Intersection Decision Support

Principal Investigator:

Max Donath, Professor, Mechanical Engineering


  • Craig Shankwitz, Fmr Director, Intelligent Veh. Lab, Mechanical Engineering
  • Nic Ward, Former U of M Researcher, Mechanical Engineering

Project Summary:

Minnesota joined with California, Virginia, and the FHWA in a pooled-fund consortium (the Infrastructure Consortium) dedicated to improving intersection safety. The Minnesota team's objective is to develop effective strategies to mitigate high crash rates at rural intersections. Rural Intersection Decision Support (IDS) focuses on enhancing a driver's ability to successfully negotiate rural intersections. The system uses sensing and communication technology to identify safe gaps in traffic on a high-speed rural expressway and communicate this information to drivers waiting to enter the intersection from a minor intersecting road. The goal of this system is to improve safety without introducing traffic signals, which on high-speed rural roads often lead to an increase in rear-end crashes. The Rural IDS research program achieved four main research results through an analysis of rural expressway intersections: (a) the development of a technique to identify those with higher-than-expected crash rates; (b) the development of a statistical model that can be used to estimate the benefits of deploying IDS at a specific rural intersection; (c) the design and implementation of a rural intersection surveillance and data-acquisition system capable of quantifying the behavior of drivers; and (d) a task analysis, design study, and simulator-based evaluation of Driver Infrastructure Interface (DII) concepts for communicating relevant information to stopped drivers. The second item (b) was the result of a project led by Professor Gary Davis. In this project, statistical modeling was applied to crash data from 198 two-way, stop-controlled intersections on Minnesota rural expressways in order to identify intersections that were plausible candidates for future IDS deployment; develop a method for estimating the crash-reduction effect of IDS deployment; develop a method for predicting the crash-reduction potential of IDS deployment; and test the hypothesis that older drivers were over-represented in intersection crashes along U.S. Trunk Highway 52. These objectives were accomplished using hierarchical model structures similar to those employed in the interactive highway safety design model. Five rural expressway intersections were identified as having crash frequencies that were atypically high, and this group included the intersection of U.S. Trunk Highway 52 and Goodhue County Highway 9, the site chosen for the prototype IDS deployment. It was then determined that a three-year count of crashes after deployment would probably be sufficient to detect any crash reduction effect due to the IDS, although a reliable estimate of the magnitude of this effect would require a longer test period. Assuming that IDS deployment would make the frequency of crashes at treated intersections similar to that of typical intersections, it was estimated that deployment of the IDS at the five high-crash intersections would, over a 15-year period, result in about 308 fewer crashes. Finally, using an induced-exposure approach, 12 intersections were showed an over-representation of older drivers, with 5 of these located on U.S. Trunk Highway 52.


Project Details:

  • Start date: 01/2002
  • Project Status: Completed
  • Research Area: Transportation Safety and Traffic Flow
  • Topics: Safety, Traffic Operations