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An analysis of the first 35 back-over crashes reported by NHTSA's Special Crash Investigations unit was undertaken with two objectives: (1) to test a hypothesized classification of backing crashes into types, and (2) to characterize scenario-specific conditions that may drive countermeasure development requirements and/or objective test development requirements. Backing crash cases were sorted by type, and then analyzed in terms of key features. Subsequent modeling of these SCI cases was done using an adaptation of the Driving Reliability and Error Analysis Methodology (DREAM) and Cognitive Reliability and Error Analysis Methodology (CREAM) (similar to previous applications, for instance, by Ljung and Sandin to lane departure crashes [10]), which is felt to provide a useful tool for crash avoidance technology development.

To help drivers monitor the road and to reduce blind spots, Camera/Video Imaging Systems (C/VISs) display live video from cameras mounted on the truck's exterior to drivers using displays inside the truck cabin. This study investigated drivers' performance with C/VISs in a real-world trucking operation. Twelve commercial drivers' performance with and without a C/VIS was continuously recorded while they each drove for four months. Half of the drivers used a commercially available C/VIS that had a side-view camera on each fender. The other drivers used an advanced C/VIS (A-C/VIS) that had side-view cameras, a rear-view camera, and night-vision capabilities. This paper presents the study's final results and expands on the preliminary results that were previously reported. Detailed analyses of drivers' involvement in Safety-Critical Events (SCEs), their lane change performance, and their opinions of the C/VISs are presented.

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.

Driver distraction, defined here as engaging in a secondary task or activity that is not central to the primary task of driving, has been shown to be a contributing factor for many crashes. The secondary tasks and other activities in which drivers choose to engage while driving is also known to be highly varied, including very complex activities(e.g., text messaging on a cellular device) to very simple activities (e.g., selecting a radio preset). Several important distinctions affect the relative risk of engaging in these tasks. Recent data from large-scale instrumented vehicle studies (i.e., “naturalistic” driving studies like the recently released “100 car study” (1)) have begun to provide data where the relative risk, in terms of crash and near crash involvement, can be directly assessed for differing secondary tasks. These data have provided some important insights into the features that create risk.

Camera/Video Imaging Systems (C/VISs) display video captured from cameras mounted on the truck's fenders and trailer to drivers using displays mounted inside the truck cabin. C/VISs provide a countermeasure to blind-spot related crashes by allowing drivers to see objects not ordinarily visible by a typical mirror configuration. They also support drivers in determining the clearance between the trailer and an adjacent vehicle when performing a lane change. The National Highway Traffic Safety Administration (NHTSA) and the Federal Motor Carrier Safety Association (FMCSA) have collaboratively funded research on the development of C/VISs that operate during the day, as well as enhancing C/VISs to operate at night and in inclement weather. This paper presents the work performed in developing a C/VIS capable of being used in an eight-month technology field demonstration (TFD), which will allow the measurement of driver behavior with the C/VIS in a revenue-producing environment.

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.

This study evaluated the performance of heavy vehicle crash avoidance systems (CASs) by collecting naturalistic driving data from 150 truck tractors equipped with Meritor WABCO OnGuardTM or Bendix® Wingman® AdvancedTM products. These CASs provide drivers with audio-visual alerts of potential conflicts, and can apply automatic braking to mitigate or prevent a potential collision. Each truck tractor participated for up to one year between 2013 and 2015. Videos of the forward roadway and drivers’ faces were collected along with vehicle network data while drivers performed their normal duties on revenue-producing routes. The study evaluated the performance of CAS activations by classifying them into three categories based on whether a valid object was being tracked and whether drivers needed to react immediately.

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.

Forward Collision Warning (FCW) systems are intended to alert drivers when they may be at risk of a rear-end crash with a vehicle directly ahead unless they take immediate action. A forward collision visual alert (FCVA) is recommended as part of a multi-modality FCW system crash alert approach also including auditory and/or haptic crash alert components. SAE J2400 recommends that a conventional dashboard location shall not be used for the FCVA, since such an alert may distract the driver from the crash threat ahead (instead of helping the driver visually orient toward the crash threat). This research examined the merit of this recommendation by examining the effectiveness of instrument panel, head-up display, and (vehicle-centerline) top-of-dashboard FCVA candidates. In this static on-road study, 49 subjects (20–70 years old) made rapid judgments on the presence and nature of scene changes over two successive forward scene exposures controlled by a visual occlusion window.