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Optometry & Vision Science:
Original Article

Effects of Age and Auditory and Visual Dual Tasks on Closed-Road Driving Performance

CHAPARRO, ALEX PhD; WOOD, JOANNE M. PhD, FAAO; CARBERRY, TRENT BSc

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Author Information

Department of Psychology, Wichita State University, Wichita, Kansas (AC), and the School of Optometry, Queensland University of Technology, Brisbane, Queensland, Australia (JMW, TC)

Received December 15, 2004; accepted June 1, 2005.

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Abstract

Purpose. This study investigated how driving performance of young and old participants is affected by visual and auditory secondary tasks on a closed driving course.

Methods. Twenty-eight participants comprising two age groups (younger, mean age = 27.3 years; older, mean age = 69.2 years) drove around a 5.1-km closed-road circuit under both single and dual task conditions. Measures of driving performance included detection and identification of road signs, detection and avoidance of large low-contrast road hazards, gap judgment, lane keeping, and time to complete the course. The dual task required participants to verbally report the sums of pairs of single-digit numbers presented through either a computer speaker (auditorily) or a dashboard-mounted monitor (visually) while driving. Participants also completed a vision and cognitive screening battery, including LogMAR visual acuity, Pelli-Robson letter contrast sensitivity, the Trails test, and the Digit Symbol Substitution (DSS) test.

Results. Drivers reported significantly fewer signs, hit more road hazards, misjudged more gaps, and increased their time to complete the course under the dual task (visual and auditory) conditions compared with the single task condition. The older participants also reported significantly fewer road signs and drove significantly more slowly than the younger participants, and this was exacerbated for the visual dual task condition. The results of the regression analysis revealed that cognitive aging (measured by the DSS and Trails test) rather than chronologic age was a better predictor of the declines seen in driving performance under dual task conditions. An overall z score was calculated, which took into account both driving and the secondary task (summing) performance under the two dual task conditions. Performance was significantly worse for the auditory dual task compared with the visual dual task, and the older participants performed significantly worse than the young subjects.

Conclusions. These findings demonstrate that multitasking had a significant detrimental impact on driving performance and that cognitive aging was the best predictor of the declines seen in driving performance under dual task conditions. These results have implications for use of mobile phones or in-vehicle navigational devices while driving, especially for older adults.

Older drivers have a high fatal crash rate per mile driven, which results in significant social and economic costs to the community.1,2 Older drivers are also involved in a disproportionate number of crashes associated with intersections and other complex traffic situations, failure to yield, inattention, and turning across traffic3–5 and are commonly found to be “at fault” in crashes.4,6 The underlying reasons for this overinvolvement of older individuals in crashes have not been well established. It is recognized, however, that the effects of age alone are not sufficient to account for many of these crashes. Importantly, the driving situation and the in-vehicle environment are becoming increasingly complex; hence, the problems of the elderly driver are likely to increase in the future. In addition, new technologies such as mobile phones add to the drivers’ attentional burden, and some vehicles are now equipped with sophisticated navigation and entertainment systems, which may distract drivers from their primary task.

The attentional burden of using these devices increases a driver’s accident risk as evidenced by findings showing a fourfold increase in crash risk among mobile phone users.7 Recent experimental studies show that drivers engaged in a secondary task such as talking on a mobile phone are less likely to detect road hazards and their response times are slower. For instance, Richards et al.,8 using a laboratory-based image-flicker task, reported that response times to search for changes in driving scene images were significantly slower in the presence of a concurrent auditory task. This is consistent with previous findings on a driving simulator that demonstrate that driving performance is little impacted by a secondary task that involves passive listening (listening to a book on tape or prerecorded conversation)9,10 as opposed to a task in which a response must be generated (engaging in a mobile phone conversation). The more complex secondary task appears to cause interference affecting visual search, detection of hazards, and changes in the driving scene.9 Such findings have significant implications for the use of mobile phones and for in-vehicle guidance systems. These devices can compete for the limited attentional capacity of the driver and may represent a relatively greater risk for older drivers given the age-related changes found in selective attention and the ability to divide attention between multiple tasks.

