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Browsing by Subject "Snowplow safety"

Now showing 1 - 3 of 3
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    Impending Box Impact Warning System for Prevention of Snowplow-Bridge Impacts: A Final Report of Investigations
    (University of Minnesota Center for Transportation Studies, 2009-02) Lindeke, Richar R.; Katmale, Hilal; Verma, Ravi
    Each year, three or four Mn/DOT snowplows suffer bridge/box collisions while plowing. These collisions can shear off the box and frame damage to the truck. The box then falls onto the road surface where it becomes an immediate life-threatening hazard to traffic. In some cases, the integrity of the bridge may also be compromised. A typical collision of this type requires expenditures of $30,000 to $40,000 and results in potentially dangerous delays in achieving clean pavement status along the affected snowplowing route. Feasibility of linking on-board GPS technology for Automatic Vehicle Location with the current bridge information database at Mn/DOT, “BrInfo,” will be investigated, on a plow-route by route basis, to create collision maps. Collision avoidance then will use some primitive form of map matching. In addition, a prototype warning system that serves as a bridge proximity sensor will be developed to alert the snow plow driver that he/she is approaching a bridge with the box at a dangerous height. This warning system is integrated in an on-board box position sensor so that the driver can be alerted that the box must immediately be lowered. While realizing that additional means for box height control may complicate snowplow maintenance, any system that relieves the driver of cognitive overload, to reduce driver stress and fatigue during plowing operating, when running extended rural plow routes, needs to be implemented.
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    Snow Rendering for Interactive Snowplow Simulation – Supporting Safety in Snowplow Design
    (Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota, 2011-10) Willemsen, Peter
    During a snowfall, following a snowplow can be extremely dangerous. This danger comes from the human visual system's inability to accurately perceive the speed and motion of the snowplow, often resulting in rear-end collisions. For this project, the researchers' goal is to use their understanding of how the human visual system processes optical motion under the conditions created by blowing snow to create a simulation framework that could be used to test emergency lighting configurations that reduce rear-end collisions with snowplows. Reaction times for detecting the motion of the snowplow will be measured empirically for a variety of color set-ups on a simulated snowplow that slows down while driving on a virtual road with curves and hills. Current efforts have implemented a blowing snow model that will eventually be integrated into a real-time driving simulation environment. Concurrently, a simulated driving environment has been developed that will serve as the basis for testing the effects of color and lighting alternatives on snowplows. In initial pilot experiments, the simulated driving environment has been effective at testing subject reaction times for following a snowplow through high luminance contrast (normal daylight driving) and low luminance contrast (daylight fog) conditions. The results of this work will move the researchers closer to determining optimal color and lighting configurations on actual snowplows.
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    Snow Rendering for Interactive Snowplow Simulation—Supporting Safety in Snowplow Design
    (Center for Transportation Studies, University of Minnesota, 2011-02) Willemsen, Peter
    During a snowfall, following a snowplow can be extremely dangerous. This danger comes from the human visual system's inability to accurately perceive the speed and motion of the snowplow, often resulting in rear-end collisions. For this project, the researchers' goal is to use their understanding of how the human visual system processes optical motion under the conditions created by blowing snow to create a simulation framework that could be used to test emergency lighting configurations that reduce rear-end collisions with snowplows. Reaction times for detecting the motion of the snowplow will be measured empirically for a variety of color set-ups on a simulated snowplow that slows down while driving on a virtual road with curves and hills. The simulated driving environment will utilize a head-mounted, virtual reality display to render an improved snow cloud model behind the snowplow. This driving simulator environment will serve as the basis for testing the effects of color and lighting alternatives on snowplows. The results of this work will move the researchers closer to determining optimal color and lighting configurations on actual snowplows.