Structural Health 

Monitoring of Steel Frames Using a Network of Self-Powered Strain 

and Acceleration Sensors: A Numerical Study.” Automation in 

Construction 85: 344–357.

 Aono, K., H. Hasni, O. Pochettino, N. Lajnef, et al. 2018. “Quasi-SelfPowered Infrastructural Internet of Things: The Mackinac Bridge 

Case Study.” Presented at the 2018 Association for Computing 

Machinery’s (ACM) Great Lakes Symposium on Very Large Scale 

Integration (VLSI). Chicago, IL: ACM. 

 Alavi, A. H., H. Hasni, P. Jiao, W. Borchani, et al. 2017. “Fatigue 

Cracking Detection in Steel Bridge Girders through a Self-Powered 

Sensing Concept.” Journal of Construction Steel Research

128: 19–38. 
Technology for Assessing Performance

76  |  EAR PROGRAM RESEARCH RESULTS

 Hasni, H., A. H. Alavi, P. Jiao, and N. Lajnef. 2017. “Detection of 

Fatigue Cracking in Steel Bridge Girders: A Support Vector Machine 

Approach.” Archives of Civil and Mechanical Engineering 17, 

no. 3: 609–622.

 Hasni, H., A. H. Alavi, N. Lajnef, M. Abdelbarr, et al. 2017. “SelfPowered Piezo-Floating-Gate Sensors for Health Monitoring of 

Steel Plates.” Engineering Structures 148: 584–601. 

 Hasni, H., P. Jiao, A. H. Alavi, and N. Lajnef. 2017. “Damage 

Localization and Quantification in Gusset Plates: A Battery-Free 

Sensing Approach.” Structural Control and Health Monitoring 25, 

no. 2: e2158..

 Hasni, H., P. Jiao, A. H. Alavi, and N. Lajnef. 2017. “A New Method for 

Detection of Fatigue Cracking in Steel Bridge Girders Using 

Self-Powered Wireless Sensors.” Presented at SPIE Smart Structures 

and Materials + Nondestructive Evaluation and Health Monitoring. 

Portland, OR: International Society for Optics and Photonics.

 Alavi, A. H., H. Hasni, P. Jiao, and N. Lajnef. 2017. “Structural Health 

Monitoring Using a Hybrid Network of Self-Powered Accelerometer 

and Strain Sensors.” Presented at SPIE Smart Structures and 

Materials + Nondestructive Evaluation and Health Monitoring. 

Portland, OR: International Society for Optics and Photonics.

 Furkan, M., Q. Mao, M. Mazzotti, J. DeVitis, et al. 2016. “An 

Investigation on Wireless Sensors for Asset Management and 

Health Monitoring of Civil Structures.” Presented at SPIE, Sensors 

and Smart Structures Technologies for Civil, Mechanical, and 

Aerospace Systems. Las Vegas, NV: International Society for Optics 

and Photonics.

 Furkan, M. O., Q. Mao, S. Livadiotis, M. Mazzotti, et al. 2017. 

“Multipurpose Wireless Sensors for Asset Management and Health 

Monitoring of Bridges.” Presented at the Structural Health 

Monitoring of Intelligent Infrastructure Conference. Brisbane, 

Australia: International Society for Structural Health Monitoring of 

Intelligent Infrastructure.
Technology for Assessing Performance

EAR PROGRAM RESEARCH RESULTS  |  77

 Furkan, M. O., Q. Mao, S. Livadiotis, C. Young, et al. 2018. “Field 

Validation of Multipurpose Wireless Sensors for Bridge 

Assessment.” Presented at NDE/NDT for Highway & Bridges: 

Structural Materials Technology. New Brunswick, NJ: American 

Society for Nondestructive Testing.

IMPACT: The wireless sensor systems that researchers developed can efficiently 

collect and transmit data to bridge owners so they can monitor structural health 

and compare conditions against reliable baseline data on an ongoing basis. The 

ability to deploy the systems and collect measurements rapidly will enhance 

bridge testing and condition assessments.

PROJECT: Ultra Low-Power Wireless Sensing System

INSTITUTIONS: Michigan State University, Washington University in St. Louis, 

and the University of Southern California

COMPLETED: 2018

OBJECTIVES: To advance the practical 

application of structural 

health monitoring 

methodologies for 

bridges by developing 

self-powered sensor 

technology, and to 

investigate novel 

damage prognosis 

methods and effective 

sensor implementation 

strategies.

