The Federal Highway Administration (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.
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”.
Making Driving Simulators More Useful for Behavioral Research
Figure 1. 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 will also 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, email@example.com.
Nanoscale Sensors for Structural Health
Figure 2. Antenna sensor tracking crack propagation.
The Georgia Institute of Technology, in an EAR Program funded project, has developed several types of wireless, self-powered, 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. The antenna sensor systems, powered by solar cells or energy captured from the signals of a wireless reader, have great potential for low-cost, large-scale monitoring of transportation structures. 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.
For more information on the Nanoscale Sensors for Structural Health project, visit the Nondestructive Evaluation Laboratory Website.
Layered Object Recognition System for Pedestrian Collision- Sensing Project
Figure 3. The camera shows a rear-view mirror with the portable processing system in an aluminum suitcase for safe mobility.
Sarnoff Corporation, in an EAR Program funded project, developed a real-time, in-vehicle, stereo vision–based system that detects, recognizes, and tracks pedestrians in the field of view. The layered object recognition system for pedestrian collision sensing can detect and track pedestrians in its field of vision at vehicle speeds of up to 30 mi/h (miles per hour) and up to 35 meters (m) away under good visibility conditions and up to 25 m away under reduced visibility with a 90 percent overall positive detection rate. To perform to the required level for real-life pedestrian detection, system performance must be improved such that detection is possible at vehicle speeds up to 45 mi/h, at distances up to 60 m, under day and evening visibility conditions, in urban and rural settings, and at intersection and nonintersection locations. Commercial implementation would require a market price of not more than a few thousand dollars, which is feasible with the components used in the prototype with sales in the tens of thousands.
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: firstname.lastname@example.org.
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.
For further information on the High-Performance Stress-Relaxing Cementitious Composites for Crack-Free Pavements and Transportation Structures project, contact Rick Meininger, Office of Infrastructure Research and Development, FHWA; 202-493-3191; email: email@example.com.