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P. J. Treffner, A. J. Petersen, and R. Barrett
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Speaking on a Hands-free Mobile Phone While Driving Degrades Perception of
Affordances
P. J. Treffner
1
, A. J. Petersen
1,2
, & R. Barrett
2
1
Complex Active Visualisation (CAV) lab, School of Information Technology, Griffith
University Gold Coast, PMB 50, Gold Coast Mail Centre, QLD 9726, Australia.
2
School of Physiotherapy & Exercise Science, Griffith University Gold Coast, PMB 50, Gold
Coast Mail Centre, QLD 9726, Australia.
To appear in: Vision in Vehicles 10, University of Derby Press, 2003.
The current study investigated the biomechanical and attentional demands of driving while
using a hands-free mobile phone under realistic conditions of driving on a closed-circuit track.
Results show that during cornering, controlled braking, and obstacle avoidance, perceptual
control of action is degraded when compared to control conditions where mobile phone
conversation is absent. Interpretation of the results is motivated by ecological psychology’s
theory of affordances and suggests that it is a driver’s direct perception of which actions the
road affords that is compromised when simultaneously speaking using a mobile phone.
1. Introduction
A major psychological factor underlying the cause of driving and locomotion accidents is
considered to be insufficient attention to the relevant dimensions of the optic array (Schiff &
Arnone, 1995; Warren & Wertheim, 1990). The antecedent of inattention—adverse cognitive
activity—can detrimentally affect concurrent driving performance. This is nowhere more
dramatic than in cognitive activities such as concurrent phone use during the largely
perceptual task of driving (Haigney & Westerman, 2001). Although manual handling of the
mobile phone can lead to pronounced distraction while driving (Salvucci & Macuga, 2002),
and although speech articulation has evolutionary origins in manual gestures (Corballis, 2002;
McNeill, 2000; Treffner & Peter, 2002), a more subtle effect of mobile phones involves the
fact that coordination can be degraded if directed attention or other cognitive activity is
introduced in addition to the primary task (Pellecchia & Turvey, 2001). For example, if one
focuses attention on one’s dominant (preferred) hand in a bimanual coordination task, then an
increased asymmetry results which may be detrimental to performance (Amazeen, Amazeen,
Treffner & Turvey, 1997; Riley et al., 1997). In sum, there appears to be an inherent relation
between cognitive activity, speech, and motor coordination.
Although use of hand-held mobile phones is becoming increasingly illegal in states world-
wide, hands-free usage (using either speaker or earphone) remains legal in most countries.
Speaker-based phones have been shown to create greater cognitive workload and frustration
than earphone-based systems (Matthews, Legg, & Charlton, 2003) but this fact has not yet
been recognised by manufacturers or users. Indeed, the availability of mobile phones has been
considered an asset to road-users (e.g., to call emergency services; Chapman & Shofield,
1998; Nunes & Recarte, 2002). However, cost benefit analysis fails to indicate a definite
advantage for mobile phone use in driving situations (Cohen & Graham, 2003).
Consequently, hands-free mobile phones may still pose a serious health risk due to the

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behavioural consequences of their use during driving (Dreyer, Loughlin, & Rothman, 1999;
Haigney & Westerman, 2001; Rothman, 2000; Strayer & Johnson, 2001).
The mechanisms that underlie the influence that speaking on a mobile phone has on driving
are complex. However, both epidemiological and experimental studies converge on degraded
attention as playing a pivotal role. An epidemiological study of Toronto drivers who had
experienced an accident revealed that the likelihood of an accident was increased by a factor
of 4 (similar to being legally drunk) compared to when not using the phone (Redelmeier &
Tibshirani, 1997). Importantly, no difference was found between hand-held and hands-free
devices, and the increased risk was not relative to driving with no distractions; it was relative
to normal driving circumstances complete with distractions (e.g., car radio, passenger
conversation, etc.; Redelmeier & Tibshirani, 2001). Another epidemiological study showed
that New York drivers who spoke for more than 50 minutes per month on a mobile phone
while driving increased their likelihood of an accident occurring by at least 5-fold (Violanti &
Marshall, 1996). It has been confirmed that the heaviest users of mobile phones have more
than double the risk of an accident compared to the lightest users (Dreyer et al., 1999;
Laberge-Nadeau et al., 2003).
Experimental studies using simulators indicate that simultaneous mobile phone use
decreases a driver’s ability to detect a car ahead decelerating with an increase of 0.5 s in
reaction time and 1 s in time to contact (Lamble, Kauranen, Laakso, & Summala, 1999).
