Emotions drive attention: Effects on driver's behaviour

Safety Science 47 (2009) 1254–1259

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Safety Science journal homepage: www.elsevier.com/locate/ssci

Emotions drive attention: Effects on driver’s behaviour Christelle Pêcher *, Céline Lemercier, Jean-Marie Cellier Cognition, Langues, Langage et Ergonomie (CLLE), UTM, EPHE, CNRS, Maison de la Recherche, Université de Toulouse le Mirail, 5 allée Antonio Machado, 31058 Toulouse Cedex 9, France

a r t i c l e

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a b s t r a c t

Keywords: Emotion Emotional valence Attention processes Driving Music

Music is the favourite activity while driving. However, very few studies have investigated its impact on driving performances. This study was designed to assess the effect of music’s emotional valence on driving behaviour. Happy, sad and neutral music excerpts were alternated with no-music phases while driving in a simulator. Results showed that happy music distracted drivers the most as their mean speed unexpectedly decreased and their lateral control deteriorated. Sad music influenced drivers in a different way as they drove slowly and kept their vehicle in its lane. These findings were discussed within the framework of attentional orienting and emotions. Ó 2009 Elsevier Ltd. All rights reserved.

1. Introduction

The combination of all musical characteristics conveys particular emotions (Bruner, 1990; Krumshansl, 2002). For instance, music with a low tempo, dissonant harmony and bass tones creates sadness (e.g. Tchaikovsky’s Overture from Romeo and Juliet, 1869) whereas music with a fast tempo, consonant harmony and highpitched sound makes people feel happy (e.g. Mozart’s Eine Kleine Nachtmusik, 1787), (Yvart, 2004). Gomez and Danuser (2007) question music as a vector of emotions and distinguish ‘‘represented emotions” (perceived by listeners) and ‘‘induced emotions” (felt by listeners), (2007, p. 377). A person may know what kind of music is presented but not necessarily feel the emotion the music is supposed to induce. The two types of emotions also involve different physiological, behavioural and psychological mechanisms, dependant on perceived arousal and valence of the musical emotion (Gabrielsson, 2002; Gomez and Danuser, 2007). Emotion is actually defined as an individual evaluation of an emotional relevant event. Consequently, each emotional experience varies in time and between subjects (Frijda, 1994). It is a complex process with different and complementary ways of expressing: physiological, behavioural and cognitive (Ekman, 1982; Frijda, 1986; Schwartz et al., 1981). This cognitive assessment integrates two main dimensions: arousal and valence. Arousal is the degree of physiological activation depicted in a vertical continuum stretching from the lowest to the highest degree (from calm and exhaustion to tension and excitement). Valence is a hedonistic value which corresponds to the way people experience a situation (pleasantness). It can be depicted in a horizontal continuum from the most negative emotional experience to the most positive (from sadness to joy), (Bower, 1981; FeldmanBarrett and Russell, 1998; Russell, 1980). However, the distinction between emotions is not so clear and Manichean (i.e., black and white). For instance, anger and sadness are both defined as

In their recent survey on in-car listening to music, Dibben and Williamson (2007) showed that listening to music while driving is the preferred activity of the majority of drivers. People report emotional effects as being their strongest motivation (Dibben and Williamson, 2007; Krumshansl, 2002; Sloboda et al., 2001). Interestingly, little is known about its effects on driving (Young et al., 2003). Our study is precisely set out to investigate this question by focusing on one particular characteristic of music – its emotional valence – on drivers’ attentional behaviour. Music is a multi-component physical object. It is composed of a set of sounds which are linked and ordered by specific ‘‘grammar” rules governing melody, mode, harmony, rhythm, tone and pitch (Mursell, 1932). So far, the majority of studies deal with the impact of tempo on cognition (Dalla Bella et al., 2001; Khalfa et al., 2008). In that sense, it has been demonstrated that performances improve with a fast musical tempo in the background. Some other studies have considered the impact of music tempo on behaviour in more complex and dynamic situations, such as driving (Beh and Hirst, 1999; McKenzie, 2004). Brodsky (2002) showed that the faster the tempo, the higher the impairment on driving performance. Three different tempos were presented (slow, moderate and fast tempo) as participants drove. Speed, speed estimation and the number of traffic violations (e.g. collisions, running red lights and straying onto another lane) increased with a fast music tempo. These results clearly indicate that music tempo alters driving behaviour, nevertheless, it does not reflect all the complexity of the music impact. * Corresponding author. Tel.: +33 0561 50 35 37; fax: +33 0561 50 35 33. E-mail address: [email protected] (C. Pêcher). 0925-7535/$ - see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.ssci.2009.03.011

