The Effects of A Simulated Cellular Phone Conversation on Search For Traffic Signs in an Elderly Sample *Charles T. Scialfa
Lisa McPhee University of Calgary
It has been observed in epidemiological and simulated driving studies, that driving while talking on a cellular telephone effects some aspects of driving behavior, such as; brake reaction time, lane position, gap judgement, and sign acquisition, [1, 3]. Survey measures show that 70% of cellular phone users consider telephone use while driving equally or more distracting than tuning a car radio [15].
Abstract The effects of clutter and a simulated cellular telephone conversation on search for traffic signs were investigated using eye movement and reaction time measures. One-half of an elderly sample searched for traffic signs while simultaneously listening to a story, followed by 15 "yes or no" questions. This simulated cellular phone conversation had detrimental effects on reaction time, fixation number and fixation duration. Performance decrements observed might be an indication of the demands cellular telephones have on a driver's processing resources. In addition, these methods could be used to further investigate the safety implications of using a cellular telephone while driving.
In fact, there is reason to believe that cellular phone use is more distracting than tuning a radio, changing a tape, eating or drinking while driving. First, the duration of a cellular phone conversation is much longer than the duration of these other activities. As well, tuning a radio, rolling down a window or adjusting the temperature in the car are practiced, automatic tasks. A phone conversation, on the other hand, is changing constantly and requires that the driver pay attention to the caller, thus limiting attentional resources. Cellular phone conversations are less controllable than in-vehicle conversations. First, the passenger affords an extra pair of eyes to the driving situation and is aware when driving conditions are busier and more demanding. Second, it may be easier to pace the in-vehicle conversation because the driver is able to indicate non-verbally when it is necessary to allocate attentional resources to driving. This is more difficult to do while using a cell phone.
CR Categories and Subject Descriptors: J.4: [Social and Behavioural Sciences]: Psychology.
Keywords: Cellular Telephone Use, Driving Performance, Conspicuity, Eye Movements, Traffic Signs, Aging.
1. INTRODUCTION Driving is a complex behavior, relying on rapid and accurate allocation of cognitive resources. In 1997, the primary cause of accidents was reported to be inattention and improper lookout [7]. Thus, activities such as talking on a cellular phone, which cause the driver to shift attentional resources, may have deleterious effects on driving behavior. The popularity of cellular telephones is increasing rapidly. The reported growth rate in the United States is approximately 40 percent per year. It was estimated recently that there are about 80 million cellular telephone users in the United States [12]. Eightyfive percent of cellular telephone owners use their phones occasionally while driving, and more than 27 percent use their phones during half or more of their trips [12]. This trend shows growth in the elderly population sector as well. Combined with the increased number of elderly drivers on the road, concerns about the effects of cellular telephone use on attentional processes while driving are warranted. In this experiment, we looked at the effects of a simulated cellular phone conversation on search for traffic signs in an elderly sample. *
Geoffrey Ho
In general, older people demonstrate deficits in visual, attentive, and cognitive tasks. There is evidence of an age-related reduction in the useful field o f view when the number o f distracters is increased, when target and distracters share similar features [20], and when there is a secondary central task [2]. Several studies demonstrate that older adults show visual search deficits [13, 16, 17, 19, 26]. Not surprisingly, older adults are five times more likely than younger people to report problems in activities involving visual search, peripheral vision and cluttered visual scenes [9]. Elderly adults also perform less proficiently than young adults under conditions of divided attention [4, 11, 14, 21]. Thus, it would not be surprising to find that older people have difficulty searching for traffic signs when engaged in a cell phone conversation. Previous experiments have shown that increases in visual clutter can increase response times significantly in the elderly [20, 8]. If cellular telephones have a deleterious effect on driving it is likely to be manifested in more challenging driving environments, such as those with more visual clutter. Under conditions of divided attention, such as talking on a cellular telephone, we would expect older participants to show greater impairments under high clutter than low clutter conditions.
Dept. of Psychology, Calgary, AB, Canada, T2N IN4
[email protected]
In this study we asked a group of older people to search for a variety of warning and regulatory signs in digitized images of daytime traffic scenes. They performed this search task while listening to and answering questions about brief prose passages. We expected that both search and memory performance would suffer in the simulated cell phone condition and that this effect would be more pronounced when scenes contained greater visual clutter.
