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Methods: Speed cameras measured travel speeds and photographed license plates and drivers of passenger vehicles traveling on roadways in Northern Virginia during daytime off-peak hours in spring 2013. The driver licensing agencies in the District of Columbia, Maryland, and Virginia provided vehicle information numbers (VINs) by matching license plate numbers with vehicle registration records and provided the age, gender, and ZIP code of the registered owner(s). VINs were decoded to obtain the curb weight and horsepower of vehicles. The study focused on 26,659 observed vehicles for which information on horsepower was available and the observed age and gender of drivers matched vehicle registration records. Log-linear regression estimated the effects of vehicle power on mean travel speeds, and logistic regression estimated the effects of vehicle power on the likelihood of a vehicle traveling over the speed limit and more than 10 mph over the limit.
Results: After controlling for driver characteristics, speed limit, vehicle type, and traffic volume, a 1-unit increase in vehicle power was associated with a 0.7% increase in mean speed, a 2.7% increase in the likelihood of a vehicle exceeding the speed limit by any amount, and an 11.6% increase in the likelihood of a vehicle exceeding the limit by 10 mph. All of these increases were highly significant.
Conclusions: Speeding persists as a major factor in crashes in the United States. There are indications that travel speeds have increased in recent years. The current findings suggest the trend toward substantially more powerful vehicles may be contributing to higher speeds. Given the strong association between travel speed and crash risk and crash severity, this is cause for concern. 相似文献
Methods: In collaboration with local police, drivers were selected for a voluntary and anonymous study using a multistage cluster sampling procedure (selection of roads, time intervals, and drivers within each interval) from September 2014 to October 2015. Age, gender, citizenship, time, and geographical site were recorded. Samples of oral fluid were collected using the Quantisal device. The samples were analyzed for alcohol with an enzymatic method and for 12 illicit drugs and 16 medicinal drugs and some metabolites using ultra-high-performance liquid chromatography with tandem mass spectrometry detection.
Results: A total of 3,228 drivers were asked to participate in the study. The refusal rate was 6.2%. Of the 3,027 participants in the study, 111 (3.7%) were Russian and 204 (6.7%) had citizenship other than Norwegian or Russian. The total prevalence of psychoactive substances was 4.3%. Alcohol was detected in 0.3%, psychoactive medicinal drugs in 2.5%, and illicit drugs in 1.6% of the samples. The most commonly found substances were the sleeping agent zopiclone (1.1%), tetrahydrocannabinol (THC; 1.1%), and the analgesic agent codeine (0.6%). Illicit drugs were detected significantly more often in samples from drivers of citizenship other than Norwegian or Russian. The prevalence of alcohol was somewhat higher among Russian drivers but not statistically significant. There were large differences between age groups and genders concerning illicit drugs and psychoactive medicinal drugs; illicit drugs were more frequently in samples from young male drivers, whereas psychoactive medicinal drugs were more frequently in samples from elderly female drivers.
Conclusion: The total prevalence of alcohol and drugs among the general driving population in Finnmark was low and similar to previous Norwegian roadside surveys. Illicit drugs were detected significantly more often in samples from drivers with citizenship other than Russian and Norwegian and among young male drivers. 相似文献