Automotive collision warning systems (CWS) can enhance hazard identification and management. However, false alarms (FAs), which occur as a random activation of the system not corresponding to a threat and not interpretable by the driver, and unnecessary alarms (UAs), which occur in situations judged hazardous by the algorithm but not by the driver, may limit CWS effectiveness. A driving simulator was used to investigate the influence of CWS (accurate, UA, FA, none) and distraction on driver performance during non-critical and critical events. FAs and UAs differentially influenced trust and compliance. FAs diminished trust and compliance, whereas the context associated with UAs fostered trust and compliance during subsequent events. This study suggests current warning descriptions based on signal detection theory need to be expanded to represent how different types of alarms affect drivers.

The results suggested that UFOV decline in normal aging can be associated with a specific attentional operation, namely attentional disengagement. These results suggest that the underlying cause of UFOV decline may not be a restriction in the breadth or scope of attention. Because the UFOV is a reliable predictor of driving safety, our results point to attentional components that are critical for the visual behavior of older adults.

Ecstasy (MDMA) use raises concerns because of its association with risky driving. We evaluated driving performance and risk taking in abstinent recreational MDMA users in a simulated car following task that required continuous attention and vigilance. Drivers were asked to follow two car lengths behind a lead vehicle (LV). Three sinusoids generated unpredictable LV velocity changes. Drivers could mitigate risk by following further behind the erratic LV. From vehicle trajectory data we performed a Fourier analysis to derive measures of coherence, gain, and delay. These measures and headway distance were compared between the different groups. All MDMA drivers met coherence criteria indicating cooperation in the car following task. They matched periodic changes in LV velocity similar to controls (abstinent THC users, abstinent alcohol users, and non-drug users), militating against worse vigilance. While all participants traveled approximately 55mph (89kph), the MDMA drivers followed 64m closer to the LV and demonstrated 1.04s shorter delays to LV velocity changes than other driver groups. The simulated car following task safely discriminated between driving behavior in abstinent MDMA users and controls. Abstinent MDMA users do not perform worse than controls, but may assume extra risk. The control theory framework used in this study revealed behaviors that might not otherwise be evident.

Neuroergonomics provides a multidisciplinary translational approach that merges elements of neuroscience, human factors, cognitive psychology, and ergonomics to study brain structure and function in everyday environments. Driving safety, particularly that of older drivers with cognitive impairments, is a fruitful application domain for neuroergonomics. Driving makes demands on multiple cognitive processes that are often studied in isolation and so presents a useful challenge in generalizing findings from controlled laboratory tasks to predict safety outcomes. Neurology and the cognitive sciences help explain the mechanisms of cognitive breakdowns that undermine driving safety. Ergonomics complements this explanation with the tools for systematically exploring the various layers of complexity that define the activity of driving. A variety of tools, such as part task simulators, driving simulators, and instrumented vehicles provide a window into cognition in the natural settings needed to assess the generalizability of laboratory findings and can provide an array of potential interventions to increase safety.

Summary: This study investigated how system failures influenced drivers' reliance on Adaptive Cruise Control (ACC). A medium-fidelity driving simulator was used to evaluate the effect of driving condition (traffic, rain) and automation (manual control, ACC) on headway maintenance and brake response. In conditions of rain, the signal continuity of the ACC sensors was degraded and in conditions of heavy traffic, the braking limits of the ACC system were exceeded. Dependent variables included response time to lead vehicle (LV) braking, number of collisions, and both time headway (THW) and time-to-collision (TTC) at instant of the brake response. Throughout the drive, a continuous (forced-paced) secondary task was introduced to determine how an in-vehicle task interacted with ACC reliance. Results showed that the failure type influenced driver's reliance on ACC with drivers relying more on ACC in traffic periods than in rain periods. ACC appeared to offer a safety benefit when drivers were distracted with complex mental tasks in periods of heavy traffic.