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Music genre induced driver aggression: A case of media delinquency and risk-promoting popular culture


Abstract and Figures

Few empirical studies have targeted the links between media delinquency or risk-promoting popular culture (specifically aversive music genres) with negative affective states and aggressive driving. Yet for over a decade, drivers have reported that they commit traffic violations while listening to loud fast-beat aggressive music styles. The current investigation seeks to explore aggressive driving behavior while considering the genre of music background. Most specifically, we look at aversive music styles and songs with violent lyrics. The article outlines the testimonials by drivers (N = 6,058) from six recent commercially solicited surveys with drivers which demonstrate “proof of concept” for driver aggression subsequent to driving with music accompaniment. Further, the article details a study (N = 50) employing a driving simulator with 30 paired music exemplars of 4 music genres. Half consisted of songs with hostile aggressive lyrics and half with neutral lyrics—both performed in the same music styles by the same artists. The results demonstrate that energetic music boosted excitement resulting in decreased lateral control, increased excursions from the lane, and an increased tendency to stray onto the hard shoulder. Drivers who were exposed to hostile music with violent content on the other hand demonstrated increased cruising speeds and a higher percentage of time exceeding speed limits. These differential effects of music on drivers can be referred to as either music-generated driver distraction or music genre induced driver aggression.
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Music genre induced driver aggression:
A case of media delinquency and
risk-promoting popular culture
Warren Brodsky
, Dana Olivieri
and Eugene Chekaluk
Few empirical studies have targeted the links between media delinquency or risk-promoting popular culture (specifically
aversive music genres) with negative affective states and aggressive driving. Yet for over a decade, drivers have reported
that they commit traffic violations while listening to loud fast-beat aggressive music styles. The current investigation seeks
to explore aggressive driving behavior while considering the genre of music background. Most specifically, we look at
aversive music styles and songs with violent lyrics. The article outlines the testimonials by drivers (N¼6,058) from six
recent commercially solicited surveys with drivers which demonstrate “proof of concept” for driver aggression subse-
quent to driving with music accompaniment. Further, the article details a study (N¼50) employing a driving simulator
with 30 paired music exemplars of 4 music genres. Half consisted of songs with hostile aggressive lyrics and half with
neutral lyrics—both performed in the same music styles by the same artists. The results demonstrate that energetic music
boosted excitement resulting in decreased lateral control, increased excursions from the lane, and an increased tendency
to stray onto the hard shoulder. Drivers who were exposed to hostile music with violent content on the other hand
demonstrated increased cruising speeds and a higher percentage of time exceeding speed limits. These differential effects
of music on drivers can be referred to as either music-generated driver distraction or music genre induced driver aggression.
Aggressive driving, driver anger, driving simulator, in-car music, music genres
Submission date: 20 June 2017; Acceptance date: 29 October 2017
In-cabin music accompaniment while driving a car is a
debated variable among researchers investigating factors
that have an impact on vehicular performance. Some claim
that in-cabin music accompaniment is advantageous (Unal,
2013; Unal, de Waard, Epstude, & Steg, 2013; Unal,
Platteel, Steg, & Epstude, 2013; Unal, Steg, & Epstude,
2012); they outline the constructive aspects of music-
evoked driver arousal. Others feel that driving with music
increases risk for miscalculations and inaccuracies, viola-
tions, incidents, and crashes (Brodsky, 2002; Brodsky &
Kizner, 2012; Brodsky & Slor, 2013); they outline the
destructive aspects of music-generated driver distraction.
Perhaps the reality is that listening to music while driving
offers both positive and negative qualities, while the crux
of the matter is not whether or not music is reproduced in
the vehicle cabin, but rather which structural features are
found within the music. The current article targets an issue
that has not as yet been raised in the safety literature: music
genre induced driver aggression. We first attempt to fill
this gap with a conceptual underpinning, and then sub-
stantiate the phenomenon through commercially solicited
driver reports and survey data. With some latitude, this
material may be seen as a prima facie effort to establish
“proof of concept.” Finally, we present a driving simulator
study that explores the impact of violent lyrics in popular
songs on vehicular performance. The overall goal of the
investigation was to provide a better explanation and
Ben-Gurion University of the Negev, Israel
Macquarie University, NSW Australia
Corresponding author:
Warren Brodsky, Music Science Lab, Department of the Arts, Ben-Gurion
University of the Negev, POB 653, Beer-Sheva, 84105, Israel.
Music & Science
Volume 1: 1–17
ªThe Author(s) 2018
Reprints and permissions:
DOI: 10.1177/2059204317743118
Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-
NonCommercial 4.0 License ( which permits non-commercial use, reproduction
and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and
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prediction of aggressive driving behavior by accounting for
music genre, rather than to target a specific music para-
meter or feature as an independent variable.
The main issue being raised relates to the distinction
between distracted driving and aggressive driving. Traffic
safety studies provide ample evidence that distracted driv-
ing involves impaired attention and/or judgment, while
aggressive driving involves intentionally unsafe and inap-
propriate behavior. In their re-analyses of data from the
100-car study (Dingus et al., 2006), Hanowski, Olson,
Hickman, and Dingus (2006) found a subset of 138
(56%) incidents that were caused by drivers themselves;
these indicated both distracted driving (23%) and aggres-
sive driving (25%). The data reveal the overriding factor
for at-fault incidents subsequent to distracted driving is
“deficient braking time when coming to a full stop,”
whereas at-fault incidents subsequent to aggressive driving
were caused by both “failing to keep a sufficient gap when
changing lanes” and “willingness to pass another car just
before a turn.” Keeping these factors in mind, one might
wonder whether music—most specifically songs with vio-
lent lyrics pertaining to certain music styles—affects driv-
ers differentially by generating driver behaviors associated
with either distracted or aggressive driving conduct.
Emotive effects of in-car music on driver anger
and aggressive driving
Anecdotal evidence from everyday road experience suggests
that people who have trait tendencies to get “hot under the
collar” and “infuriated” more easily, experience annoyance
(and even rage) while driving and drive in a riskier manner.
Mesken, Hagenzieker, Rothengatter, and de Ward (2007)
found that cruising speeds were faster when drivers felt an
overall affect involving anger, and the percentage of time
speed limits were exceeded was far greater when drivers
reported feeling angry. Other perspectives assume that mood
state (i.e., the prevailing felt emotion) modifies driver beha-
vior while in traffic (Abdu, Shinar, & Meiran, 2012). Mes-
ken et al. claim that drivers misperceive and/or miscalculate
concrete tangible driving risks when angry.
One feature of in-cabin environments that has a great
potential for emotive effects on drivers is music. Specifi-
cally, the emotional valence of the music selections seems
to influence how drivers control the vehicle (Brodsky,
2015). For example, Pecher, Lemercier, and Cellier
(2009) found that when “happy” music was heard, drivers
were easily distracted. Happy songs induced drivers to tap
on the steering wheel and hum the melody aloud, resulting
in decreased vehicular control, as demonstrated by lack of
longitudinal and lateral control, with increased excursions
from the lane, and a tendency to stray onto the hard
shoulder. Conversely, “sad” songs incited drivers to focus
attention on the gravity of the lyrics. Sad songs preoccupied
drivers’ internal thoughts, as demonstrated by slower
speeds with increased braking reaction times (RTs). Pecher
et al. envisioned a host of music-generated emotions that
could trigger distinctive driver behaviors: (1) joy or happi-
ness that would distract and increase risk-taking with abun-
dant crossing the midline of the lane; (2) excitement that
would arouse and increase speed with decreased RTs and
increase the frequency of errors; (3) sadness that would cue
passive attitudes involving withdrawn attentional self-
focus and longer RTs; and (4) frustration or anger that
would lead to outraged aggressive driving styles with
faster speeds, extreme use of brake/accelerator pedals,
hostile verbal responses, and physical viciousness. Con-
sidering this taxonomy of music-generated ill effects,it
would seem warranted to explore particular music gen-
res—especially those that promote anger and that may
foster aggressive driving.
Aversive music
Music genre is more or less a predictable categorization by
which listeners identify exemplars by a commonly
accepted set of conventions. For the most part, music gen-
res are equivalent, in the sense that every music style rep-
resents an aesthetic quality that any number of individuals
in the general population may prefer. Nonetheless, a few
have been labeled as problem music because long-term
listening and extreme fandom have been acknowledged
as harmful (North & Hargreaves, 2006). Indeed in some
cases, there is evidence for increased fatalities including an
increased frequency of suicide (Lacourse, Claes, & Ville-
neuve, 2001; Stack & Gundlach, 1992).
In a landmark study, Arnett (1991a, 1991b) demon-
strated that adolescents who preferred Heavy Metal music
styles reported higher rates of reckless behavior, including
sexual promiscuity (unprotected casual sex), drug use (mar-
ijuana, cocaine), antisocial conduct with minor criminal
activity (shoplifting, vandalism, damage to property), and
dangerous “stunt” driving. Roe (1995) found that adoles-
cents who tended to listen to Hard Rock and Heavy Metal
music performed more poorly in school, associated with
deviant peer groups, and invested massive amounts of time
watching violent television, while the opposite was true for
those “with a taste for more ‘acceptable’ types of popular
music” (p. 620). Roe developed a theory of media delin-
quency pointing to forms of antisocial behavior clustering
together and associated with the consumption of socially
devalued media content. Indeed, Heavy Metal music has
often been perceived as a form of rebellion (Delsing, Ter
Bogt, Engles, & Meeus, 2008; Dunn, de Ruyter, & Bou-
whuis, 2012; Getz, Marks, & Roy, 2014; Krcmar & Greene,
2000; McCown, Keiser, Mulhearn, & Williamson, 1997;
Mulder, Ter Bogt, Raaijmakers, Gabhainn, & Sikkema,
2010; Rentfrow & Gosling, 2006; Rentfrow & McDonald,
2010). It is a music style laden with heavily distorted elec-
tric guitars, pounding rhythms, and vulgar vocals, typically
played at extremely loud volumes while knowing that such
music exposure offends others in the environment.
2Music & Science
Although Roberts, Dimsdale, East, and Friedman (1998)
could not replicate Arnett’s original finding solely based
on music preference, they did find an equivalent picture
when “high negative emotion” was added as a covariate.
