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Accident Analysis and Prevention 40 (2008) 704–713

The effects of practice with MP3 players on driving performance
S.L. Chisholm 1, J.K. Caird ∗, J. Lockhart 2
Cognitive Ergonomics Research Laboratory, Department of Psychology, University of Calgary, 2500 University Drive N.W., Calgary, AB T2N 1N4, Canada
Received 27 February 2007; received in revised form 9 August 2007; accepted 7 September 2007
Abstract
This study examined the effects of repeated iPodTM interactions on driver performance to determine if performance decrements decreased with practice. Nineteen younger drivers (mean age = 19.4, range 18–22) participated in a seven session study in the University of Calgary Driving Simulator (UCDS). Drivers encountered a number of critical events on the roadways while interacting with an iPod including a pedestrian entering the roadway, a vehicle pullout, and a lead vehicle braking. Measures of hazard response, vehicle control, eye movements, and secondary task performance were analyzed. Increases in perception response time (PRT) and collisions were found while drivers were performing the difficult iPod tasks, which involved finding a specific song within the song titles menu. Over the course of the six experimental sessions, driving performance improved in all conditions. Difficult iPod interactions significantly increased the amount of visual attention directed into the vehicle above that of the baseline condition. With practice, slowed responses to driving hazards while interacting with the iPod declined somewhat, but a decrement still remained relative to the baseline condition. The multivariate results suggest that access to difficult iPod tasks while vehicles are in motion should be curtailed. © 2007 Elsevier Ltd. All rights reserved.
Keywords: Driver distraction; Practice effects; MP3 players; Eye movements; Driving simulation

1. Introduction
Driver distraction from a variety of in-vehicle sources, including car radios, has been cited since the 1930s as potential crash contributors (Caird and Dewar, 2007; Goodman et al., 1997). In particular, the progression of in-vehicle audio entertainment systems has included radio, 8-track, cassette, CD, and now MP3 players, which is the focus of this study. The overwhelming majority of drivers use music systems while driving. Almost 92% of drivers were observed, in a natural-
∗ Corresponding author. Tel.: +1 403 220 5571; fax: +1 403 282 8249. E-mail addresses: Susan.Chisholm@calgaryhealthregion.ca
(S.L. Chisholm), jkcaird@ucalgary.ca (J.K. Caird), jlockhar@engineering.uiowa.edu (J. Lockhart).
1 Present address: Calgary Health Region, Northwest II, Quality, Safety and Health Information, 4520 16th Avenue N.W., Calgary, Alberta T3B 0M6, Canada. Tel.: +1 403 944 2531.
2 Present address: Human Factors and Statistical Modeling Laboratory, Department of Mechanical and Industrial Engineering, University of Iowa, 2440 Seamans Center for the Engineering Arts and Sciences, Iowa City, IA 52242-1527, USA. Tel.: +1 319 335 5322; fax: +1 319 335 5669.
0001-4575/$ – see front matter © 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.aap.2007.09.014

istic study by Stutts et al. (2005), using audio/music devices while driving their own vehicles. Interaction with these systems has resulted in crashes. Music system use (i.e., adjusting the radio/cassette/CD) was a contributor to about 11% of all distraction crashes compared to 1.7% of crashes when using a cell phone (i.e., talking/listening/dialing) (Stutts et al., 2001). Interacting specifically with CD players was associated with a several fold increase in crash risk (Klauer et al., 2006). Cell phone use while driving, which has been the focus of the majority of research on driver distraction, has been associated with approximately a fourfold increase in crash risk (McEvoy et al., 2005; Redelmeier and Tibshirani, 1997).
Relatively few studies have systematically examined the impact of more recent technologies on driver performance, including MP3 players. For example, the effects of e-mail (Jamson et al., 2004; Lee et al., 2001), text messaging (Hosking et al., 2005) and MP3 players (Donmez et al., 2006) on driver performance are less common than studies of cell phones and driving (Caird et al., 2004; Horrey and Wickens, 2006). Performance decrements associated with distractive tasks have been found in significant increases in reaction time during cell phone