Studies of selective and divided attention show that older participants are more affected than their younger counterparts by the presence of distracters11 and by tasks requiring the division of attention.12 These findings have important implications for road safety because reductions in divided and selective visual attention have been shown to be associated with increased crash risk.13 These attentional abilities can be measured using a computer-based test known as the Useful Field of View (UFOV). Older drivers who have a 40% or more reduction in the UFOV have been reported to have a sixfold elevation in crash risk compared with control subjects in a retrospective study13 and are 2.2 times more likely to have a crash than those with a normal UFOV in a three-year prospective study.14 Owsley et al.15 also found that a reduction in the UFOV was more likely to predict injurious than noninjurious crash involvement, in which those older drivers with more than a 40% reduction in their UFOV were 16.3 times more likely to be involved in an injurious crash than were those drivers with minimal or no reductions in the UFOV. It should be noted, however, that the reported crash rate–UFOV relationships are based on drivers selected for high accident rates rather than older drivers in general.

Age-related changes in divided attention may increase the risk for older adults when using auxiliary electronic devices while driving, because dual task conditions have been shown to yield large and reliable age-related differences in performance.16 To date, most investigations of the effects of secondary tasks on the driving performance of older participants have used driving simulators17–19 or involved participants viewing video clips of driving scenes.20 These studies demonstrate that when engaged in a secondary task, older participants are slower to initiate braking in response to slowing by a lead vehicle than younger participants, are less likely to respond appropriately to other traffic situations,20 and show greater variability in lane position.19 Although suggestive, the external validity of findings from simulator studies has been questioned because participants may behave quite differently given the absence of any real risk to safety. A primary aim of this study was to investigate the effects of secondary tasks on the driving performance of younger and older participants under more real-world driving conditions.

An additional aim of the study was to understand how visual and auditory dual tasks might differentially impact on the driving performance of young and old participants when they are actually driving. A secondary auditory task is predicted to interfere less with the manual control task of driving because it relies on a distinct set of resources associated with auditory perception, verbal working memory, and the generation of a vocal response.21,22 However, a secondary visual task necessitates the sharing of resources associated with visual perception and spatial working memory. The visual task may also interfere more with driving because it requires the subject to take their eyes off the road to read the stimulus display. Thus, it is predicted that a visual dual task would interfere more with driving and that this may be reflected in measures of steering control, including the number of lane crossings and the percentage of time spent out of the lane.

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EXPERIMENTAL DESIGN

The effects of multitasking on measures of driving performance, including the detection and recognition of road signs, detection and avoidance of large low-contrast hazards, judgment of gaps between cones, time to complete the course, and lane keeping, were obtained for young and older participants as they drove along a closed-road driving course.

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Participants

Fourteen young (mean age = 27.3 years, standard deviation [SD] = 5.3) and 14 elderly (mean age = 69.2 years, SD = 4.9) participants with normal corrected vision completed the experiment. All participants were in good general health and were licensed drivers with at least 3 years of driving experience. All reported that they drove regularly.

The study was conducted in accordance with the requirements of the Queensland University of Technology Human Research Ethics Committee. All participants were given a full explanation of the experimental procedures, and written informed consent was obtained with the option to withdraw from the study at any time.

Participants were screened for cognitive, visual, and auditory impairment before the experiment. The cognitive tests (Mini-Mental State Exam, Digit Symbol Substitution Task, Trail Making Test A and B) and tests of visual function (visual acuity and contrast sensitivity [Pelli-Robson]) are described subsequently; the mean scores for the tests are given in Table 1.

Table 1
Table 1
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Mini-Mental State Examination

The Mini-Mental Status Examination is a short screening test of cognitive status that is designed to assess basic mental functioning, including a person’s ability to recall specific facts, to write, to calculate numbers, and to draw.

