At-Risk Drivers Can Be Identified by Visual, Cognitive Acuity
MAY 12, 2017
“This is the story of the public health issue of older drivers,” said Sheila West, PhD, PharmD, vice chair for research at the Wilmer Eye Institute. “We know that the population of older persons is increasing. We figure that in another 3 years about 17% of the population in the US will be aged 65 or older, and the automobile use is high in this age group.”
Older drivers have a higher rate of exposure to accident involvement, which often leads to disability or death, she said. However, driving is a major factor in maintaining independence.
“Research has shown that giving up a license increases the risk for older people of social isolation, depression, nursing home admission and other adverse outcomes,” West said. Because of this, it’s important to gain a better understanding of the factors that increase crash risk in older people.
To that end, West and a team of researchers studied about 1500 drivers between the ages of 70 and 84 in an area of Maryland that contained rural, semirural, semiurban and urban conditions.
At baseline, the researchers conducted vision testing on visual acuity, contrast sensitivity, the Humphrey Visual Field Test, and a test that was analogous to the useful field of view (UFOV) test. Cognitive testing was completed on attention, visual special integration, memory, executive function, and a brake time reaction test that measured processing speed and total reaction time.
A driving assessment was also conducted that included four key metrics – failure to stop at a red traffic light, failure to stop at a stop sign, failure to properly execute a left turn, and failure to properly execute a lane change.
A real-time driving performance index was used in conjunction with a driver monitoring system to collect data. This included non-video data like accelerometer and global positioning as well as three cameras – one focused on the driver and two facing forward for nighttime and daytime driving.
“People often ask me ‘Weren’t people aware of this system in their car?’ Given the videos that we saw, they were probably aware of it for a couple of minutes, then they clearly were not. We saw people changing clothes in their car and engaging in all kinds of behavior that I won’t tell you about,” West said.
Data was collected over a three-year period and overlaid onto a map that included every traffic light and stop sign in the area where the tests were conducted. Researchers found that of the four metrics measured, two were particularly related to risk of at-fault crashes – failure to stop at a red traffic light and failure to make a safe lane change.
There was no clear pattern by age for failure to stop at a traffic light. However, there were associations between tests of executive function, cognitive tests of attention, and particularly visual tests of attention, and a participant’s likelihood to drive through a red traffic light.
“For those that failed at least once [to stop at a red traffic light], their visual attention was much smaller in the vertical direction,” West said. “That makes intuitive sense when you look at how traffic lights are situated in this area – they are mostly high up above the intersection, so lack of attention in that area could very well lead to a problem.”
Failure to properly execute a lane change was the most commonly failed index, with 66% to 75% of all drivers failing at least once, and an increased likelihood of failure with increased age. Failure was more likely in a rural environment, where it was associated with various cognitive tests including visual-spatial skills and audio attention. In urban areas, lane change failure was more closely associated with loss of contrast sensitivity and visual attention.
“What we’re seeing here is that our vision factors seem to be related to the measures of diminished driving performance. The contrast sensitivity loss or visual field loss were related to the [four key metrics], which in turn were related to crash risk,” West said. “Instead of just looking at fines and violations, we could use this information to flag drivers at an MVA [Motor Vehicle Administration] or family level who could be at an increased risk of crashes.”