Department of Aeronauatics & Astronautics MIT Cambridge, MA rjhans@mit.edu

Transcription

1 Experimental Studies of Driver Cognitive Distraction Caused by Cell Margarita Marinova, Jaime Devereaux, R. John Hansman Prepared for: Transportation Research Part F Corresponding Author: Professor R. John Hansman Department of Aeronauatics & Astronautics MIT Cambridge, MA rjhans@mit.edu Abstract This study assessed the effect of cell phone conversations on driver reaction time and situation awareness at different levels of cognitive with hands-free and hand-held cell phone configurations. The experiment was conducted in a medium fidelity, fixed based automotive simulator and cognitive loading was varied by engaging the driver in conversations at 3 levels of perceived difficulty (informal conversation, recall and discussion of a movie plot, editing and correcting grammar in a document being read to the driver). Three age groups were tested: young (18-25 years), intermediate (38-48 years), and older (60+ years). Situation awareness was measured by the correct recollection of the last roadway sign passed. Reaction time was measured relative to a sudden stop sign or pedestrian stimulus programmed into the driving scenario. For situation awareness, significant differences were found between normal driving and cell phone use for all age groups however no generally significant effects of cognitive loading level were observed. Unexpectedly, no significant differences in reaction time were observed between normal driving and driving with cell phone use and no general improvement in reaction time was observed for hands-free cell phone

2 and hand-held cell phnon use. In both situation awareness and reaction time metrics the intermediate age group performed the best with the young subjects performing at somewhat lower levels, and the older subjects performing at significantly lower levels. Author Keywords: Cell phone; Driving; Safety; Distraction; Situation awareness; Reaction time; Age; Cognitive loading; Hands-free; Hand-held. 1. Introduction There is continuing debate over the effect of cell phone usage on driving safety. A number of studies suggest that drivers using cell phones drive more dangerously compared to those who do not converse on a cell phone while driving. In 1995, the National Highway Traffic Safety Administration found that distraction was a major cause in up to 26 percent of the crashes studied and that use of cellular phones did increase the chance of a crash (Ranney, Mazzae, and Goodman, 2000). The New England Journal of Medicine reported that drivers who use cellular phones while driving are up to four times as likely to get into an accident as those who do not use a phone (Redelmeier and Tibshirani, 1997). The exponentially increasing number of portable phones makes cell phone caused accidents a growing concern. The Center for Urban Transportation Research (CUTR) reported that the number of cell phones used in motor vehicles increased from 500,000 to more than 63 million between 1985 and 1999 (Buris and Cain, 1999). Spurred by these concerns, many national and state governments have passed, or are considering, laws which prohibit or restrict cell phone usage. The potential for driver distraction from cell phone use can be categorized into 4 2

3 separate concerns including: Manual Distraction - Inability or delay in operating vehicle controls due to hands being occupied or out of position due to cell phone use Visual Distraction Inability or delay in visually perceiving the driving environment due to head down operations most commonly associated with initiating or receiving cell phone calls Cognitive Distraction Lack of cognitive engagement in the primary driving task due to cognitive engagement in the cell phone conversation which could result in lack of perception or delay due to latency in mental context shifting. Emotional Distraction Inability, delay or inappropriate response in operating the vehicle due to emotional factors initiated by the cell phone conversation. The most common restriction on cell phone use while driving is to limit operation to hands-free cell phones. While this addresses the concern regarding Manual Distraction, it does not address the other potential distraction components. Cognitive Distraction is a particular area of concern but is difficult to study and limited quantitative data is available identify the significance and mechanisms of Cognitive Distraction to the driving task. A study conducted at Miami University looked at the effect of various levels of cognitive loading on braking response to a simple red light stimulus (Irwin, Fitzgerald, and Berg, 2000). Test subjects engaged in a conversation using a hands free device were 24% slower then when not talking. However, changing the difficulty of the conversation appeared to have an insignificant impact on reaction time. In this study the cognitive loading was imposed by listening to a 3

