Welcome to ROSA P | A novel approach to modeling and predicting crash frequency at rural intersections by crash type and injury severity level. - 29318 | US Transportation Collection
Stacks Logo
Advanced Search
Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.
 
 
Help
Clear All Simple Search
Advanced Search
A novel approach to modeling and predicting crash frequency at rural intersections by crash type and injury severity level.
  • Published Date:
    2015-04-01
  • Language:
    English
Filetype[PDF-1.23 MB]


Details:
  • Publication/ Report Number:
    SWUTC/15/600451-00077-1
  • Resource Type:
  • Geographical Coverage:
  • Format:
  • Abstract:
    Southwest Region University Transportation Center{114}

    Safety at intersections is of significant interest to transportation professionals due to the large number of

    possible conflicts that occur at those locations. In particular, rural intersections have been recognized as

    one of the most hazardous locations on roads. However, most models of crash frequency at rural

    intersections, and road segments in general, do not differentiate between crash type (such as angle, rear-end or sideswipe) and injury severity (such as fatal injury, non-fatal injury, possible injury or property

    damage only). Thus, there is a need to be able to identify the differential impacts of intersection-specific

    and other variables on crash types and severity levels. This report builds upon the work of Bhat et al.

    (2014) to formulate and apply a novel approach for the joint modeling of crash frequency and

    combinations of crash type and injury severity. The proposed framework explicitly links a count data

    model (to model crash frequency) with a discrete choice model (to model combinations of crash type and

    injury severity), and uses a multinomial probit kernel for the discrete choice model and introduces

    unobserved heterogeneity in both the crash frequency model and the discrete choice model. The results

    show that the type of traffic control and the number of entering roads are the most important determinants

    of crash counts and crash type/injury severity, and the results from our analysis underscore the value of

    our proposed model for data fit purposes as well as to accurately estimate variable effects.

  • Main Document Checksum:
  • Supporting Files:
    No Additional Files
No Related Documents.
You May Also Like:
Submit Feedback >