Driver sensitivity to brake pulse duration and magnitude.

Adaptive cruise control (ACC) requires that the driver intervene in situations that exceed the capability of ACC. A brake pulse might provide a particularly compatible means of alerting the driver to situations in which the acceleration authority of the ACC has been exceeded. This study examined the sensitivity of the driver to brake pulses of five different amplitudes (0.01-0.025 g) and five different durations (50-800 ms). Drivers were sensitive to accelerations as low as 0.015 g. Pulse duration interacted with pulse amplitude, such that moderate duration pulses were more detectable than long and short duration pulses at intermediate levels of pulse amplitude. A power function with an exponent of 1.0 accounted for 99% of the variance in drivers' sensitivity to pulse amplitude; however, a power function with an exponent of 0.23 accounted for only 70% of the variance in drivers' sensitivity to pulse duration. These results can help designers create ACC algorithms and develop brake pulse warnings.

Simulated car crashes at intersections in drivers with Alzheimer disease.

Current evidence suggests that car crashes in cognitively impaired older drivers often occur because of failure to notice other drivers at intersections. We tested whether licensed drivers with mild to moderate cognitive impairment due to Alzheimer disease (AD) are at greater risk for intersection crashes. In this experiment, 30 participants drove on a virtual highway in a simulator scenario where the approach to within 3.6 seconds of an intersection triggered an illegal incursion by another vehicle. To avoid collision with the incurring vehicle, the driver had to perceive, attend to, and interpret the roadway situation; formulate an evasive plan; and then exert appropriate action on the accelerator, brake, or steering controls, all under pressure of time. The results showed that 6 of 18 drivers with AD (33%) experienced crashes versus none of 12 nondemented drivers of similar age. Use of a visual tool that plots control over steering wheel position, brake and accelerator pedals, vehicle speed, and vehicle position during the 5 seconds preceding a crash event showed inattention and control responses that were either inappropriate or too slow. The findings were combined with those in another recent study of collision avoidance in drivers with AD that focused on potential rear end collisions. Predictors of crashes in the combined studies included visuospatial impairment, disordered attention, reduced processing of visual motion cues, and overall cognitive decline. The results help to specify the linkage between decline in certain cognitive domains and increased crash risk in AD and also support the use of high-fidelity simulation and neuropsychologic assessment in an effort to standardize the assessment of fitness to drive in persons with medical impairments.

Human performance models and rear-end collision avoidance algorithms.

Collision warning systems offer a promising approach to mitigate rear-end collisions, but substantial uncertainty exists regarding the joint performance of the driver and the collision warning algorithms. A simple deterministic model of driver performance was used to examine kinematics-based and perceptual-based rear-end collision avoidance algorithms over a range of collision situations, algorithm parameters, and assumptions regarding driver performance. The results show that the assumptions concerning driver reaction times have important consequences for algorithm performance, with underestimates dramatically undermining the safety benefit of the warning. Additionally, under some circumstances, when drivers rely on the warning algorithms, larger headways can result in more severe collisions. This reflects the nonlinear interaction among the collision situation, the algorithm, and driver response that should not be attributed to the complexities of driver behavior but to the kinematics of the situation. Comparisons made with experimental data demonstrate that a simple human performance model can capture important elements of system performance and complement expensive human-in-the-loop experiments. Actual or potential applications of this research include selection of an appropriate algorithm, more accurate specification of algorithm parameters, and guidance for future experiments.

Driving with Alzheimer disease: the anatomy of a crash.

Alzheimer disease (AD) affects several abilities that are crucial to automobile driving and can thereby increase the risk for a crash. The specific driver safety errors that lead up to crashes in this driver population, however, remain largely unknown. We developed a graphical means for dissecting these safety-related behaviors for application to car crashes of AD drivers. These crashes occurred in collision avoidance scenarios implemented on the Iowa Driving Simulator. Crash plots were produced by "rewinding" the data stream, then graphing the vehicle speed, path, steering wheel position, pedal positions, and driver gaze up to the very moment of impact. In this way, we were able to display in detail the patterns of vehicle and driver control to determine exactly how a crash occurred. Several different types of antecedent safety errors were noted, ranging from responding inappropriately with the hand and foot controls to not responding at all. In this paper we focus on the performance of a single impaired driver to demonstrate our technique and findings. Understanding the "anatomy" of crashes in cognitively disabled drivers with AD can help guide future efforts at injury prevention and control.

Effects of age, system experience, and navigation technique on driving with an advanced traveler information system.

This paper explores the effects of age, system experience, and navigation technique on driving, navigation performance, and safety for drivers who used TravTek, an Advanced Traveler Information System. The first two studies investigated various route guidance configurations on the road in a specially equipped instrumented vehicle with an experimenter present. The third was a naturalistic quasi-experimental field study that collected data unobtrusively from more than 1200 TravTek rental car drivers with no in-vehicle experimenter. The results suggest that with increased experience, drivers become familiar with the system and develop strategies for substantially more efficient and safer use. The results also showed that drivers over age 65 had difficulty driving and navigating concurrently. They compensated by driving slowly and more cautiously. Despite this increased caution, older drivers made more safety-related errors than did younger drivers. The results also showed that older drivers benefited substantially from a well-designed ATIS driver interface.

Human factors field evaluation of automotive headway maintenance/collision warning devices.

Three on-road studies were conducted to determine how headway maintenance and collision warning displays influence driver behavior. Visual perspective, visual perspective with a pointer, visual perspective combined with an auditory warning, discrete visual warning, and discrete auditory warning were assessed during both coupled headway and deceleration events. Results indicate that when drivers are provided with salient visual information regarding safe headways, they utilize the information and increase their headway when appropriate. Auditory warnings were less effective than visual warnings for increasing headways but may be helpful for improving reaction time during events that require deceleration. Drivers were somewhat insensitive to false alarm rates, at least during short-term use. Finally, and most important, driver headway maintenance increased by as much as 0.5 s when the appropriate visual display was used. However, a study to investigate the longterm effects of such displays on behavior is strongly recommended prior to mass marketing of headway maintenance/collision warning devices.