October 22, 2015

About the Presentation

Roadway horizontal alignment has long been recognized as one of the most significant contributing factors to lane-departure crashes. Knowing the location and geometric information of horizontal curves can greatly facilitate the development of appropriate countermeasures, and obtaining this curve data in a cost-effective way is of great interest to practitioners and researchers.

This presentation highlighted a fully automated method for the extraction of horizontal curve data from GIS roadway maps. Using a tool named CurveFinder, horizontal curves and their related data can be automatically identified from GIS roadway maps. Once curves are identified and information is extracted, CurveFinder generates a curve layer/shapefile that includes all the information and can be easily integrated with an agency’s existing asset management, roadway inventory, and crash datasets. CurveFinder has been used successfully in several states, including Delaware, Florida, Iowa, Michigan, New Hampshire, New Jersey, Wisconsin, and Wyoming.

The presentation also briefly reviewed a related project focused on supporting safety data collection in Native American tribal communities. Tools such as CurveFinder are one of many ways data collection procedures can be improved on tribal lands, where underreporting (or no reporting) of crash data can create a significant void in state DOT safety programs.

Watch Video

About the Speaker

David Noyce

David Noyce is the Arthur F. Hawnn Transportation Engineering Professor and Chair of the Department of Civil and Environmental Engineering and the director of the Traffic Operations and Safety (TOPS) Laboratory at the University of Wisconsin–Madison (UW-Madison). Recently, he has conducted research on advanced traffic signal displays, centerline rumble strips, median crossover crashes, roundabouts, tribal lands, speed management and enforcement, and driver and vehicle simulation.