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            Automated Video Inspection System for Grade Crossing Safety
      

      
  Document Series
              Research Results


      
  Author
          Federal Railroad Administration


      
Report Number
              RR 21-05

  Office
              RDI-21


      Subject
                    Artificial Intelligence,
                    Grade Crossing Pedestrian Safety,
                    Grade Crossing Technology


      
  Keywords
              VisioStack, RailLinks, artificial intelligence, forward-facing video, grade crossing safety


      

      
      
              
                  
      
              
  Document
              AVIS-A.pdf (459.22 KB)

      
              The Federal Railroad Administration (FRA) has sponsored several programs to help reduce incidents at highway-rail crossings and improve the safety of both vehicles and pedestrians. One such recent project developed an artificial intelligence (AI)-based machine vision system to help inspect highway-rail grade crossings with forward-facing video (FFV) obtained from a Class I geometry car. The goal of this research is to apply the same concepts for locomotive-mounted FFV cameras, currently in common use within the industry; it complements manual inspections. FRA supported this research through its Phase I Small Business Innovation Research (SBIR) initiative.
      
            
      
      
              Last updated: Friday, April 16, 2021 U.S. DEPARTMENT OF TRANSPORTATION

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