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tasks (A˚ lm and Nilsson, 1994, 1995; Brookhuis et al., 1991; Strayer and Drews, 2004) and speech based e-mail interactions (Jamson et al., 2004). Lateral vehicle control, as indicated by measures such as lane positioning, and steering, has not consistently been affected by cell phone conversation (Brown et al., 1969; Parkes and Ho¨o¨ijmeijer, 2001) or speech based email (Jamson et al., 2004). In contrast, text messaging while driving has been found to significantly increase the number of lane excursions observed (Hosking et al., 2005). Additional research on more recent technologies that are brought into the vehicle by the driver is needed.
To determine the allocation of attention to specific sources within and outside the vehicle requires the use of eye movement measures. Previous research has shown that drivers reduce or constrain the breadth of eye movements in the presence of a distractor (Chisholm et al., 2006; Green, 1999a; Recarte and Nunes, 2000, 2003) such as a cell phone. However, while interacting with a visual secondary device, increased visual sampling into the vehicle is required and may affect eye movement behaviours. Hosking et al. (2005) found a 400% increase in eyes off road time while sending or receiving text messages in a simulator. From a practical point of view, eyes off the roadway and the frequency of glances to a device have been used to suggest that eye movements that are too long or too frequent are unsafe (Green and Shah, 2004). When the eyes are focused into the vehicle the probability of missing critical external events while driving increases, thereby increasing the potential for collisions (Green, 2007; Klauer et al., 2006).
To address the lack of empirical studies on MP3 player interaction, the present study examined the effects of iPod interactions over multiple sessions to determine the effects of distraction on different event types and glance measures. The addition of the distraction task was expected to cause decrements on a number of measures of driving performance relative to baseline. Specifically, the more difficult iPod interactions were expected to degrade perception response times to critical hazards and increase the number of collisions observed. Whereas the easy iPod interactions would be executed with little disruption and be less distracting than the difficult interactions while driving. The complexity of the difficult iPod task was expected to increase the frequency and duration of fixations made into the vehicle to complete the task. Over the sessions participants were expected to become more efficient in their interactions with the iPod, leading to a decrease in task completion time. Some increased efficiency in task sharing was expected over sessions, which will lead to decreases in perception response time and the number of collisions as performance improved. Although improvement equal to or beyond that of the baseline measures was not expected to occur.
2. Methods
2.1. Participants
Nineteen participants (10 Females, 9 Males) between 18 and 22 years of age were recruited from the University of Calgary and surrounding community. Participants were asked to vol-

unteer for a preliminary screening session plus six simulator sessions conducted weekly over a 2-month period. Participants were scheduled to return on the same day each week at the same time period. Remuneration for the sessions increased incrementally and each participant received a total of $200.00 ($CAN) for the successful completion all seven sessions and their names were entered into a prize draw at the completion of the study.
All participants were required to hold a valid class 5 driver’s license, drive a minimum of 10,000 km per year, be in good physical and mental health, and not be under the influence of medications or drugs that would affect their driving or cognitive performance. Due to the difficulties of calibrating the eye movement system, those who required glasses to drive were not permitted to participate in the study.
Visual testing was performed using a number of tests to ensure participants met the minimum acuity requirements mandated by law for licensure, which is 20/40 acuity in Alberta (Casson and Recette, 2000). Corrected visual acuity was tested for both long and short distances, using the Snellen Visual Acuity chart and Landolt C tests, respectively. Contrast sensitivity was measured with the Vistech Contrast Sensitivity Chart (Scialfa et al., 1991) and color vision was assessed with the Ishihara Test for Color Blindness (plates no. 3 and 27) (Ishihara, 1993). Those who did not meet the minimum requirements for visual acuity, contrast sensitivity, or had color vision deficits were not allowed to participate in the study (N = 2). During the initial screening and testing session, participants drove a practice drive, to become familiar with the handling characteristics of the simulator and screen out those who experienced simulator sickness (N = 3).
2.2. Apparatus and materials
2.2.1. The University of Calgary Driving Simulator (UCDS)
The following brief description of the UCDS and eye movement system is abridged from Caird et al. (2006). The UCDS consists of three Epson 703C projectors that display the simulated images onto three (86.5 in. wide by 65 in. height) screens positioned approximately 230 cm from the drivers head position. The total projected forward field-of-view from the drivers seated position is 150◦.
Traffic environments and experimental scenarios for the driving simulator are developed and run in HyperDriveTM (v. 1.9.25). Tiles can be selected from an extensive pallet of intersections, freeway sections, streets, and so forth, all of which adhere to the Manual on Uniform Traffic Control Devices (MUTCD). The placement of dynamic objects, such as vehicles and pedestrians, require iterative testing and development using a variety of Tcl/Tk scripts.
The SimObserver system records participant and experimenter activities and integrates multiple visual and auditory inputs into a single display. Three black and white “lipstick” cameras are mounted inside the Saturn and provide views of the driver’s face, hands on the steering wheel, and feet on the brake and accelerator. A fourth color camera records the center screen of the simulated traffic environment. Video analysis is

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performed using Data Distillery, which is an offline data review the experimental sessions (3 easy and 3 difficult tasks) for a

and reduction analysis program.

total of 36 iPod interactions over the six sessions.

