Table 2 indicates also where the tints were outside the specified limits for AS/NZS 1067:2003, EN 1836:2005, and ANSI Z80.3:2008. The green tint failed each standard on one or more criteria, the yellow-green tint failed the AS/NZS 1067:2003 and ANSI Z80.3:2008 standards, and the yellow-brown and red-brown lenses passed all three standards.
Observer and experimental information have been reported in detail previously.1 Observers were 69 young, healthy (16–35 years) males, consisting of 20 color normals, 15 deuteranomals, 10 deuteranopes, 15 protanomals, and 9 protanopes. Selection criteria are given in Table 3. All observers had binocular visual acuity of 6/6 or better, with 11 observers wearing their (untinted) ophthalmic corrections behind the sunglass tints to achieve this visual acuity.
Observers viewed a fixation target in the center of a computer monitor at a 4 m working distance (Fig. 2). Simulated single aspect traffic signals were displayed for a maximum of 5 s at 5° either side of fixation and observers were instructed to identify the color as quickly as possible.
Signal size was equivalent to that of 200 mm traffic signal lantern at 100 m distance (2 mrad), which is the standard Australian practice.22,23 Signals were created with 20 W 12 V tungsten halogen globes and filters to provide the appropriate traffic signal chromaticity coordinates. Intensity was controlled using neutral density filters. The chromaticity coordinates of the signals, from spectral radiance measurements made with a Topcon SR-3 telespectroradiometer, are represented in Fig. 3(a to c) by open circles. Also shown are the color requirements of the signals. The international standard on traffic signals24 references the IS0/CIE S 004 standard on colors of signal lights.25 The red signals lie within the class A1 limits which are specified “when persons with defective color vision are included in the user group.” The yellow signals lie within the permitted limits for yellow (there are no classes) and the green signals lie within the class A requirements which are for the same application as class A1 red. In other words, the colors were, in the context of CIE S 004, optimized for use by people with defective color vision. The chromaticity coordinates of the signals viewed through the tinted lenses were calculated using the CIE 2° standard observed and are represented by the other symbols in Fig. 3 (a to c).
We presented signals of low intensity—0.32 cd for red and green and 0.96 cd for yellow and high intensity—0.64 cd for red and green and 1.92 cd for yellow which are the 4 m equivalent of the 200 mm traffic signal at 100 m complying with the maximum and minimum AS/NZS 2144 requirements.23 The signals were surrounded by black backboards in scale with the backgrounds around normal traffic lights.22,23 Around the computer monitor and the black backboards was a white matt board illuminated by two fluorescent light tubes to provide 300 cd/m2 luminance.
The experiment was divided into three sections—button reaction time, practice, and the experiment proper. The reaction times for the first section were used to adjust response times for data analysis. The first two sections are described in our previous article. In the experiment proper, we simulated driving using a divided attention task. The fixation target was a 1.5 cm diameter circle which moved in straight lines at random speed and direction on the computer monitor. The observers were asked to place the fixation target inside a 1.5 × 2 cm rectangle by moving the computer mouse. They received feedback by the circle changing into a cross when they were successful. At random intervals of between 6 and 12 s, either the left or the right light was turned on. The observer abandoned the tracking task, identified the color as quickly as possible and indicated this by pressing one of three buttons on the computer mouse: left button for red, middle button for yellow, and right button for green. Failure to respond within 3 s was regarded as a detection failure. After the response (or after 5 s if no response) the next sequence began.
The observers informed the experimenter immediately if they had made a mistake in responding to a light. This was later correlated with the computer's record of responses and these “mistakes” were not used in analysis (mean ± SD = 2% ± 1%). Observers were not given feedback about which lights were correctly or incorrectly identified.
Target presentation and response recording were under computer control. Each run consisted of 12 presentations, with 1 presentation on each side of low and high luminance red, yellow, and green lights. These presentations were randomized within each run. There were four runs per signal color, so each color was presented 16 times for each sunglass tint. At the completion of a set of runs, the next sunglass was selected. The order of sunglass wear was randomized between observers, using an incomplete Latin square design.
Repeated measures analysis of variance were conducted for both response time and response accuracy with two within group factors [lens tint (six levels) and signal color (three levels)] and one between subjects group factor (normals, deuteranomals, deuteranopes, protanomals, and protanopes). In the previous article,1 we used the term “mean adjusted response time” to allow for the button reaction time, but here we simply use the term “response time.” Sphericity assumptions for some of the analyses were violated. Analyses are therefore reported as significant only if they were also significant with adjustment for sphericity via the Greenhouse-Geisser epsilon. Given the large number of conditions in the experiment, it was not considered valid to conduct all possible follow-up comparisons, so visual inspection was used as the basis for the interpretation of any significant interactions.
