The results of a survey of 424 motorcyclists are presented in order to provide information for motorcycle safety research. Survey questions address topics related to rider demographics, riding experience (years, mileage, and trip description), motorcycle characteristics, rider training, safety issues (maintenance, equipment, and crash data), and respondent interest (willingness, reasons for hesitation, and acceptable compensation). The respondents’ interest in participating in an on-road motorcycle study is analyzed relative to the other questions, and deterrents to participation, as well as desired compensation, are also discussed in order to design such studies to encourage participation. Results of a cluster analysis are also presented to theorize possible categorizations of riders in terms of the collected variables. This information will be a useful starting block in the design and execution of motorcycle safety research.

The usage of a radio while driving has long been considered socially acceptable. There is recent concern, however, about radio usage, in its ever-changing context, remaining a relatively low-risk activity to perform while driving. This investigation examined how often drivers with access to an advanced and novel infotainment system for about four weeks were involved in crash and near crash situations. Results suggest a trend of very slight overrepresentation of infotainment system use in near crash events. Furthermore, use of infotainment systems had measurable demands on the driver’s visual resources and tended to result in a reduced propensity of response to unexpected events on the forward roadway, albeit the use had limited or no measurable effect on the control of the vehicle.

This report documents an effort to review the currently available, aftermarket telematics solutions. The project involved: (a) a survey of the current telematics market; (b) a review of the available telematics systems; (c) an analysis of the usefulness of each identified system; and (d) the creation of a findings summary document formatted as a consumer market guide to telematics systems. The detailed consumer market guide is included and follows the report.

Approximately one in four commercial motor vehicle (CMV) drivers in the U.S. are estimated to possess mild or higher levels of obstructive sleep apnea (OSA), the most common sleep-breathing disorder that is associated with significant medical consequences (including cardiovascular disease and diabetes). A major symptom of sleep apnea is excessive daytime sleepiness, which is highly correlated to impaired driving performance and may result in an increased risk of being in traffic--or work-related incidents. The most prescribed and cost-effective first-line treatment for OSA is nasal continuous positive airway pressure (CPAP). Two leading U.S. carriers partnered with commercial sleep apnea providers to implement obstructive sleep apnea (OSA) programs that screen, diagnose, treat, and manage their OSA-positive CMV drivers. This case study provides an overview of these OSA programs; outlines each carrier’s screening, testing, and compliance protocols; and compares and contrasts their approaches. Focus group research was also conducted with drivers and staff involved in each program to assess their perceptions and opinions of their respective OSA programs. While the majority of drivers expressed overall satisfaction participating in their carrier’s OSA program, both drivers and staff stressed the difficulty of healthy eating, exercise, and weight loss as adjunct OSA treatments. Finally, staff expressed the importance of coordination between the carrier and the OSA provider to provide driver support.

With the development of new light sources, options for the color and spectral output of a luminaire are wider than for traditional light sources. This can impact visibility as the spectral output of a light source may have a significant impact on the appearance of objects in the roadway environment. This study compares the visibility and color contrast afforded by three separate roadway luminaire types, each with a different spectral output. The benefit provided by the additional color information provided by the spectral distribution of a luminaire can improve detection of objects in the roadway by as much as 50%. These results, however, are not consistent across all spectral output and object color combinations. These results also indicate that the proper selection of a luminaire output will provide better visibility for the driver.

Naturalistic video data reduction is a process of identifying information from video and putting it into a format that can be analyzed. Developing a sufficiently detailed event coding scheme is critical to this process. This report outlines an effort to refine VTTI’s existing coding scheme, to identify “driver distraction” using a pragmatic definition of driver distraction from the literature.

Light-vehicle driver education programs that contain content about heavy-vehicle operation may be helpful in reducing light-vehicle/heavy-vehicle interactions. However, it is unclear as to the extent of current state curricula requirements, content, and perceived effectiveness (for both public and private programs) regarding heavy-vehicle operation and associated light-vehicle driving recommended procedures. This project involved the development of an online survey targeted at instructors and/or administrators of individual state driver education programs to identify current curricula addressing heavy vehicles (or lack thereof) and perceived effectiveness. Also, an attempt was made to locate driver education curricula and/or manuals from every state to better understand if instructors in every state have access to information on how light vehicles can safely share the road with heavy vehicles.

Despite the fact that overall road safety continues to improve, intersections and rural roads persist as trouble areas or hotspots. Using a previously developed method, naturalistic driving data were identified through intersection and rural road hotspots and compared to naturalistic driving data through similar intersections and rural road locations, but with low crash counts. Few significant differences were found between driver behaviors in the low-crash and high-crash areas of study. For the few significant differences, there was not an apparent consistent pattern.

