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Evaluation of the Exploratory Advanced Research Program (2022) / Chapter Skim
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Appendix C - Case Study on Video Analytics
Pages 54-57

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From page 54...
... Research themes included identifying vehicles, detecting eye movement, and analyzing road conditions, as well as analyzing the increasing abundance of visual data from highway and roadside cameras. Panelists for technical proposal evaluation come from within FHWA (Office of Safety R&D)
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From page 55...
... Oak Ridge researchers noted that the EAR-funded VA projects were funded at the beginning of research on artificial intelligence, such as deep learning, which has revolutionized video data analysis in general, thus limiting the appeal of those packages. C.3  VA Research Outcomes The major outcome from VA research at the EAR Program is a new set of research tools for the academic community.
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From page 56...
... 2014–2015 DCode: A Comprehensive Automatic Coding SRI International System for Driver Behavior Analysis 2014–2017 DMask: A Reliable Identity Masking System for SRI International Driver Safety Video Data 2014–2015 Automated Feature Extraction Carnegie Mellon University 2014–2017 Quantifying Driver Distraction and Engagement University of Wisconsin– Using Video Analytics Madison 2019–2022 Deep InSight: Deep Extraction of Driver State Iowa State University from Naturalistic Driving Dataset 2019–2021 Video Analytics for Automatic Annotation of Virginia Tech Driver Behavior and Driving Situations in Naturalistic Driving Data 2020–2022 Automated Video Processing Algorithms to University of Michigan–Ann Detect and Classify High-Level Behaviors with Arbor Speed and Accuracy 2019–2022 Development and Application of a Disaggregate University of Connecticut Artificial Realistic Data Generator for Computationally Testing Safety Analysis Methods 2019–2021 Multidisciplinary Initiative on Methods to University of Missouri Integrate and Create Artificial Realistic Data • Test, assess effectiveness of tool • Prototype systems; test application to other features • Provide segments of video data EAR's funding has had a significant impact on developments in VA related to transportation research. One of EAR's most significant contributions has been connecting researchers with other collaborators to expand research in this field.
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From page 57...
... Interestingly, four projects supported researchers as early as the undergraduate level, with two projects supporting more than 15 researchers. In comparison with other EAR-funded projects, VA projects supported, on average, six times more undergraduate students and two times more graduate students.
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Key Terms

  • video data
  • projects supported
  • video analytics
  • feature extraction
  • sri international

  • visual data
  • analyzing road
  • video footage
  • using video
  • automated feature

  • respondents reported
  • eye movement
  • road conditions
  • proposal evaluation
  • naturalistic driving

  • increasing abundance
  • identity masking
  • virginia tech
  • identifying vehicles
  • technical proposal

  • driver awareness
  • automatic coding
  • patent inventions
  • highway safety
  • provide segments

  • awareness factors
  • performance tests
  • ear project
  • roadside cameras
  • addressed improving


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