Improving Railroad Grade Crossing Safety: Accident Prediction Models Using Macro- and Micro-Scale Analysis

This project is working to 1) develop a methodology for analyzing rail crossing crashes at a micro level to discover trends at a single crossing or a series of crossings along a corridor or a region and 2) improve the accuracy of crash predictions by incorporating findings from the microscopic analyses and studying the regional trends that emerge in this analysis but are not observed at a national level. This new micro approach has resulted in the identification and valuation of the contribution of new variables not previously considered. For example, findings indicate that the distance to the nearest highway-highway intersection is an important factor in gated-crossing crash prediction. It was also found that the angle between railroad and highway is an important factor in crash prediction for crossings with flashing lights. Improvements in crash prediction can result in a more reliable ranking and selection of crossings for safety improvements as well as more accurate cost-benefit estimations, which can help optimize resource allocation procedures and therefore reduce crash frequencies to a greater extent than current practices. The addition of information resulting from the micro analysis into macro models is expected to further enhance predictions and to provide a multi-scale perspective not previously studied in this context. To complement dynamic tree analysis for finding contributing factors to crash frequency, a “crossing cluster” is calculated for each crossing. The crossing cluster represents the contribution of a variable to crash frequency at that crossing, which is often larger than the contribution found in the dynamic tree.

Language

  • English

Project

  • Status: Active
  • Funding: $404212
  • Contract Numbers:

    DTRT13-G-UTC35

    CTS-2015056

  • Sponsor Organizations:

    Research and Innovative Technology Administration

    University Transportation Centers Program
    1200 New Jersey Avenue
    Washington, DC  United States  20590

    Roadway Safety Institute

    University of Minnesota
    Minneapolis, MN  United States  55455
  • Project Managers:

    Stearns, Amy

  • Performing Organizations:

    University of Illinois, Urbana-Champaign

    Department of Civil Engineering, 201 Engineering Hall
    Urbana, IL  United States  61801
  • Principal Investigators:

    Benekohal, Rahim

  • Start Date: 20140801
  • Expected Completion Date: 20180630
  • Actual Completion Date: 0
  • Source Data: RiP Project 37493

Subject/Index Terms

Filing Info

  • Accession Number: 01567215
  • Record Type: Research project
  • Source Agency: Roadway Safety Institute
  • Contract Numbers: DTRT13-G-UTC35, CTS-2015056
  • Files: UTC, RiP
  • Created Date: Jun 26 2015 1:00AM