4 weather forecast, answering simple questions, answering complex questions, and talking about topics that may induce an emotional response. Other studies have shown little difference between the use of hand held and hands free phones (Strayer, Drews, Albert, and Johnston, 2002; Redelmeier and Tibshirani, 1997For example, in a University of Utah study, there was no significant increase in reaction time to a tracking task between the hands-free and hand-held devices however there was a significant increase in reaction time with both devices compared to the no cellular phone cased. They also reported that drivers were twice as likely to miss a traffic signal when they were deeply involved in a cell phone conversation (McCarley, Vais, Pringle, Kramer, Irwin, & Strayer, 2002). The primary objective of this study was to assess if driving ability decreases with an increase in cognitive distraction caused by cell phone conversations, and consequently to recommend approaches to counteract the cognitive distraction. An automobile simulator was used to determine the effect of different levels of conversation difficulty on situation awareness and reaction time. Both hands free and hand held phone set-ups were used. A secondary objective was to examine possible differences between the effect of cognitive distraction on three age groups: young (18-25), intermediate (38-48), and older (60+). 2. Technical Approach 2.1 Test Design The experiment was conducted in the fixed based part task automobile simulator shown in Figure 1. The simulator was a modified 2001 Volkswagen with automatic transmission and an 8 ft by 6 ft projected forward view of a simulated 4

5 day environment. The subjects were asked to drive at a target speed of 50 mph (73 ft/s), to brake for stop signs and pedestrians. In addition the subjects were asked to participate in cell phone conversations but were instructed to consider driving as the primary task. In the driving scenarios an the roadway signs were shown at semi-periodic intervals and used as a Situation Awareness probe. Figure 1. The MIT Age Lab car simulator used in this study. The independent variables were the presence and type of cell phone device (none, hand-held, hands-free) as well as the level of cognitive difficulty in the cell phone conversation. Each subject experienced 3 levels of cognitive loading (low, medium, high) for the hand-held and hands-free cell phone configurations. The order of presentation cell phone configuration and cognitive loading was varied and counterbalanced to avoid learning effects. In addition, age effects were 5

6 studied across subjects which three age groups (young (18-25), intermediate (38-48), and older (60+)). The primary dependant variables were the situation awareness probe (i.e. the ability to correctly recall the last roadway sign) and the reaction time to breaking stimulus (either a stop sign or pedestrian stepping onto the roadway). Because of variability in speed management and deceleration profiles between subjects it was also found to be useful to monitor the difference between the final stopping point and the stopping stimulus (i.e. did the driver successfully stop before the stop sign or pedestrian). In addition subjective results were generated by surveying the subjects after each series of test runs. 2.2 Cognitive Loading Levels A key part of the study was determining the effect of various levels of cognitive loading. Three conversation tasks were designed to generate low, medium and high levels of cognitive loading while each required interaction with the experimenter on the other end of the phone conversation. The low loading task consisted of small talk where the conversation was allowed to flow freely. The experimenter, on the phone, used a list of questions to prompt the subject in case of conversation lulls. The medium conversation task consisted of the subject retelling a plot line. The subjects were asked to recall a movie, book, play, etc. of their choice and the experimenter asked questions about the plot line in cases when the conversation halted. In the high cognitive loading task the subjects were asked to edit sentences for style in a poorly written essay and to spell 6

7 words. The text was read to the subject over the phone by the experimenter. All conversations were kept as consistent as possible between subjects. In order to validate that the perceived level of cognitive difficulty was consistent with the designed level, the subjects were asked to rate the difficulty of each conversation at the end of each run on a scale from 1 (very easy) to 5 (very difficult). The results, in Figure 3, indicate that the perceived conversation loading level was consistent with the expected level for all population groups. The low level (Small Talk) task had an average score of 1.7 with the medium level (Movie) conversation having an average score of 2.8 and the high level (Edit) task having an average score of Rating(1-Very Easy to 5- Very Difficult) HF-Small Talk HF-Movie HF-Editing HH-Small Talk HH-Movie HH- Editing Phone Setup Young Intermediate Elder Overall Figure 2. Average percieved difficulty of conversations reported by test subjects (1 = Very Easy, 5 = Very Difficult). 7

8 2.3 Driving Scenarios The simulated roadway was composed of 1 practice section and 8 separate road segments used during data collection. The practice section was ft long. Each road segment was ft long. The test subjects were asked to drive at approximately 50 mph (73 ft/s), which resulted in a driving time of about 4 minutes for the practice run and about 3 minutes per road segment of the main experiment. Four of the 3 minute sections were connected together for each phone set-up. One of these test sections lasted approximately 12 minutes and each test subject completed two sections. The practice run involved stimuli similar to those used in the actual experimental runs. The 3 minute segments used in the experiment were designed to be similar but sufficiently variable to prevent the subjects to be able to predict when an event was to occur. The same number of peripheral roadway objects (trees, oncoming traffic, pedestrians, stop signs, roadway signs) but were distributed randomly in each scenario. The pedestrian features (e.g., child, adult with red shirt, adult with blue shirt,...) to walk onto the road was randomly selected. Each segment contained one stop sign that suddenly appeared, one pedestrian who suddenly walked onto the road, and 2 situation awareness probes regarding the most recent sign. Each event occurred within ±3 ft of the programmed location. The roadway was kept straight to minimize distraction and the likelihood of simulator sickness. The reaction time stimuli were the sudden appearance of a stop sign and the pedestrian suddenly walking onto the road. The stop signs were programmed to 8