Arnett also reported that listeners who preferred Hard Rock
and Heavy Metal music styles demonstrated “lower self-
esteem” and “higher sensation seeking.” Sensation-seeking
is the characteristic engagement in hazardous menacing
activities with behavioral attitudes such as diminished risk
appraisal. Zuckerman (1994) reported that sensation
seekers drove at higher speeds, overtake vehicles in areas
of limited visibility, tailgate cars by keeping shorter head-
ways, and more often than not drive when intoxicated.
Moreover, and as might be expected, sensation seekers
prefer prototypical highly dynamic music genres such as
Classic Rock and Hard Rock styles (Litle & Zuckerman,
1986; Nater, Krebs, & Ehlert, 2005). Arnett not only sup-
ported Zuckerman’s findings regarding music preferences
among sensation seekers, but also demonstrated that
“Metalheads” reported a host of reckless driving behaviors
that were not seen for a matched group who preferred a
wider array of popular music styles. Accordingly, Heavy
Metal fans typically drive more frequently while drunk,
more frequently above 85 mph, and more frequently with-
out a seat belt. It is interesting to note that the same picture
was conveyed by Beullens (Beullens & van den Bulck,
2013; Beullens, Rhodes, & Egermont, 2014-2016), who
found that exposure to specific media among sensation-
seekers not only was linked to higher levels of aggression,
but also predicted levels of risk-taking in traffic and actual
crash involvement. Beullens established risky driving (such
as joyriding and crashes) as but one aspect of a lifestyle
among sensation seekers along with other features such as
high engagement with music videos and simulated driving
games, both of which explicitly depict sexual and violent
content accompanied by aggressive music styles including
Hard Rock, Heavy Metal, Rap, and Hip-Hop.
Although the general effects of risk-promoting media on
inclinations toward risk-taking have been summarized else-
where (e.g., see Fischer, Greitemeyer, Kastenmu
Vogrincic, & Sauer, 2011; Fischer, Guter, & Frey, 2008),
it raises the question of whether specific music genres
reflect media delinquency more generally. Arnett (1991a,
1991b) found that lyrics of Heavy Metal music enthusias-
tically encourage listeners to reject and disregard the more
accepted standard rules of society, as well as target unde-
sirable behaviors, including the transgression of traffic reg-
ulations, drug use, promiscuity, sadomasochism, Satan
worship, murder, and suicide. We would point out here that
the influence of lyrical content on destructive conduct is
not exclusive to Heavy Metal music. For example, many
studies demonstrate that listenersexposedtoHip-Hop,
Rap, and Rock songs with violent lyrics also report con-
frontational thoughts with hostile feelings as well as act out
aggressive behaviors more than matched listeners exposed
to neutral lyrics (Anderson, Carnagey, & Eubanks, 2003;
Carpentier, Knobloch, & Zillmann, 2003; Fischer & Grei-
temeyer, 2006; Krahe & Bieneck, 2012; Lennings & War-
burton, 2011; Smith & Bayson, 2002). Other studies
specifically target the lyrics as a component generating
affect and behavior. For example, songs with pro-equality
lyrics have been seen to improve attitudes and behavior
toward women (Clark & Giacomantonio, 2013; Greite-
meyer, Hollingdale, & Traut-Mattausch, 2015), and songs
with prosocial lyrics caused a reduction in reckless and
risky driving (Greitemeyer, 2013). Within the current
study, we use the term aversive music as a label for music
pieces that promote antisocial, dominating, degrading,
and demeaning materials. To be most specific in our oper-
ationalization of the concept, we exclusively use the label
violent (i.e., violent music, lyrics with violent content).
Nonetheless, perhaps listeners do not easily distinguish
between aversive music genres with neutral lyrics and
those with violent lyrics; and antagonistic thoughts or
feelings of anger, as well as tangible destructive vicious
behaviors, arise from either the hostile music backgrounds
themselves and/or the provocative lyrics. Certainly, if
aversive music leads to both anger and more general
aggressive conduct, it would be prudent to question
whether such music genre induced aggressive behaviors
occur within the dynamic context of driving.
Enlisting music genre to study negative driver affect
and aggressive driving
Social psychology studies exploring the everyday use of
music (Chamorro-Premuzic & Furnham, 2007; Delsing
et al., 2008; Lewis & Schmidt, 1991; Rawlings & Ciancar-
elli, 1997; Rentfrow & Gosling, 2003; Rentfrow, McDo-
nald, & Oldmeadow, 2009; Schwartz & Fouts, 2003) have
not explored the effects of music genre on ordinary drivers.
Even traffic safety investigations considering the impact of
background music on driver distraction have not classified
music genre as a contributing factor. Yet some time ago,
Matthews, Quinn, and Mitchell (1998) examined the
effects of loud Rock music and task-induced stress on
simulated driving. The findings demonstrated that loud
Rock music neither increased arousal to dysfunctional lev-
els nor distracted drivers from the primary task, but rather
supported resourcefulness when increased attention was
required. Most specifically, Matthews et al. found that loud
Rock music boosted driver ability to detect pedestrians (i.e.,
a high workload secondary task), with shorter braking RTs.
The study assigned participants to one of four conditions:
two music groups (listening to one song with headphones)
and two non-music groups. One music group listened to
“Brown-eyed Girl” [Van Morrison] and the other to “Two
Princes” [The Spin Doctors]. Yet we cannot rule out that the
findings were no more than effects of perceptual masking by
headphones in favor of the music groups, as the non-music
groups were exposed to room clatter, computer-generated
engine uproar, vibrotactile feedback of the road surface, and
Brodsky et al. 3
hardware clamor of the driving simulator. Indeed, music
genre is a most elusive feature and is particularly tenuous
when selecting exemplars as experimental stimuli to be used
as the criterion for empirical conditions. Most specifically,
traffic psychology researchers are unlikely to have the broad
theoretical music foundation or intensive instrument training
that music psychologists have, and hence the music pieces
they select might not always be fully conceptually justified
or reliable. For example, although Matthews et al. enlisted
two songs from an audio compilation packaged as relevant
for “driving activity” (i.e., TopGear-Rock, 1994, Epic
Records), the selected pieces might not have been ecologi-
cally valid. “Brown-eyed Girl” is a Pop song performed in a
Folk Rock style accompanied by a clear hollow-bodied
guitar, tapping tambourine, backing vocal ensemble in
chorus sections, and a slow-to-medium tempo (measured
at roughly 76 bpm). On the other hand, “Two Princes” is
distorted solid-bodied guitars, percussive snare drum rim-
shots, wailing guitar solos between the chorus sections, and
a medium-to-fast tempo (measured at roughly 110 bpm). As
the study contrasted drivers by affective states (i.e., stress vs.
nonstress) and intensity (i.e., 70 dBs vs. 90 dBs), it would
have been a stronger experimental manipulation to keep
musical features such as stylistic complexity within the
genre as constant.
Anger is a most widely studied human emotion within the
driving context. It has been considered to be both a predictor
of driver behavior and a trigger of vehicular performance
(Hauber, 1980). Underwood, Chapman, Wright, and Crun-
dall (1999) claimed that interest in driver anger is because its
manifestations not only relate to near-accidents, but also
indicate an overriding aggressive style of driving that pre-
disposes individuals to engage in dangerous behaviors such
as tailgating, speeding, flashing lights, and crossing intersec-
tions at amber. In light of this connection, we now discuss
three studies relating to music effects on aggressive driving.
The first, by Wiesenthal, Hennessy, and Totten (2000,
2003), found that drivers preferred or favorite music alle-
viated stress and anger in congested traffic. A total of 40 par-
ticipants (21–50 years old) drove a single 30-min trip on a
major highway, whereby one segment featured flowing traf-
fic and another congested traffic. The drivers were randomly
allocated to one of two conditions: listening to preferred/
favorite music tapes (or radio broadcast) or silence (i.e.,
refraining from listening to music altogether including radio
and talk shows). The most preferred/favorite music styles
heard by drivers in the music condition were Pop, Top-40,
and Country. However, given that the conditions mandated
unaccompanied driving, it is not clear what controls were put
in place to ensure that these genres reliably describe the
music styles actually heard, or if in fact engagement/absti-
nence of listening were carried out as instructed. Wiesenthal
et al. reported two general effects: increased congestion
caused significantly higher levels of perceived stress and
aggressive behaviors, and listening to preferred/favorite
music lowered levels of stress but only when drivers per-
ceived no urgency. Unfortunately, the study proclaimed that
“music had an influence on mild driver aggression in high
congestion but not low congestion” (p. 130).
The second study, by van der Zwaag (Fairclough, van der
Zwaag, Spiridon, & Westerink, 2014; van der Zwaag, Fair-
clough, Spiridon, & Westerink, 2011), explored the impact
of music genre on driver affect during anger-induced driv-
ing. Drivers participated in a single 45-min simulated driv-
ing session in which stress and angry mood states were
induced by three procedural hurdles: time pressure, emo-
tional frustration, and monetary fines. Participants were
assigned to one of five groups: four music conditions and
a no-music condition. The music conditions presented four
10-item playlists varying in valence and energy: (1) Positive-
Valence High-Energy activating joyous music (such as “Just
Can’t Get Enough” [Depeche Mode] or “Foundations” [Kate
Nash]); (2) Positive-Valence Low-Energy calming relaxing
music (such as “What A Difference A Day Made” [Dinah
Washington] or “Just My Imagination” [The Temptations]);
(3) Negative-Valence High-Energy activating angry music
(such as “Wait And Bleed” [Slipknot] or “One Step Closer”
[Linkin Park]); and (4) Negative-Valence Low-Energy
calming sad music (such as “The House Of Spirits” [Hans
Zimmer] or “Silver Ships Of Andilar” [Townes Van Zandt]).
Post-trip anger increased for all groups. Yet the NV/HE
music group rated their post-trip anger as higher, while the
PV/HE music group rated their post-trip anger as lower. Van
der Zwaag et al. concluded that while music can divert a
range of negative thoughts and angry feelings from arising,
music also allows feelings of anger to escalate.
Finally, Fakhrhosseini, Landry, Tan, Bhattarai, and Jeon
(2014) investigated the effects of emotional valence (i.e.,
“happy” vs. “sad” music) on driver anger. Antagonism was
induced with two short video clips viewed prior to testing.
A total of 53 undergraduates participating in a single 15-
min session of simulated driving were assigned to one of
four driving conditions: (1) Preinduced Anger With Happy
Music, (2) Preinduced Anger With Sad Music, (3) Prein-
duced Anger Without Music, and (4) No-Anger No-Music.
