Developing a Method to Identify Horizontal Curve Segments with High Crash Occurrences Using the HAF Algorithm
Abstract
Crashes occur every day on Utah’s roadways. Curves can be particularly dangerous as they require driver focus due to potentially unseen hazards. Often, crashes occur on curves due to poor curve geometry, a lack of warning signs, or poor surface conditions. This can create conditions in which vehicles are more prone to leave the roadway, and possibly roll over. These types of crashes are responsible for many severe injuries and a few fatalities each year, which could be prevented if these areas are identified. This highlights a need for identification of curves with high crash occurrences, particularly on a network-wide scale. The Horizontal Alignment Finder (HAF) Algorithm, originally created by a Brigham Young University team in 2014, was improved to achieve 87-100 percent accuracy in finding curved segments of Utah Department of Transportation (UDOT) roadways, depending on roadway type. A tool was then developed through Microsoft Excel Visual Basic for Applications (VBA) to sort through curve and crash data to determine the number of severe and total crashes that occurred along each curve. The tool displays a list of curves with high crash occurrences. The user can sort curves by several different parameters, including various crash rates and numbers of crashes. Many curves with high crash rates have already been identified, some of which are shown in this thesis. This tool will help UDOT determine which roadway curves warrant improvement projects.