The Federal Highway Administration's (FHWA's) Exploratory Advanced Research (EAR) Program bridges the gap between basic and applied research. The EAR Program does not fund projects through commercialization or deployment, and, in fact, stops well short. For the EAR Program to be successful, the results must be taken up by the research community, with the support of other government, industry, or nongovernmental funding. Accordingly, the EAR Program is committed to supporting a transition process.
The results of EAR Program-funded projects may include:
- New fundamental insights and how they can be applied in the field of highway transportation.
- New research methods, approaches, models, or data that can accelerate applied research.
- New system concepts or prototypes, including laboratory testing and possibly some limited field testing.
Transitioning Research Results
The value of the EAR Program lies in how researchers in government, academia, and industry use the results. For EAR Program-sponsored projects that reach or exceed their anticipated results or provide other results that have immediate or near-term value, the EAR Program is committed to providing the support necessary so that the results are not left on the shelf or in the lab.
The EAR Program uses Technology Readiness Level (TRL) assessments along with other tools to help identify which research products to emphasize for transition and which audiences would be interested in the results.
The EAR Program published a Technology Readiness Level Guidebook to assist researchers in conducting an evaluation.
Connected Highway and Vehicle System Concepts
Assistive Technologies for Visually Impaired Persons
There are approximately 2 million adults with reported vision loss in the United States. Independent travel and active interactions with the surrounding environment present significant daily challenges for these individuals, ultimately reducing quality of life and compromising safety. To begin to address these challenges, the FHWA's EAR Program funded three research projects to examine new technology solutions for wayfinding and navigation guidance for people with vision impairment and other disabilities. For more information, download the fact sheet.
Figure 1. A chest-mounted stereo camera and inertial measurement unit form part of Auburn University's pedestrian navigation system.
Efficient and Safe Merging Solutions - Advanced Freeway Merge Assistance: Harnessing the Potential of Connected Vehicles
One of the major traffic bottlenecks and safety concerns on today's busy roads occurs during freeway merges. "Advanced Freeway Merge Assistance: Harnessing the Potential of Connected Vehicles" is an EAR Program project designed to improve the efficiency and safety of freeway merges using connected vehicle technology. This project was awarded by the FHWA in 2009 and was conducted by the University of Virginia Center for Transportation Studies. Download the fact sheet to learn more.
Layered Object Recognition System for Pedestrian Collision-Sensing Project
Figure 2. The camera shows a rear-view mirror with the portable processing system in an aluminum suitcase for safe mobility.
For further information on the Layered Object Recognition System for Pedestrian Sensing project, contact Wei Zhang, Office of Safety Research and Development, FHWA; 202–493–3317; email: email@example.com.
Breakthrough Concepts in Material Science
Novel Alternative Cementitious Materials for Development of the Next Generation of Sustainable Transportation Infrastructure
Figure 3. The Route 60W/71S interchange in the Los Angeles, CA, area shows good performance after 17 years of continual heavy traffic loads.
High-Performance, Stress-Relaxing Cementitious Composites for Crack-Free Pavements and Transportation Structures Project
Figure 4. Cracks were very shallow when carbon nanofibers (CNFs) are used, and beams did not fracture through the shallow cracks during the bending test.
Texas A&M University’s Texas Transportation Institute, in an EAR Program-funded project, performed a comprehensive study of past efforts to incorporate carbon nanofibers (CNFs) and carbon nanotubes (CNTs) into cementitious materials to improve the mechanical properties and behaviors of these materials. The tasks performed in the study were important steps toward achieving the ultimate goal of this project: the development of an advanced hardened cement paste that is strong and resists shrinkage cracking under certain levels of restraint.
Human Behavior and Travel Choices
Agent-Based Approach for Integrated Driver and Traveler Behavior Modeling
The research team developed a theoretical framework for agent-based driver and traveler behavior modeling. The team evaluated traditional and emerging data collection methods for agent-based modeling systems (ABMS) in transportation, evaluated alternative implementation platforms for ABMS applications in transportation, and developed an agent-based model of en route and pretrip route, departure time, and mode choices. Learn more here.