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conspicuity task before the LM-II test. In this case, we continued asking questions and recorded when participants had finished the sign conspicuity task. Finally, the NASA-TLX rating scale was used to measure subjective workload.
2. METHOD 2.1 Participants Traffic scenes were randomly presented to 21 older participants (61-83 years of age). Participants were volunteers from the surrounding community and were paid $5 (CDN) for their participation. In addition, they were given up to $3 for accurate performance on the memory task to be described below. All participants had or exceeded 20/25 visual acuity and were normal for their age with respect to contrast sensitivity and intraocular pressure. They were active drivers and on average drove approximately 16000 kilometers per year. By self-report they were assessed to be in good health and were not taking any medications that would affect their performance.
2.3 Apparatus All participants were fitted with a set of Burton Trial Lenses with their own visual correction. If no correction was needed, neutral lenses were used. Visual acuity was tested using a Landolt C Visual Acuity Chart, contrast sensitivity was tested using the Vistech Contrast Sensitivity Chart and intraocular pressure was tested using a Reichart NCT2 non-contact tonometer. Photographs were taken in a 1991 Pontiac Tempest, using a Minolta SRT 202 and Kodak Ektachrome Elite 200 film. Light readings were taken with a Minolta LS 100 photometer. Slides were digitized using a power Macintosh 7100/80 computer and a Nikon 35 mm Film Scanner LS-100. Adobe PhotoShop 4.0 was used to manipulate the digitized pictures. The digitized pictures were saved in CD-ROM format using a Kodak PhotoCD writer. Images were presented on a Sony Trinitron Multiscan CPD-100 GS 14" monitor connected to a 486 platform. Monitor resolution was set at 640 X 480 pixels and the refresh rate was 60Hz.
2.2 Stimuli The signs used for the fixation screens (i.e., to define the trial target) were either created using a graphics program or downloaded from the Internet. Those that were downloaded from the Internet were converted to PCX format and resized so that all target signs had a mean length and width of 2 deg and 1.9 deg, respectively. Average sign luminance was 57.73 cdgm2. Positioning of the signs used as fixation stimuli corresponded to the center of the roadway in the subsequent image; that is, they were placed centrally along the horizontal axis of the screen, and approximately 3.81 deg below the horizontal meridian on the vertical axis. Traffic scenes were photographed in urban and residential areas of Calgary, Alberta, Canada. All photos were taken between 8:00 a.m. and 2:00 p.m. under sunny conditions from the driver's seat, 1.16 m above the road. All exposures were taken at a fixed distance of 18.3 m from the target traffic sign. The traffic scenes included regulatory signs (e.g., a stop sign), and warning signs (e.g., a yield sign). Low clutter scenes often contained only the target sign, with no more than one other sign in view. High clutter scenes had several objects, including other signs and vehicles in proximity to the sign in both the horizontal and vertical planes. These scenes were reliably classified as containing either high or low clutter by young observers in a previous experiment [8]. There were 13 low clutter and 8 high clutter scenes. Figure 1 provides examples of low and high clutter images. To simulate a cellular phone conversation, we used the Wechsler Memory Scale - Third Edition, Logical Memory 1I (LM-II) test. It consists of two short prose passages, which had been tape recorded to minimize variability in pacing and inflection. A recognition test, which consists of 15 "yes-or-no" questions, followed each passage. This test was chosen because cellular phone conversations can be paced by the participant idiosyncratically and thus are not under experimental control. As well, previous research suggests cellular phones are most frequently used to make business calls while commuting to or from work [7]. The factual content of this type of conversation, for example names, meeting places, phone numbers and appointment times, is similar to the details participants are required to remember when answering questions on the LM-II. There is also more context to facilitate encoding and retrieval in the prose passage compared with other tests, such as the Working Memory Span Test, that have been used previously to simulate cellular phone conversations [1]. The duration of this test generally corresponded to the duration of the sign conspicuity task, thus the participant was always attending to both tasks. When there was a mismatch in duration it occurred because the participant finished the sign
Eye movements were recorded using the Eyegaze Development System (EDS) and software from LC Technologies, Inc. Low-level, infrared light (880 nm) was directed to the participant's eye and its reflection measured with a Sanyo, infrared-sensitive camera, using a monocular, pupil center-corneal reflection technique to track the eye at 30.3 Hz. A fixation was recorded if there were two consecutive samples that were within a spatial window of 11 pixels, which is approximately 0.50 deg. A velocity-based algorithm was not used to determine saccades (or fixations) because of the low temporal resolution of the EDS. For more details on the Eyegaze Development System see Scialfa, et al. [19]. A Sony TCM-737 Cassette Corder was used to record and playback the prose passages on a TDK SA-X 100 cassette.