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Digit Symbol Substitution Task

The DSS task is part of the Wechsler Adult Intelligence Scale. Participants were presented with a coding key, which paired the numbers 1 through 9 with a corresponding symbol. On the lower half of the sheet of paper were rows of random numbers below each of which appeared an empty box. Participants were given 90 seconds to transcribe as many of the symbols to match the numbers as possible into the empty boxes in the order that the numbers appeared beginning at the top left row of numbers. The number of correct transcriptions was recorded.

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Trail Making Test A and B

The Trail Making test requires participants to connect either a sequence of numbers (1-2-3-4; Test A) or to alternate between numbers and letters (i.e., 1-A-2-B, and so on; Test B) that are distributed across a page. The time to complete each sequence was recorded.

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Visual Acuity

Static high-contrast visual acuity was assessed binocularly using a Bailey Lovie Chart, which uses log minimum angle of resolution principles. The charts were viewed from a working distance of 3.0 meters. Participants were required to guess letters when they were unsure until a full line of letters was incorrectly read. Each letter reported correctly was scored as -.02 log units.

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Contrast Sensitivity

Letter contrast sensitivity was determined binocularly using the Pelli-Robson chart under the recommend viewing conditions. Participants were instructed to look at a line of letters and forced to guess the letter when they were not sure. Each letter reported correctly was scored as 0.05 log units.

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Auditory Thresholds

All participants had normal hearing sensitivity for their age as defined by pure tone thresholds lower than or equal to 20-dB hearing loss at octave frequencies between 500 Hz and 4000 Hz.

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Assessment of Driving Performance

Driving performance was assessed on a 5.1-km road circuit,23 which was free of other vehicles and representative of rural roads. The participants drove a righthand-drive sedan with automatic transmission and power steering. Participants were given a practice run to familiarize themselves with the car, the road circuit, and the driving tasks. The practice run was identical to the test run except that it was performed in the opposite direction to the recorded run to minimize any familiarity effects. For the main test circuit, participants were instructed that they would be required to perform a number of concurrent tasks while driving at what they felt was a safe speed, to drive in their own lane except when avoiding hazards, and to obey all regulatory signs. The trial runs were randomized and conducted over two visits to the test track separated by at least a week to minimize learning effects. Performance measures included the time to complete the road course, number of road signs recognized, number of road hazards recognized and avoided, correct gap judgments, lane keeping, as well as correct responses on the secondary task. Details for each of the performance measures are provided subsequently.

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Time to complete the road course.

An experimenter in the rear of the vehicle recorded the total time taken to complete the 5.1-km road course.

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Road sign recognition.

The road sign recognition task required participants to report the information on any of 42 road signs located along the course containing a total of 65 items of information. A participant’s score represents the total number of correctly reported items of information.

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Road hazard recognition and avoidance.

Participants were instructed to report and avoid hitting any of nine large low-contrast foam rubber road hazards centered across the driving lane. The road hazards were constructed from sheets of 15 cm × 80 cm × 220-cm thick gray foam rubber (reflectance of approximately 10%). Although the hazards could be felt when run over, they had little effect on vehicle control. The position of the road hazards was randomized between each run; during any given trial, only nine of a total of 11 hazards were positioned on the course. Performance was measured as the number of road hazards recognized and the number hit.

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Gap perception.

Nine pairs of traffic cones with variable lateral separations were also positioned throughout the course. Equal numbers of cones were set to be not wide enough, just wide enough, and wide enough for the car to pass through. Participants were instructed to report if the clearance between cones was sufficient to pass through and if so, to attempt to do so. If the cone separation was judged to be too narrow, they were instructed to drive around the cones. The separation of the cone pairs was varied between test runs. Performance was measured as the number of cone gaps judged correctly as well as the number of times a participant was successful in maneuvering through the gap without hitting the cones.

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Lane keeping.

Lane keeping was recorded by two video cameras mounted on the roof of the vehicle and angled downward to view the left and right front corners of the vehicle. The videotapes were analyzed by recording the number of times the vehicle crossed the right and left white lane boundaries and the total amount of time spent out of the lane. Lane crossings for the left and right lane boundaries were calculated separately. Lane crossings when the participant was responding to a hazard on the road were excluded from the lane keeping score.

