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Exploratory Advanced Research Program

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Computer Vision in Highway Transportation Research


 

Highway transportation researchers are collecting and analyzing an increasing amount of video data. Reasons include recent technological breakthroughs that provide new and enhanced visual and other sensors for conducting research in multiple areas such as system planning, operations, safety, and infrastructure condition assessment.

 

  • Eye tracking technology now allows for more natural behavior and field applications. Examples of research using this technology include the Exploratory Advanced Research (EAR) Program-sponsored research projects, “Seeing in the Dark Improving Understanding of Driver Visibility Requirements at Night,” [more] and “Development of Methodologies to Evaluate the Nighttime Safety Implications of the Roadway Visual Scene Under Varying Cognitive Task Loads.” [more]

  • Increased use of traffic cameras and improved analysis software are providing data on vehicle classification, weight, speed, routing. Road-based and vehicle-based cameras also are providing improved recognition of pedestrians, e.g. the EAR Program-sponsored project, “Real–Time Pedestrian Detection Layered Object Recognition System for Pedestrian Collision Sensing.” [more]

  • Use of LIDAR and improved analysis software are assisting with the cataloguing of road and roadside conditions including pavement surface conditions, roadside topography, and roadside hardware.

 

The Strategic Highway Research Program (SHRP) 2 safety area includes elements of the above types of data in the naturalistic driving study (NDS). The amount of data can be orders of magnitude larger than what the highway researcher has worked with previously with research results expected to exceed one petabyte. FHWA’s EAR Program working with the Office of Safety R&D is sponsoring five research projects that will explore breakthroughs in machine learning to automate extraction of safety data from NDS such as SHRP2 project.  The NDS involved collection of data on the daily travels of 3,150 volunteer drivers, whose vehicles were heavily instrumented for the study. Those drivers traveled 49.5 million miles during the study period, resulting in over 1.2 million hours of video and vehicle data. See http://www.trb.org/StrategicHighwayResearchProgram2SHRP2/Public/Pages/Safety_153.aspx, for more information on the SHRP2 safety area.

 

FHWA is also working with experts at Oak Ridge National Laboratory to test the research results and develop methods and test data sets for future researchers to use in comparing and validating the performance of automated data extraction algorithms.

 

While the research community is fortunate to be able to collect more and better data, the amount of data has the potential to overwhelm the capacity to assess the data using current methods. Current methods include a mix of automated and manual, frame-by-frame coding that is not able to manage massive data stream and provides results that are not consistent or error free enough. Large data sets in their present form are too time-consuming and expensive to analyze using traditional data extraction methods, yet they are important for providing understanding of the context around rare events such as crashes. Automating data extraction from video files is expected to dramatically reduce the costs of using these data, making them accessible to the widest possible pool of researchers.

 

ITS America conducted a technology scan for the USDOT Intelligent Transportation Systems (ITS) Joint Program Office. The scan report, "Connected Vehicles: Trends in Computer Vision," are located at http://www.itsa.org/knowledgecenter/technologyscan. As the technology moves from stand alone to integrated systems and from systems that provide driver or operator warnings to direct control of vehicle and infrastructure systems (i.e. steering, acceleration, braking, taffic signals) there is a critical need for compatible systems architecture and common conditions against which multiple manufacturers can test their equipment and software.

Exploratory Advanced Research Program

Research Highlights


Brochures

EAR Program Research Results - Updated Through 2013,(FHWA-HRT-14-033)- December 2013

Multimedia Downloads

Investigating Advanced Traffic Signal Control, (N/A)- April 2011

Project Fact Sheets

Understanding Material Durability - Workshop Examines Aging of Composite Materials,(FHWA-HRT-14-068)- June 2014

Reports

Multiscale Materials Modeling Workshop Summary Report April 23-24, 2013(FHWA-HRT-13-103)- December 2013

Scanning and Convening Activities Fact Sheets

Understanding Material Durability - Workshop Examines Aging of Composite Materials,(FHWA-HRT-14-068)- June 2014

Summaries

Technological Innovations in Transportation for People with Disabilities: Workshop Executive Summary(FHWA-HRT-11-042)- September 2011

Web Articles

For Georgia State Students, EAR Program Opens a Window on Transportation Research ()- March 2014

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