Study on driving behaviors for adults with Autism Spectrum Diagnoses.

1. ORIGINAL PAPER
Driving Behaviors in Adults with Autism Spectrum Disorders
Brian P. Daly • Elizabeth G. Nicholls •
Kristina E. Patrick • Danielle D. Brinckman •
Maria T. Schultheis
Published online: 13 June 2014
Ó Springer Science+Business Media New York 2014
Abstract This pilot study investigated driving history and
driving behaviors between adults diagnosed with autism
spectrum disorders (ASD) as compared to non-ASD adult
drivers. Seventy-eight licensed drivers with ASD and 94
non-ASD comparison participants completed the Driver
Behavior Questionnaire. Drivers with ASD endorsed sig-
nificantly lower ratings of their ability to drive, and higher
numbers of traffic accidents and citations relative to non-
ASD drivers. Drivers with ASD also endorsed significantly
greater numbers of difficulties on the following subscales:
intentional violations, F(1, 162) = 6.15, p = .01, gp
2
= .04;
mistakes, F(1, 162) = 10.15, p = .002, gp
2
= .06; and slips/
lapses, F(1, 162) = 11.33, p = .001, gp
2
= .07. These
findings suggest that individuals with ASD who are current
drivers may experience more difficulties in driving behav-
iors and engage in more problematic driving behaviors
relative to non-ASD drivers.
Keywords Autism Adults Driving Violations
Introduction
An estimated 1 in 88 American children is diagnosed with an
autism spectrum disorder (ASD) each year, representing a
78 % increase over the last decade [Centers for Disease
Control (CDC) 2012]. Although ASD presentation varies
greatly along a spectrum, the majority of these children
(62 %) do not have intellectual disability (CDC 2012).
Consequently, many individuals with ASD have the capa-
bility to participate in the same educational, occupational,
and social experiences as their neurotypical peers if given
proper resources and support (Virués-Ortega 2010). How-
ever, full integration into the community remains challeng-
ing as youth with ASD transition into adulthood (Hendericks
and Wehman 2009). Consequently, identification of deficits
associated with ASD in high functioning individuals and
interventions or supports aimed at improving quality of life
are becoming increasingly important.
One skill increasingly recognized as central to inde-
pendent community functioning for individuals with a
disability or an ASD is the ability to drive a car (Cox et al.
2012; Schultheis et al. 2002). Driving confers advantages
such as increased mobility and independence which, in
turn, promotes physical, social, and economic well-being
(Collia et al. 2003). Despite the importance of this skill,
responses from a recent survey revealed that only 24 % of
adults with autism—many of whom described themselves
as ‘‘higher functioning’’ indicated that they were indepen-
dent drivers (Center for Advanced Infrastructure and
Transportation 2011). Although it has been suggested that
individuals with ASD experience difficulties with driving
(Tantam 2003), the few studies that have examined driving
behaviors in this population have focused exclusively on
teenagers and young adults (Cox et al. 2012; Huang et al.
2012; Reimer et al. 2013; Sheppard et al. 2010). Thus, to
the best of our knowledge, no studies have examined the
driving behaviors of licensed adult drivers with ASD, and
thus little is known about whether these individuals
encounter challenges when driving.
A number of ASD symptoms and correlates may present
obstacles to learning and maintaining safe driving behav-
iors. For example, neurocognitive issues such as problems
with motor coordination, attention modulation, motion
B. P. Daly () E. G. Nicholls K. E. Patrick
D. D. Brinckman M. T. Schultheis
Department of Psychology, Drexel University, 3401 Chestnut
Street, Philadelphia, PA 19104, USA
e-mail: brian.daly@drexel.edu
123
J Autism Dev Disord (2014) 44:3119–3128
DOI 10.1007/s10803-014-2166-y