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‘‘negative emotions” but their features (interpretation, appraisal, physiological state, action potential, overt behaviour etc.) are very different. The period from 1980 to the present day has provided a wealth of literature describing the impact of emotional valence on cognition and information processing (Chartrand et al., 2006; Chepenik et al., 2007; Schwarz and Clore, 1996). A negative emotion, such as sadness, is associated with an accommodative processing style where the attentional focus is narrowed to particular current elements of the environment (Fiedler and Bless, 2001). Empirically, sadness involves longer reaction times, a low self-esteem score, negative bias, distortions in judgement, pessimism (Power and Dalgleish, 2008; Gotlib and McCann, 1984; Silvia and Abele, 2002) and a tendency to self-focus and to ruminations (Lyubomirsky et al., 2003; Silvia et al., 2005). Conversely, a positive emotion such as joy is associated with an assimilative processing style, characterized by a broadening of attentional focus, i.e., the taking into account of future plans and actions (Fiedler and Bless, 2001; Rowe et al., 2007). It leads to shorter reaction times and an excessively high self-confidence score (which can result in greater risktaking) (Wright and Bower, 1992; Power and Dalgleish, 2008). A large number of studies highlighted this distinction between the two processing styles. For example, Koster et al. (2005) examined mood-congruent attentional bias in dysphoria. Dysphoric and non-dysphoric participants performed an attentional task with positive, negative and neutral stimuli. Results indicated that dysphoric participants maintained their attention on negative stimuli and failed to disengage attention from it, particularly for longer stimuli presentation. Koster et al. (2005) confirmed the mood-congruent effect and highlighted all the difficulties for dysphoric-depressed people in devoting their attention to all elements of their environment. Wadlinger and Isaacowitz (2006) observed a different pattern of results when inducing a positive emotion. Half of the participants were positively induced and half were non-induced before performing an attentional task with negative, positive and neutral visual stimuli. Results showed that induced participants fixated more highly-positive and peripheral stimuli than the control group and did more saccades for neutral and positive stimuli. Authors concluded that a positive emotion was not only associated with a broadened attention to positive stimuli but also this attentional broadening facilitated the maintenance of the current positive emotion. All these results demonstrate precisely that emotion and attention are linked and have an impact on performances. In a more complex and dynamic situation such as driving, however, the question of how performances are influenced still remains. In the research field of driving, the reciprocal influence between emotion and attention is of great interest. Driving requires high attentional resources (Chilsholm et al., 2008; Lemercier and Cellier, 2008; Wickens et al., 2008) in order to manoeuvre, control and plan (Dibben and Williamson, 2007; Michon, 1985; Young et al., 2003). Since the 1970s, a large number of studies have dealt with the impact of external (e.g. road, traffic, weather, in-vehicle systems, etc.) and internal variables (e.g. age, expertise, fatigue, drugs, etc.) on drivers’ attention (Levis-Evans and Charlton, 2006; Strayer et al., 2003). Mesken (2006) put forward that many emotions (as internal variables) occur while driving in both laboratory and onroad studies. Self-reports, questionnaires and driving simulations were used. In one study, the author noticed that drivers who experienced anger accelerated and committed more traffic violations than others. Mesken (2006) concluded that emotions influence traffic risk evaluation and general driving behaviour. Nevertheless, this conclusion is modulated with regards to other results about experiencing anger while driving. Anger is one of the most common negative emotion experienced during driving (Deffenbacher et al., 2002; Mesken et al., 2007), leading to aggressive driving