“Happy” music consisted of three upbeat fast-paced
instrumental selections in a major tonality (including
“Brandenburg Concerto No. 3” [J. S. Bach]), while “Sad”
music consisted of three somber slow tempo instrumental
selections in a minor tonality (including “Prelude in E
Minor” Op. 28 [F. Chopin]). Although the study found no
significant effects of emotional valence, nor were there
differences between the driving conditions themselves,
Fakhrhosseini et al. claimed that all music seemed to alle-
viate the ill effects of driver anger.
The relationship between violent media
and traffic safety
The General Aggression Model (GAM) described by
Anderson and Bushman (2001, 2002) is a relatively recent
4Music & Science
model which adopts a social-cognitive approach to aggres-
sion theory. Although GAM has been applied to a variety of
behavioral and other effects (Allen & Anderson, 2017), the
predominant use of GAM has been in the domain of psy-
chological aspects of the effects of media violence (Fergu-
son & Dyck, 2012). The model distinguishes between
aggression on the one hand and violence on the other. Spe-
cifically, GAM defines aggression as requiring three com-
ponents: action, intent, and an unwilling victim. There are
similarly different forms of aggression, referred to as
“direct” and “indirect,” which are subsumed within the
model. GAM incorporates both proximal and distal factors
to explain aggression. As mentioned, the model has been
particularly well studied and evaluated when looking at the
effects of media violence. GAM proposes the notion that
violent media content is associated with increased arousal.
Namely, that exposure to violent media content through
television, movies, computer/video games, and music
lyrics not only associates with feelings of anger, but also
with actual aggressive inclinations (Anderson et al., 2003;
Fischer & Greitemeyer, 2006). Krcmar and Greene (2000)
suggest a link between exposure to violent television and
participation in various forms of risk-taking, especially
reckless driving. More recently, Fischer et al. (2011) found
that violence in movies, video games, and song lyrics
increases the accessibility of aggression-related cognitions,
attitudes, emotions, and behaviors. Of particular relevance
here is the link between media that promotes violence and
risk-taking. Most pertinent to the discussion here is the link
found between risk-promoting media and risk-taking dur-
ing simulated driving (Fischer et al., 2008). For example,
after exposure to “risk-promoting movie sequences,” parti-
cipants who engaged in a simulated car race (Need For
Speed, EA Games) demonstrated more accidents (damage
to car body, engine, and suspension), less time to accelerate
between 0 and 160 kph, less time to complete the racing
course, and higher maximum speeds throughout the course,
than did participants exposed to “neutral-scene video
clips.” Following these findings, Beullens (Beullens & van
den Bulck, 2013; Beullens et al., 2014-2016) demonstrated
that media-promoted images of risky driving (i.e., speed-
ing, joyriding, stunt-driving) not only shaped young driv-
ers’ perceptions of associated dangers, but also their
propensity to engage in risks. Notably, Beullens found that
the frequency of accumulated hours engaged in driving
games and music videos throughout high school not only
correlated with attitudes about joyriding, but also predicted
actual crash involvement 5–10 years later.
While studies investigating violent television, movies,
music videos, PC computer games, video games, and
smartphone apps may be valuable in their own right, they
do not provide information about the effects of exposure to
music alone or songs with violent lyrics. Anderson et al.
(2003) assert that the lack of real perceptible visual images
in violent lyrics allows a wider array of imaginary meta-
phors to surface, and hence one would expect violent lyrics
in songs to be even more influential than violent videos.
Both Anderson et al. and Carpentier, Knobloch-
Westerwick, and Blumhoff (2007) concede that aversive
music genres with violent lyrics not only prime aggressive
thoughts and perceptions, but inspire actual behaviors.
Given this connection, it is of interest that drivers have
been reporting rage-like driving patterns subsequent to lis-
tening to songs for over a decade. These reports have
appeared in newsprint and the electronic media and seem
to be consistent over long periods of time among a wide
population in several countries. We present below six com-
mercially solicited survey studies.
Testimonials of everyday drivers
Several surveys support the fact that the majority of drivers
who committed traffic violations were listening to fast-beat
Rock, Dance, or House music styles (ACF, 2009; Dibben &
Williamson, 2007; Milne, 2009; Quicken, 2000; Telegraph,
2009). The American Quicken Insurance Survey found that
most drivers linked Rap and Hip-Hop music to adverse
effects, and 20%disclosed these specific genres as having
prompted aggressive conduct. Dibben and Williamson
found that 23%of British drivers involved in a previous
at-fault accident reported listening to quick-paced dance-
type music during the incident. We acknowledge that sur-
vey studies may be unreliable and that those solicited by
commercial agencies are often implemented with less sci-
entific rigor. However, we concede here that even though
such studies were not originally intended for scientific pub-
lication, basic procedural details are missing, and that the
use of inferential statistics is nonexistent, given the very
limited experimental research about the effects of music on
aggressive driving, it is still worthwhile to portray testimo-
nials by large samples of everyday drivers as they none-
theless detail explicit behaviors that thus far remain
ACF Finance. In 2009, the UK specialist subprime car dealer
ACF Finance implemented a survey about the use of
music in the car (ACF, 2009; Betts, 2009). ACF reported
that 70%of drivers who had received a traffic fine for
speeding in the previous year also admitted to having been
listening to “pounding fast dance music” prior to the
Auto Trader magazine. In 2009, Auto Trader magazine con-
ducted a “Readers’ Poll” among N¼2,000 motorists
regarding the music they listen to when driving (Noyes,
2009; Telegraph, 2009). The main outcome was that Rap
and Hip-Hop music styles placed drivers more at-risk for
road rage and car accidents. The two most favorite songs
heard in the cabin were “The Real Slim Shady” [Eminem]
(n¼600) and “Dance Wiv Me” [Dizzee Rascal] (n¼500).
Yetalmost50%(n¼980) of the drivers believed that
songs by artists such as Eminem, Dizzee Rascal, and
Brodsky et al. 5
Jay-Z had an adverse effect on their mood and driving
behavior. Although 6%(n¼120) reported feeling
relaxed when driving with either Rap or Hip-Hop music
styles, one in five (20%,n¼500) claimed that Rap and
Hip-Hop made them highly aggressive behind the wheel.
It is interesting to note that roughly half of the sample
felt “orchestral music” to be relaxing, and hence per-
ceived Classical music as offering the highest level of
safety. Other music genres identified as causing driver
aggression were Dance (6%), Classic-Rock (6%), Pop
(2%), and Classical (1%). In total, 65%(n¼1,340)
claimed to have experienced some form of music genre
induced aggressive driving.
Quotemehappy insurance. In 2011, the UK insurance com-
pany Quotemehappy examined the relationship between
music genre and driving behaviors. A polling firm, Popu-
lus, was employed to implement the survey recruiting
N¼2,050 drivers from the general public (Quotemehappy,
2011; Williamson, 2011). Quotemehappy reported that
British drivers listening to Rock, Heavy Metal, or Hip-
Hop were the most likely to speed, tailgate, and be involved
in accidents; drivers listening to Heavy Metal or Drum&-
Bass were most likely to act out aggressive behaviors; and
drivers listening to Pop or Classical experienced less stress.
The data indicated that those who swore and made rude
gestures listened significantly more to Rock (73%)and
Hip-Hop (39%) (compared to 32%listening to Pop and
16%listening to Classical). Further, drivers who listened
to Heavy Metal reported the highest levels of anger and
aggressive driving: 75%admitted to “speeding as a driving
style” (compared to 42%listening to Classical); 62%
revealed that they “frequently lose their temper with other
drivers on the road” (compared to 34%listening to Classi-
cal); and 11%disclosed they were recently involved in a
near-crash because of “how the music affected their
behavior,” which they described retrospectively as a driver
demeanor dominated by overly forceful, belligerent, and
antagonistic conduct. Drivers who listened to Jazz
received more speeding tickets than drivers who listened
to any other music genre. In addition, drivers who listened
to Reggae reported more near-crashes than drivers who
listened to any other music genre. Quotemehappy reported
that drivers who listened to Rock (31%), Hip-Hop (20%),
and Pop (13%) had been involved in at least one acci-
dent during the previous 3-year period. Finally, more
than half of the drivers perceived music background as
cheering them up, making the journey more pleasant,
and keeping them awake and alert. Rhythm & Blues
was the background most often reported to “relieve the
monotony of driving.” In 2013, the UK insurance price comparison
website implemented a closed-course test-
track evaluation; the data were subsequently corroborated
at London Metropolitan University (Brice, 2013; Dolak,
2013a, 2013b; Jolley, 2013; Katic, 2013; Philipson, 2013;
Presta, 2013; Rao, 2013; Sanchez, 2013; TheMayFirm,
2013). The study measured eight driver performances dur-
ing two trips totaling 500 miles. The first 250 miles served
as a baseline, while the second run assessed vehicular per-
formance variegated by six music genres monitored online
via a smartphone application (“Motormate”) analyzing
speed, acceleration, and braking. reported
that Hip-Hop, Rap, Dance, and Heavy Metal songs lead
to more aggressive driving styles (including faster accel-
erations and last-minute braking), while Classical music
caused more erratic behavior than Soft Rock. Confused.
com compiled two playlists of 50 songs (,
2013a, 2013b) reflecting the most recommended Safe
Tunes (e.g., “Come Away With Me” [Nora Jones] or
“Billionaire Feat.Bruno Mars” [Travie Mccoy]) and most
Dangerous Driving Songs (e.g., “Hey Moma” [The Black
Eyed Peas] or “Dead On Arrival” [Fall Out Boy]).
Kanetix insurance. In 2013, a Canadian online insurance
company Kanetix subcontracted VisionCritical (a research
agency specializing in marketing and branding insights) to
recruit N¼1,000 participants via a third-party online
forum, to explore associated links between driver music
preferences and driving behaviors (CanadianUnderwriter,
2013; CNW-Newswire, 2013; McGee, 2013; MetroNews,
2013; Mulholland, 2013; Qureshi, 2013). Kanetix reported
that the music people listen to while on the road not only
sheds light on their past driving history, but indicates their
current driving style. Kanetix disseminated infographics
characterizing driving profiles across four music genres—
Classic Rock, R&B, House/Dance, and Country (Kanetix,
2013a, 2013b). The infographics depicted the impact of
music genre on DUIs, speeding, at-fault accidents, and
aggressive dangerous driving. Subsequently, Kanetix and
VisionCritical collaborated with Brodsky (2015) in an
effort to reanalyze the data (Kanetix, 2013c). Unfortu-
nately, two lacunas could not be removed from the revised
dataset. First, there are twice the number of responses (n¼
2,026) than respondents (n¼908)—Drivers had been
allowed to indicate more than one preferred music genre.
