Vicki L. Neale

Investigation of Driver-Infrastructure and Driver-Vehicle Interfaces for an Intersection Violation Warning System

Research was undertaken to design, develop, and evaluate interfaces for a signalized- and stop-controlled violation warning system. Both infrastructure-based warnings (Driver Infrastructure Interface, DII) and vehicle-based warnings (Driver Vehicle Interface, DVI) were considered. The developed interfaces were tested by placing a driver in an instrumented vehicle on a closed test course with a working signalized intersection. The goal of the effort was to determine which DIIs/DVIs were most effective based upon the time to intersection at which the DII/DVI elicited the correct driver response of braking by the stop bar. While the DIIs that were tested were shown to be largely ineffective for violation warning, results showcase the potential of several DVI modalities, by themselves or in combination, to provide effective warnings to a driver violating a signal- or stop-controlled intersection. Furthermore, results indicate that a DVI warning combined with a vehicles enhanced braking capability (brake precharging and panic brake assist) may enhance the range of acceptable DVIs.

Driver Inattention: A Contributing Factor to Crashes and Near-Crashes

Driver distraction, or inattention, has been receiving wide media attention recently as many state legislatures are considering various levels of restricting cell phone use. Research has been conducted using a variety of experimental methods to determine the level of risk associated with driving inattention. While most of this research suggests that inattention impairs driving, there have been no studies to directly link driving inattention to crashes. Data from the 100-Car Naturalistic Driving Study, an instrumented vehicle study for which data was collected on 100 drivers in the Washington, DC metropolitan area for 12 months, were used in the following analyses. Crashes and near-crashes were identified in the data using post-hoc triggers based upon driving performance metrics, (i.e. hard braking). Results suggest that inattention contributed to 78% of all crashes collected over the 12 month data collection period.

Effects of Haptic Brake Pulse Warnings on Driver Behavior during an Intersection Approach

Intersection crashes account for nearly a quarter of all police reported crashes, and 39% of these result in injury or death. In this experiment, haptic warnings were explored as an alternative to auditory and visual warnings as part of an overall effort to reduce the number of intersection related crashes. The study objective was to determine the haptic brake pulse warning candidate that most often results in the driver successfully stopping for an intersection. Five candidate brake pulse warnings were tested; these varied with respect to length and number of pulses. Significant differences were found between haptic conditions for peak and constant deceleration. Participants receiving the haptic warning were 38 times more likely to stop than those receiving no warning.

Evaluation of Unassigned Sign Colors for Incident Management Trailblazing

Efforts to design and evaluate a new sign design for incident route trailblazing are reported here. Phase 1 was an off-road field experiment conducted to determine the best sign color combination, letter stroke width, and letter size for emergency signs. Based on the results of Phase 1, three color combinations were chosen for testing (black on coral, black on light blue, and yellow on purple) against a baseline color combination of black on orange. Phase 2 was conducted with an instrumented vehicle through a construction zone-related detour. Questionnaire data were also obtained. The independent variables of interest were sign color combination, age, and visibility condition. The findings of Phase 2 indicated that use of a color combination other than the traditional black-on-orange sign would improve driver performance and safety when used for trailblazing during critical incidents. The following conclusions were reached: (a) yellow on purple or black on light blue will likely result in fewer late-braking maneuvers if the road geometry includes many tight curves; (b) black on light blue will result in the fewest number of turn errors; (c) black on orange will result in more turn errors, especially during the day and particularly when it is overlapped with existing detour and construction zone signs; (d) black on coral is least preferred by older and younger drivers; and (e) younger drivers tend to prefer yellow on purple and older drivers tend to prefer black on light blue.

Driver Deceleration and Response Time When Approaching an Intersection: Implications for Intersection Violation Warning

It is estimated that as many as 2.7 million crashes per year occur at intersections or are intersection related. These crashes result in over 8,500 fatalities every year and have prompted substantial research of technologies that provide vehicle-based, infrastructure-based, or infrastructure-cooperative Intersection Violation Warnings (IVWs) to drivers. Such a system would use a pre-specified algorithm to identify drivers that have a high likelihood of violating a traffic control device and subsequently warn the driver to stop. However, prior to developing these algorithms, scientists must understand how drivers respond to traffic signals. The current study characterized this driver response in terms of driver deceleration rates and response time. Drivers approached a signalized intersection at 35 mph (56.3 km/h), while their state (baseline, distracted, and willful) was manipulated and the signal phase changed at various distances. Results indicate that the chosen level of deceleration varied with the state of the driver (e.g. distracted) and the distance from the intersection at which the light changes. Response times, however, did not vary based on these factors. Implications of these results are discussed in terms of their applicability toward adapting the performance of existing Forward Collision Warning algorithms for use in IVW applications.