2.2.2. ASL-501 eye tracking system Eye movements were captured during half of the experimen-
tal sessions (i.e., sessions 2, 4, and 6) using an Applied Science Laboratory (ASL) 501 eye tracking system. The ASL 501 uses a lightweight, head-mounted, infrared corneal reflection system that allows data collection while head and body movements occur. Eye position is sampled at a rate of 60 Hz with a spatial error of 1◦ at the center of the plane of view (Applied Sciences Laboratory, 2001).
2.3. Procedure
2.3.1. Secondary tasks During each session, the participants interacted with a 20GB
Apple iPodTM while driving (see Fig. 1). The iPod was mounted on the center console of the Saturn, and connected to a portable speaker system (i.e., JBL on tour). For a person 5 8 tall, the iPod was positioned 37◦ down and 53◦ to the left of road center. Both easy and difficult iPod tasks were performed during each session. Easy tasks were defined as having one or two steps, represent common tasks (i.e., achieved frequent goals), and took less than 5 s to accomplish when tested alone. These included turning off the iPod, pausing, and skipping ahead a couple of songs. Difficult tasks required five to seven steps, are used to accomplish more complex or specific tasks, and took about 20–30 s to complete when tested alone. Difficult interactions required participants to turn on the iPod and find a specific song in the song titles menu. A total of 900 songs were programmed into the iPod and were arranged alphabetically by song title. All iPod task instructions were presented in green writing on the center screen during the drives and informed participants of the tasks they were to perform immediately. For example, difficult iPod instructions included the song title they had to play, i.e., “Play: Jack and Diane”. Six iPod interactions were performed within each of

2.3.2. Experimental sessions The first experimental session included training on the iPod
functions and the tasks. During each of the six experimental sessions, participants drove a total of three drives. The first was a practice drive to familiarize participants each week with the handling characteristics of the simulator. The second and third drives were counterbalanced for presentation and included a drive interacting with the iPod and a baseline drive with no secondary task, each lasting approximately 12 min.
Occasionally, participants were required to respond to three different types of critical events during iPod interactions as well as baseline drives (see Fig. 2). The first event involved a pedestrian who emerges from between two parked cars and “walks” into the path of the driver on the road. The second event involved a parked vehicle that pulled out from the side of the roadway into the path of the participant. Both the pedestrian and pullout events occurred on the 50 km/h residential or urban roadways. The third event involved a lead vehicle traveling 1.5 s (approximately 40 m) in front of the participant on the 100 km/h freeway that brakes suddenly. All three events required braking, steering, or a combination therein to avoid a collision and have been developed and used previously (Caird et al., 2008; Chisholm et al., 2006). A total of three occurrences of each event type were encountered within the easy iPod, difficult iPod, and baseline secondary task conditions. Event placement during the iPod tasks varied randomly; some were encountered early in the task performance while others were delayed further into the task. All events were counterbalanced across the six experimental sessions, with no one event iPod combination occurring more than once within a single session, to reduce anticipation on the part of the driver.
2.3.3. Experimental drive descriptions Eighteen experimental drives were created and used during
the six experimental sessions. Parked cars and commercial buildings lined the urban route and parked cars and single-family homes with attached garages lined the residential routes. The freeway roads consisted of six-lanes of traffic, three in each direction, separated by a grassy median. The volume of ambient traffic encountered in the scenarios varied depending on road type, and consisted of a mix of cars, trucks, and SUV’s.

3. Results

3.1. Participants

Fig. 1. Participant with eye movement apparatus and the 20 GB iPod mounted on the center console in the simulator.

All 19 young drivers successfully completed the screening and six experimental sessions. A summary of the demographic, driving experience and visual acuity test measures for the sample of participants is shown in Table 1. In our sample, 15 participants owned MP3 players, eight of whom reported owning a model of the Apple iPod player. Six of the 15 owners reported having used their MP3 players while driving.

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Fig. 2. Pedestrian event in residential roadways (top left), pullout event in urban roadways (top right), and lead vehicle braking event (bottom).

3.2. Experimental design
Hazard response data were analyzed using repeated measures ANOVA with secondary task (easy iPod, difficult iPod, baseline), event type (pedestrian, lead vehicle braking, and pullout vehicle), and occurrence of the event (3 per secondary task condition) as within-subjects variables. To reduce expectancy, each combination of event and secondary task condition were not encountered within each session. Over the six sessions each event and secondary task combination was presented 3 times, occurrence denotes the order across sessions. Overall analyses examined the larger design with all events, secondary tasks and occurrences included to determine the pattern of results.
Variation in steering wheel angle data was analyzed using repeated measures ANOVA with secondary tasks (difficult iPod and baseline), and road type (residential, urban, and freeway) as within-subject factors. Eye movement data was analyzed by secondary task (easy iPod, difficult iPod, baseline), areas of interest (on-road, in-vehicle, off road, and rearview mirror), and road type (residential, urban, and freeway). Multiple comparisons were made using the Sidak adjustment (Tabachnick and Fidell, 2006).