There were significant main effects of signal color (F2,128 = 83.72; p < 0.001) and lens tint (F5,320 = 33.35; p < 0.001) on response times and the group effect was also significant (F4,64 = 14.18; p < 0.001), where the deuteranopes had significantly longer response times than all the other groups except for the protanopes. Fig. 4 shows response times for the different color vision groups, collapsed across all signals, for each sunglass tint. It clearly shows that the response times for all color deficient groups were longer than those of the color normals for the clear and gray lenses. There were also significant two-way interactions between signal color and group (F8,128 = 8.15; p < 0.001), lens color and group (F20,320 = 3.66; p < 0.001), as well as a three-way interaction between signal color, lens color and group (F40,640 = 2.96; p < 0.001). As seen in Fig. 4, the green and yellow-green lenses exacerbated the increase in response times for all of the color deficient groups relative to the color normal group.
Given the significant three-way interaction, the data were broken down and analyzed for each of the five participant groups. Results for the normal group are shown in Fig. 5a. There was a significant main effect of signal color (F2,38 = 6.67; p = 0.003) but not lens tint (F5,15 = 0.15; p = 0.98) on response times. There was also a significant interaction effect between signal color and lens tint (F10,190 = 5.97; p = 0.045), where response times were increased when viewing the Y signal through the yellow-green lens relative to the other lens tints, and responses times were decreased when viewing the R signal through the yellow-green lens.
Results for the deuteranomals are shown in Fig. 5b. The response times were significantly affected by signal color (F2,28 = 12.0; p < 0.001) and lens tint (F5,70 = 10.08; p < 0 0.001), and there was also a significant interaction between signal color and lens tint (F10,140 = 11.61; p < 0 0.001). Examining the two-way interaction (Fig. 5b) it is evident that response times were slower to the G signal when viewed through the green lens and to the Y signal when viewed through the yellow-green lens compared with the other lens tints.
Results for the deuteranopes are shown in Fig. 5c. The response times were significantly affected by signal color (F2,18 = 21.55; p < 0.001) and lens tint (F5,45 = 3.65; p = 0.007). The observers responded slower to the R signal, across all lenses, than to either Y or G signals, and they responded slower to the Y than to the G signal. The differences were considerable at 59% (R vs. G) and 47% (Y vs. G). There was also a significant two-way interaction between signal color and sunglass lens tint (F10,90 = 3.01, p = 0.003), where response times to the G signal were longer when viewed through the green and yellow-green lenses compared with the other sunglass lens tints (Fig. 5c).
Results for the protanomals are shown in Fig. 5d. The response times were significantly affected by signal color (F2,28 = 28.89; p < 0 0.001) and lens tint (F5,70 = 9.33; p < 0 0.001), and there was also a significant interaction between signal color and lens tint (F10,140 = 7.12; p < 0 0.001). The significant interaction effect reflects the increase in response times to the G signal viewed through the green lens and to the R signal viewed through the red-brown lens.
Results for the protanopes are shown in Fig. 5e. The response times were significantly affected by signal color (F2,16 = 25.95; p < 0.001) and lens tint (F5,40 = 11.32; p < 0.001) and there was also a significant two-way interaction (F10,80 = 7.0; p < 0.001). This interaction effect reflects the increase in response times to the G and Y signals for the green and yellow-green lenses; interestingly, the effects of signal color were greatest for the red-brown lens, where responses were clearly slower to the R and Y signals compared with the G signal.
From considering Fig. 5a to e, it is clear that the response times of the color normals were less affected by either signal color or sunglass tint than were the color deficient groups. Response times for the color deficient groups were considerably slower than the color normals for both R and Y signals at all sunglass colors, but for the G signals they were only noticeably slower with the green and yellow-green lenses.
There were significant main effects of signal color (F2,128 = 42.41; p < 0.001), and sunglass tint (F5,320 = 9.58; p < 0.001) on error rates. The group effect was also significant (F4,64 = 37.33; p < 0.001), with the deuteranopes making significantly more errors than any other group, as shown in Fig. 6, which represents error rate as a function of sunglass tint and group collapsed across all signal colors. There were also significant two-way interactions between signal color and group (F8,128 = 12.99; p < 0.001), between lens color and group (F20,320 = 1.88; p = 0.013) and a three-way interaction between signal color, lens color, and group (F40,640 = 2.77; p < 0.001). Given the three-way significant interaction effect, the data were broken down and analyzed for each of the five participant groups.
Results for the normal group are shown in Fig. 7a. There were no significant effects of signal color (F2,38 = 2.38; p = 0.106) or sunglass lens tint (F5,95 = 2.14; p = 0.068) on error rates, but there was a significant two-way interaction effect (F10,190 = 4.29; p < 0.001). Only the Y signal viewed through the yellow-green lens produced higher error rates relative to the other conditions.