9 appear 250 ft in front of the car. The pedestrians were clustered in groups, consisting of both walking and stationary pedestrians. The pedestrians used as the reaction time stimulus started walking when the car was 350 ft away from them. Reaction time was measured as the time between the showing of a stimulus until the subjects pressed the brake and reached a deceleration of 5 ft/s 2 (maximum deceleration was ft/s 2 ). Situation awareness was tested by placing roadway signs - right turn arrow, left turn arrow, blank diamond, and yield sign (shown in Figure 3) - at random intervals along the road. These signs had no significance other than for the memory task used to measure situation awareness. The subjects were told about the task before the start of the experiment. A 1000 ft after the sign, a programmed voice asked "What was the last road sign?" The subject was scored with a Boolean correct or incorrect on his/her identification of the last sign. Figure 3. The four road signs used in the situation awareness task. The signs were situated at random points along the road. 2.4 Survey Design Before the experiment, the drivers were asked questions on their driving background and cell phone use. After each 12 minute driving section the test 9

10 subject was asked to rate their driving performance during each segment on a scale of 1 (Very dangerously) to 10 (Overly safely) and the conversation difficulty on a scale of 1 (Very easy) to 5 (Very difficult). In addition the experimenter on the opposite end of the conversation rated the driver s attentiveness on a scale of 1 (Not coherent; very broken conversation) to 5 (Fluent conversation; no pauses) Test Subjects A total of 20 subjects were tested in this study, comprising of the three age groups: young (N=8), intermediate (N=4), and older (N=8). The young age group contained members between 18 and 25 years of age (mean=22.1, S.D.=1.55; 4M, 4F). The intermediate age group contained subjects between 38 and 48 years of age (mean=42.5, S.D.=1.91; 3M, 1F). The older age group had members over the age of 60 (mean=73.4, S.D.=6.44; 7M, 1F). All test subjects were licensed drivers with at least one year of driving experience. In addition, the test subjects needed to be proficient in written English. Most of the test subjects (85%) owned a cell phone; 3 out of the 8 older test subjects did not own cell phones. As shown in Figure 4, 40% of the test subjects reported use of a cell phone while driving 50% of young, 75% of intermediate, 12.5% of older subjects. Average driving experience was 6.4 years for young, 25 years for intermediate, and 56 years for older subjects. Each age group showed different levels of driving frequency. The younger subjects drove on average less than weekly and 50% only drove approximately once a month. The intermediate 10

11 subjects drove more than once a week and the older subjects on average drove daily. Figure 4. Total fraction of subjects who reported using a cell phone while driving. 2.8 Test Procedure Each subject was tested in the normal driving (no conversation, no phone) scenario twice, and was asked to converse at the three cognitive loading levels for both the hands free and hand held phone set-ups, as shown in Table 1. Reaction time and situation awareness was tested within each element of the test matrix. 11

12 Table 1. Each subject was tested for reaction time (RT) and situation awareness (SA) in each of the scenarios shown. Phone Set-up Cognitive Loading None Hands Free Hand Held None RT, SA N/A N/A Low (Small talk) N/A RT, SA RT, SA Medium (Plot line) N/A RT, SA RT, SA High (Editing) N/A RT, SA RT, SA Test subjects initially completed a 4 minute practice run to ensure that they were used to the handling of the simulator. After the practice run, the test subject entered the first 12 minute driving section. The beginning of the section was a 3 minute normal driving run (no conversation), which was used as a benchmark. After this run, the test subject continued with either the hand held or the hands free phone set-up. An experimenter outside the room conducted the three phone conversations with the test subject. Between test runs subject rested as long as desired to avoid simulator sickness, and then proceeded with the second 12 minute section. This section contained a normal run at the end. Again the appropriate surveys were completed. Typical chronological actions by both experimenters and the test subject are shown in Figure 5. 12

13 Figure 5. A chronological timeline of the test protocol. 3. Analysis 3.1 Data collection and extraction Vehicle dynamic data was collected through the simulation system. This data included time from the beginning of the run, distance from the beginning of the run, velocity, acceleration, and steering wheel angle. This data was collected at a at a frequency of 20 Hz during the road sections where the stimuli appeared. Reaction time was normally measured from stimulus onset to the initial brake application. In cases where the subject was already decelerating at the onset of the stimulus, the response time was taken when there was a significant change in the rate of deceleration. In some cases, the test subject swerved for the pedestrian rather than stopping, an accurate reaction time could not be computed. Cases in which the subject did not notice the stimulus and therefore did not brake at all, were also not included in the reaction time analysis although these cases were noted. 13