The results are organized by hazard response (i.e., PRT and collisions), lateral control (SD of steering wheel angle), eye movements (glance frequency, glance duration), and secondary task performance (task completion time). Definitions of each of these dependent variables precede the results of each analysis.
3.3. Hazard detection and response
3.3.1. Perception response time Perception response time (PRT) was calculated in seconds
from the immediate onset of an event to a braking response (Olson and Farber, 2003). The longest PRT was found while drivers were performing the difficult iPod tasks (M = 1.30 s, S.E. = .03), than in the easy iPod (M = 1.17 s, S.E. = .03) and baseline (M = 1.12 s, S.E. = .03) conditions, F(2, 37) = 9.76, p < .001, which is illustrated in Fig. 3. Post hoc analyses showed significant differences between the difficult iPod and baseline conditions, p < .05, and between the difficult iPod and easy iPod conditions, p < .05.
Drivers’ PRT improved significantly over occurrences, with PRT in the 3rd occurrence being significantly faster (M = 1.10 s, S.E. = .03) than both the 2nd (M = 1.21 s, S.E. = .03) and 1st (M = 1.29 s, S.E. = .03) occurrences, F(2, 39) = 8.87, p = .001.

Table 1 Gender, number of participants in each group, mean participant age (standard deviation, S.D.), average reported kilometers driven per year, number of reported crashes in the last 5 years, moving violations reported in the last 5 years, left and right eye visual acuity, and short distance visual acuity with correction (minimum angle of resolution, MAR)

N Mean age (S.D.) Avg. (km/year)

Crashes

Moving violations Visual acuity left Visual acuity right Short distance VA

Male

9

Female 10

19.33 (0.87) 19.4 (1.35)

22,222 (10,663) 18,040 (12,246)

0.11 (0.33) 0.60 (0.70)

0.44 (0.73) 0.90 (1.29)

1.0 (0.18) 1.13 (0.38)

0.99 (0.20) 1.17 (0.50)

0.81 (0.15) 0.98 (0.10)

Total 19 19.37 (1.12)

20,021 (11,407) 0.37 (0.60) 0.68 (1.06)

1.07 (0.30)

1.08 (0.39)

0.90 (0.15)

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Secondary task also significantly affected drivers’ PRT to the braking event, F(2, 39) = 3.30, p = .048. The fastest PRT to the lead vehicle braking was observed in the baseline condition (M = 1.24 s, S.E. = .06), followed by the easy iPod condition (M = 1.40 s, S.E. = .06), and finally the difficult iPod condition (M = 1.44 s, S.E. = .06). Only the difference between the baseline and difficult iPod conditions was significant, p < .05.

Fig. 3. Perception response time (PRT) by secondary task and occurrence.
However, no differences were found between the 1st and 2nd occurrences in post hoc analyses, p > .05.
Event type also significantly affected perception response times to hazards, F(2, 368) = 35.78, p < .001. Lead vehicle braking events had the longest mean PRT (M = 1.36 s, S.E. = .03) followed by the pullout vehicle (M = 1.19 s, S.E. = .03), and the pedestrian (M = 1.04 s, S.E. = .03) events. All of which differed significantly from each other, p < .001.
The two-way interactions between occurrence and event type, F(4, 368) = 3.56, p = .007, and between secondary task and event type, F(4, 368) = 2.87, p = .023, were also significant. Both interactions however, were embedded in a significant three-way interaction among occurrence, secondary task, and event type, F(7, 368) = 7.45, p < .001. Follow-up analyses examined each event type separately.
3.3.1.1. Pedestrian event. Secondary task had a significant effect on PRT to the pedestrian event, F(2, 36) = 6.27, p = .005. The fastest PRT to the pedestrian event was observed with the easy iPod tasks (M = 0.90 s, S.E. = .05), which was significantly faster than the difficult iPod task (M = 1.15 s, S.E. = .04), p < .05. However, both iPod tasks did not differ significantly from the baseline condition (M = 1.03 s, S.E. = .04), p > .05.
The interaction between occurrence and secondary task type was significant, F(3, 53) = 11.75, p < .001. For the 1st occurrence of the pedestrian event, there were no differences in PRT between the baseline condition or difficult iPod task, F(1, 35) = 2.31, p > .05. In the 2nd occurrence of the pedestrian the fastest PRT was found in the easy iPod condition (M = 0.78 s, S.E. = .07) followed by the baseline (M = 1.05 s, S.E. = .07), and the longest PRT times were found in the difficult iPod condition (M = 1.46 s, S.E. = .07), F(2, 54) = 21.07, p < .001. All of which significantly differed from each other, p < .05. By the 3rd occurrence of the pedestrian event, no significant differences were found between the secondary task conditions, F(2, 54) = 0.58, p > .05.

