Driving while distracted: effects of in-vehicle
information systems (IVIS)
Distraction as a cause of accidents:
Stevens and Minton (2001): 5,740 fatal accident reports
from 1985-1996: 2% involved distraction - passenger, radio,
eating.
Lansdown (2002): recorded drivers' eye-movements in a
simulator while using the radio-cassette. Actions took over
half a second - 30 ft. at 40 mph.
Hanowski et al. (2005): naturalistic study of truck drivers.
7% of "2737 critical incidents" due to distraction. Risk
depends on frequency, time to complete an action, and
visual demand.
Wallace (2003): distraction may account for 10-30% of all
accidents - a significant threat to road safety.
Stutts et al. (2003): 70 drivers with instrumented cars:
Percentage of drivers engaging in distracting activities during 3 hours of driving, and
percentage duration of these activities while in motion:
Potential Distraction
% of Subjects
% of Total Driving Time
Talking on cell phone
30.0
Answering cell phone
15.7
Dialing cell phone
27.1
Eating, drinking, spilling
71.4
1.45
Preparing to eat or drink
58.6
3.16
Manipulating music/audio controls
91.4
1.35
Smoking (includes lighting and extinguishing)
7.1
1.55
Reading or writing
40.0
0.67
Grooming
45.7
0.28
Baby distracting
8.6
0.38
Child distracting
12.9
0.29
Adult distracting
22.9
0.27
Conversing
77.1
15.32
Reaching, leaning, etc.
97.1
Manipulating vehicle controls
100.0
Other internal distraction
67.1
External distraction
85.7
1.30
3.78
1.62
Theoretical models of dual-task performance:
Schneider and Shiffrin (1977): distinction between
"automatic" and "controlled" processing.
Norman and Shallice (1980, 1986): lower-level "contention
scheduling" and higher-level "supervisory attentional
system".
Could experienced
drivers rely on
contention
scheduling, leaving
plenty of spare
capacity for other
tasks (hazard
perception, radio,
phone use)?
Hockey's "compensatory control theory":
Drivers might preserve performance on "primary"
driving-related tasks (e.g. lane-keeping) by withdrawing
resources from "secondary" tasks (e.g. use mirrors less).
Problem is ensuring drivers assign priority to the correct
tasks (Cnossen, Meijman and Rothengatter 2004).
Loop A: routine/welllearned behaviour handled
b y automatic processes.
Loop B: activated if
mismatch between actual
and desired performance change task goals or
change amount of effort
expended.
Wickens' (1984) "multiple resource theory":
task interference affected by 3 factors mode of information input (auditory, visual, tactile);
type of coding (spatial or verbal);
type of response (manual or visual).
Driving involves visual
input/ spatial code/
manual output .
Phoning involves
auditory input/verbal
code/vocal output.
Therefore should not
compete for the same
resources.
Empirical data on risks of mobile
phone use:
1. Accident statistics
2. Driving simulator studies
3. Real-world driving
1. Studies of accident data:
Difficult, since phone-use was rare until recently.
55% of all U.S. citizens own a phone (U.S. Census 2004).
Stutts et al. (2002): 54.7% of 1006 North Carolina
interviewees reported using a phone while driving.
Sullman and Baas (2004): 57% of NZ participants used a
phone at least occasionally while driving. 17% hands-free.
Gras et al. (2006): over 60% of 371 Spanish university
workers used a mobile phone at least occasionally while
driving. 14% hands-free.
0.5% thought using a phone was not at all hazardous.
Redelmeier and Tibshirani (1997):
Case-control study.
Itemised phone bills of 699 Toronto drivers who owned a
phone and reported a crash.
Estimated when the accident occurred, and whether the
phone was in use at the time.
Compared this time to a comparable time-period on the
previous day.
If phone-use increases accident risk, more calls should
occur in the period before the collision than in the
corresponding period on the accident-free day.
If phone-use does not increase accident risk, should be
no systematic difference in phone use between the two
periods.
Redelmeier and Tibshirani (1997) (cont.):
Risk of a collision within 10 minutes of using a phone
was 3 to 6.5 times greater than when a phone was not
used.
24% had used their phone during the 10 minutes before
their accident.
5% had used their phone during the same period the day
before.
Collision risk was similar for all types of driver (young or
old, experienced phone users or inexperienced users).
No difference between hand-held and hands-free.
Laberge-Nadeau et al. (2003):
Questionnaire to 22,942 male and 13,136 female Quebec
drivers.
41% of males and 25% of females owned phones; 90%
used it while driving.