2.4 Procedure Prior to the sign conspicuity test, participants were screened for visual health, i.e. visual acuity, contrast sensitivity and intraocular pressure. To measure visual acuity, and contrast sensitivity, participants rested their head on chin rest 45 cm from the respective charts for each test. Intraocular pressure was then measured. Participants were randomly assigned to two groups. In the control condition, participants completed the LM-II after completing the sign conspicuity and NASA-TLX tasks. In the cellular phone condition, participants listened to and verbally responded to the LM-II while performing the sign conspicuity task. Participants were rewarded ten cents for each correct response, which provided additional motivation to attend to the memory test while simultaneously attending to the sign conspicuity task. Participants rested their head on a chin rest to fix the test distance at 50 cm. In the sign conspicuity task, the first screen that appeared was a fixation screen that consisted of a traffic sign, indicating the target traffic sign they had to search for in the subsequent image. Once participants were ready to begin the experiment proper, they pressed any key and the fixation screen appeared. The fixation screen remained until participants were ready to view the traffic scene. Once they were ready, they pressed any key and after a variable foreperiod of 0, 50, or 150
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msec, the traffic scene image appeared. The traffic scene remained on the screen until the participant responded or until 5 s had expired. On one-half of the trials, the traffic scene contained the sign presented in the fixation screen, on the other one-half it did not. The participant's task was to respond "present" or "absent" by pressing predetermined keys as quickly as possible. After each response, the participants were given accuracy feedback. A "plus" sign indicated they were correct, and a "minus" sign indicated they were incorrect. Participants were initially guided through 10 practice trials that contained both target present and target absent scenes that were not used in the experiment proper. To ensure that all participants understood the task, an accuracy of 90% had to be obtained on the practice trials before continuing to the actual testing. If the participant failed to obtain 90% accuracy, the instructions were repeated, and the practice trials were presented again. There was one block of 25 trials preceded by calibration of the Eyegaze Development System. Clutter and target presence was randomly ordered for each participant. On average the procedure did not exceed one hour.
3. RESULTS A trial was omitted if the participant responded incorrectly to the visual search task, i f a saccade exceeded the screen boundaries, or if the participant was not properly fixating on the screen prior to the onset of the fixation screen. Data from 5 people in the cell phone group were omitted because head movements prevented the recording of eye position. Data from2 people in the control condion were omitted because we were not able to obtain a good corneal reflection from them. Four dependent measures were analyzed; reaction time (RT), fixation number, average fixation duration and first fixation duration. For each dependent measure, the effects of clutter, target presence and cellular phone conversation were evaluated. As can be seen in Figure 2, RTs, and fixation frequencies are greater on target absent than target present trials. The reverse trend is observed for average and last fixation duration.
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Figure 2. Performance as a function of clutter and target presence. The dependent measures are (from top to bottom); fixation number, RT, average fixation duration and last fixation duration. More fixations, that is more eye movements, were executed on high clutter trials and RTs were longer for the more cluttered scenes. In contrast, both average and last fixation durations were longer on target present trials and tended to be longer for low clutter scenes. These last two results are consistent with the recent reports that observers trade overt and covert search demands in many search tasks [17, 18].
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Although not shown, those in the cell phone condition made more errors (39% vs 28%), more eye movements (4.95 vs. 4.7), and responded more slowly (1728 ms vs 1548 ms) than controls. However, the simulated cell phone conversation did not produce a uniformly detrimental effect, because those in the cell phone condition often did not show as large a clutter effect as did controls.
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Much of the data from participants in the cell phone condition were lost due to increased head movements executed when they were answering questions for the LM-II. The reduced data set made comparisons between cell phone group and control group difficult and the results were not systematic for eye movement data. To overcome this problem, data were analyzed omitting the eye movements and accepting all trials ending in a correct response. This allowed us to keep data from a larger number of trials and participants.
