Identifying Deer-Vehicle Collision Concentrations in Minnesota

Deer-Vehicle Collisions (DVCs) are a significant risk to public safety on Minnesota roads, causing property damage, human injuries and deaths, and also killing deer. In 2019, there were 1,573 DVCs reported to the Minnesota Department of Public Safety (MnDPS), or roughly 4.5 DVCs per day. Reducing the number of DVCs in a cost-efficient manner would require an analysis of DVCs, using geographic, road type, land use, deer, traffic volume, and other data to identify locations where safety measures or warnings would be most beneficial. In this project we will analyze about 10,000 DVCs to identify factors which increase the risk of a DVC in Minnesota. Many DVCs without significant vehicle damage or passenger injury go unreported to MnDPS. We will collect roadkill data to estimate the number of unreported DVCs in 2021-2022 in the Duluth area, with possibility of applying this method more broadly across Minnesota. This data is critical to establish that DVCs that have caused significant property damage or human injury are not different from DVCs that are unreported. We will use the results of the DVC analysis to construct a data-driven machine-learning-based model to predict hotspots for DVCs. This model will identify road and habitat features that are associated with higher DVC rates.

    Language

    • English

    Project

    • Status: Active
    • Funding: $165,450.00
    • Contract Numbers:

      1036342 WO#11

    • Sponsor Organizations:

      Minnesota Department of Transportation

      395 John Ireland Boulevard
      St Paul, MN  United States  55155
    • Principal Investigators:

      Stern, Raphael

    • Start Date: 20210513
    • Expected Completion Date: 20231130
    • Actual Completion Date: 0

    Subject/Index Terms

    Filing Info

    • Accession Number: 01762349
    • Record Type: Research project
    • Source Agency: Minnesota Department of Transportation
    • Contract Numbers: 1036342 WO#11
    • Files: RIP, STATEDOT
    • Created Date: Jan 19 2021 3:32PM