behaviour (Parker et al., 1998; Ellison-Potter et al., 2001). In this sense, angry drivers intentionally endanger others with aggressive verbal and/or physical expressions; they also use their car to trouble other users etc. (Deffenbacher et al., 2003). This aggressive behaviour needs to be distinguished from risky behaviour (Dula and Scott Geller, 2003; Deffenbacher et al., 2003) where drivers unintentionally perform dangerous actions (dangerous for themselves or others) such as speeding, manoeuvring without signalling, eating, drinking, phoning etc. While anger often involves aggression, other emotions like sadness, discontentment or joy are likely to impact on attention, leading to a different driving style. For instance, Bulmash et al. (2006) investigated the psychomotor disturbance in depression with a driving simulator. Major Depressive Disorder patients exhibited not only slower reactions times but also a larger number of car crashes when compared to controls. These results are consistent with reaction time deficits on cognitive tasks and an elevated risk of an accident due to delayed reactions in dynamic situations for sad and depressed individuals (Margolis et al., 2002). Again, it can not be generalized to all driving situations. For instance, Vassallo et al. (2008) studied the co-occurrence of risky behaviours and other problem behaviours among Australian drivers. They indicated that emotional problems such as anxiety and depression were not significantly associated with risky behaviours. In line with this theoretical and methodological background, the current study therefore sought to examine the effects of emotions on driver’s attentional behaviour. In order to convey emotion, happy, neutral and sad music excerpts were presented while driving on a simulator. It was assumed that listening to ‘‘sad” music would lead drivers to adopt an accommodative processing style, with a no risk, general slowing down, driving behaviour (Power and Dalgleish, 2008; Vassallo et al., 2008; Gotlib and McCann, 1984). In contrast, listening to ‘‘happy” music would lead drivers to adopt an assimilative processing style, characterized by fast driving and a tendency to take risks (Fiedler and Bless, 2001; Wright and Bower, 1992; Power and Dalgleish, 2008). 2. Method 2.1. Participants Seventeen volunteers participated in the experiment. The sample comprised eight men and nine women aged between 21 and 29 years old (Mean = 25.37, SD = 2.24). All participants had a valid French driver’s licence, for at least 4 years and with 10,000 km driving experience per year. They all had normal or corrected vision, and did not take any kind of medication. 2.2. Musical stimuli Eighteen 1-min music excerpts were selected for the experimental audio-track. Musical periods (named Driving with Music phase –DM-) alternated with silent periods lasting 1 min (named Driving Alone phase –DA-), (see Fig. 1). These silent periods were introduced to control for the effects of the preceding musical excerpt and to insure a recovery and preparation time for participants. The random presentation of excerpts basically created situations where music of the same emotional valence could be

DAneu

DMneu

DAhap

DMhap

DAsad

DMsad

Fig. 1. Organization of the music soundtrack with an alternation of Driving with Music phases (DM) and Driving Alone phases (DA). Music excerpts were happy (DMhap/DAhap), sad (DMsad/DAsad) or neutral (DMneu/DAneu).

