Completing the Picture of Traffic Injuries: Understanding Data Needs and Opportunities for Road Safety

Police recorded crash data has improved over time, but still fails to report all aspects of crashes that are important to developing a full understanding of crash mechanism, injury burden, pre-crash conditions, and ultimately total health and cost outcomes. Traditionally, safety and injury analysis has occurred in siloed fields, with road safety researchers relying predominately on police-recorded crash reports, and public health researchers relying on hospitalization records. Depends on context of the study and used database, findings vary, this is the case for micro-level (e.g., injury severity of an individual) to macro-level (injury rate) scale. This work will begin to map disparate datasets to inform questions surrounding crashes. The data-mapping process will aim to build linkages between police-crash datasets and other datasets (i.e., Incident-Oriented Data, Spatial Data, Emerging Datasets) and scale it up to larger geographic areas. Efforts to augment crash data are not new. A notable health-oriented example which sought to link health and police records was Crash Outcome Data Evaluation System (CODES). Although this federal program ended in 2013, some states have continued this effort, including California, North Carolina, and Tennessee. Added data and analytics will result in a more "complete picture” of crashes and injuries. This Complete picture enables researchers to improve their modeling, assist policy makers, and contribute to visualization that helps tell compelling safety stories that guide safety improvements. The key objectives of this study are: 1. To "complete the picture" of crashes and determine which elements of data that exist outside of conventional crash data can contribute to this picture. These elements likely include EMS, ED, DMV, Health Expenditure, Census, and Land Use, among others. We will build on existing efforts (e.g., CODES, CMOD, SW8 and others). We hope to understand how emerging datasets can be mapped to crash data. 2. To identify innovative statistical, probabilistic, and big data visualization tools to link crashes with other records, either by record-matching, or augmenting datasets based on spatial or temporal indicators to perform more-advanced safety analysis. Project outcomes of this study are: 1. Comprehensive Data Map: A safety-oriented data map will inform methods to link datasets. This map will result in a more complete picture of crashes, where researchers can use the framework to improve safety analysis. 2. Improved Modeling Efforts: Supplementing crash data with complementary legacy and emerging datasets will improve modeling efforts. These linkages will be tested through three proof-of-concept applications. 3. Journal Publications: We intend to publish results of this study, focusing on both framework methodology and applications, and anticipate at least three journal articles from this effort. 4. Stakeholder Engagement and Tech Transfer: We will engage stakeholders through our partnerships with CMOD and other NC and TN Departments of Health, Transportation, and Safety. The project will contribute to work force development through the education, training, and professional development opportunities provided to students engaged in the project.

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  • Supplemental Notes:
    • The first-year effort will aim to begin several of these applications. We intend to explore three applications of the more complete datasets, led by three of the collaborating faculty. Possible applications follow: 1) Injury Burden Among Bicyclists and Pedestrians 2) Crashes and Destination Accessibility 3) Work Zone Crash Impacts


  • English


  • Status: Active
  • Contract Numbers:


  • Sponsor Organizations:

    Office of the Assistant Secretary for Research and Technology

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

    Collaborative Sciences Center for Road Safety

    University of North Carolina, Chapel Hill
    Chapel Hill, NC  United States  27514
  • Project Managers:

    Sandt, Laura

  • Performing Organizations:

    University of Tennessee, Knoxville

    Knoxville, TN  United States 
  • Principal Investigators:

    Cherry, Christopher

  • Start Date: 20170301
  • Expected Completion Date: 20180228
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers Program

Subject/Index Terms

Filing Info

  • Accession Number: 01627999
  • Record Type: Research project
  • Source Agency: Collaborative Sciences Center for Road Safety
  • Contract Numbers: 69A3551747113
  • Files: UTC, RiP
  • Created Date: Feb 24 2017 1:27PM