Evolutionary Agent System for Transportation Outlook (VASTO)
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 researchers delivered a set of comprehensive modeling tools and a revolutionary system for a multiagent modeling system framework. Learn more here.
Driver Behavior in Traffic
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. Click here for more information or download the fact sheet.
Behavioral Science's Approach to Testing, Validating, and Establishing Best Practices for Alternative Highway Revenue Collection
Understanding driver reaction to congestion pricing has been limited, partly because data are commonly collected via simple surveys that ask for intended responses to proposed congestion pricing. These surveys lack clear incentives for respondents to answer truthfully and accurately. Although the surveys are useful for some purposes, these methods are known to generate biased and unpredictable responses.
This study used experimental economics to observe choices with precise monetary incentives. The participant pool was drawn from drivers in Orlando, FL, and Atlanta, GA. Participants received travel options with travel time and financial consequences. The overall objective of the study is to understand why drivers change their route choices when tolls change. A particular focus is the extent to which responses differ depending on varying preferences and perceptions of travel times and travel time reliability. Many of the instruments and procedures used in this study represent new methods of generating behavioral data on policy issues.
Making Driving Simulators More Useful for Behavioral Research
Figure 5. Actual road data (red points) used in response comparisons for a roundabout scenario.
The University of Iowa, in an EAR Program-funded project, identified highway design needs and matched them to specific characteristics of driving simulators (e.g., motion, field of view, speed, and steering torque). The researchers developed and demonstrated tools to characterize how closely responses to simulator characteristics match real-world driving outcomes. In experiments conducted on four different simulator platforms, they 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 high-fidelity simulator, with attention to accurately rendering the visual complexity of the roadway, will influence drivers in the simulator to drive at speeds comparable to those observed on actual roadways. Project models will enable the driving safety research community and highway designers to predict real-world driving behavior more accurately. The models also will save time and money by informing researchers when experiments require high-fidelity simulation and when lower fidelity approaches are adequate.
For more information on the Making Driving Simulators More Useful for Behavioral Research project, contact Brian Philips, Office of Safety Research and Development, FHWA; 202–493–3468; email, firstname.lastname@example.org.
Technology for Assessing Performance
Preventing Fuel Tax Evasion: Developing a Real-Time Fuel Tax Evasion Detection Solution
The U.S. Department of Energy’s Oak Ridge National Laboratory (ORNL), in an EAR Program-funded project, aims to reduce or eliminate fuel tax evasion schemes. Motor fuel and other highway-use taxes provide the primary source of funding for the Nation’s highway transportation system. Instead of relying on a single solution to prevent fuel tax evasion, researchers developed entirely new inline sensors and integrated other advances in sensor technology to combine wireless communications, vehicle tracking, and information analysis. Developing a fuel tax evasion detection system can potentially reduce or eliminate fuel tax evasion schemes, resulting in millions of dollars of additional revenue in the Highway Trust Fund.
For more information on this research project, check out the Public Roads article on “Nailing The Cheats.”
Assessing the Structural Health of America's Highway Bridges
Figure 6. Prototype sensor board with piezoelectric-floating-gate chipset inside
a 915 MHz telemetry box.
Bridges and other highway structures age, crack, and weaken over time. They can deteriorate because of wear and tear from everyday traffic, weather events, and crashes. FHWA requires a visual inspection of bridges every two years. Inspections may not always provide a complete picture of structural conditions because the naked eye cannot detect internal changes or damage that occurs at a microscopic level. The EAR Program is supporting research to develop self-powered wireless sensors that can monitor structural health or assess bridge conditions.
Michigan State University (MSU) is working on a project focused on structural health monitoring using wireless monitors. The project is called the "Ultra Low-Power Wireless Sensing System." Washington University in St. Louis and the University of Southern California are collaborating with MSU on this project.
Drexel University researchers are developing a suite of portable wireless sensors to provide important baseline data on structural health. These sensors can be installed as needed to assess damage from floods, accidents, or similar incidents that might compromise structural integrity. The Drexel project is called "Multipurpose Wireless Sensors for Asset Management and Health Monitoring of Structures."
To learn more, download the fact sheet.