Results for the deuteranomals are shown in Fig. 7b. The error rates were significantly affected by signal color (F2,28 = 8.31; p = 0.001) and by lens tint (F5,70 = 5.29; p < 0.001), and there was also a significant interaction between signal color and lens tint (F10,140 = 7.18; p < 0.001). The interaction effect reflects the stronger detrimental effect of the yellow-green lens for Y signals, such that the yellow-green lens resulted in an error rate of 18%, 3.5× higher than that with the gray lens.
Results for the deuteranopes are shown in Fig. 7c. The error rates were significantly affected by signal color (F2,18 = 16.02; p < 0.001) but not lens tint (F5,45 = 1.19; p = 0.331). There was also a significant two-way interaction between the factors (F10,90 = 4.05, p < 0.001) representing a complex series of effects. The error rates for R and Y signals were 21× higher overall than that for G signals, but the pattern of error rates was quite different, with the error rates for R signals exacerbated for the yellow-brown and red-brown lenses and with the error rates for Y signals exacerbated for the green and yellow-green lenses.
Results for the protanomals are shown in Fig. 7d. The error rates were not significantly affected by either signal color (F2,28 = 2.17; p = 0.133) or lens tint (F5,70 = 2.07 p = 0.79), nor was there a significant interaction between signal color and lens tint (F10,140 = 2.403; p = 0.103).
Results for the protanopes are shown in Fig. 7e. Error rates were significantly affected by signal color (F2,16 = 4.47; p = 0.03) and lens tint (F5,40 = 3.83; p = 0.006). There was also a significant two-way interaction effect (F10,80 = 4.09, p < 0.001), such that error rates were elevated for the Y signal when viewed through the yellow-green lenses.
From considering Fig. 7a to e, it is apparent that for most of the color deficient groups there were particular problems for Y signals combined with the green and yellow-green lenses. In addition to this, deuteranopes had particular problems for R signals combined with the yellow-brown and red-brown lenses. Although the patterns were somewhat different from those seen for response times, in general combinations of signals and sunglasses of similar colors were of particular concern.
For the clear lens component of our study, we found that the individuals with a color deficiency had longer response times and made more recognition errors than color normals in response to signals simulating traffic signals.1 Deutans performed noticeably worse than protans.
In the current article, we considered the effect of different sunglass tints on response times and errors and found that the poorer performance of those with a color deficiency was exacerbated by non-neutral sunglass tints, with combinations of signals and sunglasses of similar colors being of particular concern. Two of these tints (yellow-brown and red-brown) passed the current European, U.S., and Australian standards, whereas the yellow-green tint failed the Australian standard and the U.S. standard (marginally for the latter), and only the green tint unequivocally failed all three standards (Table 2).
Anything that limits their ability to design products is generally disliked by the sunglass industry and the restriction placed on them by the color limits of sunglass standards is no exception. It is often pointed out that most analyses, especially those in the detailed articles of Clark, are theoretical. However, given the immense variability of on-road conditions and the range of color vision deficiencies that exist, it is unlikely that adequate on-road studies will ever be funded and the data collected in accident cases have never included documentation of any tinted media worn by the driver(s) involved. So “real-life” studies are not a viable option in exploring the important question of whether sunglass tints compromise the road safety of color deficient individuals; reasonable representations in the laboratory are the only feasible option.
What has been carried out in the current study is an evaluation of tints that are representative of those that are permitted or used in everyday life. The study used contemporary traffic signal design standards in the design of the stimuli and a task that represented the dual task components of driving performance. Therefore the on-road situation was replicated, as best as is possible, in the laboratory.
The study has shown that some sunglass tints, currently permitted for wear by drivers and riders, cause a measurable decrement in the ability of color deficient observers to detect and recognize traffic signals. This is prima facie evidence of a risk in the use of these lenses. What this study has not addressed is how that risk might translate into road accidents nor what might be an acceptable risk (because driving is already a risky business), nor how the magnitude of that risk might be considered relative to other avoidable or controllable factors. However, the study has illustrated that the issues that authors such as Clark have raised over many years are real.
This study was supported by a Queensland University of Technology Research Encouragement Award. Eddie Matejowsky wrote the computer program and built the electronic circuitry for the experiment, Carol Pedersen assisted with experiments, and Nancy Spencer and Phillipe Lacherez provided statistical advice. Barry Cole provided comments on a draft.
Institute of Health and Biomedical Innovation
Queensland University of Technology
60 Musk Avenue
Kelvin Grove Q 4059, Australia
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Keywords:© 2009 American Academy of Optometry
color vision deficiency; driving; sunglasses; sunglass standards; traffic signals