The Effects of Visual Perceptual Repetition Priming of Road Signs on Driving Performance in Young and Old Adults

SIGNIFICANCE: Older adults tend to suffer from cognitive deficits and thus reflect on quality of life. There exists an association between older adults’ car accidents and the failure to identify traffic signs. This creates driving safety concerns for the older adult population. Therefore, it is important to understand how older adults interpret road signs and to measure their response rate while driving. The significance of this research lies in the theory that implicit memory can supplement explicit memory while driving. Therefore, through repetition priming along with visual perception priming, it is intended to elicit implicit memory to enhance explicit memory. There is growing speculation in recognition of which road sign can increase response rates in the older population while driving, but there is gap. Most of the research has been done in young adults, which does not reflect the present theories on how explicit memory affects driving performance in older adults.

INNOVATION: This study takes the innovative approach of repetition priming in traffic sign and symbols through a dynamic driving simulator. A virtual, vivid driving scenario has been created to simulate a real driving experience for the participants. Therefore, the data acquired through the scenario would be a close representative of an actual driving experience. In addition, this research is innovative as it bridges the gap between the fields of neuroscience with engineering design. This trans-disciplinary approach is needed to solve problems of this magnitude. This innovated research looks not only at the possible scientific significance of the findings but also at the societal good that can be obtained through the findings.

HYPOTHESES: The purpose of the study was to compare the effects of two types of visual–perceptual priming—word format and symbol format—of road signs on younger (control) and older adults’ driving performance at a stop sign intersection. We hypothesized that the repetition of road sign information would improve younger and older adults’ driving performance as measured by (1) driver’s brake reaction time (in seconds; time between the appearance of a stop sign and initiation of the brake), (2) brake reaction distance (in feet), (3) total time (in seconds; from stop sign appearance to complete stop), and (4) car stopping distance from the intersection. We also hypothesized that the vehicle would stop earlier in both priming conditions when compared to the control conditions, and there would be significant differences between younger and older adults’ driving performance.

RATIONALE/BACKGROUND: In 2011, of 35 million licensed older adult drivers (aged 65 yr and older), 185,000 experienced nonfatal injuries and 5,401 sustained fatal injuries due to motor vehicle accidents. In 2005, the total estimated cost of crash-related deaths among older adult drivers was $91 million.

One of the main reasons for accidents in older adults has been the failure to recognize road signs. Comprehension of road signs during driving requires an interaction between implicit and explicit memory. As explicit memory is compromised with advancing age, comprehension of federally regulated road signs becomes difficult, leading to accident-prone behaviors in older adult drivers. It is imperative to find support for declining explicit memory to keep older adult drivers safe on the road.

A long line of cognitive research suggests that a specific type of implicit memory known as repetition priming can be used to generate explicit behavior. Repetition priming refers to the effects of a prior presentation of a stimulus (prime) on the processing of a subsequent stimulus (target). The priming effect is expressed as a faster and often more accurate performance on the target. In the present study, we explored the effect of repetition priming on stop signs to assess whether older drivers efficiently and accurately react to a traffic sign in a simulated driving scenario under priming conditions.

METHOD: Nineteen older adults (aged 65 yr and older) and 42 young adults (aged 18 to 38 yr) participated in this study. The participants were required to have a valid driver’s license, have adequate vision, and use both feet for the gas and brake pedals. To participate in the study, they could not be susceptible to motion sickness or be required to use orthopedics. Written informed consent was obtained from each participant prior to the experiment. Participants were given a $40 gift card after finishing the study.

After the participants arrived at the driving simulation laboratory, they were asked to sign a consent form. Prior to performing a warm-up trial, participants filled out a dizziness questionnaire, the Driving Habits Questionnaire (DHQ), a demographics questionnaire, and the Montreal Cognitive Assessment (MOCA). The participants then familiarized themselves with the simulator by driving for 5 min in a practice scenario. In addition, they were also asked whether they needed more time to get familiar with the simulator. In the case that they did, they were allowed extra time. Following, participants drove through the experimental scenarios in a random order.

Participants were divided randomly into two groups. The first group started driving through scenarios with the word format road signs followed by a 10-min break; then the participants drove drive through symbol format road sign scenarios. The second group started in the opposite sequence.

Participants’ driving performances were tested with driving simulation scenarios implemented on a high-fidelity driving simulator (STISIM Drive^TM M400). Driving scenarios consisting of a stop–intersection were programmed with traffic signs following the repetition priming parameters of a visual-perceptual format (symbol–symbol or word–word). Prior to the series of signs, three black Xs on a white sign were shown as a fixation point.

The driving simulator provided three different types of conditions in two different formats. The road signs that were shown had both word and symbol format scenarios. A word format scenario consisted of diamond-shape signs with the word “Stop” written on it. The symbol format scenarios consisted of diamond-shape signs with a hand sign drawn in it, signifying the action of stop. The stop signs were placed on the right side of the road to mimic actual driving scenarios.

The simulator collected the response rate of older adults’ driving performance. These included the driver’s reaction time (s), throttle acceleration (ft/s/s [fps2]), brake deceleration (fps2), forward velocity (mph), and maneuvering initiation distance to the stop scene (ft).

Using a between-subjects design, two-way repeated measures analysis of variance (ANOVA) was used to analyze the response time and errors between subjects. Tests of within-subject effects, utilizing two-way mixed repeated measures ANOVA were conducted to compare the effects of priming and age on double control, repetition control, and repetition priming conditions for brake reaction time, break reaction distance, total time, and car stopping distance from the intersection.

RESULTS: The results demonstrate that repetition priming significantly affects the brake reaction time (Pillai’s Trace = .424, F[5, 46] = 6.762, p = .000, η² = .424). However, age insignificantly affects the brake reaction time (Pillai’s Trace = .139, F[5, 46] = 1.491, p = .211, η² = .139). On the other hand, both repetition priming (Pillai’s Trace = .538, F[5, 46] = 10.698, p = .000, η² = .538) and age (Pillai’s Trace = .230, F[5, 46] = 2.748, p = .030, η² = .230) have a significant effect on brake reaction distance. Similarly, for the car stopping distance outcome variable, the results demonstrate that both repetition priming (Pillai’s Trace = .297, F[5, 46] = 3.887, p = .005, η² = .297) and age (Pillai’s Trace = .235, F[5, 46] = 2.832, p = .026, η² = .236) have a significant effect. Last, repetition priming has a significant effect on total time (Pillai’s Trace = .237, F[5, 46] = 2.858, p = .025, η² = .237), and age insignificantly affects total time (Pillai’s Trace = .137, F[5, 46] = 1.462, p = .221, η² = .137). Taken together, the results demonstrate that brake reaction time and total time outcome variables do not show a correlation between repetition priming and age.

CONCLUSION: The results of the study support the hypothesis that repetition priming of stop signs in either word or symbol format produced a more efficient and accurate driving performance in both younger and older adult drivers. Additionally, the older adult group behaved differently than the younger adult group under priming conditions.

Furthermore, to increase overall driving safety, it is imperative to explore which visual perceptual priming works best and whether priming works better on younger adult drivers when compared to older adult drivers. We have shown that by using priming, older adults driving behaviors can be altered by accessing their implicit memory, thus improving their functional mobility while driving. This concept can be applied among other populations who may also have explicit memory deficits, such as beginning stages of Alzheimer’s disease or attention deficit hyperactivity disorder. By manipulating road signs, using repetition priming, and following the parameters of memory, we are creating an effective and quicker reaction to road signs and improving adherence to traffic rules and regulations. This may ultimately increase driver performance and road safety compliance.