A Comparative Approach of Crash Frequency Modelling in Two Lane Rural Roads

Road accidents are now one of the leading causes of death in the world. Investigating the underlying factors that contribute to increased risk of these accidents is an essential procedure to take effective countermeasures. In this study, the authors take a particular interest in two lane rural roads in South Korea. Six count data regression models were developed and evaluated for the goodness of fit. Traditionally, the evaluation is performed using information criterion such as Akaike Information Criterion. In this research, assessment of different models' performances was carried out using additional methods that include machine learning techniques, i.e. data splitting, and graphical tools, i.e. rootgrams . Based on the results of every evaluation technique, negative binomial hurdle model clearly outperformed all other regression models. Therefore, three variables were identified to have a significant impact on crash occurrence in two lane rural roads. These features are safety barrier, shoulder width and Annual Average Daily Traffic.

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 13p

Subject/Index Terms

Filing Info

  • Accession Number: 01764417
  • Record Type: Publication
  • Report/Paper Numbers: TRBAM-21-00971
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 23 2020 11:25AM