Second, responses were not exclusively for incidents occur-
ring while respondents were driving, but may have also
occurred while they were passengers. Such discrepancies
invalidate the use of comparative analysis contrasting
response data by distinctive categories. Hence, data were
appraised by calculating grand mean scores (of equally
weighted violations) as well as weighted mean scores
(whereby “aggressive driving” accounted for twice the
influence that “at-fault accidents” and “speeding” did; see
Table 1). It should be noted that about half (52%)ofthe
sample had never been at fault for committing an accident,
and roughly 41%had never received a speeding ticket.
However, when accounting for the other 600 participants,
those behaving in the most “dangerous” manner listened to
Heavy Metal, House/Dance, Reggae, and Hip-Hop. As can
6Music & Science
Table 1. Kanetix-R Music Survey (N¼908), driving behavior (%) by music genre.
Pop Top 40
Classic Rock
A. At-fault accidents
Never 52 58 52 59 57 56 51 46 45 40 58 55
1 time 24 24 25 21 20 25 26 21 25 22 22 19
2 times 6 7 5 5 6 6 7 6 6 6 9 10
3 times 0 3 1 3 3 2 4 2 2 3 2 4
4 times 0 0 0 1 1 0 0 4 2 2 0 0
Total % accidents 30 34 31 29 29 33 37 29 33 31 33 33
B. Speeding tickets
Never 53 42 42 38 39 37 42 28 36 30 31 31
1–3 tickets 35 44 44 44 43 45 42 46 43 46 48 55
>4 Tickets 9 7 10 12 12 13 9 18 13 16 15 14
Total % tickets 44 51 54 56 55 58 51 64 56 62 63 69
C. Charged with
DUI 3 4 1 2 6 5 3 5 3 5 3 6
Careless driving 0 2 2 2 3 2 3 3 6 5 5 6
Stunt driving 0 0 0 2 0 0 2 1 4 2 0 1
Dangerous driving 0 0 1 0 2 1 0 0 0 0 0 1
Total % charges 0 2 3 4 5 3 5 4 10 7 5 8
D. Accumulated incidents
Mean % ([A þBþC]/3) 25 29 29 30 30 31 31 32 33 33 34 37
Level of risk: 1 2 2 3 3 3 3 4 4 4 4 5
Very low Low Low Moderate Moderate Moderate Moderate High High High High Very high
Weighted % ([A þB]/4) þ(C/2) 14 22 23 23 24 24 25 25 27 27 27 30
Level of risk: 1 2 2 2 3 3 3 3 4 4 4 5
Very low Low Low Low Moderate Moderate Moderate Moderate High High High Very high
Source: Provided by Kanetix (2013c).
be seen in Table 1, music genres presented in columns from
right to left reflect a ranked level of risk; the “safest” driv-
ers listened to Folk, Oldies, and Pop Top 40.
Allianz Insurance (2014). The UK-based Allianz “Your
Cover” Insurance provided Brodsky with data from an
unpublished British survey implemented between 2011 and
2012 by survey pioneers 72 Point (N¼1,000, 18–60 years
old, female ¼50%). The study assessed the effects of
music listening on driver behavior. Brodsky (2015) con-
cluded three general trends from the data: 23%stated that
music distracts them; 13%admitted to have had a near-
crash incident due to music-generated distraction; and 9%
revealed previous involvement in an actual crash/accident
resulting from music-generated distraction (see Table 2).
As can be seen in Table 2, music genres presented in col-
umns from right to left reveal the combined percentage (%)
of near-crash incidents and crash accidents—signifying a
ranked level of risk. The highest level of incidents were by
drivers listening to Jazz/Blues (50%), followed by Country
(42%), Hip-Hop/R&B (29%), and so on. We note a positive
correlation among the “Top-3 High-Risk Music Styles”: as
the level of distraction increased, so too did the frequency
of incidents. Yet among the “Bottom-3 Low-Risk Music
Styles,” this is not the case: as the level of distraction
increased, conversely the frequency of incidents decreased.
Our explanation for this finding concerns the structural
features found within the music; that is, the low-risk music
styles seem to support more adaptive driver behaviors bet-
ter than the high-risk music styles. Finally, the study found
Car-aoke (i.e., singing aloud to songs played in the cabin
while driving) to be a highly prevalent activity across all
music genres.
Among other findings that surface from the above survey
studies is a phenomenon Brodsky (2015) labeled as music
genre induced aggression. Drivers perceived this experi-
ence differently than music-generated distracted driving.
Specifically, while drivers listening to Heavy Metal,
House/Dance, Hip-Hop, Rap, and Hard Rock recounted
aggressive driving most often, they also conveyed that
when they listen to songs with lyrics of a neutral content,
the incidence of aggressive driving was roughly one in five
(20%), but when listening to songs with hostile lyrics in
either Heavy Metal or House/Dance genres, negative affect
increased by another 28%to an overall incidence of 48%.
Such a picture is similar to that reported by Smith and
Boyson (2002), who investigated the prevalence of vio-
lence among a corpus (N¼1,984) of music video clips:
aversive and harsh violence was most prevalent in Rap
(29%), Heavy Metal (27%), and Rock (12%) music videos
compared to other music genres. Finally, the survey studies
are in line with Anderson et al.’s (2003) extensive critical
review suggesting a link between music genres and mala-
daptive behaviors: those preferring Rap and Heavy Metal
exhibited more hostile attitudes than those who preferred
Alternative, Dance-Soul, or Country. Nonetheless, driving
research has not yet explored such a link between aversive
music genres and driver behavior, let alone the effects of
violent lyrics on vehicular performance. With this in mind,
Table 2. Allianz “Your Coverage” Insurance Music Survey (N¼1,000), driving behaviors (%) by music genre.
Rock Indie
Soul Reggae
Pop Chart
Jazz Blues
Preference of genre among full
921 3 36 42 9 8 4
A. Music is a distraction 28 19 19 14 16 7 27 36 37
All the time 100% 2 1 0 1 0 0 1 22 3
Half of the time 50% 1 2 3 2 2 0 7 4 18
B. Near-crash incident due to
3 8 10 7 9 13 21 19 29
Crash accident because
of music
22 3 69782321
C. In-car music aids
24 22 13 22 33 20 27 27 18
In-car music helps pass
the time
52 64 52 63 53 73 53 47 42
In-car singing is enjoyable 16 49 39 44 35 33 54 18 26
In-car music aids relaxation 47 53 42 47 53 47 38 27 34
In-car helps block out
road noise
815 13 1114015 918
D. Annoyed by other drivers’
loud music
84 62 61 61 47 80 50 62 74
Source: Provided by Allianz “Your Coverage” Insurance (2014).
8Music & Science
we implemented a driving simulator study to evaluate these
Driving simulator study
The main purpose of the current study was to explore the
impact of songs from aversive genres containing violent
content on driver performance. To our knowledge, this is
the first ever attempt to empirically differentiate between
music-generated distraction and music genre induced
aggression. We compared repeated simulated driving while
listening to two pairs of exemplars, each by the same per-
former in the same genre, whereby one contained violent
lyrics whereas the other contained neutral lyrics. Further,
we compared between the same pieces as sung vocals ver-
sus instrumental renditions, to account for the possibility
that some listeners might not pay attention to lyrics at all,
and hence finding effects for instrumental renditions pos-
sibly point to aspects of musical genre that still evoke neg-
ative effects. Finally, we included a control condition in
which participants drove without music background.
A total of 50 drivers from New South Wales, Australia,
participated in the study; 37 were psychology undergradu-
ates from Macquarie University. The inclusion criteria
required that participants (1) held a valid driver’s license,
(2) would self-report to always listen to music when driv-
ing, (3) wee acquainted with Pop, Rap/Hip-Hop, Heavy
Metal, and Country music genres, and (4) were familiari
with two music items by the same performing artist from a
30-item playlist (as listed in Table 3). The data from one
participant were removed because of noncompliance. The
final sample (N¼49) consisted of young adults (M
19.80, SD ¼2.75; 71%¼female). The participants had
held a driver’s license for an average of 4 years (M
3.6, SD ¼2.70, range ¼1–14), drove on a daily basis
Days per month
¼24, SD ¼9.89), and less than a third
(32%) had previously received a traffic violation.
Driving simulator. The driving simulator was a fixed-base
STISIM Drive (Model 400); this model is reported to have
high ecological validity (de Winter et al., 2009). The simu-
lator employs features found in an automatic transmission
vehicle cabin; adjustable car seat with seat belt, accelerator
and brake pedals, steering wheel, turning indicator, warn-
ing horn, and dashboard display (speedometer, tachometer,
odometer; see Figure 1). The simulator was powered by
three 2,349 Hz networked computers (Dell, DXP061) and
three 17-inch monitor screens providing a 135visual field.
Vehicle and road sounds were reproduced by an external
audio system (Altec Lansing, Model V54121) with speak-
ers positioned at the left and right of the visual display; a
central subwoofer for lower frequencies and vibrotactile
sensations was placed under the driver’s seat. The simula-
tor was preprogrammed to log five performance variables:
speed exceedances (frequency and distance traveled), lane
deviations (frequency and distance traveled), and collisions
Four driving scenarios were programmed: three short
trips of roughly 3.75 km (2.33 miles) and one longer trip
of 6.5 km (4 miles). The trips were on average of 8-min
duration; they occurred during daylight hours with sunny
weather, in suburban, inner city, and highway traffic envir-
onments. The roadway consisted of two lanes in each direc-
tion, at 50 kph (31 mph) speed limits for three trips that
Table 3. Playlist of the simulated driving study.
