Intersection Decision Support Surveillance System: Design, Performance and Initial Driver Behavior Quantization
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Intersection Decision Support Surveillance System: Design, Performance and Initial Driver Behavior Quantization
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2007-08
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Minnesota Department of Transportation
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Report
Abstract
In rural Minnesota, approximately one-third of all crashes occur at intersections. Analysis of crash statistics and reports of crashes at rural expressway through-stop intersections shows that, for drivers who stop before entering the intersection, the majority of crashes involve an error in selecting a safe gap in traffic. The Intersection Decision Support system, developed at the University of Minnesota, is intended to reduce the number of driver errors by providing better information about oncoming traffic to drivers stopped at intersections.
This report deals primarily with the surveillance technology which serves as the foundation upon which the IDS system will be built. Three components of the surveillance system are described in detail in the body of the report: 1) a Mainline Sensor subsystem; 2) a Minor Road Sensor subsystem; 3) a Median Sensor subsystem. These subsystems include radar units, laser-scanning sensors, and infrared cameras, integrated with a vehicle tracking and classification unit that estimates the states of all vehicles approaching the intersection. The design, installation, performance, and reliability of each of these three subsystems are documented in the report.
The report concludes with an analysis of driver gap acceptance behavior at an instrumented intersection. Gap selection is examined as a function of time of day, traffic levels, weather conditions, maneuver, and other parameters. Log-normal distributions describe gaps acceptance behavior at rural, unsignalized expressway intersections.
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Minnesota Department of Transportation
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Alexander, Lee; Cheng, Pi-Ming; Donath, Max; Gorjestani, Alec; Menon, Arvind; Shankwitz, Craig. (2007). Intersection Decision Support Surveillance System: Design, Performance and Initial Driver Behavior Quantization. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/5584.
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