14 Because of differences in deceleration profiles it was also found useful to measure the point at which the vehicle came to a stop. The reported Distance to Stimulus Distance is the remaining distance. Negative values indicate that the vehicle did not stop before the pedestrian or stop sign. No values were included in the analysis for subjects who completely missed a stop sign or swerved around a pedestrian. A larger positive distance is considered better performance. Statistical significance of the performance results were determined with a onetailed t-test and single factor ANOVA with a level with p values less than 0.05 (i.e. greater than 95% confidence). 4. Results 4.1 Surveys The subjective results, show in Figure 6 appear to support the hypothesis that cell phone conversations degrade the perceived driving performance with all conversations having a lower perceived driving level than the normal case. In addition, the perceived driving level significantly decreased with increasing cognitive difficulty of the conversation. 14

15 Figure 6. Average subjective ratings on driving performance, conversation difficulty and drivers attentiveness to conversation. The left vertical axis represents the subjects evaluation of their driving (1-Very Dangerous to 10- Overly Safe), right vertical axis represents the driver s evaluation of the conversation difficulty (1-Very Easy to 5-Very Difficult) and the experimenters evaluation of the drivers attentiveness to the conversation (1-Not Coherent to 5- Very fluent). 4.2 Situation Awareness The situation awareness, as measured by correct recall of roadway signage questions, is show in Figure 7 averaged across all subjects and conversation levels. For the aggregate data there was a significant (p < 0.14) decrease in correct responses for both the hand-held and hands-free cell phone conversations compared with the normal condition indicating that the awareness of the environment was degraded during cell-phone conversations. There was no significant difference in situation awareness observed between the hands-free and hand-held cell phone conditions. 15

16 Figure 7. Situation awareness, measured as the average percent correct, for the Normal, Hands Free (HF), and Hand held (HH) cases. The error bars represent the standard error. The detailed situation awareness data, separated by age group and conversation level is shown in Figure 8. Age was observed to have a significant impact on situation awareness (p = ). Percentage correct responses were 71% correct for younger, 86% correct for intermediate and 55% correct for older subjects. There was significant variability between age groups and conversation levels which confounded clear trends in the overall data. The intermediate age group (which had the most recent driving experience) consistently had better performance in the situation awareness task. 16

17 Figure 8. Situation awareness, measured as the average fraction correct for each age group and each conversation scenario. Error bars on the overall data represent the standard error. Within each subject group there was no significant difference between the low (Small Talk) and medium (Movie) conversation levels. There were significant differences between the medium (Movie) and high (Edit) conversation levels for some population groups with inconsistent trends and the highest variability in the high (Edit) conversation. It is hypothesized that the nature of the editing task caused temporal variability in the cognitive loading or the use of different attention management strategies which may have confounded the situation awareness probe and made the results sensitive to timing issues. Therefore no strong conclusions can be drawn from the high (Edit) conversation level data. 17

18 4.3 Reaction Time The results from the stop sign reaction time probe are shown in Figure 9. Unexpectedly, no significant differences were found between normal driving and cell phone conversations for any of the age groups and no significant differences were found between cognitive loading levels. There was however a significantly slower reaction time for the older age group. Figure 9. Response time data for the stop sign stimulus. Error bars on the overall data represent the standard error. 18

19 Reaction time to the pedestrian stimulus is shown in Figure 10. There was a significant decrease in reaction time between the first and second normal runs indicating that learning effects may have been present and may have confounded the effect of conversation level within each age group. In the fully counterbalanced overall data there was no significant effect of conversation level on the pedestrian reaction time. Again for the pedestrian stimulus the older age group had significantly slower reaction times. Figure 10. Response time data for the pedestrian stimulus. Error bars on the overall data represent the standard error. 19

20 4.4 Distance to Stimulus The distance to stimulus data is shown in Figures 11 and 12. Again no strong and consistent trends are observed as a function of conversation level however the slower reaction times of the older age group resulted in significantly poorer performance in stopping distance with the average stopping point being past the stop sign for 3 of the 6 conversation level cases. Figure 11. Distance remaining to the stop sign stimulus after the car comes to a complete stop. 20