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presented consequentially. Each DM phase was compared with the previous DA phase. For instance, DM hap (Driving with happy Music) was compared with DA hap (Driving Alone phase presented just before DM with happy excerpts). All 1-min excerpts had been pre-tested using the Self-Assessment Manikin scale (S.A.M., non verbal pictorial assessment technique, Bradley and Lang, 1994) with 30 students to discriminate the emotional valence. Thus, the experimental soundtrack contained six sad music excerpts, six happy music excerpts and six music excerpts. Excerpts were taken from soundtracks, instrumental pieces, and performances with lyrics. 2.3. Apparatus The fixed-based simulator used for the experiment was located at the University of Toulouse II-Le Mirail and consisted of a complete automobile (Renault 19) with automatic transmission. It was positioned 5 m in front of a 3 4 m projection screen, providing a 180° field of vision. Sensors on the steering wheel, accelerator and brake collected information about mean speed, proportion of Time to Line Crossing (T.L.C., time in seconds before going over the hard shoulder line), braking and accelerating amplitude every 200 ms. Both the training and experimental circuits were highways with two-lane traffic in each direction (separated by a grass median strip). The two scenarios used daytime dry-road conditions with good visibility. These circuits did not include other road users. Bend warning signs and road signs announced slight bends and sharp turns. 2.4. Procedure First, participants completed a questionnaire to assess their interest in driving and music. They were then given the opportunity to familiarize themselves with the driving simulator using a 15–45-min adaptation sequence. Training involved drivers controlling both trajectory and speed (40 km/h, 80 km/h, and 120 km/h). After a 5-min break, participants performed the experimental session for 37 min. Within this session, they had to drive in the right-hand lane, control their trajectory, maintain speed between 80 and 120 km/h and brake before significant bends. The experimental sound track was presented with an alternation of music periods (with three emotional valences) and silent periods of 1-min each. Drivers were told that driving was the priority, even in the presence of music. At the end of the experiment, all participants were individually interviewed to assess their feelings, describe their main difficulties while driving and express the impact of music’s emotional valence on their driving performances. Lastly, they were informed about the experiment’s goals and thanked for their participation.

3.1. Mean speed The analysis revealed a main effect of Phase [F(1, 16) = 50.54; MSe = 10.1; p = .000]. Mean speed was about 95 km/h for DM phases which increased to 99.4 km/h for DA phases. A main effect of Valence [F(1, 16) = 78.71; MSe = 7.8; p = .000] was found. An interaction between Phase and Valence [F(2, 32) = 36.83; MSe = 8.5; p = .000] was observed, (see Fig. 2). Planned comparisons revealed that mean speed decreased greatly for DMhap (86.6 km/h), compared to DAhap (97.5 km/h), [F(1, 16) = 67.27; MSe = 15.79; p = .000]. It increased slightly for DMsad (97 km/h), compared to DAsad (101 km/h), [F(1, 16) = 14.13; MSe = 4.79; p = .001]. Finally, DMneu (100 km/h) did not differ from DAneu (99 km/h), [F(1, 16) = 0.49; NS]. These results show that longitudinal control is dependant on the emotional valence of music. Happy music is associated with an important decrease of mean speed whereas it slightly decreases for sad music. There are no differences of mean speed for neutral music. 3.2. Proportion of TLC < 0.6 s Analysis indicated neither an effect of Phase [F(1, 16) = 0.06; NS], nor an effect of Valence [F(1, 16) = 0.72; NS]. However, there is an interaction between Phase and Valence [F(2, 32) = 6.91; MSe = 2.5; p = .003], (see Fig. 3). Planned comparisons revealed that the proportion TLC < 0.6 s increased for DMhap (9.7%), compared to DAhap (8.1%), [F(1, 16) = 160.17; MSe = 16.57; p = .000]. Proportion TLC < 0.6 s decreased for DMsad (8.5%), compared to DAsad (8.9%) [F(1, 16) = 118.52; MSe = 21.91; p = .000] and DMneu (7.5%) compared to DAneu (8.9%), [F(1, 16) = 132.41; MSe = 17.19; p = .000]. Results demonstrate that lateral control deteriorated for happy music (proportion of TLC < 0.6 s increases, indicating that participants drove closer to the hard shoulder line). Inversely, lateral control improved for both sad and neutral music (proportion of TLC < 0.6 s decreases, showing that participants drove far from the hard shoulder line). 3.3. Post-experimental individual interviews At the end of the experiment, participants were interviewed about their perception of the impact of music on their driving.

3. Results A 2 (Phase: Driving Alone –DA- and Driving with Music –DM-) 3 (Valence of music: happy –hap-, sad –sad-, and neutral –neu-) ways repeated measures ANOVA was conducted on both longitudinal and lateral parameters. Mean speed is the most common parameter to analyze longitudinal control and is expressed in km/h. Proportion of TLC < 0.6 s is an indicator of lateral control and corresponds to the proportion of time (in seconds) before driving over the hard shoulder line (the higher the proportion of TLC < 0.6 s, the closer the hard shoulder line). Planned comparisons between Driving Alone –DA- phases and Driving with Music –DMphases were performed in order to observe the specific effects of the emotional valence of music. An alpha level of .05 was used for all statistical tests.