3.3.1.3. Pullout vehicle event. During the pullout vehicle event, PRTs were significantly longer in the difficult iPod task (M = 1.36 s, S.E. = .04), than the easy iPod (M = 1.15 s, S.E. = .04), and the baseline conditions (M = 1.08 s, S.E. = .04), F(2, 36) = 12.95, p < .001. Significant differences were found between the difficult iPod and baseline, p < .001, and between the difficult iPod and the easy iPod conditions, p < .001. The two-way interaction between occurrence and secondary task was significant, F(4, 70) = 4.37, p = .003.
As can be seen in Fig. 4, for the pullout event over occurrences, baseline means remained relatively constant whereas in the difficult iPod condition, a decrease in PRT was found over occurrence. In the 1st occurrence of the pullout event results, as expected, the shortest PRT times occurred in the baseline (M = 1.10 s, S.E. = .05), followed by the easy iPod task (M = 1.14 s, S.E. = .05), and the longest PRT found in the difficult iPod condition (M = 1.41 s, S.E. = .05), F(2, 54) = 10.08, p < .001. No significant differences were found between the baseline and easy iPod conditions, but both differed significantly from the difficult iPod condition, p < .05. During the 2nd occurrence of the pullout event, the shortest PRT was observed during the baseline (M = 0.998 s, S.E. = .07), followed by the difficult iPod (M = 1.33 s, S.E. = .07), and easy iPod (M = 1.34 s, S.E. = .07) conditions, F(2, 53) = 7.73, p = .001. Comparisons show that PRT for both iPod tasks were significantly longer than the baseline, p < .05. In the 3rd occurrence of the pullout event, PRT was significantly affected by secondary task, F(2, 53) = 4.72, p = .013. However, the easy iPod condition resulted in the shortest PRT (M = 0.96 s, S.E. = .07), followed by the baseline (M = 1.13 s, S.E. = .07), and the difficult iPod condition (M = 1.28 s, S.E. = .08). PRT in the difficult iPod condition was significantly longer than the easy iPod condition, p < .05.

3.3.1.2. Lead vehicle braking event. Perception response time (PRT) for the braking event indicated steady improvement in performance between the 1st occurrence (M = 1.54 s, S.E. = .06), and decreasing on the 2nd (M = 1.34 s, S.E. = .06), and 3rd occurrences (M = 1.20 s, S.E. = .06), F(2, 39) = 8.61, p = .001. The difference between the 1st and 3rd occurrence was significant, p < .05.

Fig. 4. Perception response time (PRT) to the pullout vehicle by secondary task and occurrence.

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3.3.2. Collisions A total of 513 event occurrences were included in this anal-
ysis, which represents all the experimental combinations of the independent variables (i.e., pedestrian, lead vehicle braking, and pullout vehicle), for each of the secondary tasks (i.e., baseline, easy iPod, and difficult iPod). Of the 513 events encountered by participants over the course of the six sessions, a total of 115 collisions resulted. Secondary task had a significant effect on collision frequency, χ2(2) = 11.67, p = .003. Twenty-eight collisions occurred during the baseline drives, 34 during the easy iPod interactions, and 53 in the difficult iPod interactions. Significant differences in collision frequency were found between the difficult iPod and baseline conditions, χ2(1) = 10.35, p = .001, and between the difficult iPod and easy iPod conditions, χ2(1) = 5.60, p = .018. Frequency of collisions also decreased significantly from the 1st occurrence (52) to the 2nd occurrence (39) and finally the 3rd occurrence (24), χ2(2) = 8.98, p = .011. Significant differences were found between the 1st and 3rd occurrences, as well as between the 2nd and 3rd occurrences, p < .05.
3.4. Standard deviation of steering wheel angle
Steering angle variation was used to determine steering corrections made while interacting with the iPod and comparable baseline measures on matched roadways. Collected data commenced at the beginning of the iPod task and excluded any event response data, curve navigation, or turns. Due to the short time needed to complete the easy iPod task, only the difficult iPod and baseline analyses were performed.
The difficult iPod tasks had larger variation in steering wheel adjustments (M = 2.11◦, S.E. = .05) than during the baseline (M = 1.17◦, S.E. = .05), F(1, 18) = 62.02, p < .001. Roadway type showed a significant effect on deviation of steering wheel angle, F(2, 36) = 85.96, p < .001. The significantly larger variation occurred on the freeways (M = 2.20◦, S.E. = .07) compared to the residential (M = 1.38◦, S.E. = .06), and urban (M = 1.33◦, S.E. = .07) roadways, p < .05.
3.5. Eye movement variables
Eye movements were collected on the even numbered sessions (sessions 2, 4, and 6) in both the iPod and baseline conditions. Video data analysis of eye movements was analyzed using SimObserver and Data Distillery hardware and software. A glance was defined as consecutive fixations to an area of interest (i.e., in the vehicle, on road) not including saccade transition time and blinking behaviour (International Organization of Standards, 2002). In-vehicle, on road, off road (which included any signs, buildings, parked cars that are not in the central roadway), and rearview mirror were the areas of interest (AOI) that were extracted.
3.5.1. Mean glance frequency Glance frequency is defined as the number of glances to
a target during the task where each glance is separated by at least one glance to a different target (ISO, 2002). The number

