Evaluation of Near-Miss Crashes Using a Video-Based Tool

Vision-based trajectory data provide useful information on the trajectories of roadway users (vehicles, pedestrians, bicycles) that could be used for analyzing roadway safety and users’ interactions. Several companies offer vision-based software that promise to identify near-miss crashes between vehicles, pedestrians and vehicles, or bicycles and vehicles, by estimating surrogate measures for near-misses through the trajectory data. However, the accuracy of these methods in terms of predicting near-misses has not been evaluated. Therefore, the objective of this research is to install a commonly-used video-based software, and evaluate its accuracy of predicting near-misses at a busy signalized intersection in the Lawrence, KS area. The main objective of this research is to evaluate a video-based tool offered by “Brisk Synergies” in terms of its accuracy of predicting near-misses at signalized intersections. The findings of this study will help KDOT and local transportation partners to decide whether to invest or not in video-based tools at signalized intersections.

  • Supplemental Notes:
    • Final report is pending.


  • English


  • Status: Active
  • Funding: $71500
  • Contract Numbers:

    K-TRAN: KU-21-4



  • Sponsor Organizations:

    Kansas Department of Transportation

    Eisenhower State Office Building
    700 SW Harrison Street
    Topeka, KS  United States  66603-3754
  • Performing Organizations:

    University of Kansas Center for Research, Incorporated

    2291 Irving Hill Drive, Campus West
    Lawrence, KS  United States  66045
  • Principal Investigators:

    Schrock, Steven

    Kondyli, Alexandra

  • Start Date: 20200701
  • Expected Completion Date: 20231130
  • Actual Completion Date: 0

Subject/Index Terms

Filing Info

  • Accession Number: 01760107
  • Record Type: Research project
  • Source Agency: Kansas Department of Transportation
  • Contract Numbers: K-TRAN: KU-21-4, RE-0816-01, C2171
  • Files: RIP, STATEDOT
  • Created Date: Dec 15 2020 3:29PM