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Summing task.

The secondary task required participants to verbally report the sums of numbers presented either through a computer speaker (auditorally) or through a dashboard-mounted monitor (visually) while driving. The monitor was positioned just left of the steering wheel on dashboard. The visual task consisted of the simultaneous presentation of pairs of large numbers (e.g., 1 + 5) subtending between 3.5° and 4.8° of visual angle at the viewing distance of the participants, which were well above threshold. The auditory stimuli were presented at a comfortable listening level set by the participant. Pairs of numbers were presented roughly every 3.5 seconds. Performance measures included the percentage of correct responses, incorrect responses, and nonresponses.

A composite driving score was also derived to capture the overall driving performance of the individual participants compared with the whole group and included road sign recognition, cone gap perception, course time, and the number of road hazards hit. Z scores for each of these four driving measures were determined and the mean Z score for each participant calculated to give an overall score. Equal weighting was assigned for all tasks.

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RESULTS

Tests of Cognitive and Visual Function

The young participants performed significantly better than the older participants on all the tests of cognitive and visual function (t-test). However, the mean scores for each group fell within normal limits for their respective age groups.

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Overall Driving Z Score

The data analysis consisted of a split-plot analysis of variance. There was a significant main effect of task for overall driving Z score (F2,52 = 25.46, p = 0.0001). The composite driving score was significantly better for the single task condition compared with both the dual visual (F1,26 = 37.40, p = 0.0001) and auditory task conditions (F1,26 = 50.20, p = 0.0001) (but these were not significantly different from one another) (Fig. 1). There was a significant main effect of age for the composite driving score, in which the younger drivers performed significantly better than did the older drivers (F1,26 = 7.3, p = 0.012).

Figure 1
Figure 1
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Road Signs

There was a significant main effect of task for reporting road signs (F2,52 = 11.95, p = 0.0001), Single task performance was significantly better than either visual (F1,26 = 8.76, p = 0.006) or auditory (F1,26 = 21.10, p = 0.0001) dual task performance (which did not differ from each other) (Fig. 2). The young subjects detected significantly more road signs than did the older group (F1,26 = 4.94, p = 0.035).

Figure 2
Figure 2
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Time to Complete the Road Course

There was a significant main effect of task for time to complete the course (F2,52 = 18.11, p = 0.0001). All of the task conditions were significantly different from one another, in which single task performance was significantly faster than either visual (F1,26 = 30.72, p = 0.0001) or auditory dual task (F1,26 = 14.80, p = 0.001) and driving time under auditory dual task conditions was significantly faster than for the visual dual task (F1,26 = 4.65, p = 0.04). There was also a significant interaction of group and task for time to complete the course (F2,52 = 3.35, p = 0.043). Single task performance was significantly better than either visual dual task (F1,26 = 26.16, p = 0.0001) or auditory dual task (F1,26 = 20.24, p = 0.001) (but visual and auditory did not differ significantly from each other) for the young. For the elderly, single and auditory dual task performance was significantly faster than visual dual task performance (F1,26 = 11.176, p = 0.005 and F1,26 = 9.770, p = 0.008, respectively).

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Gap Judgments

There was a significant main effect of task on gap judgments (F1,2 = 3.88, p = 0.027). Performance under the single task condition was significantly better (F1,26 = 7.78, p = 0.01) than under the auditory dual task.

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Hazards Hit

The main effect of task on hazards hit was also significant, in which participants hit significantly more hazards under the auditory dual task than the single task condition (F1,26 = 4.52, p = 0.043).

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Summing Task

Analysis of the data from the secondary summing task showed that subjects missed more sums (F1,26 = 15.15, p = 0.001) and reported significantly fewer correct sums (F1,26 = 12.18, p = 0.002) (shown in Fig. 3) when performing the auditory compared with the visual dual task, but there was no effect of age. Summing errors were very rare for both groups, accounting for <1% of responses.