RESULTS: This team of researchers 

explored the benefits of self-powered 

piezoelectric floating gate (PFG) 

sensors. These materials can convert 

mechanical energy, such as strains and 

vibrations, into electrical energy. The 

generated electrical signals, which are 

Top to bottom: Michigan’s Mackinac 

Bridge and a 0.468-inch piezoelectric 

transducer. © Michigan State University.
Technology for Assessing Performance

78  |  EAR PROGRAM RESEARCH RESULTS

The sensors pictured in the inset image—wireless magnetic stain 

gauge (left), wireless displacement gauge (middle), and wireless 

accelerometer (right)—were tested on this 11-span viaduct carrying 

Interstate 76 west of Philadelphia, PA. © Drexel University.

directly proportional to the mechanical excitation, also are used to power all 

electronics in the sensing system. The researchers’ models integrated finite 

element, experimental testing, and statistical and artificial intelligence. The 

information delivered by the piezoelectric transducer is stored in these gates. 

The gates record the duration of strain/voltage events when the amplitudes of 

the input signals, generated by the piezoelectric transducer, exceed certain 

predetermined thresholds. The output of the sensor is presented in the form of 

a histogram in which each gate denotes the cumulative time of the events at a 

specific, predetermined strain level. Prototypes of the PFG sensor and 

telemetry box were deployed on the Mackinac Bridge for fatigue-prone 

monitoring of structure components.

PROJECT: Multipurpose Wireless Sensors for Asset Management 

and Health Monitoring of Structures

INSTITUTIONS: Drexel University and Smartsensys

COMPLETED: 2018

OBJECTIVE: To transform reliable wired sensors, including displacement 

sensors, strain gauges, and accelerometers, into wireless 

devices to allow rapid bridge structural assessments.

RESULTS: The battery-powered wireless sensors developed in this project 

eliminated the need for long cables to connect sensors to data loggers, a 
Technology for Assessing Performance

EAR PROGRAM RESEARCH RESULTS  |  79

process that is costly and time-consuming. The wireless sensors can be 

deployed rapidly, and they establish baseline measurements when bridges are 

constructed. These measurements can be used later to assess potential bridge 

damage from floods, accidents, and other incidents. Field tests of the 

technology accurately measured factors like strain, displacement, and tilt of 

structural components. One field test on a multispan bridge that has 

experienced significant vibration showed that wireless strain and displacement 

gauges are as accurate as wired sensors. A second field

test on a multispan steel bridge over the Delaware River used wireless 

accelerometers to extract and study vibration properties (mode shapes

and frequencies) and calibrate a numerical model of the structure.

PROJECT: A Remote, Self-Sustained System for Monitoring 

Water Quality Near Highways

INSTITUTION: Montana State University

COMPLETED: 2015

OBJECTIVE: To develop an in situ water monitoring system that can provide 

real-time data and is powered by fuel cells that use biological 

activity of common stream bacteria to generate electricity.

RESOURCES: Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/16018/index.cfm.

 Project summary at https://highways.dot.gov/research/

projects/remote-self-sustained-system-monitoring-waterquality-near-highways.

 More information at https://www.environment.fhwa.dot.gov/

ecosystems/wet_storm.asp. 

RESULTS: Collecting water quality data from streams near highways can be 

difficult in hard-to-reach or remote locations. Conventional sample collection 

and laboratory analysis miss important information about pollution that occurs 

over short periods, such as highway spills or in the first flush of stormwater 

runoff from highways. In this project, researchers demonstrated the feasibility of 

using microbial fuel cells (MFC) as a reliable power source for onsite sampling 

instruments. The MFCs harvest power from electrochemical reactions driven by 

naturally occurring bacteria that oxidize magnesium, which is common in stream 

water. The MFCs generate electricity during periods of high biological activity 
Technology for Assessing Performance

80  |  EAR PROGRAM RESEARCH RESULTS

and act as batteries to store and 

release energy as needed during 

periods of low biological activity. 