of glances into the vehicle made during iPod interactions was examined to determine the average number of glances needed to complete the required tasks. Obviously the difficult iPod task required significantly more glances into the vehicle (M = 16.70, S.E. = .42) than the easy iPod interactions (M = 1.98, S.E. = .47), F(1, 18) = 190.45, p < .001.
The number of glances to the rearview mirror could not be compared using parametric statistics because too few participants in the iPod tasks glanced at the rearview mirror. Chi-square analyses revealed that there was a significantly higher frequency of glances to the rearview mirror in the baseline condition (76 of the events out of 95 generated a look to the mirror) compared to the easy iPod condition (where 11 out of 171 events elicited a look to the rearview mirror), χ2(1) = 150.18, p < .001; and difficult iPod condition (27/171), χ2(1) = 106.12, p < .001.
3.5.2. Mean glance duration Glance duration was calculated as the time (in seconds) from
first looking at an AOI until gaze was moved off that area. The mean duration of each glance in seconds was extracted and categorized into various AOIs (i.e., in-vehicle, on-road, off-road) for each secondary task (i.e., baseline, easy iPod, hard). The duration of glances significantly differed depending on the AOI, F(2, 43) = 22.18, p < .001. Specifically, longer glances were made into the vehicle (M = 0.78 s, S.E. = .02) than on the road (M = 0.67 s, S.E. = .02), and off the road (M = 0.42 s, S.E. = .03), all of which significantly differed from one another, p < .05.
Mean glance durations differed by secondary task, F(2, 49) = 14.04, p < .001. Significantly longer glance durations were found in the difficult iPod condition (M = 0.73 s, S.E. = .02) compared to the easy iPod (M = 0.55 s, S.E. = .03) and baseline conditions (M = 0.60 s, S.E. = .02), p < .05. The three-way interaction among AOI, secondary task, and road type was also significant, F(8, 613) = 2.76, p = .005. Follow-up analyses examined each AOI (i.e., on road, in-vehicle, and off road) separately to determine the effects of secondary task on glance duration.
3.5.2.1. On-road. Glance duration to the roadway differed depending on secondary task, F(2, 43) = 5.37, p = .008. Longer glances to the roadway were found in the baseline condition (M = 0.82 s, S.E. = .05) followed by the difficult iPod (M = 0.64 s, S.E. = .04) and easy iPod (M = 0.54 s, S.E. = .05) conditions. Only the glances to the roadway during the easy iPod task were significantly shorter than the baseline, p < .05. Significantly longer glances to the road were also found on the freeway (M = 0.76 s, S.E. = .04) compared to the residential (M = 0.61 s, S.E. = .04) roads, F(2, 176) = 4.18, p = .017.
Mean glance duration to the roadway significantly differed depending on the two-way interaction between secondary task and road type, F(4, 176) = 4.42, p = .002. On the residential roadways, significantly longer glances were made during the baseline condition (M = 0.81 s, S.E. = .08) than the difficult iPod (M = 0.54 s, S.E. = .05), and easy iPod (M = 0.47 s, S.E. = .06) conditions, F(2, 39) = 5.89, p = .006. No difference was found between the iPod conditions, p > .05, but both means differed significantly from the baseline, p < .05. There was no significant

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three sessions: session 1 (M = 37.90 s, S.E. = 2.99), session 2 (M = 45.20 s, S.E. = 2.27), and session 3 (M = 42.50 s, S.E. = 2.19) did not differ significantly, p > .05. As well, TCT in session 4 (M = 30.88 s, S.E. = 2.90), session 5 (M = 27.57 s, S.E. = 2.63), and session 6 (M = 28.67 s, S.E. = 2.11) did not differ significantly from each other, p > .05. However, TCT in sessions 2 and 3 were significantly longer than the last three sessions, p < .05.

Fig. 5. Mean duration of glances (s) made into the vehicle by secondary task and road type.
differences between the secondary task conditions on the urban (F(2, 29) = 2.71, p > .05), or freeway (F(2, 37) = 2.09, p > .05) roads (Fig. 5).

