Rear-end collisions account for almost 30% of automotive crashes. Rear-end collision avoidance systems (RECASs) may offer a promising approach to help drivers avoid these crashes. Two experiments performed using a high-fidelity motion-based driving simulator examined driver responses to evaluate the efficacy of a RECAS. The first experiment showed that early warnings helped distracted drivers react more quickly---and thereby avoid more collisions---than did late warnings or no warnings. Compared with the no-warning condition, an early RECAS warning reduced the number of collisions by 80.7%. Assuming collision severity is proportional to kinetic energy, the early warning reduced collision severity by 96.5%. In contrast, the late warning reduced collisions by 50.0 % and the corresponding severity by 87.5%. The second experiment showed that RECAS benefits even undistracted drivers. Analysis of the braking process showed that warnings provide a potential safety benefit by reducing the time required for drivers to release the accelerator. Warnings do not, however, speed application of the brake, increase maximum deceleration, or affect mean deceleration. These results provide the basis for a computational model of driver performance that was used to extrapolate the findings and identify the most promising parameter settings. Potential applications of these results include methods for evaluating collision warning systems, algorithm design guidance, and driver performance model input.

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Background Effects of cannabis, the most commonly encountered non-alcohol drug in driving under the influence cases, are heavily debated. We aimed to determine how blood Δ9-tetrahydrocannabinol (THC) concentrations relate to driving impairment, with and without alcohol. Methods Current occasional (≥1×/last 3months, ≤3days/week) cannabis smokers drank placebo or low-dose alcohol, and inhaled 500mg placebo, low (2.9%)-THC, or high (6.7%)-THC vaporized cannabis over 10min ad libitum in separate sessions (within-subject design, 6 conditions). Participants drove (National Advanced Driving Simulator, University of Iowa) simulated drives (~0.8h duration). Blood, oral fluid (OF) and breath alcohol samples were collected before (0.17h, 0.42h) and after (1.4h, 2.3h) driving that occurred 0.5–1.3h after inhalation. We evaluated standard deviations of lateral position (lane weave, SDLP) and steering angle, lane departures/min, and maximum lateral acceleration. Results In N=18 completers (13 men, ages 21–37years), cannabis and alcohol increased SDLP. Blood THC concentrations of 8.2 and 13.1μg/L during driving increased SDLP similar to 0.05 and 0.08g/210L breath alcohol concentrations, the most common legal alcohol limits. Cannabis-alcohol SDLP effects were additive rather than synergistic, with 5μg/L THC+0.05g/210L alcohol showing similar SDLP to 0.08g/210L alcohol alone. Only alcohol increased lateral acceleration and the less-sensitive lane departures/min parameters. OF effectively documented cannabis exposure, although with greater THC concentration variability than paired blood samples. Conclusions SDLP was a sensitive cannabis-related lateral control impairment measure. During-drive blood THC ≥8.2μg/L increased SDLP similar to notably-impairing alcohol concentrations. Despite OF’s screening value, OF variability poses challenges in concentration-based effects interpretation. KEYWORDS: Cannabis, Alcohol, Driving, Lateral Control, THC, Oral Fluid

As computer applications for cars emerge, a speech-based interface offers an appealing alternative to the visually demanding direct manipulation interface. However, speech-based systems may pose cognitive demands that could undermine driving safety. This study used a car-following task to evaluate how a speech-based e-mail system affects drivers' response to the periodic braking of a lead vehicle. The study included 24 drivers between the ages of 18 and 24 years. A baseline condition with no e-mail system was compared with a simple and a complex e-mail system in both simple and complex driving environments. The results show a 30% (310 ms) increase in reaction time when the speech-based system is used. Subjective workload ratings and probe questions also indicate that speech-based interaction introduces a significant cognitive load, which was highest for the complex e-mail system. These data show that a speech-based interface is not a panacea that eliminates the potential distraction of in-vehicle computers. Actual or potential applications of this research include design of in-vehicle information systems and evaluation of their contributions to driver distraction.

Both HFL-TMS and LFR-TMS have treatment efficacy in patients with medication-resistant major depression. Treatment for at least 4 weeks is necessary for clinically meaningful benefits to be achieved. Treatment with LFR-TMS may prove to be an appropriate initial repetitive TMS strategy in depression taking into account safety, tolerability, and efficacy considerations.