Music genre Artist/band performer Songs associated with neutral content Songs associated with violent content
I. Pop
1. Christina Aguilera Ain’t No Other Man Oh Mother
2. Rihanna Diamonds Man Down
II. Rap/Hip-Hop
3. Eminem Lose Yourself Kim
4. Eminem Mockingbird Kill You
5. Eminem When I’m Gone Love the Way You Lie
6. 50 Cent 21 Questions I’ll Still Kill
7. Ludacris What’s Your Fantasy Runaway Love
8. Black Eyed Peas Just Can’t Get Enough Karma
III. Heavy Metal
9. Metallica Astronomy All Within My Hands
10. Five Finger Death Punch Never Enough White Knuckles
11. Mo
¨tley Cru¨e Kickstart My Heart Knock Em’ Dead Kid
IV. Country
12. Olivia Newton-John Take Me Home Country Road Banks of the Ohio
13. Miranda Lamber Famous in a Small Town Gunpowder and Lead
14. Johnny Cash Get Rhythm Cocaine Blues
15. Dixie Chicks Not Ready to Make Nice Goodbye Earl
Brodsky et al. 9
increased to 90 kph (56 mph) for one trip. Each trip
included three provoking events (i.e., a vehicle tail-
gaiting and honking the driver) followed by a sudden hazar-
dous event (i.e., pedestrians jaywalking) occurring at 2:30,
5:00, and 7:30 min. A pre-study pilot (N¼16) confirmed
that no event was too easy to always be avoided, and none
were too difficult to always cause a crash.
Music stimuli. The experiment employed 30 songs; each
containing either violent or neutral content. Violence was
defined as:
any overt depiction of a credible threat of physical force or the
actual use of such force intended to physically harm an ani-
mate being or group of beings ...[including] depictions of
physically harmful consequences against an animate being
or group that result from unseen violent means. (Smith &
Boyson, 2002, p. 66)
Exemplars were obtained through a web search target-
ing four musical genres: Pop, Rap/Hip-Hop, Heavy Metal,
and Country. A total of 15 songs with associated violent
content sung vocally (V-V) were chosen because their text
blatantly employed words such as “murder” and “kill you”
(e.g., “Kill You”, Eminem). A second set of 15 songs with
associated neutral language lyric content sung vocally
(N-V) by the same artists within the same musical genres
(to control for features including tone and tempo) were
chosen (e.g., “Mockingbird”, Eminem). The methodology
of paired songs has been employed elsewhere: Anderson
et al. (2003) used paired Rock songs (with violent content
vs. neutral content) to assess post-exposure hostility;
Fischer and Greitmeyer (2006) employed paired Rock,
Pop, and Rap songs (with misogynous lyrics vs. neutral
lyrics) to demonstrate post-exposure aggressiveness toward
women; and Carpentier et al. (2007) employed paired Pop
songs (with sexually suggestive lyrics vs. neutral lyrics) to
demonstrate post-exposure attraction toward potential
romantic partners. A pre-study pilot (N¼13) verified all
30 songs in the current playlist as detectable for idiosyn-
cratic semantic content (see Table 3). Subsequently, an
instrumental-only karaoke “cover” version was obtained
for each V-V and N-V item (referred to as V-I or N-I).
An audio file was constructed in a standard fashion for
each participant for each of the four trips: (1) vocal version
song (V-V or N-V) [2:30 min]; (2) silence [3 s]; (3) instru-
mental version of same song (V-I or N-I) [2:30 min]; (4)
silence [3 s]; and (5) no-music silence [2:30 min]. The
music conditions (violent vs. neutral content, vocal vs.
instrumental renditions, music vs. no-music) were counter-
balanced across the four trips for the same participant as
well as across the sample between participants. Audio files
were reproduced with an Apple iPad coupled to two speak-
ers (Logitech, Model S-02648) placed on the floor to the
right and left of the simulator. Volume was controlled at
approximately 70 dBA.
Design and procedure. Prior to onset, a Human Research
Ethics Committee approved the study. After coupling the
seat belt, each driver listened to a 2-min excerpt of each of
the four songs (two V-V pieces and two N-V pieces) chosen
for their trips; this exposure acclimated the drivers to the
songs in an effort to offset possible artifacts that might arise
from unfamiliarity. Then there was a 2-min practice drive,
Figure 1. STISIM Drive 400 driving simulator.
10 Music & Science
after which the experiment monitor left the room, and par-
ticipants completed four trips, with a 3-min rest period
between trips. Every participant completed each drive at
their own pace. The entire session (roughly 60 min) was
captured by a digital video camera.
Data analysis. Data were analyzed with five repeated mea-
sures analyses of variance (ANOVAs) to evaluate main
effects of the five driving conditions (V-V, N-V, V-I,
N-I, NoMusic) for each of the five dependent variable out-
come measures (frequency of excessive speed, distance of
driving above the speed limit, frequency of lane deviation,
distance out of the mid-lane, and frequency of crashes; see
Table 4). When the assumption of sphericity was violated
as indicated by Mauchley’s Test of Sphericity, and Green-
house–Geisser epsilon was <.75, then both F-values and
associated significance for a Greenhouse–Geisser correc-
tion were employed. However, when the Greenhouse–
Geisser epsilon was >.75, and therefore too conservative,
then both F-values and associated significance for Huynh–
Feldt correction were employed. Subsequently, planned
pairwise comparisons ensued to test differences between
the driving conditions themselves.
Accelerating above the speed limit. A repeated measures
ANOVA indicated a statistically significant main effect
of the driving conditions (F
¼3.342, MSe ¼
.564, p¼.022, Z2
P¼.065). Pairwise comparisons demon-
strated that while drivers accelerated above the speed limit
more often with V-V versus N-V, these differences were
not statistically significant. Moreover, speed exceedances
were about the same whether the violent content was pre-
sented with lyrics or as purely instrumental background.
Nonetheless, the same cannot be said for N-I; drivers
exceeded the speed limit significantly more frequently
when purely instrumental versions with neutral content
were heard in the background (t
¼3.017, p¼.004,
d¼.431). However, there was no significant difference
between the two purely instrumental backgrounds. In gen-
eral, the participants kept to the speed limit more often in
the NoMusic condition; that is, background music caused
participants to accelerate above the speed limits more
often, and differences between NoMusic versus Music
were statistically significant for both instrumental versions
(V-I: t
¼2.588, p¼.013, d¼.370; N-I: t
p¼.003, d¼.447), near significant for sung violent songs
¼1.818, p¼.075, d¼.260), but not at all statistically
different for sung neutral songs.
Distance driving over the speed limit. A repeated measures
ANOVA indicated a statistically significant main effect
of the driving conditions (F
¼3.715, MSe ¼
27737.61, p¼.011, Z2
P¼.072). Pairwise comparisons
demonstrated that drivers traveled a longer distance above
the speed limit with V-V versus N-V, and this difference
was statistically significant (t
¼2.064, p¼.044, d¼
.310). Although this difference was similar whether or not
the violent content was presented as lyrics or as a purely
instrumental background, the same cannot be said for
pieces with neutral content, when drivers traveled a signif-
icantly longer distance exceeding the speed limit with
instrumental versions (t
¼2.728, p¼.009, d¼.390).
However, no differences surfaced when comparing the two
purely instrumental backgrounds. In general, participants
drove above the speed limit for the shortest distances in the
NoMusic condition. In other words, the music background
caused participants to accelerate above the speed limits for
longer distances, and these differences between NoMusic
versus Music conditions were statistically significant for
both instrumental versions (V-I: t
¼2.051, p¼.046,
d¼.293; N-I: t
¼2.357, p¼.023, d¼.337), near
significant for sung violent songs (t
¼1.945, p¼.058,
d¼.278), but not at all statistically different for sung neutral
Lane deviations. A repeated measures ANOVA did not
indicate a main effect of the driving conditions (F
¼1.770, MSe ¼.182, p¼.136, Z2
P¼.036). However,
pairwise comparisons demonstrated that drivers did deviate
from their lane more often with N-V versus V-V. These
differences were near statistical significance (t
p¼.061, d¼.276). Further, while differences were not
found between sung songs and instrumental versions for
backgrounds associated with either violent or neutral
Table 4. Outcome variables of the simulated driving pilot study.
Dependent variable
V-V V-I N-V N-I NoMusic
Speed exceedances
1.14 1.37 1.19 1.14 0.91 0.88 1.26 1.20 0.89 0.86
Distance over speed limit
198 272 212 277 120 176 208 269 145 185
Lane deviation
0.26 0.43 0.31 0.44 0.40 0.49 0.46 0.59 0.39 0.46
Distance lane deviation
8.69 18.0 11.0 18.6 19.6 38.1 26.3 52.2 15.2 23.9
0.84 0.43 0.81 0.41 0.83 0.42 0.70 0.41 0.73 0.34
Frequency (n).
Meters (m).
Brodsky et al. 11
content, near significant differences did surface between
the two instrumental backgrounds; that is, drivers deviated
more from the lane when driving with background music
associated with neutral content (t
¼1.721, p¼.092,
d¼.246). In general, drivers deviated from the lane in a
similar fashion whether or not there was music background,
as well as if the music background was a vocal song or
instrumental cover. The one exception was that drivers
deviated from the lane less with V-V; however, this differ-
ence was near statistical significance (t
p¼.090, d¼.247).
Distance deviating from the lane. A repeated measures
ANOVA indicated a main effect of the driving conditions
that was near levels of statistical significance (F
¼2.887, MSe ¼1575.01, p¼.057, Z2
P¼.057). Pairwise
comparisons demonstrated that drivers traveled a longer
significant distance when deviating from their lane with
N-V versus V-V; these differences were statistically signif-
icant (t
¼2.296, p¼.026, d¼.383). Although purely
instrumental versions caused participants to drive longer
distances outside of their lane than either sung songs of
violent or neutral content, such differences were not statis-
tically significant. However, differences surfaced when
comparing between the two purely instrumental back-
grounds. Drivers deviated from the lane for a longer dis-
tance with music associated with neutral content (t
2.172, p¼.035, d¼.310). In general, drivers deviated
from the lane in a similar fashion whether or not there was
music in the background, or if the background was sung
songs or instrumental music. The one exception was that
the distance participants deviated from the lane was less
with V-V; however, this difference was near statistical sig-
nificance (t
¼1.852, p¼.070, d¼.265).
Crashes. A repeated measures ANOVA did not indicate
a main effect of the driving conditions (F
MSe ¼.160, p¼.357, Z2
P¼.022). Pairwise comparisons
demonstrated that participants engaged in just as many
crashes whether or not they drove with music background,
whether or not the background consisted of violent or neu-
tral content, and whether or not the background was sung
songs or instrumental versions.