3.6.1.2. Easy iPod interactions. Time to complete task differed depending on the session, F(5, 87) = 12.42, p < .001. Essentially, only session 2 (M = 6.80 s, S.E. = .45) had significantly longer TCT times than all other sessions: session 1 (M = 4.05 s, S.E. = .36), session 3 (M = 3.94 s, S.E. = .45), session 4 (M = 4.38 s, S.E. = .36), session 5 (M = 3.76 s, S.E. = 2.05), and session 6 (M = 3.54 s, S.E. = .43), p < .05.
4. Discussion and conclusion

3.5.2.2. In-vehicle. The in-vehicle AOI was defined as any glances that were made into the vehicle, whether at the iPod device, center console, or speedometer. Mean glance durations made into the vehicle, ostensibly at the iPod or speedometer differed depending on secondary task, F(2, 38) = 52.46, p < .001. Longer glances were made in the difficult iPod condition (M = 1.15 s, S.E. = .03) compared to the baseline (M = 0.54 s, S.E. = .04) and easy iPod (M = 0.66 s, S.E. = .03) conditions, all of which differed significantly from each other, p < .05. Glances made into the vehicle did not differ significantly depending on road type F(2, 220) = 2.20, p > .05.
3.5.2.3. Off road. The off-road AOI was defined as any area surrounding the roadway; including signs, buildings, parked cars, and grass medians. Task difficulty did not have a significant effect mean glance durations made off road, F(2, 61) = 0.96, p > .05. Nor did road type have an effect on off-road glances, F(2, 148) = 2.58, p > .05.
3.6. Secondary task performance
3.6.1. Task completion time (TCT) Time needed to complete each task was analyzed using
SimObserver and Data Distillery and began when participants made their first movement toward the device to begin the task until the task was completed. Because various songs were required for each difficult iPod interaction, they differed in their position in the menu system. Therefore, song position in the menu system was used as a covariate to account for differences in task time due to distance in the menu system. All analyses were performed on each of the secondary tasks separately. Adjustments for violations of sphericity using the Greenhouse–Geisser correction are indicated with a GG next to certain results (Tabachnick and Fidell, 2006).
3.6.1.1. Difficult iPod interactions. Task completion time (TCT) for the difficult iPod task differed by session, F(5, 270) = 9.94, p < .001. Task completion time in the first

This study examined the effects of repeated iPod interactions on driver performance to determine if performance decrements decreased with practice. A multi-measure approach was used to understand the range of driver performance dimensions including hazard detection and response, lateral vehicle control, eye movements, and secondary task performance. A comprehensive and convergent view of the effects of distraction on driver performance with practice is evident.
4.1. Hazard detection
iPod interactions impaired drivers’ ability to respond to hazards on the roadway and maintain safe vehicle control. The difficult iPod interactions resulted in decrements to PRT. Over the events and occurrence, PRT increased by 0.18 s or 16% over the baseline when performing the difficult iPod task, depending on event type. During the difficult iPod interactions, a 0.42 s increase in perception time was found for the first occurrence over that of the baseline for the braking events.
Overall, a 16% increase in PRT was found for braking events in the present study. However, a 26% increase in PRT during the difficult iPod interactions over the baseline was found for the first occurrence of the lead vehicle braking events. iPod interactions are both cognitively and visually absorbing, requiring attention to be directed away from the roadway and to the interface. Second, when an event occurs, attention must be disengaged from the iPod back to the roadway. Many argue that prolonged glances away from the road pose increase crash risk (Dingus et al., 1989; Green, 2007; Klauer et al., 2006). Support for this argument is provided in this study by the higher frequency of collisions while interacting with the difficult iPod tasks (53) than during either the easy iPod (34) or the baseline drives (28).
During the easy iPod tasks, no consistent detrimental effects were found. The easy iPod task took very little time to complete (M = 4.39 s). The average time to complete difficult iPod tasks was approximately 35 s. This difference in task completion