The system’s sensor array uses 

wireless open-source (TelosB) 

sensors attached to probes that 

provide information on water 

quality measures, including 

temperature, dissolved oxygen, 

chloride concentration, and pH 

level. Because energy generated 

by the MFCs fluctuates, researchers 

also developed a power 

management system that can 

release stable voltage over short 

periods to power in situ sensors. A 

3-mo field test in a natural stream showed that the system can provide continuous 

monitoring of key water quality measures at a frequency of four to seven 

samples per day. 

IMPACT: This project represents an important advance toward the goal of 

developing a network of real-time, self-powered, environmental monitoring 

stations that will reduce manpower and logistical costs while improving the 

reliability and accuracy of monitoring to protect and maintain water quality 

near highways.

PROJECT: Nanoscale Sensors for Structural Health

INSTITUTION: Georgia Institute of Technology 

COMPLETED: 2013

OBJECTIVE: To develop and field-test the use of wireless, self-powered 

nanosensors and nanosensor arrays for real-time, autonomous 

strain and crack monitoring of steel bridges and other 

structures. 

The project’s control system collects, 

processes, and transmits the real-time water 

quality data provided by the in situ sensors. 

© Qing Yang, Montana State University.
Technology for Assessing Performance

EAR PROGRAM RESEARCH RESULTS  |  81

RESOURCES: Yi, X., C. Cho, J. Cooper, Y. Wang, et al. 2013. “Passive Wireless 

Antenna Sensor for Strain and Crack Sensing—Electromagnetic 

Modeling, Simulation, and Testing.” Smart Materials and 

Structures 22, no. 8: 085009. http://iopscience.iop.org/0964-

1726/22/8/085009/

 Yi, X., T. Wu, Y. Wang, R. T. Leon, et al. 2011. “Passive Wireless 

Smart-Skin Sensor Using RFID-based Folded Patch Antennas.” 

International Journal of Smart and Nano Materials. 2, no. 1: 

22–38. http://www.tandfonline.com/doi/full/10.1080/19475411.2

010.545450.

 Project details at https://highways.dot.gov/research/projects/

nanoscale-sensors-structural-health

 Fact sheet at https://www.fhwa.dot.gov/publications/research/

ear/13057/13057.pdf

RESULTS: The research team has developed several types of wireless, selfpowered, low-cost antenna sensors that can monitor potentially dangerous 

cracks in steel bridges. To reduce the costs of large-quantity production, multiple 

sensors are printed with inkjet printers and nanoscale conductive inks onto a 

thin, flexible film that can be applied to fatigue-prone areas of a bridge. The 

sensors create a network that can detect and measure multiple small cracks in 

proximity and their propagation. Powered 

by solar cells or energy captured from the 

signals of a wireless reader, the antenna 

sensor systems have great potential for 

low-cost, large-scale monitoring of 

transportation structures.

IMPACT: The research results demonstrate 

the potential for designing low-cost, 

advanced, strain-sensing systems that can 

improve the efficiency of maintenance and 

repair for steel bridges, provide substantial 

savings in operations, and increase safety.

Antenna sensor tracking crack 

propagation. Source: FHWA.
Technology for Assessing Performance

82  |  EAR PROGRAM RESEARCH RESULTS

PROJECT: Flexible Skin, Areal Shear Stress, and Pressure-Sensing 

System for Experimental Bridge Scour Research

INSTITUTIONS: National Aeronautics and Space Administration Jet Propulsion Lab 

and FHWA’s J. Sterling Jones Hydraulics Research Laboratory 

COMPLETED: 2011

OBJECTIVE: To advance technology for measuring and understanding the 

complex flow fields and boundary shear stresses and pressure 

fields associated with bridge pier scour. 

RESOURCE: Technical report at https://ntrs.nasa.gov/search.

jsp?R=20120007389.

RESULTS: In this project, NASA Jet Propulsion Laboratory investigators 

conducted research on an integrated, flexible-skin, areal shear- and pressuresensor system in a miniaturized array that measures changes in shear stress and 

pressure associated with scour-hole formation. The sensor elements were 

intended to measure shear forces in the range of 0.05 to 6 Pa and variations in 

pressure in the range of 0 to ±100 Pa, with a sampling rate of more than 

500 data points/s. Such a system will help researchers understand erosive flow 

mechanisms related to turbulence structures, together with local flow 

convergence and contractions around the fronts and flanks of piers or between 

piles of complex pier configurations. Direct measurements of shear forces are 

essential to validated computational fluid dynamic models.