16% of users had an accident in previous 2 years,
compared to 13% of non-users (no sex-differences).
OddsRatio = 1.3 - 1.4, depending on age-group.
The greater the use, the worse the risk.
Frequent phone users (>100 calls/month) had twice the
accident risk.
2. Driving simulator studies:
Alm and Nilsson (1994):
Emergency braking in response to a symbol in road
ahead.
With/without Working Memory Task on hands-free phone.
RT on easy (straight) roads increased from .95 to 1.3 sec.;
no difference on hard (curvy) roads.
Alm and Nilsson (1995):
Emergency braking in response to sudden braking by car
in front while using/ not using hands-free phone.
29 year-olds: RT increased from 1.6 to 2.2 sec.
68 year-olds: RT increased from 2 sec to 3.5 sec.
No compensation by increasing headway.
Strayer and Johnston (2001):
RT to red light while tracking with a joystick.
Listened to radio, conversed with absent experimenter or
undivided attention.
No difference between hands-free and hand-held phones:
missed 7% of red lights, compared to 3% in undivided
attention condition, and 40 ms increase in RT.
Radio condition (and passively listening to a book being
read) were similar to undivided attention condition.
Conclusion: merely listening to information does not
significantly impair performance - active engagement in
conversation via a phone is the problem.
Strayer, Drews and Johnston (2003):
Motorway driving in simulator: car following in heavy or
light traffic, in silence or with natural conversation.
Heavy traffic/phone use condition:
180 msec slower to react to lead car's braking.
Increased headway, but inadequate to cope with
impairment.
3 rear-end collisions.
In heavy traffic, other vehicles may have distracted
drivers' attention from the lead vehicle - "change
blindness" effects.
Beede and Kass (2006):
Simulated driving, with/without a primarily visuo-spatial
conversation on a hands-free phone.
Also with/without an arrow detection task.
Phone use narrowed attention: poorer on peripheral red
arrow detection task.
More violations, more attention lapses, less frequent lane
changes, but quicker RT to events in line of sight (by 0.03
sec).
3. Real-world driving:
Brookhuis, de Vries and de Waard (1991):
Effects of hands-free and hand-held phones on
motorway, ring-road and city driving.
Drove instrumented car, following experimenter's car.
No significant effect on RT to lead car's braking; but
small N (12).
Phone-use increased workload (heart-rate).
Effects at tactical and strategic levels, not at operational
level - affected speed choice and mirror-use, but not lanekeeping (except when dialling).
Patten, Kircher, Ostlund and Nilsson (2004):
Effects of hands-free and hand-held phones on peripheral
detection task during undemanding (motorway) driving.
Task: respond to small lights appearing on windscreen.
Professional experienced drivers, used to mobile phones.
No difference between hands-free and hand-held phones.
Undivided attention: RT = 584 msec, 4% of lights missed.
Both phones, simple arithmetic: 656 msec, 15% missed.
Both phones, complex arithmetic: 845 msec.
Small, but inadequate, compensation by speed reduction
in hand-held condition.
Cooper and Strayer (2008):
Similar impairments for experienced and inexperienced users.
Strayer, Drews and Crouch (2006):
RT was worse when using a phone than after 0.08% alcohol.
Horrey and Wickens (2006):
Meta-analysis of 22 studies. RT increased by an average of .13
seconds. No difference between hand-held and hands-free.
Caird et al (2008):
Meta-analysis of 33 studies (2000 participants).
RT increased by .25 seconds, with no accompanying increase in
safety margins.
Why does mobile phone use increase
accident risk?
Recarte and Nunes (2000):
Verbal and spatial imagery tasks while driving.
Both increased pupil dilation (workload indicator).
Both tasks reduced gaze distribution -
verbal task by 25% horizontally and 40% vertically;
spatial task by 40% horizontally and 60% vertically.
Spatial task produced "eye freezing" - long fixations.
Both tasks reduced number of glances to internal mirror no task: 14/1000, verbal task: 4/1000, spatial task:2/1000.
Offside mirror inspections decreased from 4% of
fixations to <1% during both tasks.
Effects of visual imagery on driving performance (Briggs,
Hole and Land 2007):
Conversation often involves imagery.
Imagery and perception share processing systems.
Effects of mobile phone conversations on driving might arise from the
imagery component of the conversation.
"What did you do yesterday?"
"Oh nothing much dear, just picked up a
couple of hitch-hikers..."
1. Effects of imagery on hazard detection:
High and low imagers.
Primary driving-related task: video-based hazard
detection.
