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Technical Paper

Development of a Performance Specification for Indirect Visibility Systems on Heavy Trucks

2007-10-30
2007-01-4231
Approximately 28,000 crashes involving combination unit trucks occur each year when they are making lane changes, merges, or turns. One contributing factor in these crashes is inadequate visibility for truck drivers. Recent advances in video technology have heightened the prospect of improving commercial vehicle safety by improving drivers' vision around the truck. For such video systems to be implemented on heavy trucks, the systems/driver interface should be demonstrated as viable through research. This paper presents the Camera/Video Imaging Systems (C/VISs) developed at Virginia Tech Transportation Institute (VTTI), the methodology used to test them, and some results obtained.
Journal Article

Enhanced Camera/Video Imaging Systems (E-C/VISs) on Heavy Vehicles

2008-10-07
2008-01-2627
Large trucks were involved in more than 26,000 crashes between April 2001 and December 2003 as a result of making lane changes, merges, and turns [1]. As an alternative to mirrors (surrogate system), or to be used in combination with mirrors (enhancement system), the industry has been developing Camera/Video Imaging Systems (C/VISs) directed toward improving visibility to the sides and rear of heavy vehicles. The current study describes development of an Enhanced C/VIS (E-C/VIS) directed at improving visibility in less favorable environmental conditions, such as nighttime and inclement weather.
Technical Paper

Methodological Overview of the Drowsy Driver Warning System Field Operational Test

2004-10-26
2004-01-2718
To address the issue of fatigued truck drivers, the U.S. Department of Transportation sponsored research to develop a Drowsy Driver Warning System. This system has been under development for several years and is at a point where it is ready for a Field Operational Test. The experimental plan calls for 102 drivers, each operating one of 34 instrumented heavy trucks for 16 weeks. Each vehicle is instrumented with video cameras and a variety of sensors to capture driver input/performance. This paper describes the method being used to conduct the study, including an overview of the data collection instrumentation.
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