Tom Dingus, director of the Virginia Tech Transportation Institute, said:
“The overall level of distraction suprized us quite a bit. Over half the time, the drivers are doing something other than driving, such as messing with the radio, messing with their cell phones, looking around at something not related to driving, or interacting with passengers.”
Dingus and his colleagues analyzed crash risk factors from a huge study that was collected between 2011 and 2013 the second Strategic Highway Research Program Naturalistic Driving Study
(SHRP 2 NDS).
Dingus and his group were able to calculate what the driving risks were for "model driving" behavior, that is when drivers were sober, alert and paying attention to the road. Using this as a baseline, the group were then able to calculate the increased risks of a crash for distracted driving and other factors such as alcohol or drug use.
Such a huge collection of driving data has, for the first time, allowed Dingus and his colleagues to calculate the crash risks for “model driving” behaviors: when drivers were sober, alert, and paying attention to the road. The model driving scenario became the baseline for calculating the increased crash risks related to distracted driving, driving under the influence of alcohol or drugs, and other factors. Dingus was lead author on the resulting research detailed in the most recent issue of the journal
Proceedings of the National Academy of Sciences (PNAS).
An article
here gives a summary of the increase in risks for a crash for various factors. Cellphone handheld use increased the likelihood of a crash by 3.6 times and occurred 6.4 percent of the time. Fatigue and drowsiness was another important factory but happened less often at just 1.57 percent of the time. Emotions caused an even larger increase in risk at 9.8 times but happened only ,22 percent of the time. Driving under the influence of drugs or alcohol increased the risk of a crash by a large almost 36 times but was rare in the study happening on only .08 percent of the driving time. No doubt the fact that the cars were fitted with sensors and cameras were a factor in the low percentage of time driving under the influence of drugs and alcohol.
The Virginia Tech study improves upon older techniques that relied on crash investigations. The method often involved reliance upon memories of individuals involved in crashes which were sometimes incomplete or even faulty. Another method involved volunteers and driving simulation but often did not replicate well the actual responses of drivers during regular driving.
The U.S. fatal crash rate has been actually falling for some time. This no doubt reflects better road conditions and better safety factors built into new cars. Driver behavior, however, may not have improved in some respects. Newer technological devices such as mobile phones have increased the likelihood of risky behaviors by drivers.
The data led the researchers to quantify the risks of driver errors such as going the wrong way on a one-way street. Doing so increased the risk of a crash by a whopping 936 times but occurred only .01 percent of the time. Failing to stop at a stop sign increased crash risk by 5.3 times and happened more often at 1.04 percent of the time.
Eventually self-driving cars may get around the issue of driver errors altogether but that may be far in the future as yet and the cars have their own problems.
Mark Rosekind, administratory of the National Highway Traffic Safety Administration claims that driverless cars could lead to a 94 percent decrease in the number of fatal crashes caused by human error. At present, there are various features of automated car systems that can help reduce accidents.
One new feature that will help reduce accidents is
automatic emergency braking. Ten automakers, Audi, BMW, Ford, General Motors, Mazda, Mercedes-Benz, Tesla, Toyota, Volkswagen, and Volvo have all committed to working with the National Highway Traffic Safety to install such systems in their new vehicles. However, some safety advocates suggest that this move is actually intended to forestall mandatory measures and regulations that would be passed by the U.S. government.
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