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Exploratory Advanced Research Overview

  • Figure shows four stacked photos in a square arrangement.  The top left photo is a street scene showing homes and parked cars to

    Breakthroughs in Computer Vision for Highway Transportation Research

    FHWA’s Exploratory Advanced Research Program working with the Office of Safety R&D is exploring breakthroughs in machine learning for automating extraction of safety data from video files to dramatically reduce the costs of using these data, making them accessible to the widest possible pool of researchers.
  • Photo shows two white mid-sized SUVs approaching a railroad crossing on a test track.

    Simulating Connected Vehicle Technologies in Virtual Traffic Environments

    Connected vehicle (CV) technology exchanges information between vehicles, mobile devices, and traffic control systems using vehicle-to-vehicle and vehicle-to-infrastructure wireless communication. CV data can be used to enhance safety, improve traffic flow, increase fuel efficiency, and reduce emissions.
  • Novel Surface Transportation Modes Report Cover

    Novel Modes Explored During Multimodal Workshop

    The Office of the Assistant Secretary for Transportation published summary reports on a 2014 Novel Modes Workshop. This initial stage investigation was a multimodal effort, supported by the Federal Highway Administration’s (FHWA’s) Exploratory Advanced Research (EAR) Program.
  • The Impact of Automated Transit, Pedestrian, and Bicycling Facilities on Urban Travel Patterns Report Cover

    The Impact of Automated Transit, Pedestrian, and Bicycling Facilities on Urban Travel Patterns

    A recent summary report from the Federal Highway Administration’s (FHWA’s) Exploratory Advanced Research (EAR) Program provides an overview of research into the potential of a hypothetical driverless vehicle to improve access to and use of an available rapid-transit rail service.
  • This video shows two video clips (one right after the other) to show how people merge, either manually, or using the cooperative

    Cooperative Adaptive Cruise Control: Merging Behavior

    "Cooperative Adaptive Cruise Control (CACC): Investigation of Key Human Factors Issues" is an Exploratory Advanced Research Program project designed to investigate CACC as a way to address congestion and safety issues on today’s highway system.


Technology Readiness Level Guidebook Released

A publication by the Exploratory Advanced Research (EAR) Program helps those working in transportation research conduct an evaluation to determine the maturity of a technology and identify the next steps in the research process. The Technology Readiness Level (TRL) Guidebook explains what a TRL is and how to prepare for, conduct, and use the results of TRL assessments. [more]

Read the full text of the TRL Guidebook.

NRC Postdoctoral Fellows Help EAR Program Solve Transportation Issues

The Turner-Fairbank Highway Research Center (TFHRC) conducts research across a wide range of topics and disciplines. To supplement the expertise of the permanent staff, it is important to bring in researchers with the appropriate backgrounds to investigate specific problems at short-term basis. Through the EAR Program, FHWA utilizes the Resident Associates (or Postdoctoral Fellows) program of the National Research Council (NRC) for this purpose. The NRC provides a process for selecting candidates on a competitive merit basis and subsequently for administration of the Resident Fellows during their tenures at FHWA.

Is It Possible for a Bridge to "Feel" Changes in Loading Caused by Traffic or the Environment and Respond by Redistributing Loads Throughout the Structure?

Answering this intriguing question is the goal of research supported by the EAR Program. The project, "Self-Sensing Adaptive Material for a New Generation of Multifunctional Bridge-Bearing Systems," is part of a 3-year EAR Program-funded inquiry into developing responsive smart materials for bridge components. The University of Nevada, Reno, is conducting the research under the EAR Program. Click here for more information.