Fig. 2. Mean Speed in km/h as a function of the emotional valence of music (happy, sad and neutral) and the phase (Driving with Music and Driving Alone phases).


Fig. 3. Proportion TLC < 0.6 s as a function of the emotional valence of music (happy, sad and neutral) and the phase (Driving with Music and Driving Alone phases).

All drivers reported that happy music was the most disturbing. Nearby 76% of drivers were distracted by music because they followed the melody, they sang, whistled, and/or clapped their hands. As one driver put it, ‘‘It was hard for me to control what I did with this kind of music because I had to follow the rhythm and lyrics. I felt good and, to be honest, driving was no longer my priority.” Interestingly, drivers described an opposite effect for sad music excerpts. Another driver reported that ‘‘with sad songs, I was calmer and I couldn’t help feeling sad. The rhythm and melody caught my attention and I couldn’t help listening to them. When sad songs were played, I tended to think about what was wrong with me, my job or my family.” At this point and contrary to happy music excerpts, experimenters observed that drivers were extremely focused as a result of keeping quiet and only 2% of them hummed songs. Still participants expressed the need to concentrate and be calm for this type of music; none of them noticed any important deterioration in their driving performance. This is an extremely interesting point in comparison with the perception of neutral music. One driver expressed it as ‘‘some of the music excerpts, the ones you called neutral, didn’t affect me at all. By this, I mean, I don’t know whether I felt happy or sad or both. I didn’t really listen when it was being played. I just kept on driving. The music just didn’t exist for me. It was useless”. Here, for 92% of drivers, music with a neutral valence was characterized by the absence of any effect on behaviour. 4. Discussion Previous research about driving has found that concurrent tasks (phone conversation, integrated systems manipulation or radio listening, etc.) impact on drivers’ attention. With regards to radio listening, studies have only dealt with the effects of listening to specific broadcasts (weather or political broadcasts). It is surprising because people actually spend most of their driving time listening to music on their radio or CD player, particularly for its emotional nature (Dibben and Williamson, 2007). In this study, we specifically examined the impact of music’s emotional valence on drivers’ behaviour. Results confirmed the contrasting effect of music on driving according its emotional valence. Driving with neutral music represented a baseline situation where drivers stayed concentrated on