Fluorescent sign colors for incident management trailblazing: Evaluation of assignments in manual on Uniform Traffic Control Devices

Previous research evaluated the use of unassigned sign colors from the Manual on Uniform Traffic Control Devices for incident management trailblazing; however, fluorescent sign colors were not evaluated. Since evidence suggests that fluorescence on signs improves conspicuity, the following colors were evaluated along a contrived test route with an instrumented vehicle: black on fluorescent coral, fluorescent yellow on fluorescent purple, black on fluorescent yellow-green, and yellow on purple in nonfluorescent colors. No significant differences in driving performance were exhibited among the four experimental sign-color combinations. Based on questionnaire results, the black on fluorescent yellow-green sign was preferred by younger and older drivers during both day and night visibility conditions. However, fluorescent yellow-green was subsequently assigned by the Federal Highway Administration for pedestrian, school, and bicycle crossings. For the remaining colors, black on fluorescent coral was ranked highest for visibility and overall preference, followed by fluorescent yellow on fluorescent purple, with nonfluorescent yellow on purple least preferred. Black on fluorescent coral was preferred over fluorescent yellow on fluorescent purple during daytime viewing conditions, while the reverse was true for nighttime. Drivers also commented that the arrow on the sign was too small to determine directional information from a comfortable distance.

Naturalistic Data Collection of Driver Performance in Familiar and Unfamiliar Vehicles

The 100-Car Naturalistic Driving Study was the first large-scale instrumented vehicle study with no special driver instructions, unobtrusive data collection instrumentation, and no in-vehicle experimenter. The final data set includes approximately 2,000,000 vehicle miles, almost 43,000 hours of data, 241 primary and secondary drivers, 12 to 13 months of data collection for each vehicle, and data from a highly capable instrumentation system. In addition, 78 of 102 vehicles were privately owned and 22 were leased. After 12 months, leased vehicles were provided to 22 private vehicle drivers who then drove the leased vehicles for an additional four weeks. Driving performance for the same drivers in familiar and unfamiliar instrumented vehicles was then compared. Results provided evidence of increased relative risk for the same driver for weeks 1 through 4 of driving an unfamiliar leased vehicle as compared to the same period of driving their privately owned vehicle.

Normal and Hard Braking Behavior at Stop Signs and Traffic Signals

A testbed intersection violation warning system was developed to address the problem of intersection crashes. The effectiveness of such systems is fundamentally dependent on the driver-braking model used to decide if a warning should be issued to the driver. If the model is unrealistic, drivers can either be annoyed due to assumed braking levels that are too low, or can be warned too late if braking expectations are too high. Initial algorithm development relied on data from the Collision Avoidance Metrics Partnership (CAMP) Forward Collision Warning (FCW) project. However, it was unknown whether the CAMP data (collected in the presence of stopped lead vehicles) would be applicable to the intersection problem (e.g., will drivers respond similarly to red traffic signals and stopped lead vehicles). Braking profile and performance tests were thus conducted to determine the applicability of the CAMP FCW results to the intersection violation warning.

Rapid Prototyping Improves Research on Red-Light-Running Behavior

FEATURE AT A GLANCE: Unintentional red-light running is a relatively rare occurrence in everyday driving, but it can lead to serious crashes. While developing systems that warn drivers who are about to run a red light, we conducted tests that allowed us to place naive drivers in unexpected red-light-running scenarios on a test track. By adapting rapid prototyping design concepts, we were able to quickly iterate through research scenarios and develop a method that was repeatable, efficient, and realistic. We discuss lessons learned and pitfalls to avoid in the application of rapid prototyping concepts to human factors research design.

Lessons Learned during Two Naturalistic Truck-Driving Studies

The Virginia Tech Transportation Institute (VTTI) was contracted by the Federal Motor Carrier Safety Administration (FMCSA) and the National Highway Traffic Safety Administration (NHTSA) to collect data from Commercial Vehicle Operators (CVO) under two contracts. The first study, Impact of Local/Short Haul Operations on Driver Fatigue (Hanowski, et al., 2000), focused on those drivers who drive an average of three hours a day while delivering goods but sleep at home each night. The second study, Impact of Sleeper Berth Usage on Driver Fatigue (Dingus, et al., 2002), studied fatigue in drivers who are on the road up to two weeks at a time and use the truck sleeper-berth unit for rest. Each study presented unique obstacles to overcome in order to make data collection possible. This paper will summarize the lessons learned during recruiting, truck licensing, and coordination and will provide insight into the rigors of collecting data in a truck-driving environment.