Concurrent phone use decreases speed adopted (Haigney, Taylor, & Westerman, 2000) and
increases by 30% the failure to respond to critical traffic situations (Hancock, Lesch, &
Simmons, 2003; McKnight & McKnight, 1993). Most dramatically, in an emergency stopping
scenario at 70 mph, use of a mobile phone increased reaction time and distance travelled by 8
m for a hands-free phone, 14 m for a hands-held phone, with both conditions more
detrimental than being legally drunk (which resulted in only a 4 m extension of braking
distance; Direct Line Insurance, 2002). Indeed, although more numerous than studies
involving actual road driving, simulator studies consistently report that mobile phone usage
degrades driving performance (Alm & Nilson, 1994, 1995).
The current experiment involved coordinated driving on a real track and investigated how
anticipatory control of actual driving is compromised while maintaining a hands-free mobile
phone conversation. Which aspects of the perception-action cycle for driving might be
affected by concurrent speech on a mobile phone?
2. Methods
Nine novice drivers (average age = 18.4 years) holding provisional licenses (average
driving experience = 19 months) completed driving tasks while simultaneously speaking on a
hands-free mobile phone. Testing occurred at the Holden Performance Driving Centre’s
closed circuit driving track (Fig. 1). A Holden Commodore sedan vehicle with automatic
transmission was instrumented with a range of biomechanical sensors and GPS (Doyle,
Treffner, Barrett, & White, 2000; Treffner, Barrett, & Petersen, 2002). Participants completed
two laps without phone conversations in order to develop familiarisation with the track
(Figure 2). For safety reasons, a driving instructor remained in the passenger’s seat during
testing.
Conversations involved presentation of two numbers to the driver from a track-side
researcher and these required an appropriate reply. The relations between “input” (from base
to driver) and response or “output” (from driver to base) were quantified according to
communication theory and the amount of information reduction between input and output

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(Pellecchia & Turvey, 2001). For example, there is less information in my utterance if I say to
you “seven” than if I say “four and three” since there are many different 2-number utterances
that can produce a sum of 7. In contrast, 4 plus 3 is definite as well as unique and specific to
its sum (i.e., 7). There were four conditions: (C1) 2-digit reversal (e.g., “one, two”…“two,
one”; 0 bits), (C2) summation (e.g., “one, two”…“three”; 2.7 bits), (C3) categorisation of a
resultant 2-digit number (less than or greater than 50 and also whether odd or even (e.g., “one,
two”…“less than, even”; 4.5 bits), and (NC) a control condition of no conversation.
Participants listened to the track-side researcher via a microphone/earphone attached to the
right ear and dialogue was maintained for the full length of a lap.
Three driving tasks consisted of cornering (at 80kmhr
-1
the driver approached a right-hand
hairpin corner that required deceleration for comfortable travel), controlled braking (at
80kmhr
-1
the driver decelerated and stopped before a stationary car at a traffic light simulated
by a line of boxes), and obstacle avoidance (the driver approached an obstacle course at
50kmhr
-1
and the manoeuvre involved a left-hand approach towards a traffic cone obstacle
followed by a swerve to the right and recovery back to the left lane). Three trials in each
condition were completed, task order was randomised, and drivers were informed that they
could use the full width of the track.
There were three hypotheses tested: (1) Conversing on a mobile phone will detract from a
driver’s ability to control a vehicle compared to when driving in silence, (2) conversation
level will detract from a driver’s ability to control a vehicle, and (3) driving while engaged in
a categorisation conversation will affect driving the most. Analysis of variance with repeated
measures was used to address the first hypothesis, while planned comparisons (simple and
Helmert contrasts) were used to address the second and third hypotheses. Simple contrasts
compared the dependent measure associated with a particular conversation level against the
NC condition. The Helmert contrasts tested the hypothesis that conversation affects driving
regardless of conversation type by comparing the combined mean (C-all) from C1, C2, and
C3, against the NC reference. Dependent measures included various kinematic and kinetic
measures as well as time to contact (TTC or tau) and the rate of change of tau (tau-dot) at the
initiation of braking (with tau measured to corner entry or front of boxes) (Lee, 1976; Lee &
Young, 1985; Yilmaz & Warren, 1995; Treffner et al., 2002).
Figure 1. Aerial view of the Holden
Performance Driving Centre.
