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.

Over the past several years, traffic fatality rates in South Carolina have been consistently ranked among the highest in the country. Furthermore, South Carolina incurs an annual economic loss of over two billion dollars because of roadway traffic crashes. The South Carolina Department of Transportation, in collaboration with the South Carolina Department of Public Safety, has undertaken a series of initiatives to reduce the number of vehicle crashes, with a particular emphasis on injury and fatal crashes. One of these initiatives is the deployment of a map-based geocoded crash reporting system that has greatly improved the quality of crash location data. This paper provides an assessment of improvements in crash geocoding accuracy in South Carolina and how improved accuracy is beneficial to systematic statewide safety analysis. A case study approach is used to demonstrate practical applications and analysis techniques based on spatially accurate crash data. A survey of U.S. state highway agencies indicates that there are disparate crash reporting systems used across the country with regard to crash geocoding procedures and accuracies. Survey results indicate that not only does geocoded accuracy of crash locations vary by state, but accuracies often vary by jurisdiction within each state. Research results suggest that poorly geocoded crash data can bias certain types of safety analysis procedures and that many state safety initiatives, analysis methods, and outcomes can benefit from improving crash report geocoding procedures and accuracies.