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The RT data are presented in Figure 3, where it is apparent that participants in the cellular phone group show detrimental effects. They also made more errors (13% vs !1%). Consistent with the view that the simulated cell phone task placed greater processing demands on observers, those in the cell phone condition remembered less of the stories they were read (58% vs 80%), and reported that the task was subjectively more demanding (5.94 vs 5.17 on the Mental Demand Scale of the TLX). Despite these trends, an ANOVA did not find a significant difference in the RTs of those in the cell phone vs. control conditions.
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Figure 3. RT as a function of clutter, presence and condition (cell phone vs. control).
4. DISCUSSION At a general level, our results are consistent with past research indicating that it is more difficult to process scenes containing larger amounts of visual clutter. Eye movements are more frequent and, as a result, RTs are longer when scenes are filled
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Location, And Display Type. Proceedings of the Human Factors and Ergonomics Society 41 st Annual Meeting (pp. 1108 -1012). Santa Monica, CA: HFES, 1997.
with non-target information. Fixation durations tend to be inversely related to clutter, but this is easily explained because high clutter scenes are associated with a larger number of eye movements, and fixation durations tend to be short on trials associated with large numbers of eye movements.
[5]
The effects of the simulated cell phone task were not as systematic as we had expected. Still, there were several indicators that it was more difficult to carry on the cell phone and sign search tasks simultaneously. Those in the cell phone condition were slower and less accurate in responding and showed a tendency to look away from the driving scene when engaged in the simulated cell phone conversation. If these trends generalize to the driving world, they indicate that cell phone use has clear implications for safety.
Chun, M.H., and J.M. Wolfe. Just Say No: How Are Visual Searches Terminated When There Is No Target Present? Cognitive Psychology, 30 : 39-78, 1996.
[6] Freeman, M. J., and D. I. Miller. Effects Of Locus Of Control And Pacing On Performance Of And Satisfaction With A Simulated Inspection Task. Perceptual and Motor Skills, 69 (3) : 779-785, 1989. [7] Goodman, M.J., F. D. Bents, L. Tijerni, and W. W. Wierwille. Using Cellular Telephones In Vehicles: Safe Or Unsafe? Transportation Human Factors, I (1) : 3-42, 1997.
Our results were based on a small sample size. Compounding this problem was the omission of several trials due to head movements made while participants verbally responded to the prose passages. In future studies, using a within-subjects experimental design, increasing the sample size, and using a chin and head rest to isolate head movements would reduce the amount of variability, increase the number of accepted trials, and thus enhance the sensitivity of the tests conducted.
[8] Ho, G., Caird, J.K., T. Graw, and C. T. Scialfa. Visual Search For Traffic Signs: The Effects Of Clutter Luminance And Aging. Human Factors, under review. [9] Kosnik, W., D. Kline, and L. Winslow. Visual Changes In Daily Life Throughout Adulthood. Journal of Gerontology, 43:63-70, 1998. [10] MacFarling, L. H., and N.H. Heimstra. Pacing, Product Complexity, And Task Perception In Simulated Inspection. Human Factors, 7 : 361-367, 1975.
In this experiment, it was observed that several people hesitated in initiating trials while simultaneously engaged in the visual search task and simulated cellular phone conversation, indicating that participants were pacing their responses. It is likely that self-pacing is lessened in cellular phone conversations because visual cues can not be used to control timing. For example, a passenger can see when the traffic situation demands the driver's full attention and can pace the conversation accordingly, whereas the caller on the cellular telephone has no such information to guide their behavior. It is possible, then, that external pacing may be more typical o f a cellular phone conversation. An experimentally-paced condition could be used to investigate if performance deteriorates as the temporal demands are increased and the possibility of self-pacing is eliminated.
[11] McKnight, A. J., and A. S. McKnight. The Effects Of Cellular Phone Use Upon Driver Attention. Accident Analysis and Prevention, 25 (3) :259-265, 1993. [12] National Highway Traffic Safety Administration. An Investigation Of The Safety Implications Of Wireless Communications In Vehicles. U.S. Department of Transportation, November, 1997. [13] Plude, D. J., and J. A. Doussard-Roosevelt. Aging, Selective Attention, And Feature Integration. Psychology andAging, 4 : 98-115, 1989.
Studies on the effects of pacing on performance of a simulated inspection task have shown that self-pacing increases the detection of defects [6, 10]. As well, there is evidence that on the Stroop task, external pacing had deleterious effects on accuracy. There is strong evidence that older people are especially penalized when the task is externally paced, or when responses must be made within a brief time limit [25, 26]. It seems reasonable to predict that both young and old adults will be negatively affected by pacing and the older participants will show the greatest decrement in performance.
