How Do Mode-Specific Network Metrics Impact Safety Outcomes?

Public transit and active transportation networks have been shown to enhance multimodal traffic safety, yet their impacts in rural and peri-urban areas remain underexplored. This research evaluates the role of mode-specific network metrics—quantifying size, structure, and connectivity—on crash outcomes across New England using crash data and socioeconomic variables. Predictive models incorporating regression and machine learning methods will identify which network features influence safety, providing actionable insights for urban planners and policymakers. Outputs include an open-access dataset of network metrics, a dashboard for visualizing results, and a decision-support tool for improving roadway safety and equity in diverse community settings.

    Language

    • English

    Project

    • Status: Active
    • Funding: $150000
    • Contract Numbers:

      69A3552348301

    • 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:

      University of Massachusetts, Amherst

      Department of Civil and Environmental Engineering
      130 Natural Resources Road
      Amherst, MA  United States  01003
    • Performing Organizations:

      University of Massachusetts, Amherst

      Department of Civil and Environmental Engineering
      130 Natural Resources Road
      Amherst, MA  United States  01003
    • Principal Investigators:

      Oke, Jimi

    • Start Date: 20240901
    • Expected Completion Date: 20250831
    • Actual Completion Date: 0
    • USDOT Program: University Transportation Centers Program
    • Subprogram: University Transportation Centers

    Subject/Index Terms

    Filing Info

    • Accession Number: 01938989
    • Record Type: Research project
    • Source Agency: New England University Transportation Center
    • Contract Numbers: 69A3552348301
    • Files: UTC, RIP
    • Created Date: Dec 9 2024 10:04AM