Search Results

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.

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.

Sixteen participants aged 55–65yrs provided deBoer scale ratings of discomfort glare for a vehicle with horizontally swiveling HID headlamps and a vehicle with the same headlamps that did not swivel in eight scenarios staged in a darkened parking lot. Participants, who were seated in the driver’s position of a stationary vehicle and instructed when to look, viewed the oncoming test vehicles in scenarios of 180m left turn, 180m right turn, 80m left turn, 80m right turn, left turn beside participant vehicle, crossing left in front of participant vehicle, right turn beside participant vehicle, and straightaway, in counterbalanced presentation orders. The swiveling headlamp vehicle provided statistically lower glare ratings in both 180m curves and the 80m right curve and statistically lower or similar in the intersection scenarios than the fixed headlamp vehicle.

Twent-two participants of varying ages detected roadside targets in two consecutive dynamic evaluations of a horizontally swiveling headlamp vehicle and a vehicle with the same headlamps that did not swivel. Participants detected targets as they drove unlighted low-speed public roads. Scenarios encountered were intersection turns, and curves with approximate radii of 70-90m, 120-140m, 170-190m, and 215-220m. Results from the first study found improved detection distances from the swiveling headlamps in left curves, but unexpectedly decreased detection distances in larger radius right hand curves. The swiveling algorithm was altered for the second study, and the headlamps used did not have the same beam pattern as in the first study. Results from the second study again found improved detection distances from the swiveling headlamps while in the larger radius right hand curves fixed and swivel were not statistically different.

This research compared driver detection performance with low-beam halogen headlamps supplemented by a General Motors production Night Vision system to low-beam halogen headlamps alone. This research was conducted with 18 participants between the ages of 40 and 70 years on a 3.2km (2-mile) section of closed road. Participants encountered seven scenarios, including crossing or standing pedestrians dressed in either white or black clothing. Additional scenarios included pedestrians in a curve and near an oncoming glare vehicle, as well a tire tread. Results indicated that the GM Night Vision system improved drivers' detection distances in nearly all pedestrian scenarios examined.

This paper presents a novel infrastructural traffic monitoring approach that estimates traffic information by combining two sensing techniques. The traffic information can be obtained from the presented approach includes passing vehicle counts, corresponding speed estimation and vehicle classification based on size. This approach uses measurement from an array of Lidars and video frames from a camera and derives traffic information using two techniques. The first technique detects passing vehicles by using Lidars to constantly measure the distance from laser transmitter to the target road surface. When a vehicle or other objects pass by, the measurement of the distance to road surface reduces in each targeting spot, and triggers detection event. The second technique utilizes video frames from camera and performs background subtraction algorithm in each selected Region of Interest (ROI), which also triggers detection when vehicle travels through each ROI.

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.

Vehicle headlamps and roadway lighting are the major sources of illumination at night. These sources affect contrast - defined as the luminance difference of an object from its background - which drives visibility at night. However, the combined effect of vehicle headlamps and intersection lighting on object contrast has not been reported previously. In this study, the interactive effects of vehicle headlamps and overhead lighting on object contrast were explored based on earlier work that examined drivers’ visibility under three intersection lighting designs (illuminated approach, illuminated box, and illuminated approach + box). The goals of this study were to: 1) quantify object luminance and contrast as a function of a vehicle’s headlamps and its distance to an intersection using the three lighting designs; and, 2) to assess whether contrast influences visual performance and perceived visibility in a highly dynamic intersection environment.