21 Figure 12. Distance remaining to the pedestrian stimulus is shown. 5. Discussion The significant decrease in situation awareness between normal driving and driving during cell phone conversation is thought to be due to the fact that both of these tasks engage high level cognitive resources. Consistent with this hypothesis, some significant differences were found with changes in cognitive loading level; however, these trends did not consistently show a decrease in situation awareness with what was perceived to be increasing cognitive loading level. There was no significant difference observed between a driver s situation awareness while driving with a hands-free phone versus a hand held phone, possibly because holding a phone is a physical task and therefore does not interfere with the cognitive task. It should be noted that the drivers were not required to dial or otherwise operate the phones during the experimental runs. Unexpectedly, and inconsistent with some previous studies, no significant difference in reaction time between normal driving and driving with cell phone use was observed. In should be noted that this study was focused on cognitive loading and did not include head down tasks such as dialing and picking up the cell phone which may have degraded reaction time in other studies. Also due to the relatively low level of the stimulus-response reaction tested it may be that there was limited interaction between the reaction task and the conversation task or that the drivers were able to prioritize the reaction task so as to maintain performance which engaging in cell phone conversations. 21

22 Changes in cognitive loading level resulted in no significant differences for situation awareness for the overall averaged data; however, significant differences were found for some of the age groups and phone set-ups. This result may indicate that there is some effect of cognitive loading on situation awareness though this experiment was unable to assess it to the limited number of test subjects. No significant trend was found between cognitive loading levels for reaction time and distance to stimulus. However drivers did subjectively rate themselves as being increasingly more dangerous as they engaged in conversations with higher levels of cognitive difficulty. Given that driving was their highest priority it is possible that they may have allocated more cognitive resources and attention to the road to compensate for the higher cognitive loading. This hypothesis is supported by the decreasing subject attentiveness from the low (small talk) to high (edit) conversations, as rated by the experimenter conversing with the subject. The effect of cognitive loading levels is inconclusive and should be studied further. Age did have a significant effect on situation awareness and reaction time. Intermediate subjects may have performed better than young subjects because of a longer driving experience and higher recent driving experience. The older subjects may have experienced some aging effects that reduce situation awareness and reaction time. All age groups performed similarly for the distance to pedestrian metric, likely due to the strategies used by each group. The older age groups consistently slowed down for all groups of pedestrians, thereby increasing their distance to pedestrian despite their slower reaction time. 22

23 6. Conclusion This experiment found a significant decrease in situation awareness caused by cell phone usage; however, there was no significant of cell phone use on reaction time observed. This is consistent with anecdotal reports of drivers missing roadway exits or loosing track of their location while engaged in cell phone conversations. No significant improvement was observed with hands-free cell phone use as compared with similar hand-held conditions. The level of cognitive loading in the cell phone conversations was not observed to be significant however the experiment was not sufficiently diagnostic to be conclusive in this area. Based on the results, countermeasures that increase the driver's awareness of important situation events and minimize head down time are most likely to improve driving safety if cell phone use is to be allowed. Hazard alerting or turn warning devices may compensate for reductions in situation awareness. Other than the dialing and pick up it is unclear how effective hands-free cell phone operation is at mitigating the risk from cell phone use. 7. Acknowledgements This project has been aided by advice, help, and support of Dr. Masha Maltz, Prof. Joseph Coughlin and the MIT Age Lab, Prof. Kim Blair, Prof. Earll Murman, Dr. Andrea McKenzie, Dick Perdichizzi, Peggy Udden and the Dept of Aeronautics and Astronautics at MIT. References 23

24 Buris, M. & Cain, A. (1999). Investigation of mobile phones while driving. Tampa, FL: University of South Florida, Center for Urban Transportation Research, 46pp. April. Irwin, M., Fitzgerald, C., Berg, W. P. (2000). Effect of the Intensity of Wireless Telephone Conversations on Reaction Rime in a Braking Response. Journal of Perceptual and Motor Skills. 90(3), McCarley, J.S., Vais, M., Pringle, H., Kramer, A.F., Irwin, D.E., Strayer, D.L., "Conversation Disrupts Visual Scanning of Traffic Scenes", in press. Ranney, T. A., Mazzae, E. M., and Goodman, M. J. (2000). NHSTA Driver Distraction Research: Past, Present and Future. NHTSA Report, pp. 4. Redelmeier, D.A. and Tibshirani, R.J. (1997). Association Between Cellular Telephone Calls and Motor Vehicle Collisions. The New England Journal of Medicine, 336, Strayer, D. L., Drews, F. A., Albert, R. W., Johnston, W. A. Cell Phone Induced Perceptual Impairments During Simulated Driving. in press. 24

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