[14] Ponds, R. W., H. M. Brouwer, and P. C. van Wolffelaar. Age Differences In Divided Attention In A Simulated Driving Task. Journal of Gerontology: Psychological Sciences, 43 : 151-156, 1988. [15] Prevention Magazine. Auto Safety in America 1995: A Prevention Magazine report by Princeton Survey Research Associates. Emmaus, PA: Rodale 1995. [16] Scialfa, C. T., E. Hamaluk, L. Jenkins, and P. Skaloud. Aging And The Development Of Automaticity In Conjunction Search. Journal of Gerontology: Psychological Sciences, 55B (1) : 27-46, 2000.
5. REFERENCES
[17] Scialfa, C. T., and K. M. Joffe. Age Differences In Feature And Conjunction Search: Implications For Theories Of Visual Search And Generalized Slowing. Aging, Neuropsychology, and Cognition, 4 : 227-246, 1997.
[1] Aim, H., and L. Nilsson. The Effects Of A Mobile Telephone Task On Driver Behavior In A Car Following Situation. Accident Analysis and Prevention, 27 (5) : 707715, 1995.
[18] Scialfa, C. T., and K. M Joffe. Response Times And Eye Movements In Feature And Conjunction Search As A Function Of Target Eccentricity. Perception and Psychophysics, 60 : 1067-1082, 1998.
[2] Ball, K., B. L. Beard, D. S. Griggs, R. L. Miller, and D. L. Roenker. Age And Visual Search: Expanding The Useful Field Of View. Journal of The Optical Society of America, 5 (12) : 2210-2219, 1988.
[19] Scialfa, C. T., K. M Joffe, and D. M. Thomas. Age-Related Changes In The Eye Movements Subserving Feature Search. Optometry and Vision Science, 71 : 736-742, 1994.
[3] Brookhuis, K.A., G. De Vries, and D. De Waard. The Effects Of Mobile Telephoning On Driving Performance. Accident Analysis and Prevention, 23 : 309-316, 1991.
[20] Scialfa, C. T., D. W. Kline, and B. J. Lyman. Age Differences In Target Identification As A Function Of Retinal Location And Noise Level: Examination Of The
[4] Caird, J. K. and J. Chugh. The Time Cost Of Head-Up Displays For Older Drivers: Critical Event Onset, Task
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Useful Field Of View. Psychology andAging, 2 : 14-19, 1987. [21] Seialfa, C. T., and D. M. Thomas. Age Differences In SameDifferent Judgements As A Function Of Multidimensional Similarity. Journal of Gerontology: PsychologicalSciences, 49 : 173-178, 1994. [22] Shoptaugh, C. F. and L. A. Whitaker. Verbal Response Times To Directional Traffic Signs Embedded In Photographic Street Scenes. Human Factors, 26 : 235-244, 1984. [23] Tun, P. and A. Wingfield. Speech Recall Under Heavy Load Conditions: Age, Predictability, And Limits On Dual-Task Interference. Aging Neuropsychology and Cognition, 1 : 2944, 1994. [24] Violanti, J.M., and J. R. Marshall. Cellular Phones And Traffic Accidents: An Epidemiological Approach. Accident Analysis and Prevention, 28 (2) : 265-270, 1996. [25] Welford, A. T. Aging and Human Skill. Oxford: Oxfod University Press, 1958. [26] Welford, A. T. Motor performance. In J. E. Birren and K.W. Schaie (Eds.), Handbook Of The Psychology Of Aging (lst ed.). New York: Van Nostrand Reinhold, 1977. [27] Yee, D. A Survey Of The Traffic Safety Needs And Problems Of Drivers Age 55 And Over. In J. L. Malfetti (Ed.) Drivers 55+: Needs And Problems Of Older Drivers: Survey Results And Recommendations, pages 96-128. Falls Church, VA: AAA Foundation for Traffic Safety, 1985. [28] Zacks, J.L. and R.T. Zaeks. Visual Search Times Assessed Without Reaction Times: A New Method And An Application To Aging. Journal of Experimental Psychology." Human Perception and Performance, 19 : 798-813, 1993.
This research was supported by a grant from the Natural Science and Engineering Research Council of Canada.
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