Review of Minnesota's Rural Intersection Crashes: Methodology for Identifying Intersections for Intersection Decision Support (IDS)
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Review of Minnesota's Rural Intersection Crashes: Methodology for Identifying Intersections for Intersection Decision Support (IDS)
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2004-03-01
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Abstract
Minnesota's rural crash records were analyzed in order to develop a better understanding of crashes at rural intersections and their cause. The objective in studying the causes of crashes at rural intersections is to support development of technology based strategies to mitigate high crash rates. Since previous research found that 80 percent of intersection crashes at thru-STOP intersections may be related to selection of insufficient gaps, the development and validation of Intersection Decision Support (IDS) technology that assists in proper gap selection was identified as a primary goal.
A database of over 3,700 intersections was examined. Using the critical crash rate as an indicator, 23 rural expressway intersections and 104 rural two-lane intersections were identified as unusually 'dangerous' locations.
Right angle crashes (which are most often related to gap selection) were observed to account for approximately 50 percent of all crashes at the 'dangerous' intersections, up from 28 percent for all rural thru-STOP intersections.
A specific intersection identified, evaluated and then was selected for testing IDS technologies that can track vehicles approaching on the major roadway, compute the gap and communicate the information to drivers stopped on the minor street waiting to enter the intersection. The data acquisition system to be installed will allow analysis of driver decision-making behavior and study the effects of introducing an IDS under development at the University of Minnesota.
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No. 1 in the Series: Developing Intersection Decision Support Solutions
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Minnesota Department of Transportation
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Mn/DOT 2004-31
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Preston, Howard; Storm, Richard; Donath, Max; Shankwitz, Craig. (2004). Review of Minnesota's Rural Intersection Crashes: Methodology for Identifying Intersections for Intersection Decision Support (IDS). Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/795.
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