The purpose of the current study was to explore whether
aggressive driving behavior might result not simply from
the effects of in-car music, but specifically from aversive
music genres that use hostile lyrics and content promoting
violent texts and imagery. The first finding supports earlier
reports by Brodsky (2002), Brodsky and Kizner (2012), and
Brodsky and Slor (2013): driving with music impacts accel-
erated speed. In the current study, frequency of speed
exceedances and the duration of driving above the speed
limit were higher when driving with music, whether or not
the background included lyrics. Nonetheless, a second find-
ing demonstrates the impact of songs containing hostile
content in the form of violent lyrics and imagery: Partici-
pants deviated from their lane more often and for a longer
distance with songs of neutral content, whereas they accel-
erated above the speed limit more often and for a longer
distance with songs of violent content. These findings are
in line with Mesken et al. (2007) and Pecher et al. (2009),
who found that that energetic music boosted excitement,
resulting in decreased lateral control, increased excursions
from the lane, and an increased tendency to stray onto the
hard shoulder, while drivers who were exposed to hostile
music demonstrated increased cruising speeds and a higher
percentage of time that speed limits were exceeded. A third
finding of the current study sheds light on the presence of
lyrics in music while driving a car. We addressed whether
the ill effects of in-car music depended on the presence of
language (i.e., attention to the semantic meanings of the
text or to phonological memory, retrieval, and rehearsal
of singing the text); that is, the current study examined
whether music void of concrete language (i.e., an instru-
mental version) induced similar emotional states as did the
vocal renditions. This question is pertinent because there is
the possibility that some drivers do not listen to lyrics pre-
sented in the songs, but rather that the characteristic fea-
tures within a music style may still evoke emotional
responses (both positive and negative). Critically, the study
found no statistical differences between the two instrumen-
tal subtypes (violent vs. neutral content). Nonetheless,
comparisons between neutral content vocal performances
and the associated instrumental renditions indicated that
the latter caused drivers to exceed speed limits significantly
more frequently (and for a longer distance) as well as
caused them to deviate more from the lane (and for longer
distances). However, such differences were not applicable
to exemplars with violent content; that is to say, both rendi-
tions with or without lyrics carried similar effects. One
possible explanation might be that violent and/or aggres-
sive affect associated with textual content is indeed
transferred to the music itself. Finally, the study found
no differences of crash rate between driving conditions
(music style type or no-music background). This finding
is similar to those of Abdu et al. (2012), who concluded
that while induced anger certainly affects driving style,
drivers in simulated driving studies are not necessarily
affected to the extent that they can no longer maintain
vehicular control.
General discussion and conclusion
Everyday drivers anticipate taking their music along for the
ride, and they have been doing so since the 1930s when
mass ownership of the automobile paralleled the growth of
domestic technologies such as the radio, gramophone, and
telephone (Brodsky, 2015). Now, leading up to the first
century after the advent of the car radio, newly developed
12 Music & Science
entertainment technologies, loudspeaker configurations,
and ergonomically designed acoustic interiors have more
than influenced social perceptions about in-car music. Sub-
sequently, in-car music has leaped from simply being an
accessory for driving, to being more of the purpose for
using the car—at least among younger drivers. In an exten-
sive review of the literature, Brodsky found that the range
to which drivers recognize in-car music as a fundamental
component of the driving experience is between 72 and
100%, and the “car” is the location most often mentioned
for existentially strong experiences with music. Yet, as the
current study indicates, drivers need not only account for
the actual presence of music while driving, but should
explicitly consider that particular aversive music genres,
especially when employing violent content, may elicit
emotional states that induce aggressive driving styles.
While the last decade has seen just a few initiatives explor-
ing the more general aspects of in-car music, none have
attempted to disentangle music genre as a specific variable
of impact on automotive control. Nevertheless, for at least a
decade, some drivers have been reporting music-related driv-
ing behaviors resulting from particular music genres among
Internet posts, newsprint articles, magazine exposes, and the
tabloid press. Yet little to no empirical evidence has surfaced
to corroborate or dismiss such reports. Among the strengths
of the current investigation, then, are our collation of these
data, and in two cases the tabulation of the raw data that we
were able to access and revise from the original sources.
Hence, we have attempted to fill a gap toward seeking some
form of conceptual underpinning to substantiate the phenom-
enon. Despite the noted limitations surrounding the collec-
tion of these commercially produced datasets, these materials
can serve as prima facie evidence offering researchers a
starting point for future explorations regarding the effects
of media delinquency and risk-promoting popular culture
involving aversive music genres on everyday drivers. Such
ill effects were previously referred to by Brodsky (2015) as
music genre induced driver aggression.
A clear strength of the current simulator study was that it
specifically employed a broad range of four music genres
that are known as overwhelmingly hard-hitting to begin
with, and then in an effort to explore the impact of aversive
elements found in music on aggressive driving it had parti-
cipants also listen to another set of songs with violent con-
tent. The simulator study revealed that aversive song lyrics
from particular music genres had an impact on actual aggres-
sive driving behavior. The findings suggest that differences
in potentially unsafe driving may not only be due to the
general presence of music, but that such negative behaviors
differ depending on the particular nature of the music itself.
Hence, the investigation was successful in providing a better
explanation (and perhaps prediction) of aggressive driving
behavior by accounting for music genre, rather than continu-
ing to target a specific parameter or feature of music as an
independent variable (such as volume, tempo, or valance),
which has been the accepted practice in the past.
The main limitation of the study is that our platform
consisted of simulated driving. We acknowledge that driv-
ing simulators provide drivers with an artificial environ-
ment, and these conditions are never quite the same as
real driving conditions. For example, the longitudinal and
lateral accelerations are limited, and only parts of the
extremely complicated transport system can be simulated.
It should be noted that the differences between the simu-
lated and the real driving environment may influence sub-
jects’ driving behavior and performance, and hence our
outcome measures (vehicular performance data collected
via the driving simulator) may differ from the same mea-
sures had we collected them during real-world on-road
naturalistic driving. On the other hand, we point out that
the main advantages of driving simulators are their funda-
mentally safe environment for participants of driver beha-
vior research, and they can be easily and economically
configured to investigate a variety of human factors. More-
over, a driving simulator is linked to digital computer sys-
tems that provide online storage and the reduction of data
streams into custom-made compacted arrangements of
data, as well as allow for data formatting, processing, and
analyses based on specific research needs, all the while
controlling the experimental conditions over a wider range
of variables than can usually be accommodated when
employing naturalistic driving.
In terms of the General Aggression Model (GAM), our
results can be interpreted as tapping into the proximal fac-
tors of that model. The situation in which drivers are
placed, namely exposure to music while driving in (virtual)
crosstown traffic, is able to have an effect on their internal
state by producing arousal which may also lead to aggres-
sive priming (as is the case when exposed to media vio-
lence). The outcome phase of the proximal component of
GAM can be used to interpret some of the results of the
simulator study. For example, Pecher et al. (2009) had pre-
viously reported that angry drivers showed increased cruis-
ing speeds and an increased percentage of time over posted
speed limits. If the violent content of the songs played to the
driver (a proximal situational input according to GAM)
produces anger via arousal, and this results in aggression
according to GAM, then we would expect an increase in the
percentage of time over the speed limit (in the violent music
condition in the simulated drive). This was indeed one of
our findings. Furthermore, our suggestion that the textual
context of the music may be transferred to the music itself is
also interpretable in the light of GAM, that is, the music
itself produces sufficient arousal and anger to result in
speed exceedances and lane deviation. Finally, the interpre-
tation of our last result is similarly compatible with GAM—
although it does not test it directly. That is, the aggression
produced may simply be insufficient to result in the grossest
measure of vehicular control: crashing. In summary, the
results of the simulator study may be interpreted in the
context of GAM, although we point out that our aim in the
current simulator study was not to test GAM.
Brodsky et al. 13
Clearly cars are here to stay, and in-car music listening
will forever be part of vehicular performance. To this end,
we feel that an increased number of investigations need be
undertaken by traffic-related human factor researchers, as
well as by music psychologists, targeting the effects of in-
vehicle background music on driver behavior and automo-
tive control.
WB, DO, and EC researched the literature and conceived the
study. WB was responsible for the survey material, driver testi-
monials, and overall supervision of all music science aspects of
the study. DO and EC were responsible for the driving simulator,
including: design, programing, ethics approval, participant
recruitment, and data analysis. WB, DO, and EC, wrote all drafts
of the manuscript including edited revisions and approved the
final version of the manuscript.
Declaration of conflicting interests
The author(s) declared no potential conflicts of interest with
respect to the research, authorship, and/or publication of this
The author(s) received no financial support for the research,
authorship, and/or publication of this article.
Peer review
Alex Lamont, Keele University and one anonymous reviewer.
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... Insurance company and police records illustrate how young drivers are at particular riskto themselves and to other road users -when their music choices are less than optimal (i.e. loud/aggressive music; Brodsky, Olivieri, and Chekaluk 2018;Dibben and Williamson 2007). Sophisticated conceptual frameworks pertaining to driving behaviour, such as Fuller's (2011) Driver Control Theory, place considerable emphasis on the mismatch between young/ inexperienced drivers' perception of their driving abilities and their actual driving abilities. ...
... Essentially, at the scene of many crashes, police encounter the blare of aggressive forms of music (e.g. gangsta rap or heavy metal) and such music has been shown to result in higher cruising speeds and a higher percentage of time in excess of the speed limit (Brodsky, Olivieri, and Chekaluk 2018). The present study has a particular focus on young and inexperienced drivers, with a group of middle-aged drivers sampled for comparative purposes. ...
... Our participants tended to report that, either positively or negatively, music influenced their capability. In critical situations, the presence (or absence) of music with specific characteristics might be the difference between loss of control or staying on the road (Brodsky, Olivieri, and Chekaluk 2018). ...
Underpinned by pragmatism and symbolic interactionism, an inductive content analysis was conducted to assess driving experiences under a variety of music conditions. Many quantitative studies have addressed the effects of music on drivers, but there has been a conspicuous dearth of qualitative research to provide a more nuanced understanding of music-related phenomena. Data collection took place over three simulated driving studies, each with different tasks/participants (Study 1 – n = 34, Study 2 – n = 46, and Study 3 – n = 27). The inductive content analysis was conducted by two members of the research team and a peer debriefing was conducted by a third. Findings show that music can have a range of affective, behavioural and cognitive effects (both positive and negative), that are moderated by the driving environment (i.e. urban vs. highway) and aspects of the musical stimulus (i.e. inclusion/non-inclusion of lyrics, loudness and tempo). Participants were mindful of the implications of in-vehicle music vis-à-vis the safety–performance–pleasure trade-off. The analysis suggested a perceived beneficial effect of music and consequent contribution to driving style/safety-related performance. Younger drivers’ apparent reliance on music as a means by which to regulate their emotion highlights an education need in terms of optimising selections. Supplemental data for this article is available online at .