Figure 3
Figure 3
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Overall Z Scores

An overall Z score was calculated, which took into account both driving and the secondary task (summing) performance under the two dual task conditions and is represented in Figure 4. Overall performance was significantly worse for the auditory dual task (F1,26 = 10.80, p = 0.003) compared with the visual dual task, and the older participants performed significantly worse than did the young subjects (F1,26 = 3.68, p = 0.011), but the age times task interaction was not significant.

Figure 4
Figure 4
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Lane Crossings

Analysis of the lane crossing data revealed significant main effects of task for the left (F2,52 = 5.74; p = 0.006) but not the right (F2,52 = 2.53; p = 0.09) lane crossing measures. There were significantly fewer left lane crossings for the visual dual task as compared with either the single task (F1,26 = 5.87; p = 0.02) or auditory dual task (F1,26 = 7.65; p = 0.01), whereas there were significantly more righthand lane crossings in the visual than in the auditory dual task (F1,26 = 5.10; p = 0.03). There were no significant differences in left or right lane crossings between the single and auditory dual task (F1,26 = 2.36; p = 0.14 and F1,26 = 3.16; p = 0.09), respectively). Age had a significant effect only on left lane crossings (F1,26 = 9.17; p = 0.005); older participants crossed the left hand lane significantly more times than did the young.

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Regression Analysis

An exploratory multiple regression analysis was performed to investigate whether any of the measures of cognitive and visual function were predictive of the overall driving Z scores obtained for the single task, visual dual task, and auditory dual task. The data for the young and older participants were combined as a result of the small number of participants relative to the number of visual and cognitive measures. Table 2 displays the correlations among the variables, the standarized regression coefficients (B), the intercept, standardized regression coefficients (Beta), and R2 and adjusted R2 values. For the single task condition, only the DSS test was predictive of overall driving Z score. Both DSS and age were found to be predictive of performance in the visual dual task. For the auditory dual task only, Trail A was found to be predictive of overall driving performance. The correlation between DSS and Trail Making Test A was significant: R = -.661 (p = 0.01); however, after controlling for age, the correlation was no longer significant.

Table 2
Table 2
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DISCUSSION

The results demonstrate that secondary tasks have a pervasive effect on measures of driving performance assessed under real-world driving conditions. Drivers reported fewer road signs, took longer to complete the road course, hit more road hazards, and misjudged cone gaps more frequently under the dual task compared with the single task condition. Interestingly, when driving under visual dual task conditions, participants’ lane positioning changed such that they crossed the righthand boundary more and the left lane boundary less than under either single or auditory dual task conditions. Hence, vehicle control was sensitive to the type of secondary task performed rather than by performing a secondary task per se. Earlier studies of closed-road driving also found that lane-keeping behavior was little affected by secondary auditory tasks, especially if the secondary task did not involve manual manipulation of radio or cellular phone controls.24–27

Significant age-related differences were observed for reporting road signs but not for hazards hit or gap judgments. The differences between the two age groups for sign detection are consistent with the literature demonstrating age-related declines in divided and selective attention13 and dual task performance.12 Ball and colleagues28 reported that older subjects performed more poorly on divided and selective attention tasks that required subjects to identify a central target while also reporting the location of concurrently presented peripheral targets as measured using the UFOV. The selective attention task was similar except that the peripheral target was embedded among distracters. Age-related declines in divided and selective attention may be important for the sign detection task because unlike the other driving tasks, the subjects had to maintain visual attention and search for signs or rely on the salient features of the signs to attract their attention. In contrast, the gap judgment and road hazard tasks were located in the center of the traffic lane. Finally, unlike the younger drivers, older participants drove significantly more slowly under visual dual task conditions than under the auditory dual task. It is likely that the older drivers drove more slowly because reading the numbers on the display required them to take their eyes off the road. This may be another example of a strategy adopted by older drivers to manage risk and multiple task demands; older drivers report that they drive more slowly and are less likely to drive at night, during rush hour traffic, or to unfamiliar destinations than younger drivers.29,30