Secondary task: sentence verification, with imageryinducing or non-imagery-inducing statements:
‘In a rowing boat, the rower sits with his back to the
front of the boat'
versus
‘The official language of Mexico is Spanish’.
Number of hazards detected:
detected
ofofhazards
number
Mean Mean
Number
Events Reacted
To
7
High imagers
6
Low
High Imagers
Low Imagers
imagers
5
4
3
2
1
0
Undistracted
Undistracted
Imagery
Imagery
No Non
imagery
Imagery
Experimental Condition
Experimental
condition
Distracted participants detected fewer hazards.
Distraction worse if it involved imagery.
Effects worst for high-imagers with imagery distraction.
Reaction times to respond to hazards:
Time to respond to pedestrian stepping in front of vehicle:
(seconds)
Mean
Mean
RTRT
for Event
Four (secs)
2.5
HighHigh
imagers
Imagers
2
Imagers
LowLow
imagers
1.5
1
0.5
0
No Driving
Undistracted
Imagery
Imagery
Imagery
No Non
imagery
Experimental Condition
Experimental
condition
Distracted participants much slower to react.
Imagery-distraction worse than non-imagery distraction.
Unaffected by participants' imagery ability.
Hancock, Lesch and Simmons (2003):
Combined phone use with emergency stopping decision on
test track.
Drivers' RTs slowed by dual-task; therefore brake harder.
(a) Normal driving = "long
periods of sub-critical
demand interspersed with
moments of crucial
response, or hours of
boredom and moments of
terror".
(b) Emergency responses
are not over-learned, and do
not allow drivers to adapt
their control actions.
Stop light detection rates:
No phone: 95% Phone: 80%
Gugerty, Rakauskas and Brooks (2004):
Simulated driving while performing a verbal task with a
partner who was present or remotely located.
Remote interactions were slower (more difficult) and
degraded situation awareness more.
Crundall, Bains, Chapman and Underwood (2005):
Driving in silence, in conversation with passenger, or in
conversation on mobile phone.
Passenger sighted or blindfolded.
Similar distraction from blindfolded passenger and
mobile phone - both worse than sighted passenger.
Conversation suppression by sighted passengers.
Drains on processing
resources
maintain
conversation without
visual cues
mobile
phone
problem solving
Working Memory for
conversation
mental imagery
emotional effects of
conversation
Immediate
consequences
Ultimate
consequences
compensatory
behaviours - drive
slower, use
mirrors and
indicators less
compensatory
behaviours - rely
more on
expectations
reduced eye
movements
increased RT to
unexpected
hazards
less situational
awareness
poorer hazard
detection
earlier onset of
fatigue
lane-keeping
driving
vehicle control
situational awareness
hazard anticipation
hazard detection
increased accident risk
from failure to cope in
critical / unexpected
situations
Drivers' beliefs about the risks of using
a mobile phone while driving:
Strayer, Drews and Johnston (2003):
50% of the drivers in their study thought their driving was unaffected
by phone use, a belief unsupported by the data.
Said they had noticed other people driving erratically!
Lesch and Hancock (2004):
Rated confidence in coping with distractors while driving was
correlated with actual driving performance in males, but not females
(whose emergency braking RTs were also more affected by
distraction).
Horrey and Wickens (2008):
Drivers are unaware of how much they are impaired: no correlation
between self-rated and actual driving performance.
Conclusions:
In-car distractions pose a significant threat to road safety.
Mobile phones particularly problematic, because of
(a) cognitive burden of maintaining conversation;
(b) remote conversers are unaware of driver's situation
(and hence are more distracting than passengers);
(c) visual imagery in conversation may compete directly
with visual perception of surroundings;
(d) involve relatively extended periods of distraction.
Increases RT by c. .5 sec, reduces situational awareness.
Hands-free are no safer than hand-held because the
primary problem is distraction, not loss of vehicle control.
Problem of in-car distraction will get much worse:
Satellite Navigation systems, emailing, internet access,
warnings generated by collision-avoidance systems, lanedeparture systems, augmented road-signs, traffic flow
information, etc.
Microsoft aim to turn cars into mobile offices; telematics
is a lucrative market.
"Hands-free / voice-based" is not necessarily safe cognitive demands of auditory IVIS interfere with visual
processing during driving (Blanco et al. 2006, Harbluk et
al. 2006).
Garmin Nuvi 1690 - available now...
Norman (2004, 2005): Humans are inherently distractible -
Good for survival on the Savannah...
Bad for survival on the M25 !
Photos © Kristin Oguntoyinbo/University of North Carolina Highway Safety Research Centre