... Using this information, we know that volume as well as music characteristics can affect reaction time. Additionally, Brodsky and colleagues evaluated driver aggression when listening to different genres of music [4]. Music with aversive language, regardless of the genre, had a higher incidence rate than music with neutral lyrics [4]. ...
... Additionally, Brodsky and colleagues evaluated driver aggression when listening to different genres of music [4]. Music with aversive language, regardless of the genre, had a higher incidence rate than music with neutral lyrics [4]. These participants had increased cruising speeds, and a higher percentage of time exceeding speed limits. ...
... More energetic music was also shown to increase excitement, which led to decreased lateral control, increased excursions from the lane, and an increased incidence of straying into the shoulder of the road. These findings were labeled as "musicgenerated driver distraction" [4]. In the context of this study, we chose to look at the effect of music genre on reaction times, and use this information to determine if music-generated driver distraction was affected by music preference. ...
A series of 4 collective, exploratory case studies were conducted in order to determine the effect of different genres on reaction time. The Brain Gauge System was used to measure raw reaction time via a tactile reaction time test, testing three different conditions: no music, preferred genre, classical music. The subjects listened to 10 minute increments of music on noise-cancelling headphones and took the tactile reaction time test once before listening and twice (2 minute and 8 minute mark) while the music was playing. Results indicated that there was a general trend of increased reaction time (i.e., decreased performance) with music playing in the background. An ANOVA test was performed, with a resulting p-value of 0.411. While statistical analysis proved the results to be insignificant, the trends found in the case studies indicate that listening to music worsens your reaction time. Furthermore, preferred types of music do not have a significant effect on reaction time. Consistent with literature, this indicates that music in general is a form of distraction, regardless of preference and genre. Further in-depth studies need to be conducted with a larger sample size in order to expand upon these preliminary findings.
... Los artículos recabados ascendieron a un total de 46 (Anexos 1 y 2). Con respecto al tipo de estudios, la distribución fue la siguiente: 42 estudios experimentales [1,2,6,8,9,10,11,12,13,14,17,18,19,20,21,22,23,24,25,28,29,30,31,32,33,34,35,37,39,40,41,42,43,44,45,46,47,49,51,50,52], un estudio de revisión [48], uno descriptivo [38], un estudio exploratorio [7] y un meta-análisis [26]. 1968, 1995, 1996, 2000, 2008, 2011, 2015, y 2017. ...
... Otro aspecto que se ha evaluado en los conductores es el control lateral que consiste en el mantenimiento del vehículo en el carril correspondiente. Los resultados son interesantes dado que algunos investigadores han reportado efectos detrimentales en el control lateral de los conductores expuestos a música personalmente seleccionada [9], a música instrumental con contenido neutro [19], y en combinación con tareas de selección de piezas musicales en dispositivos móviles [20] [21]. De esta manera, el control lateral parece verse afectado con independencia de las preferencias musicales. ...
... Los estudios sobre el control longitudinal del vehículo -que incluye el mantenimiento y las variaciones en la velocidad, así como el tiempo empleado en realizar un recorrido-parecen apuntar hacia un mismo resultado e indicar que el escuchar música mientras se conduce, especialmente música a alto volumen y con un tempo acelerado, se asocia a un aumento de la velocidad [22] [9] [19] [23] [18] [26] [13]. Este exceso de velocidad es registrado, en algunas ocasiones, por los conductores, quienes toman medidas autorregulatorias [27] [21], si bien no siempre es el caso [28] [29]. ...
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Fecha de recepción: 15 de octubre de 2019. Fecha de aceptación: 8 de abril de 2020. RESUMEN INTRODUCCIÓN. Los accidentes de tránsito representan una problemática de relevancia en el mundo actual. A pesar de la existencia de literatura que aborde esta temática, el abordaje destinado a la relación entre la música que escuchan los individuos y el desempeño en su conducción ha sido escaso. OBJETIVO. El presente artículo expone una revisión sistemática según los lineamientos PRISMA sobre estudios que exploren la relación entre la música y la conducción vehicular. MÉTODO. Mediante una búsqueda bibliográfica en bases de datos Scopus, Eric, y Dialnet, se obtuvo una muestra de 46 publicaciones que cumplieran con los criterios de elegibilidad. RESULTADOS. El análisis documental realizado permite concluir la existencia de evidencia empírica sobre los efectos detrimentales en el desempeño cognitivo y conductual de los sujetos al estar expuestos a música con un tempo acelerado, a gran volumen o intensidad, con alto nivel de activación fisiológica, o música no autoseleccionada. En cuanto al campo emocional, se reportaron efectos positivos ya que la música mejoraba los estados afectivos de los conductores. DISCUSIÓN Y CONCLUSIONES. Se espera que esta investigación resulte útil a interesados en la temática, si bien se destaca que la comprensión de los siniestros viales es compleja y multicausal. Palabras clave: conducción de automóvil, revisión sistemática, música ABSTRACT INTRODUCTION. Traffic accidents represent a problem of relevance in the modern world. Despite the existence of literature that addresses this topic, the approach aimed at the relationship between the music that the subjects listen to and their driving performance has been scarce. OBJECTIVE. This article presents a systematic review according to the PRISMA guidelines on studies that explore the relationship between music and vehicle driving. METHOD. Through a bibliographic search in Scopus, Eric, and Dialnet databases, a sample of 46 publications was obtained that met the eligibility criteria. RESULTS. The documentary analysis carried out allows us to conclude the existence of empirical evidence on the detrimental effects on the cognitive and behavioral performance of the subjects when exposed to music with an accelerated tempo, at high volume or intensity, with a high level of physiological activation, or non-music self-selected. Regarding the emotional field, positive effects were reported since the music improved the affective states of the drivers. DISCUSSION AND CONCLUSIONS. It is hoped that this research will be useful to those interested in the subject, although it is highlighted that the understanding of road accidents is complex and multi-causal.
... Los artículos recabados ascendieron a un total de 46 (Anexos 1 y 2). Con respecto al tipo de estudios, la distribución fue la siguiente: 42 estudios experimentales [1,2,6,8,9,10,11,12,13,14,17,18,19,20,21,22,23,24,25,28,29,30,31,32,33,34,35,37,39,40,41,42,43,44,45,46,47,49,51,50,52], un estudio de revisión [48], uno descriptivo [38], un estudio exploratorio [7] y un meta-análisis [26]. 1968, 1995, 1996, 2000, 2008, 2011, 2015, y 2017. ...
... Otro aspecto que se ha evaluado en los conductores es el control lateral que consiste en el mantenimiento del vehículo en el carril correspondiente. Los resultados son interesantes dado que algunos investigadores han reportado efectos detrimentales en el control lateral de los conductores expuestos a música personalmente seleccionada [9], a música instrumental con contenido neutro [19], y en combinación con tareas de selección de piezas musicales en dispositivos móviles [20] [21]. De esta manera, el control lateral parece verse afectado con independencia de las preferencias musicales. ...
... Los estudios sobre el control longitudinal del vehículo -que incluye el mantenimiento y las variaciones en la velocidad, así como el tiempo empleado en realizar un recorrido-parecen apuntar hacia un mismo resultado e indicar que el escuchar música mientras se conduce, especialmente música a alto volumen y con un tempo acelerado, se asocia a un aumento de la velocidad [22] [9] [19] [23] [18] [26] [13]. Este exceso de velocidad es registrado, en algunas ocasiones, por los conductores, quienes toman medidas autorregulatorias [27] [21], si bien no siempre es el caso [28] [29]. ...
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INTRODUCCIÓN. Los accidentes de tránsito representan una problemática de relevancia en el mundo actual. A pesar de la existencia de literatura que aborde esta temática, el abordaje destinado a la relación entre la música que escuchan los individuos y el desempeño en su conducción ha sido escaso. OBJETIVO. El presente artículo expone una revisión sistemática según los lineamientos PRISMA sobre estudios que exploren la relación entre la música y la conducción vehicular. MÉTODO. Mediante una búsqueda bibliográfica en bases de datos Scopus, Eric, y Dialnet, se obtuvo una muestra de 46 publicaciones que cumplieran con los criterios de elegibilidad. RESULTADOS. El análisis documental realizado permite concluir la existencia de evidencia empírica sobre los efectos detrimentales en el desempeño cognitivo y conductual de los sujetos al estar expuestos a música con un tempo acelerado, a gran volumen o intensidad, con alto nivel de activación fisiológica, o música no autoseleccionada. En cuanto al campo emocional, se reportaron efectos positivos ya que la música mejoraba los estados afectivos de los conductores. DISCUSIÓN Y CONCLUSIONES. Se espera que esta investigación resulte útil a interesados en la temática, si bien se destaca que la comprensión de los siniestros viales es compleja y multicausal.
... With reference to Millet et al.'s (2019) conceptual model, the PSel fast-tempo music has the potential to mediate a broad range of driving outcomes, as do gender, age and driving experience (see Fig. 1). We sampled young, male drivers in the present studyidentified as one of the most at-risk groups on British roadswho have a tendency to self-select loud, fast-paced and aggressive music (Brodsky and Slor, 2013;Brodsky et al., 2018). Fuller's (2011) theoretical contribution details how drivers constantly adjust their behaviour in line with their perceived capability to match driving demands. ...
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We investigated the effect of participant-selected (PSel) and researcher-selected (RSel) music on urban driving behaviour in young men (N = 27; M age = 20.6 years, SD = 1.9 years). A counterbalanced, within-subjects design was used with four simulated driving conditions: PSel fast-tempo music, PSel slow-tempo music, RSel music and an urban traffic-noise control. The between-subjects variable of personality (introverts vs. extroverts) was explored. The presence of PSel slow-tempo music and RSel music optimised affective valence and arousal for urban driving. NASA Task Load Index scores indicated that the urban traffic-noise control increased mental demand compared to PSel slow-tempo music. In the PSel slow-tempo condition, less use was made of the brake pedal. When compared to extroverts, introverts recorded lower mean speed and attracted lower risk ratings under PSel slow-tempo music. The utility of PSel slow-tempo and RSel music was demonstrated in terms of optimising affective state for simulated urban driving.