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time had varying effects on driving performance. Specifically, the longer difficult iPod tasks exhibited consistent detrimental distraction effects, whereas the detrimental effects of the easy iPod task were brief and transient.
While iPod interactions had a consistent detrimental effect on hazard detection, vehicle control, however, was affected by the difficult iPod task. Previous studies on cell phones (Shinar et al., 2005) and speech-based e-mail (Jamson et al., 2004) found a significant decrease in steering wheel variation while drivers were engaged in conversations or e-mail, respectively. Participants in this study had greater amounts of steering angle variability in the difficult iPod condition than in the baseline. Cell phone conversations and speech based e-mail tasks do not require a driver to physically manipulate something, and thus may not affect steering per se. Therefore, the driver is able to focus on the road and control the vehicle. Completion of the difficult iPod task, however, required attention to be directed into the vehicle and physical manipulations to be made. In particular, iPod interactions required attention to be focused, in a serial fashion, between the iPod and the roadway to accomplish both tasks. On average, it took approximately 17 glances into the vehicle to complete a difficult iPod task.
The largest eye movement effects occurred between the difficult iPod and baseline conditions. Glance durations toward the roadway during the difficult iPod task were 0.27 s shorter. Furthermore, average duration of glances into the vehicle during difficult iPod tasks was 1.16 s compared to 0.54 s in the baseline. This increase in glance duration is similar to previous findings (Green and Shah, 2004). Normal glances into the vehicle are shorter in duration than glances towards the center of the road, 0.41 s and 0.73 s, respectively (Olson et al., 1989). Attention to in-vehicle tasks caused other sources of driving information to be dropped from scan patterns (i.e. off road objects and rearview mirror). A serial sampling between in-vehicle task and immediate forward roadway resulted (cf., Horrey et al., 2006; Wierwille, 1993).
4.2. Prolonged experience
The purpose of a multiple-session approach was to determine if repeated practice of the secondary task while driving in demanding contexts would lessen the detrimental impact of the distraction on driver performance. The present study used an event-based paradigm to examine the impact of a common MP3 player on distraction. Although decreases in PRT were found with practice, performance with the difficult iPod task never achieved the same level of performance as in the baseline condition. Even after additional practice, drivers were still unable to improve their dual-task performance to a safe level. This study found improvements in performance over the six sessions. However, it did not determine the extent of experience over which participants might continue to improve. Presumably a plateau or “ceiling” would be reached and no additional practice would affect performance. Single session or cross-sectional studies may not provide an accurate picture of cumulative distraction effects. Results are likely to differ with driver practice.

Fig. 6. Frequency of glances made into the vehicle and task completion time (s) for the easy iPod and difficult iPod interactions.
Multiple session studies do provide information with which to determine the practical effects of in-vehicle distractions over time compared to single session designs. For instance, Shinar et al. (2005) found repeated trials of conversation with a cell phone lessened the performance decrement on the vehicle control measures of speed maintenance, lane positioning, and steering wheel deviations. Shinar et al. (2005) did not measure PRT or eye movements in their study.
4.3. Distraction metrics
Two metrics have been suggested to quantify distraction potential of in-vehicle devices. These include number of glances to the device and task completion time (Blanco et al., 2005; Green, 1999b). Tasks that require more than nine glances or greater than 15 s to complete statically represent problematic tasks that should not be engaged while the vehicle is in motion. As illustrated in Fig. 6, using the suggested metrics of task completion time and glance frequency, the easy iPod tasks (filled circles) conform to the suggested criteria of less than nine glances and 15 s completion time. However, the difficult iPod results (open circles) took, on average, 17 glances and 35 s to complete the task. The difficult iPod interactions are clearly not appropriate to perform while the vehicle is in motion.
4.4. Conclusion
Complex multi-interaction tasks such as the difficult iPod task in the present study impaired perception and response to hazards and increased the frequency of collisions. Difficult interactions also require numerous glances to be made into the vehicle and prolonged interactions to complete.
Actual iPod use in-vehicles is likely to produce greater performance decrements than those recorded in this study. iPods are frequently placed in the lap of the driver or in the center cup holder. Interaction with it is accomplished by holding and

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looking at it. These results are conservative estimates of actual behaviour as task times did not include the time to pick up the iPod or glances further into the vehicle.
Many vehicle manufacturers have made integration of iPods into vehicles a necessary “lifestyle enhancement” capability. The multivariate results of this study suggest that access to difficult iPod tasks while vehicles are in motion should be curtailed. Vehicle manufacturers and Apple, in cooperation, should lock out these functions, while the vehicle is in motion before legislation to address this problem is required. Future research should identify related device functions (e.g., on other MP3 players, Blackberries, iPhones, and so forth) that produce prolonged glance behaviour and tasks interactions.
Acknowledgments
Bill Horrey and another anonymous reviewer provided valuable guidance about the focus and clarity of this manuscript. A debt of gratitude is owed to Elise Teteris and Lisa Fern for their assistance in the development, recruitment and running of participants, and data reduction. Don Kline, Saul Greenberg and Chris Edwards keenly edited earlier versions of this manuscript. Mike Boyle programmed several real time and data reduction modules. Tak Fung provided statistical consultation on several aspects of the experimental design. Funding for scenario development, experimental execution, participant payment, data reduction, and statistical analyses was provided by the AUTO21 Network of Centres of Excellence (NCE) and the University of California at Berkeley/PATH. An abstract of this paper was presented at the 4th International Driving Symposium on Human Factors in Driving Assessment, Training, and Vehicle Design in Stevenson, WA.
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