Identifying Highly Correlated Variables Relating to the Potential Causes of Reportable Wisconsin Traffic Crashes

Currently, Wisconsin Department of Transportation (WisDOT) lacks a systemic method in identifying the most pertinent behavioral and non-behavioral variables and/or their combination, which factor into reportable crashes involving motor-vehicles, pedestrians and bicyclists statewide. In order to more closely align with the “Zero in Wisconsin” vision and achieve the most optimal outcomes that eliminate reportable fatal and other types of crashes in Wisconsin, the department has a need to quantify and qualify the reportable motor vehicle crashes and identify possible countermeasures that can be implemented to mitigate those crashes. The overall objective of this project is to quantify and qualify the reportable motor vehicle crashes in Wisconsin and identify cost-effective safety countermeasures, engineering improvements and behavior modifications to reduce the number and severity of crashes. The goal will be achieved through two phases. The expected product in phase I of the research project is a statistical model (regression, Poisson, etc.) that through narrative and equations depicts the relationship between the most important variables identified as being correlated to accurately predicting crashes by collision type (intersection, head-on, single vehicle, etc.), crash severity type (fatal, injury, and property damage), user type (car, truck, pedestrian, bicycle) and the functional classification of road type, if possible, in Wisconsin. Phase II of the project will provide possible Safety Performance Functions (SPFs) that are created with the most pertinent variables selected from the initial phase. As a result of this research, WisDOT will gain information on existing and new variables that are highly correlated with traffic crashes in Wisconsin, be provided with applications that are ready for implementation and learn of effective communication methods it can use when sharing findings with practitioners. The research team will provide WisDOT with recommendations for collecting data on newly identified variables and for ensuring that data related to existing variables continues to be collected in an appropriate manner. Information on the costs and benefits of data collection practices will also be provided. WisDOT will also receive a list of SPFs that are guided by the WisDOT Strategic Highway Safety Plan (SHSP) and calibrated with Wisconsin data to help quantify the safety impacts. WisDOT will have the ability to manage and make regular updates to the SPFs as new safety data becomes available. WisDOT’s existing safety applications and programs, as well as decision-making support, will be enhanced by this report. The research team will work closely with the WisDOT Traffic Safety Engineering Workgroup (TSEWG) and the Traffic Safety Council (TSC) to determine where and how to implement the findings and recommendations. Engineering solutions can be piloted in the appropriate sections in the WisDOT Facility Design Manual (FDM) or integrated into MetaManager or similar safety analysis tools at WisDOT. Non-engineering recommendations can be used to guide and support the enforcement programs and policy decisions in response to changes in driver demographics and driving behaviors.


  • English


  • Status: Active
  • Contract Numbers:


  • Sponsor Organizations:

    Wisconsin Department of Transportation

    4802 Sheboygan Avenue
    Madison, WI  United States  53707
  • Project Managers:

    Moorman, Evan

  • Performing Organizations:

    University of Wisconsin, Milwaukee

    Center for Great Lakes Studies
    Milwaukee, WI  United States  53201
  • Principal Investigators:

    Xiao, Qin

  • Start Date: 20160926
  • Expected Completion Date: 20180331
  • Actual Completion Date: 0

Subject/Index Terms

Filing Info

  • Accession Number: 01640968
  • Record Type: Research project
  • Source Agency: Wisconsin Department of Transportation
  • Contract Numbers: 0092-16-11
  • Files: RiP, STATEDOT
  • Created Date: Jul 13 2017 5:14PM