The current report investigated the “high-risk” driver concept, and predictors associated with group membership, in a sample of 200 CMV drivers using naturalistic data from the Drowsy Driver Warning System Field Operational Test and the Naturalistic Truck Driving Study. A cluster analysis revealed three distinct groups of drivers (safe, average, and risky) based on the rate of safety-critical events per mile traveled. The risky group accounted for 50.3% of the total safety-critical events, but only 7.1% of the total miles traveled. Various anthropometric and demographic variables were found to have an association to group membership; however, these relationships were weak (mainly due to the small sample size). The current study found support for the high-risk driver concept; future research should focus on identifying risky drivers so that targeted safety management techniques can be used to improve driving behavior.

Ensuring the safety of travelers by the use of technology, and protecting the personal information that is collected for those applications, is an important transportation policy concern. Perceptions of an abuse of privacy protection is a growing obstacle to speed monitoring and red-light-running applications. Many states and numerous localities have barred the use of technology for these safety applications. This report offers a detailed review, from a legal and operational perspective, of how personal privacy is (or is not) protected. Two unique sections contained in the report are (1) a state-by-state and court-involved inventory of relevant laws, and (2) a survey of the members of ITS America questioning how developers, manufacturers, operators, marketers, researchers, and deplorers of transportation technology comply with current privacy principles.

A survey was administered to 1,524 Virginia Tech faculty, staff, and students and Blacksburg Transit drivers in an effort to differentiate between commercial driver’s license holders (72 of the respondents) and “regular” (i.e., non-commercial) drivers in terms of their ownership and personal in-vehicle usage of handheld devices (e.g., cell phones and MP3 players). Results indicated that discrepancies exist between these two groups for some devices and usage. For instance, almost 35% of commercial drivers reported that they “never” text while driving their personal vehicles compared with only 4% of the non-commercial drivers.

This effort was a comparison and application of multiple existing measures of contrast involving the luminance of objects. Specifically of interest were pedestrians in a nighttime environment and how they visually are contrasted against their background.  Results indicate that some contrast metrics are more applicable than others as realistic measures in a driving environment.

This report describes an investigation of factors related to the prevalence of red-light violations at signalized intersections. A sample of 3,000 violators were compared to a matched set of compliant vehicle approaches using a logistic regression model. The focus was on identifying and exploring causal factors with the aim of assisting efforts to discover potential strategies for mitigation.

The 100-Car Naturalistic Driving data set was collected in 2003 and 2004 and has been mined numerous times since. The object of this project was to conduct a complete inventory of this data set in order to record driver identification, seatbelt usage information, ambient lighting, and other video-based metrics that would facilitate secondary analyses in the future. This report summarizes these data for the 407 unique drivers identified and provides mileage and seatbelt usage information that was previously unavailable.

This study developed an integrated framework for modeling the safety outcomes of naturalistic driving studies and addressed several critical methodological issues. The results indicate a certain level of discrepancy between the model-based approaches and the crude odds ratios.

By employing the functionality of GIS, code was written which allows for an automated process to compare the GPS data recorded in the naturalistic driving data with geographic map data from the U.S. Census Bureau and road data from various sources, such as state departments of transportation or other providers. Points recorded in the naturalistic driving data which fall outside the boundaries of the Census Bureau's urbanized Areas or urban Clusters are determined to be rural. The points are further evaluated to determine whether or not the vehicle was being driven on an interstate highway. Points that are determined to be rural and not on interstate highways are segments of interest in addressing the rural road crash problem.

VTTI researchers have developed a method for rating driver drowsiness based on the evaluation of naturalistic video footage of the driver's face and upper torso. This measure, referred to as the Observer Rating of Drowsiness (ORD) is based on subjective assessments of the driver's facial tone, behavior, and mannerisms, and is set to a 100-point continuous scale. ORD is assessed based on the 60 seconds of video prior to a trigger event (or baseline epoch). Therefore, ORD is a relatively quick/efficient method for assessing one's drowsiness level, which can then be used to describe a driver's state and investigate whether drowsiness was a contributing factor to a safety-critical event.

Under the sponsorship of the National Surface Transportation Safety Center for Excellence (NSTSCE), an effort was undertaken to develop a system of image capture to analyze luminance data gathered in naturalistic driving research.

Fatigue is a major risk factor in commercial motor vehicle operations, identified in naturalistic driving studies as a contributing factor in approximately 20 percent of safety-critical incidents. Understanding the nature of fatigued driving requires attention to several elements of the driving situation, including driver characteristics. The purpose of the present report is to explore driver body mass index (BMI) as a characteristic which may put one at increased risk for driving while fatigued.

Under the sponsorship of the National Surface Transportation Safety Center for Excellence, an existing naturalistic data set from the Drowsy Driver Warning System Field Operational Test (DDWS FOT) was expanded and analyzed to gain a greater understanding of the conditions which are associated with fatigue in commercial motor vehicle (CMV) driving.