ABSTRACT
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 55 mph (89 kph), the MDMA drivers followed 64 m closer to the LV and demonstrated 1.04 s 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.
Subject(s)
Adrenergic Uptake Inhibitors/adverse effects , Automobile Driving , Automobiles , Hallucinogens/adverse effects , Illicit Drugs , N-Methyl-3,4-methylenedioxyamphetamine/adverse effects , Adrenergic Uptake Inhibitors/pharmacology , Adult , Attention , Cognition/drug effects , Cognition Disorders/chemically induced , Female , Fourier Analysis , Hallucinogens/pharmacology , Humans , Male , N-Methyl-3,4-methylenedioxyamphetamine/pharmacology , Risk Assessment , Risk-Taking , Safety , Statistics as Topic , Statistics, Nonparametric , Young AdultABSTRACT
Parkinson's disease (PD) impairs driving performance, and simulator studies have shown increased crashes compared to controls. In this pilot study, eight drivers with PD participated in three drive sessions with multiple simulator intersections of varying visibility and traffic load, where an incurring vehicle posed a crash risk. Over the course of the three sessions (once every 1-2 weeks), we observed reduction in crashes (p=0.059) and reaction times (p=0.006) to the vehicle incursion. These findings suggest that our simulator training program is feasible and potentially useful in drivers with PD. Future research questions include transfer of training to different driving tasks, duration of benefit, and the effect on long term real life outcomes in comparison to a standard intervention (e.g., driver education class) in a randomized trial.
ABSTRACT
Using an instrumented vehicle, we have studied several aspects of the on-road performance of healthy and diseased elderly drivers. One goal from such studies is to ascertain the type and frequency of driving safety errors. Because the judgment of such errors is somewhat subjective, we applied a taxonomy system of 15 general safety error categories and 76 specific safety error types. We also employed and trained professional driving instructors to review the video data of the on-road drives. In this report, we illustrate our rating system on a group of 111 drivers, ages 65 to 89. These drivers made errors in 13 of the 15 error categories, comprising 42 of the 76 error types. A mean (SD) of 35.8 (12.8) safety errors per drive were noted, with 2.1 (1.7) of them being judged as serious. Our methodology may be useful in applications such as intervention studies, and in longitudinal studies of changes in driving abilities in patients with declining cognitive ability.
ABSTRACT
Older drivers are at risk for vehicle crashes due to impairments of visual processing and attention, placing these drivers at greater risk in driving tasks that require continuous attention to neighboring traffic, especially lead vehicles (LVs). We investigated car following behavior in 42 younger drivers (ages 18 to 44 years) and 58 older drivers (ages 65 to 86 years) in a driving simulator. The drivers were instructed to maintain two car lengths from a virtual LV. The LV varied its velocity according to a sum of three sine waves, making the velocity changes unpredictable to the drivers. A Fourier analysis was performed using the vehicle trajectory data to derive measures of coherence, gain, and delay as indices of car following behavior. These measures as well as headway distance were compared between the two groups. Older drivers were less able to match changes in the LV velocity indicated by lower coherence (0.76 v. 0.84, p=0.019) and larger gain (2.24 v. 1.74, p=0.031). However, these drivers followed further behind the LV than younger drivers, a potential compensatory strategy that may reduce collision risk for older drivers.
