Automatic Safety Diagnosis in Connected Vehicle Environment (Project F4)

Traditionally highway safety studies rely on historical crash data. Yet because crashes are rare events, crash-data possess deficiency in availability and quality. As an alternative, the non-crash-data approach which measures conflict and near-crash based on Traffic Conflict Technology (TCT) has been increasingly widely used. Connected vehicle (CV) is a major research initiative of the US Department of Transportation to capture vehicle position, motion and instantaneous driving for information connectivity. In the CV environment, massive Basic Safety Messages (BSMs) are being generated and exchanged between vehicles and infrastructures. Driving behavior differs considerably among individuals and each driver has her/his own driving patterns, among which the most important feature for safety diagnosing is threshold segmenting normal and abnormal/aggressive driving status. Due to the tremendous volume and complexity, it is not realistic to store all the BSMs generated in CV into the data center. Extensive researches have been dedicated to the big data of BSMs but not yet on individual level for near-crash detection. This research is motivated to explore what information imbedded in BSMs need to be stored, how to extract it and how to process it for real-time traffic safety diagnosis combining the TCT technology. The goal of this research is to construct a computational pipeline of Near-crash Diagnoses System to process the BSMs generated in the CV environment to identify near-crash events on the individual level.


  • English


  • Status: Completed
  • Funding: $57500
  • Contract Numbers:


  • Sponsor Organizations:

    Southeastern Transportation Research, Innovation, Development and Education Center (STRIDE)

    University of Florida
    365 Weil Hall
    Gainesville, FL  United States  32611

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Managing Organizations:

    U.S. Department of Transportation Research and Innovative Technology Administration

    1200 New Jersey Avenue, S.E.
    Washington, DC,     20590
  • Project Managers:

    Tucker-Thomas, Dawn

  • Performing Organizations:

    Jackson State University, Jackson

    Department of Civil and Environmental Engineering
    Jackson, MS  United States  39217-0168
  • Principal Investigators:

    Tu, Shuang

  • Start Date: 20200801
  • Expected Completion Date: 20210731
  • Actual Completion Date: 20220613
  • USDOT Program: University Transportation Centers

Subject/Index Terms

Filing Info

  • Accession Number: 01768221
  • Record Type: Research project
  • Source Agency: Southeastern Transportation Research, Innovation, Development and Education Center (STRIDE)
  • Contract Numbers: 69A3551747104
  • Files: UTC, RIP
  • Created Date: Mar 25 2021 9:01PM