Identifying and Quantifying Factors Affecting Vehicle Crash Severity at Highway-Rail Grade Crossings: Models and Their Comparison

The purpose of this paper is to develop a preferred multinomial logit (MNL) and ordered logit (ORL) model, compare their performance to identify factors that are important in making an injury severity difference and to explore the impact of such explanatory variables on three different severity levels of vehicle-related crashes at highway-rail grade crossings (HRGCs) in the United States. Vehicle-rail crash data on USDOT highway-rail crossing inventory and public crossing sites from 2005 to 2012 are used in this study. Preferred MNL and ORL models are developed using SAS PROC LOGISTIC procedure and marginal effects are also calculated and compared. A majority of the variables have shown similar effects on the probability of the three different severity levels in both models. In addition, based on the Akaike information criterion, it is found that the MNL model is better than the ORL model in predicting the vehicle crash severity levels on HRGCs in this study. Therefore, the researchers recommend the use of MNL model in predicting severity levels of vehicle-rail crashes on HRGCs.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee AHB60 Standing Committee on Highway/Rail Grade Crossings.
  • Corporate Authors:

    Transportation Research Board

    500 Fifth Street, NW
    Washington, DC  United States  20001
  • Authors:
    • Fan, Wei (David)
    • Gong, Linfeng
    • Washing, Edward Matt
    • Yu, Miao
    • Haile, Elias
  • Conference:
  • Date: 2016

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: References; Tables;
  • Pagination: 21p
  • Monograph Title: TRB 95th Annual Meeting Compendium of Papers

Subject/Index Terms

Filing Info

  • Accession Number: 01592103
  • Record Type: Publication
  • Report/Paper Numbers: 16-2085
  • Files: TRIS, TRB, ATRI
  • Created Date: Feb 29 2016 4:56PM