Short Segment Statewide Screening of Midblock Crashes in South Carolina

The AASHTO Highway Safety Manual (HSM) presents a variety of methods for quantitatively estimating crash frequency or severity at a variety of locations. The HSM predictive methods require the roadway network to be divided into homogeneous segments and intersections, or sites populated with a series of attributes. It recommends a minimum segment length of 0.1?mi. This research focuses on segment lengths of less than 0.1?mi for statewide screening of midblock crash locations to identify site specific locations with high crash incidence. The paper makes an argument that many midblock crashes can be concentrated along a very short segment because of an undesirable characteristic of a specific site. The use of longer segments may “hide” the severity of a single location if the rest of the segment has few or no additional crashes. In actuality, this research does not divide sections of roads into short segments. Instead, a short-window approach is used. The underlying road network is used to create a layer of segment polygons using GIS buffering. Crash data are then overlaid and aggregated to the segment polygons for further analysis. The paper makes a case for the use of short fixed segments to do statewide screening and how accurately geocoded crash data is key to its use. A comparison is made with a sliding-window approach (Network Kernel Density). The benefit of using fixed segments is that they are much less complex than using the sliding-window approach. Because the segmentation can be the same from year to year, direct comparisons can be made over time while spatial integrity is maintained.

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  • Supplemental Notes:
    • The Standing Committee on Highway Safety Performance (ANB25) peer-reviewed this paper (19-01589). © National Academy of Sciences: Transportation Research Board 2019.
  • Authors:
    • Famili, Afshin
    • Sarasua, Wayne
    • Iqbal, Adika Mammadrahimli
    • Kumar, Devesh
    • Ogle, Jennifer Harper
  • Publication Date: 2019-10

Language

  • English

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  • Accession Number: 01707668
  • Record Type: Publication
  • Files: TRIS, TRB, ATRI
  • Created Date: Jun 4 2019 3:04PM