Figure 2. GPS-based recreation of track
indicating cornering (A), obstacle avoidance
(B, C), and controlled braking (D) sections.

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3. Results & Discussion
During cornering, the position of the vehicle when the accelerator pedal was released was
marginally closer to the corner for C-all (65.19 m) compared to NC (68.92 m), F(1,8) = 4.01,
p = 0.08. The distance from the corner at which initial brake depression occurred was
marginally significant (50.11, 47.02, 45.11, and 47.80 m, for NC, C1, C2, C3, respectively),
F(3,24) = 2.90, p = 0.06, and was closer for C-all (46.64 m) compared to NC (50.11 m),
F(1,8) = 8.90, p < 0.05. With conversation, drivers were closer to the corner when initiating
control actions than when not conversing.
When breaking was initiated, the instantaneous value of tau was lower for C-all (2.37 s)
than for NC (2.53 s), F(1,8) = 7.15, p < 0.05 (delay = 0.16 s), and was marginally lower for
C3 (2.34 s) than for NC (2.53 s), F(1,8) = 4.94, p = 0.06 (delay = 0.19 s). In accord with the
“field of safe travel” concept of Gibson and Crooks (1938), drivers may have misjudged the
corner’s affordance properties and did not anticipate the upcoming corner and initiate control
actions as effectively when maintaining a conversation as when not. Comparatively, non-
simulator studies showed that emergency brake responses under phone usage ranged from
0.38 s for older females to 0.07 s for older males (Lesch & Hancock, 2003) and that responses
are delayed under phone use (Hancock, Lesch, & Simmons, 2003). Since attention has been
compromised, the ability to detect the prospective information for safe locomotion may have
been compromised (Lee & Young, 1985).
During controlled braking, the distance to the boxes when the driver depressed the brake
was not significant but the effect of type of deceleration (as indexed by tau-dot) was so.
Deceleration for NC yielded a smaller tau-dot (0.53) compared to C-all (0.55), F(1,8) = 5.97,
p < 0.05. Similarly, deceleration for NC yielded a tau-dot (0.53) less than for C3 (0.56),
F(1,8) = 5.87, p < 0.05. Thus, deceleration during conversation yielded information
specifying a “hard contact” (tau-dot > 0.5) more so than when breaking without conversation
(which yielded a braking style more consistent with smooth constant deceleration and tau-dot
≈ 0.5) (Yilmaz & Warren, 1995). The degree of braking was therefore less when conducting a
mobile phone conversation and
For the obstacle avoidance task the average approach velocity to the entrance of the
obstacle course was marginally significant (51.13, 49.81, 50.54, and 50.34 kmhr
-1
, for NC,
C1, C2, C3, respectively), F(3,24) = 2.88, p = 0.06. Further, C-all (50.34 kmhr
-1
) was lower
than NC (51.13 kmhr
-1
), F(1,8) = 8.30, p < 0.05. Subsequent planned comparisons indicated
that when comparing C-all to NC, the average velocity was lower between entry marker and
the central obstacle (47.52 vs. 49.05 kmhr
-1
), F(1,8) = 5.33, p = 0.05, between the obstacle
and the exit marker (46.99 vs. 48.42 kmhr
-1
), F(1,8) = 6.48, p < 0.05, and that the average
departure velocity was lower (50.43 vs. 51.48 kmhr
-1
, F(1,8) = 14.17, p < 0.05. The preceding
results support the often-reported effect of driving slower under conversation (Haigney &
Westerman, 2001).
The lateral forces experienced during obstacle avoidance are unavoidable and potentially
detrimental to control of a vehicle. The first peak g-force associated with the initial obstacle
avoidance turn was not significant, although the time of the peak was later for C-all compared
to NC (3.21 vs. 3.14 sec), F(1,8) = 6.41, p < 0.05. For the second peak g-force, when the
driver steered around the obstacle, the planned comparison between NC and C-all was
marginally significant (0.48 vs. 0.44 g), F(1,8) = 4.85, p = 0.06, as was that between NC and
C3, (0.48 vs. 0.44 g), F(1,8) = 4.86, p = 0.06. The timing of this second peak was later for C-
all compared to NC (4.82 vs. 4.68 sec, respectively), F(1,8) = 9.90, p < 0.05. This continued

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with the timing of the third peak, which was later for C-all compared to NC (6.36 vs. 6.12 sec,
respectively), F(1,8) = 7.29, p < 0.05. Thus, under conversation there was a later onset of
lateral g-forces (which corresponds with the lower velocities observed), and suggests a
delayed or slower anticipatory response under critical conditions such as obstacle avoidance.