... As such, phone-using drivers can have both hands on the steering wheel and both eyes on the road but can fail to notice pertinent parts of the driving situation-even when they are looking directly at them-leading to reduced hazard detection and increased crash risk (Strayer et al. 2003;Dingus et al. 2016). The same has been found of listening to music, with different types of music-listening affecting driver behaviour in different ways (Brodsky et al. 2018). The motivation for wanting to believe this to be true comes from the perceived need to use a phone while driving, whilst 'common sense' explanations based on the physical and observable aspects of driving-sitting correctly, with hands on the wheel-provide the evidence, or means, to reject safety messages. ...
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Evidence for how phone-use impacts driving is clear: phone-using drivers are four times more likely to crash; demonstrate poor hazard detection ability; take longer to react to any hazards they notice; and can look yet fail to see. However, drivers are often resistant to research findings and, despite it being an enforceable offence, many still admit to using their phones. This paper combines what is known about the dangers of distracted driving with what research tells us about how drivers think about themselves, the law, and their risk of both crashing and being prosecuted. These blended insights explain why evidence may be resisted both by drivers and policymakers, highlighting the inconvenient truth of the distraction caused by mobile phone-use.
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Traffic crashes remain a leading cause of accidental human death where aggressive driving is a significant contributing factor. To review the driver’s performance presented in aggressive driving, this systematic review screens 2412 pieces of relevant literature, selects and synthesizes 31 reports with 34 primary studies that investigated the driver’s control performance among the general driver population in four-wheeled passenger vehicles and published with full text in English. These 34 selected studies involved 1731 participants in total. By examining the selected 34 studies, the measures relating to vehicle speed (e.g., mean speed, n = 22), lateral control (e.g., lane deviation, n = 17) and driving errors (e.g., violation of traffic rules, n = 12) were reported most frequently with a significant difference observed between aggressive driving and driving in the control group. The result of the meta-analysis indicates that the aggressive driving behaviour would have 1) a significantly faster speed than the behaviour in the control group with an increase of 5.32 km/h (95% confidence interval, [3.27, 7.37] km/h) based on 8 studies with 639 participants in total; 2) 2.51 times more driving errors (95% confidence interval, [1.32, 3.71] times) than the behaviour in the control group, based on 5 studies with 136 participants in total. This finding can be used to support the identification and quantification of aggressive driving behaviour, which could form the basis of an in-vehicle aggressive driving monitoring system.
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Penelitian ini bertujuan untuk mengetahui pengaruh emosi yang diinduksi oleh musik terhadap penilaian moral terhadap sebuah cuplikan adegan film. Penelitian ini merupakan replikasi penelitian eksperimen online Steffens (2018) dengan tujuan yang sama. Sebanyak 69 partisipan ditempatkan secara acak berdasarkan skor Moral Foundation Questionnaire aspek Harm/Care ke dalam tiga kelompok (tanpa musik, musik negatif dan musik positif). Eksperimen dilakukan dengan google form yang dikirimkan kepada partisipan melalui pesan WhatsApp. Hasil penelitian menunjukkan bahwa tidak ada pengaruh manipulasi jenis musik pada emosi yang dirasakan serta penilaian moral� terhadap adegan film, kecuali pada partisipan yang menggunakan headphone. Pada kasus tersebut, terdapat perbedaan rileks dan reflektivitas (reflectiveness), yang diinduksi di antara tiga kelompok. Selanjutnya emosi yang dirasakan, yaitu agresi, keterhubungan, kebahagiaan, reflektivitas, sedih, dan tegang berhubungan dengan penilaian moral. Penelitian lebih lanjut dapat melihat efek mediasi dari reflectiveness dalam hubungan musik dan penilaian moral.
Identifying risky driving behavior is of central importance for increasing traffic safety. This paper tackles the task of analyzing real (naturalistic) driving data captured by in-vehicle sensors using interpretable data science methods. In particular, we focus on symbolic time-series abstraction and the subsequent behavioral profile identification using topic modeling approaches. For our experiments, we utilize a real-world dataset. Our results indicate interesting behavioral driving profiles including important patterns and factors for traffic safety modeling.
Technical Report
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The “100-Car Naturalistic Driving Study” is a three-phased effort designed to accomplish three objectives: Phase I, Conduct Test Planning Activities; Phase II, Conduct a Field Test; and Phase III, Prepare for Large-Scale Field Data Collection Effort. This report documents the efforts of Phase II. Project sponsors are the National Highway Traffic Safety Administration (NHTSA) and the Virginia Department of Transportation (VDOT). The 100-Car Naturalistic Driving Study is the first instrumented-vehicle study undertaken with the primary purpose of collecting large-scale, naturalistic driving data. Drivers were given no special instructions, no experimenter was present, and the data collection instrumentation was unobtrusive. In addition, 78 of 100 vehicles were privately owned. The resulting database contains many extreme cases of driving behavior and performance, including severe drowsiness, impairment, judgment error, risk taking, willingness to engage in secondary tasks, aggressive driving, and traffic violations. The data set includes approximately 2,000,000 vehicle miles, almost 43,000 hours of data, 241 primary and secondary drivers, 12 to 13 months of data collection for each vehicle, and data from a highly capable instrumentation system including 5 channels of video and many vehicle state and kinematic sensors. From the data, an “event” database was created, similar in classification structure to an epidemiological crash database, but with video and electronic driver and vehicle performance data. The events are crashes, near-crashes, and other “incidents.” Data is classified by pre-event maneuver, precipitating factor, event type, contributing factors, associative factors, and the avoidance maneuver. Parameters such as vehicle speed, vehicle headway, time-to-collision, and driver reaction time are also recorded. The current project specified ten objectives or goals that would be addressed through the initial analysis of the event database. This report addresses the first 9 of these goals, which include analyses of rear-end events, lane change events, the role of inattention, and the relationship between levels of severity. Goal 10 is a separate report and addresses the implications for a larger-scale data collection effort.
Conference Paper
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Research has focused on music's negative effects on a driver's attention, whereas little research has addressed the possibility of using music to reduce emotional effects on driving. In the present study, we investigate how music can mitigate the degenerated driving performance associated with angry driving. To this end, fifty-three drivers participated in a simulated driving study either with or without induced anger. Three groups of participants with induced anger drove in a simulator while listening to happy or sad instrumental pieces, or without music. In the control group, anger was not induced and they did not listen to music during driving. The results show that participants who listened to either happy or sad music had significantly fewer driving errors than those who did not listen to music. However, no significant differences were found between happy and sad music conditions. Results are discussed with an affect regulation model and future research.
The general aggression model (GAM) is an integrative, bio-social-cognitive, developmental framework for explaining human aggression that incorporates many domain-specific theories of aggression. This entry discusses and defines important concepts in the study of aggression (i.e., aggression, violence, proactive vs. reactive aggression, direct vs. indirect aggression, and displaced and triggered displaced aggression). Next, the theoretical precursors to GAM (i.e., cognitive neoassociation theory, social learning theory, script theory, excitation transfer theory, social interaction theory, and the general affective aggression model) are reviewed. Finally, the structure and functions of GAM are described and implications for media effects are discussed.
Conference Paper
The traffic psychology literature targeting driver behavior has scarcely investigated music as a source of inattention or distraction. There is great confusion regarding what is music, and the difference between 'music' versus 'auditory' stimuli is not always clear. Unfortunately, traffic and automotive researchers employing music in their investigations demonstrate little knowledge about musical structures (i.e., the actual complex of sound, rhythm, harmony), and further exhibit a total disregard for the level of rigor necessary to incorporate music stimuli within empirical frameworks. For the most part, exemplars selected as stimuli for studies have been contaminated, and conditions of exposure have been flawed. In general, hypotheses about in-car music listening are based on intuition without scientific grounding. It is no wonder that findings have typically inferred that 'music causes little, if any, effects'. This tutorial attempts to fill that gap and expose researchers of the automotive sciences to the effects of music on driver behavior. The session will offer guidelines for implementing future studies incorporating music.
Recently, a growing number of studies have shown a relationship between exposure to risk-glorifying media and risky driving perceptions, attitudes, and behaviors. The present study contributes to this line of research by examining emerging adults' behavioral approach system (BAS) and behavioral inhibition system (BIS) as moderators of the relationship between music video-viewing and joyriding attitudes. A cross-sectional survey among a sample of 539 emerging adults (ages 18-24) was conducted to examine the relationships between these constructs. Advanced moderation analyses indicated that, after controlling for sensation-seeking, physical aggression, gender, BIS, and BAS, the relationship between music video-viewing and joyriding attitudes only existed for respondents with a low BIS profile. Thus, low sensitivity to punishment functioned as a condition for the relationship between music video-viewing and joyriding attitudes. Furthermore, the results provided initial evidence for the hypothesis that the relationship between sensation-seeking and joyriding attitudes is explained by respondents' BAS scores. Accordingly, it seems advisable to include BIS and BAS in future media research. The present study also has important implications for the construction and planning of prevention campaigns, which are extensively discussed.
A naturalistic driving study involving 100 light vehicles equipped with video cameras and other data collection equipment was recently completed. The resulting data set was searched to identify critical incidents involving both light vehicles (LVs) and heavy vehicles (HVs). Each incident was coded on a number of dimensions including the type of incident (what happened) and the Critical Reason for the incident (why it happened). Goals of the analysis included gaining a better understanding of LVHV interactions and providing background information that would serve as a necessary prerequisite to the development of crash countermeasures. For 217 of the 246 LV-HV interaction incidents recorded, the event initiator was attributed to either the LV driver (64%) or the HV driver (36%). The most frequent Incident Type for LV driver initiated incidents was Late Braking for Stopped/Stopping Traffic (41.3%), followed by Lane Change Without Sufficient Gap (21.7%). The most frequently noted Critical Reasons for LV driver initiated incidents were Aggressive Driving Behavior (24.6%), Too Fast for Conditions (15.2%), and Internal Distraction (13.8%). Given that LV drivers were more likely to have initiated an incident, it is believed that efforts at addressing the LV-HV interaction problem should include focusing on the LV driver.
Past research has provided evidence for the notion that media exposure may increase negative attitudes and behavior toward women. In contrast, little is known whether media exposure may also improve people's images of women. In fact, four studies tested and found support for the hypothesis that listening to music with proequality lyrics is causally associated with positive attitudes and behavior toward women. These effects appeared to be unaffected by arousal and mood properties of the songs used and were not due to differences in liking. Thus, the current set of studies successfully extends the media exposure literature into the domain of positive attitudes and behavior toward women.