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Vehicle-to-vehicle (V2V) communication systems can enable a number of wireless-based vehicle features that can improve traffic safety, driver convenience, and roadway efficiency and facilitate many types of in-vehicle services. These systems have an extended communication range that can provide drivers with information about the position and movements of nearby V2Vequipped vehicles. Using this technology, these vehicles are able to communicate roadway events that are beyond the driver's view and provide advisory information that will aid drivers in avoiding collisions or congestion ahead. Given a typical communication range of 300 meters, drivers can potentially receive information well in advance of their arrival to a particular location. The timing and nature of presenting V2V information to the driver will vary depending on the nature and criticality of the scenario.

The design of a safe transportation system requires numerous design decisions that should be based on data acquired by rigorous scientific method. Naturalistic data collection and analysis methods are a relatively new addition to the engineer's toolbox. The naturalistic method is based on unobtrusively monitoring driver and vehicle performance under normal, everyday, driving conditions; generally for extended collection periods. The method generates a wealth of data that is particularly well-suited for identifying the underlying causes of safety deficiencies. Furthermore, the method also provides robust data for the design and evaluation of safety enhancement systems through field studies. Recently the instrumentation required to do this type of study has become much more cost effective allowing larger numbers of vehicles to be instrumented at a fraction of the cost. This paper will first provide an overview of the naturalistic method including comparisons to other available methods.

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.

This paper discusses radio usage habits observed during analysis of 700 hours of video sampled from the 100-Car Naturalistic Driving Study database. Analysts used large-scale printouts of each vehicle's radio faceplate and recorded interactions based on video analysis of hand movement and location (without the assistance of audio recordings). The duration and specific manipulations or adjustments were recorded for each interaction. The results summarize the length and type of interactions, most often-used controls, and total percentage of time drivers interacted with the radio.

Two navigation systems, one a turn-by-turn and the other a moving-map, were compared using the same routes and waypoints in the area of Roanoke, VA. Challenges as a result of their varying algorithms used to determine route guidance were overcome in finding a common route between the two systems. The study was designed to be conducted without an in-vehicle experimenter. This approach was thought important to reduce potential experimental biases. The methodology described provides a low-cost, valid method to test way-finding using the actual system in its actual driving environment. The purpose of this paper is not to discuss the benefit of a moving-map system as compared to a turn-by-turn system, but to discuss the methodology of this way-finding study conducted without an in-vehicle experimenter. Suggested data to collect and/or analyze as well as lessons learned are also discussed.

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.

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 study examined whether the effect of subsidiary tasks on driving performance can be predicted from stationary (static) testing. Alternative methods for assessing the performance of drivers during their use of in-vehicle information systems were examined. These methods included static testing in stationary vehicles, as well as dynamic, on-road testing. The measures that were obtained from static tests were evaluated in terms of how well they could predict measures obtained from driving performance during on-road testing (which included concurrent use of secondary information systems). The results indicated that measures obtained in static test settings were highly correlated with corresponding measures obtained from on-road performance testing.