IMPACT: Scour is the predominant 

cause of failure in bridges over 

water. The ability to capture shear 

stress and pressure data will 

significantly aid small-scale scour 

experiments in bridge scour 

research.

The flexible (skin) sensing system is based on 

an elastically mounted, floating plate concept. 

A single pressure sensor was inserted in the 

middle of this array. The optical encoder of 

each shear force sensor is encapsulated so the 

assembled sensor can be immersed in water. 

Source: FHWA.
Technology for Assessing Performance

EAR PROGRAM RESEARCH RESULTS  |  83

PROJECT: Development of Stiffness-Measuring Device for Pad Foot 

Roller Compaction

INSTITUTIONS: Colorado School of Mines, with Caterpillar Inc., BOMAG, 

and the Colorado Department of Transportation 

COMPLETED: 2011

OBJECTIVE: To develop a methodology to achieve continuous, real-time 

sensing of soil properties during static compaction with a pad 

foot roller. 

RESOURCES: Mooney, M. A., and R. V. Rinehart. 2007. “Field Monitoring of 

Roller Vibration during Compaction of Subgrade Soil.” Journal 

of Geotechnical and Geo-environmental Engineering 133, 

no. 2: 257–265.

 Rinehart, R. V., and M. A. Mooney. 2008. “Instrumentation of a 

Roller Compactor to Monitor Vibration Behavior during 

Earthwork Compaction.” Journal of Automation in 

Construction 17, no. 2, 144–150.

RESULTS: Measurement of soil stiffness during compaction of foundations for 

highway structures is critical to ensuring that design-life specifications are met. 

In this study, investigators developed a conceptual framework for determining 

pad–soil contact force and displacement (and thus soil stiffness) from sensors 

built into the pads and roller, constructed a prototype measurement system, and 

devised a wireless data acquisition system to enable field-scale testing. They 

successfully measured plastic and elastic soil deformation during compaction 

using laser-based distance sensors and pad-strain-based techniques. Laboratory 

and field testing confirmed the predicted strain field 

changes. Some elements of the model need further 

refinement to ensure repeatable and accurate 

measurement across various soil conditions.

IMPACT: Intelligent compaction allows 100 percent 

quality control in real time. More comprehensive, 

accelerated measurement of compaction could improve 

long-term performance of roadway base courses and 

extend pavement life.

Strain gauges, installed within selected pads that are welded to 

the drum, are wired to a signal processing box that transmits 

data wirelessly to a computer in the cab. Source: FHWA.
New Technology and Advanced Policies 

for Energy and Resource Conservation

84  |  EAR PROGRAM RESEARCH RESULTS

Advances in harvesting and embedding energy are allowing for placement of 

sensors and control technology where it previously would have been 

impractical and for increased reliability where current systems are subject to 

disruption from extreme events. Research in this area combined with new 

approaches to sensing, assessment, and control will allow for improved 

resilience of the highway system. 

PROJECT: Creating Productive Roadways: Developing an Advanced 

Energy Production, Storage, and Distribution System

INSTITUTION: University of Nebraska-Lincoln

COMPLETED: 2014

OBJECTIVE: To use existing roadway and right-of-way infrastructure to 

produce, store, and distribute stable and renewable electric 

power.

RESOURCES: Zhao, M., and A. Sharma. 2015. “Optimal Deployment of Hybrid 

Alternative Power System at Signalized Intersections.” Journal 

of the Transportation Research Board 2438: 72–80. 

 Zhao, M., A. Sharma, D. G. Bernt, A. J. Meyer, et al. 2013. 

“Economic Analysis of Using Renewable Wind Power System 

at a Signalized Intersection.” Journal of Intelligent 

Transportation Systems 17, no. 3. 210–220. 

 Zeng, J., Z. Zhang, and W. Qiao. 2014. “An Interconnection and 

Damping Assignment Passivity-Based Controller for a DC-DC 

Boost Converter with a Constant Power Load.” IEEE Trans. 

Industry Apps. 50, no. 4: 2314–2322. 

 Zeng, J., Q. Wei, L. Qu, and Y. Jiao. 2014. “An Isolated Multiport 

DC-DC Converter for Simultaneous Power Management of 

Multiple Different Renewable Energy Sources.” IEEE J. Emerg. 