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their primary task, driving. As a result, mean speed was maintained at 100 km/h for both neutral and no-music phases. Surprisingly, lateral control deteriorated with a significant decrease of the proportion of TLC < 0.6 s for neutral music, compared to no-music phases. It could be argued that each no-music phase was not only a recovery time but also a preparation and expectation time concerning music type of the next excerpt. In case of a neutral music excerpt, participants did not listen to it and they only wanted to drive as in their everyday life. Consequently, longitudinal control was not affected and the distance from the hard shoulder line reflected drivers’ natural tendency to be closer to the centre on straight roads, specifically in right-hand drive countries (Rosey et al., 2008; Steyvers and de Waard, 2000). When the neutral music excerpt ended, driving was re-adapted for a new preparation phase and so on. Driving with happy music involved a deterioration of control. Unexpectedly, if compared to a no-music situation, mean speed was slower (86.6 km/h) whereas the proportion of TLC < 0.6 s was higher, showing a tendency to stray onto the hard shoulder line. Nonetheless, it confirmed that drivers did not control their longitudinal and lateral driving parameters. In their report, 76% of our set of drivers agreed with the conclusion that happy music affected their behaviour most. They felt happy, joyful and tended to tap on their wheel or whistle along to the music. Happy music has particular technical characteristics (i.e., fast tempo, high pitch, happy lyrics etc.) which are, in essence, external sources which could attract drivers’ attention. They are not aware of their reactions to music (i.e., with tapping, singing along etc.) and they are easily distracted from their driving task (Posner, 1980; Lemercier and Cellier, 2008). Drivers who were particularly sensitive to happy music reacted with gestures and mimics, and unconsciously created a dual-task situation (for instance, driving and whistling) increasing their mental load (Blanco et al., 2006; Recarte and Nunes, 2002; Michon, 1985). They were no longer able to control their parameters, resulting in a deterioration of mean speed and proportion of TLC < 0.6 s. This first external attentional control also occurred when drivers listened to sad music excerpts. The consequences, however, were substantially different from the aforementioned situation. Mean speed slightly decreased (101 km/h with sad music, compared to 98 km/h without music) as well as the proportion of TLC < 0.6 s. Drivers not only tried to maintain a ‘‘no risk” speed but also to control their trajectory in the centre lane. In their report, they said their attention was automatically caught up by the rhythm or the lyrics of sad music (Posner, 1980). Nonetheless, they added that this type of music also induced a withdrawn attitude. It could suggest that attentional focus was progressively oriented to an internal stimulus. According to Posner (1980), internal control is voluntary, progressive and durable. Lemercier and Cellier (2008) defined it as inattention. Drivers involuntarily listened to music but they were gradually overcome with the emotion of the music and recollected personal emotional events that echoed the music. As a result, they had to adapt their driving to reduce all potential risks and to have enough time to correct their driving actions (Summala, 2002). Our findings supported the hypothesis of contrasted effects of emotions, according to its valence. However, the manipulation of this variable in a dynamic situation such as driving, considering the traditional opposition between positive and negative emotions, remains uncertain. Our results indicated that sad music would lead to no-risk driving whereas happy music would be associated with more dangerous driving (with regards to an unexpected speed decrease and a tendency to drive near the hard shoulder line). As a matter of fact, it would be clever to consider emotions not only for their valence but also for the consequences on drivers’ behaviour (i.e., in terms of risky/no risk, aggressive or passive behaviour

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and so on). For instance, negative emotions such as anger and frustration would lead to aggressive behaviour: faster speeds, extreme use of the brake and accelerator, verbal and physical aggression to others (Deffenbacher et al., 2002, 2003; Stephens and Groeger, 2006). Negative emotions as sadness and depression, conversely, would lead to a more passive attitude involving attentional self-focus, longer reaction times (Bulmash et al., 2006) and some attempts to control both lateral and longitudinal parameters, in a none risky way. Positive emotions such as joy and happiness would engage drivers’ and distract them with risk-taking and some difficulties in controlling both speed (decrease of mean speed) and trajectory (near the hard shoulder line). Finally, it could be supposed that another positive emotion like excitement would create a different driving style – speed increase, a better acknowledgment of stimuli on central vision, shorter reaction times but numerous driving errors (Brodsky, 2002; Turner et al., 1996). It is worth noting that this new and hypothetical classification of emotions requires both theoretical and experimental validation in different driving situations. Indeed, the use of music as an emotional stimulus is quite ecological while driving but some questions remain. Drivers were quite young and maybe more sensitive to the modern music presented in the experiment (for example, for a happy music excerpt we used ‘‘Everybody needs somebody” from The Blues Brothers soundtrack). Furthermore, the impact of neutral music has to be discussed. We are not sure that all participants definitively perceived all excerpts as neutral, despite the pre-test. Again, the distinction between ‘‘represented” and ‘‘induced” emotions is essential (Gomez and Danuser, 2007). Another methodological limitation of this current study is the type of road used for the experiment. It was a straight 2 2 lane highway (except for some slight curves), without traffic and road signs. Results could be very different in a more complex situation, as in slow traffic conditions on an urban road for instance. The current research is in keeping with other experimental studies on emotions and driving. We observed that music with different emotional valence distracted drivers’ attention with different ways of expressing. Further research may be directed in determining what exact attentional function (detection, orienting and control) is influenced by musical emotion. For this purpose, we aim to develop an adaptation of the Attentional Network Test (ANT, Fan et al., 2002) in a simulated and more complex driving task.

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