4. Conclusions
The hypothesis that more difficult conversations would lead to worse driving was
unsupported possibly because the novice drivers of the current experiment exhibited high
between- and within-subject variability. Others have shown that complexity of conversation
does matter and that simple conversations have a null or comparable effect to conversing with
a passenger (Nunes, & Recarte, 2002; Recarte & Nunes, 2003). However, the results from the
planned comparisons suggest that it is not difficulty of conversation, but conversation per se
that affects driving, and indeed the most complex task of categorisation was often
significantly different from no conversation. An issue for further investigation is to refine the
nature of the conversations used. Quantifying the complexity of a cognitive task is non-trivial
and although we employed communication theory in order to scale the difficulty of the three
cognitive tasks or conversations used (Pellecchia & Turvey, 2001), the procedure is not
perfect. For example, although repeating two numerals in reverse order involves zero
information reduction and appears to capture the triviality of this task, repeating the alphabet
backwards clearly is difficult but still yields zero information reduction. Alternative
procedures may involve more naturalistic, ecologically valid conversations (e.g., Nunes, &
Recarte, 2002) but building an acceptable and quantitatively testable theory upon such tasks
(such as perceptual-motor destabilisation using a dynamical systems approach; Kelso, 1995;
Kelso & Treffner, 1999) will then be all the more challenging.
With regards to the control of driving, the current results indicate that speaking on a hands-
free mobile phone while driving may degrade critical components of the perception-action
cycle such as exploiting prospective information about time to contact for the initiation of
crucial actions such as swerve and recovery (Cooper, Zheng, Richard, Vavrik, Heinrichs, &
Siegmund, 2003), or cornering and breaking (e.g., via tau detection; Cavallo & Laurent, 1988;
Cooper & Zheng, 2000; Land, & Horwood, 1995; Lee, 1976), and utilising this information
for on-line guidance of manoeuvres such as smooth braking (e.g., via maintaining tau-dot
close to 0.5 and thus maintaining constant deceleration; Kim, Turvey, & Carello, 1993;
Warren, 1998; Yilmaz & Warren, 1995).
A concept that is becoming increasingly used in telematics and HCI design is that of an
affordance—the perceivable possibilities for action in the environment (Norman, 1988/1990).
However, this concept has deeper origins in the perception-action or ecological approach to
psychology (Gibson, 1979/1986; Warren, 1984) which primarily focuses upon the issue of
what information in the ambient optic (or acoustic, haptic, or gravito-inertial) array can
specify upcoming events of critical importance to the organism (e.g., the affordance of an
upcoming bend in the road, or a wet and slippery pavement). Recently, a debate has emerged
as to whether there might be a single higher-order invariant or parameter of specificational
information, that this could involve the confluence of various arrays (e.g., optic, acoustic,
haptic, gravito-inertial), and that it is sensitivity to such a single parameter that is degraded
under conditions of diverted attention (Foque, Bardy, Stoffregen, & Boutsma, 1999;
Stoffregen & Bardy, 2001). Speaking on a mobile phone while locomoting would seem to
compromise critical anticipatory coordination and control actions when one’s attention is

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directed away from the central task of picking up information specific to the affordances of
the road environment.
Drivers can be trained to drive more effectively through guidance in techniques that
increase postural stability and consequently perceptual sensitivity to the critical multimodal
perceptual information available in the driving environment (Treffner, Barrett, & Petersen,
2002). Whether by using such techniques non-professional drivers might learn to cope with
cognitive distractions as effectively as do professional drivers who use telecommunications
regularly (e.g., taxi drivers) remains to be empirically tested. It seems more hopeful, however,
that new telematics and information technologies might be developed that can present
information that is more specific to the meaning of the conversation (e.g., via visual or haptic
modalities perhaps) and so lighten the cognitive burden (Laurie, Andres, & Fisher, 1999;
Stanney, 2002; Ware, 2000). Until then, drivers would do well to conform to laws banning
hands-held mobile phones (e.g., McCartt, Braver, & Geary, 2003) and adopt the personal
choice of no mobile phone—of any kind—while driving. Together with empirical evidence
that supports a deep speech-language-hand-gesture connection (Corballis, 2002; McNeill,
2000; Treffner & Peter, 2002), the available evidence clearly warns against participating in
dual task activities while driving such as maintaining a hands-free mobile phone conversation.
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