Select. Topics Power Electron 2, no. 1: 70–78. 

 Zeng, J., and W. Qiao. 2013. “Short-Term Solar Power 

Prediction Using a Support Vector Machine.” Renewable 

Energy 52: 118–127. 

 Zeng, J., and Qiao, W. 2012. “Short-Term Wind Power 

Prediction Using a Wavelet Support Vector Machine.” IEEE 

Trans. Sustain. Energy 3, no. 2: 255–264. 
New Technology and Advanced Policies

for Energy and Resource Conservation

EAR PROGRAM RESEARCH RESULTS  |  85

 Project information is located at http://energyplusroadways.

unl.edu/.

RESULTS: The project investigators demonstrated the feasibility and effectiveness 

of a Roadway Wind/Solar Hybrid Power Generation and Distribution System 

(RHPS). Reliable, renewable power generation within the roadway and right-ofway infrastructure can significantly reduce the cost of operating and maintaining 

highway systems. Excess power generation can be a source of revenue to further 

offset operating costs. Moreover, reliable and renewable power can provide 

important backup to keep critical roadway safety and control systems operating 

during periods of local or regional power failure. The main element of the RHPS 

is the energy-plus roadway traffic signal light (EPRTL), which includes a wind 

and solar power system installed on a traffic pole. Key components of the RHPS are:

 • Wind turbines and solar panels mounted on the poles of existing traffic 

signals and street lights. 

 • High-efficiency, low-cost, electronic power converters, controls, and 

communication boards. 

 • Power management algorithms and software to coordinate operation of 

various EPRTL elements and allow the RHPS to operate in a grid-connected 

configuration.

IMPACT: The RHPS represents a significant advance toward development of 

roadway structures that use renewable sources to produce more energy than 

they consume. The RHPS will provide stable, reliable power to ensure that critical 

transportation system components operate safely and continuously during local 

or widespread power outages.

The renewable infrastructure of this project in place.

© University of Nebraska-Lincoln.
86  |  EAR PROGRAM RESEARCH RESULTS

RESULTS FROM RESEARCH

ASSOCIATESHIP PROGRAM

The Federal Highway Administration (FHWA) participates in the 

National Research Council (NRC) Research Associateship Program 

(RAP) with other sponsoring Federal laboratories and approved 

research organizations. RAP provides high-skilled, promising 

postdoctoral and senior scientists and engineers with opportunities 

to research problems that are compatible with the interests of 

sponsoring laboratories. To supplement the expertise of the 

permanent staff, FHWA, through the EAR Program, uses the RAP 

to invite researchers with appropriate backgrounds to investigate 

specific problems on a short-term basis across a range of topics 

and disciplines. The associates have researched a variety of topics, 

such as nanoadditives for concrete and asphalt, alternative 

intersection and interchange design, and cost-benefit analysis of 

connected and automated vehicle operations.

For more details on the projects or to view a copy of the most 

recent version of the EAR Program’s Research Associates Program

booklet, please visit our publication web page at https://www.fhwa.

dot.gov/publications/lists/advancedresearch/pubs.cfm.

The Exploratory Advanced Research Program

86  |  EAR PROGRAM RESEARCH RESULTS
EAR PROGRAM RESEARCH RESULTS  |  87

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.

The program has awarded 101 research projects on 57 different topics 

between 2007 and 2021. The research awards include work by 

multidisciplinary teams at 80 academic institutions, 57 private 

companies, 13 State and local agencies, 10 Federal laboratories, and 10 

foreign institutions.

LEARN MORE

For more information, see the EAR Program website at http://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.
88  |  EAR PROGRAM RESEARCH RESULTS
89  |  EAR PROGRAM RESEARCH RESULTS
90  |  EAR PROGRAM RESEARCH RESULTS

EAR PROGRAM RESULTS

As a proponent of applying ideas across traditional research fields to stimulate new 

problem-solving approaches, the EAR Program strives to develop partnerships with 

the public and private sector. 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.

FHWA-HRT-22-034

HRTM-30/12-21(200)E

Recommended Citation: Federal Highway Administration, 

EAR Program Research Results - Updated Through 2021 

(Washington, DC: 2021) https://doi.org/10.21949/1521708.