Although the older participants generally performed more poorly than the younger participants, the task by age group interaction only reached significance for time to complete the course. However, the results of the regression analysis revealed that cognitive aging rather than chronologic age was a better predictor of how driving performance was affected by the demands of performing a dual task. The DSS task, which is hypothesized to reflect the speed of information processing and selective attention, was found to be the best predictor of driving performance for both the single and visual dual task. When those with lower scores on the DSS were more compromised by the effects of dual tasking, the worse the DSS performance, the greater the impact of visual demands. The Trail A was found to be the best predictor of performance on the auditory dual task; however, the correlations between DSS and performance on the Trail Making Test A indicate that they may be tapping common cognitive processes that decline with age. An association between Trail A and measures of driving performance has been reported previously.31–33

Closer scrutiny of the data reveals differential effects of the auditory and visual tasks on different aspects of driving performance. The auditory task was associated with worse performance on gap judgments and hazards hit, whereas the visual dual task resulted in more central lane crossings and slower speeds than the auditory dual task. However, when considered as an overall score, which included performance on all of the driving measures and the secondary summing task, the auditory dual task resulted in the greatest decrement in performance. These findings appear to be contrary to predictions derived from the model of multiple resources,22 which predicts greater interference by the visual dual task because it competes for the same visual perceptual codes and working memory subsystems (i.e., visuospatial sketchpad) as the visually demanding driving task. The finding is also surprising because unlike the auditory task, the visual dual task required the drivers to take their eyes off the roadway to view the monitor.

One explanation for the differential effects of the dual tasks is that the auditory condition produced greater interference at a higher cognitive level associated with managing multiple tasks. Task coordination is potentially more difficult in the auditory condition because a delay in attending to the auditory stimuli would result in the subject missing the next pair of numbers. The summing data shows that the percentage of no responses increased significantly in the auditory dual task condition relative to the visual dual task, whereas the increase in incorrect responses was small. Participants may have prioritized the primary driving task over that of the summing task as a result of the difficulty of coordinating performance of the sums with the other tasks. Unlike the auditory task, the visual dual task affords greater flexibility because the sums were continuously available on the dashboard-mounted display (for an average of 3.5 seconds) until the next number pair was presented. The participants could coordinate the multiple task demands, attend to the visual sums task, and report the result when it was convenient.

Recent experimental findings show that loads on working memory, especially loads on cognitive control functions (i.e., executive function), responsible for coordinating behavior diminish the effectiveness of visual selective attention.34–36 This could help explain why participants reported fewer road signs under the dual task conditions and why tasks such as talking on a mobile phone interfere with the attention-capturing properties of stimuli in the driving environment,9,10 response selection,9,10 and the processing of visual information at fixation.10

In summary, the results suggest that the driving performance of both the young and older participants was affected by the presence of a secondary task. Older drivers were significantly worse at detecting peripheral road signs in the single task condition, and cognitive aging was the best predictor of the declines seen in driving performance under dual task conditions. This finding is consistent with reports that elderly drivers are more likely to be found at fault for accidents as a result of failures to respond to traffic signs and lights.3,4 The findings also suggest that there is no particular benefit in presenting information in either an auditory or visual domain, although there was a trend for the visual dual task to have less impact on overall driving performance and performance on the secondary task was also typically better when information was presented visually. The implications of these findings are far reaching in modern society in which the driving and in-vehicle environments are becoming increasingly complex and the elderly comprise the fastest growing segment of the driving population.

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ACKNOWLEDGMENTS

This research was conducted while Dr. Chaparro was on sabbatical leave at Queensland University of Technology. The research was funded by a Queensland University of Technology Research Fellowship, Australian Research Council, and Wichita State University. The authors thank Jocelyn Stewart, Alex Black, and Mathew Roodveldt for assistance in data collection; Kathy Sifrit for comments on the paper and assistance with statistical analyses; and Queensland Transport, Mt. Cotton Driver Training Centre.

Alex Chaparro, PhD

Department of Psychology

Wichita State University

Wichita, KS 67260-0034

e-mail: alex.chaparro@wichita.edu

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Keywords:

aging; driving; visual attention; multitasking

© 2005 American Academy of Optometry

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