2. perception, and reaction time (Hofvander et al. 2009;
Kaiser and Shiffrar 2009; Weiner et al. 2001) may limit a
driver’s capacity for detecting and quickly responding to
road hazards. Social-cognitive processing issues (Klin
2000; Zalla et al. 2009) also may impact a drivers’ ability
to predict movements and/or objectives of pedestrians or
other motorists, while difficulties with emotional regulation
may reduce capacity for tolerating frustration and manag-
ing anxiety on the road (Cox et al. 2012; Hofvander et al.
2009). Moreover, many individuals with ASD show
impairments in executive functioning (for a review, see
Hill 2004), which are critical skills for driving. Specifi-
cally, individuals with ASD often demonstrate impairments
in problem solving, especially planning and goal directed
behavior, which could make driving navigation difficult. In
addition, limited cognitive flexibility, including rigidity
and perseverative behaviors characteristic of this popula-
tion, may create considerable driving challenges for indi-
viduals with ASD (Hofvander et al. 2009). Furthermore,
ASD-related problems with inhibition, self-monitoring, and
generation of novel solutions to adjust to unexpected
changes (Hill 2004; Turner 1999) could lead to unsafe and
problematic driving behaviors. Safe driving requires com-
plex skills such as divided attention, ability to adjust goals
rapidly in the context of sudden environmental demands,
and generalization of skills to novel environments, all
adaptive proficiencies that may be impaired for persons
with ASD (Cox et al. 2012).
Despite the range of core and associated symptoms of
ASD presenting potential barriers to driving, only four
studies have investigated the experience of learning to
drive or driving independently for individuals with an
ASD. Huang et al. (2012) administered a survey to parents
of driving and non-driving teenagers with high functioning
ASD. Findings of responses to the survey revealed that
only 12 % of driving teenagers had received a driving
citation or been involved in a motor vehicle crash, per-
centages that are lower when compared to the general teen
population (12 vs. 31 % and 12 vs. 22 %, respectively).
The authors also noted that many parents in the study
indicated that their teens were more ‘‘rule-bound’’ and less
‘‘reckless’’ (Huang et al. 2012). In another parent-report
survey, Cox et al. (2012) reported that youth with ASD
experienced significant difficulties during driver education.
More specifically, the majority of parents reported that
although their child was competent when engaging in
‘‘simple’’ driving skills such as speed control or main-
taining lane position, significant struggles were evident
when navigating ‘‘complex’’ driving skills such as merging
into traffic or multitasking while driving.
Results from a study in which young adults viewed
video clips of driving hazards indicated that participants
with ASD were comparable in performance to a control
group on non-social hazards, but were significantly less
likely to perceive hazards involving social information
(e.g., a pedestrian entering the roadway) (Sheppard et al.
2010). The authors interpreted these findings to suggest
that young adults with ASD may be especially vulnerable
to navigating driving hazards that rely on social processing
skills. Findings from a recent small study that employed a
driving simulator revealed that young adult men (ages
18–24 years) with high functioning ASD performed on a
comparable level to controls in the frequency of simulated
crashes and on a standard measure of vehicle control
(Reimer et al. 2013). In contrast, when the level of cog-
nitive demand was increased by adding either a phone task
or an auditory continuous performance task to the driving
simulation, individuals with ASD focused their visual
attention on different parts of the road as compared to
controls, which was interpreted by the authors to suggest a
potentially hazardous response (Reimer et al. 2013).
While findings from three of the four referenced studies
suggest the presence of potential driving deficits in the
ASD population, it is notable that all of these investigations
focused on samples of teenagers or young adults, examined
a relatively narrow range of driving behaviors, and utilized
non-validated instruments. Furthermore, questions related
to driving abilities in individuals with ASD were answered
by their parents rather than directly by the individual. As
such, little is known about whether adult drivers with ASD
that are licensed and currently driving report/perceive
specific challenges when they drive.
The goals of this pilot study were to (1) compare the
self-reported driving history, preferences, and behaviors of
adult drivers with ASD versus non-ASD drivers; (2) to use
a comprehensive, validated driving questionnaire to
determine whether differences exist in the rates at which
adult drivers with ASD versus non-ASD drivers report
deliberate violations (e.g., intentionally ignoring red lights
or passing illegally); unintended violations (e.g., mistak-
enly exceeding the speed limit); mistakes (e.g., underesti-
mating the speed of an oncoming vehicle); driving slips or
lapses (e.g., misreading a sign or failing to notice signs
entirely) as defined by the Driving Behavior Questionnaire
(DBQ); and, (3) to determine whether differences exist in
terms of the relative risk of such behaviors (definite risk to
others versus possible risk to others versus no risk to oth-
ers) as quantified by the DBQ.
Methods
Participants
Individuals with ASD were invited to participate in this
study via a link posted on an ASD support website, while
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123

3. control subjects were recruited from an existing database of
adult drivers. Initial eligibility for both groups was based
on their self-report of having a current driver’s license and
being an active driver. Inclusion criteria specific to the
ASD group included a self-reported diagnosis of an ASD
(autism, Asperger’s disorder, or pervasive developmental
disorder—not otherwise specified). Exclusion criteria for
the control group included a history of developmental
disabilities or neurological conditions that could potentially
impact driving abilities or behaviors (e.g., traumatic brain
injury). All participants completed the survey online. The
first screen of the survey described the nature of the study,
informed participants about the voluntary nature of the
study, ensured them of privacy and confidentiality of their
responses, and also provided contact information for the
study coordinator in case participants had questions. After
participants read this information, electing to take the
survey was considered implied consent. Participants’ con-
fidentiality was protected by an honest broker from the
study institution that engaged in all contact with partici-
pants, but did not have access to the study data. Upon
survey completion, contact information for this individual
was provided to participants. If participants contacted the
honest broker, they were provided with a gift card in the
amount of $10.00. All study protocols were reviewed and
approved by the Institutional Review Board at Drexel
University.
Given the internet-mediated nature of the current study,
measures were taken to encourage accurate reporting.
Consistent with current practices in internet-mediated
psychological research (Prince et al. 2012), total time spent
completing the survey was used to distinguish legitimate
from fraudulent responses. In order to establish a time
frame for reasonable completion of the survey, a small
group of healthy adults were asked to pilot the survey
before it went live on the website. These individuals were
not provided with any information about the survey itself,
but rather sent the survey link and directed to respond to
questions accurately. None of the pilot testers completed
the survey in5 min. As such, a 5-min cutoff was used to
distinguish fraudulent from legitimate responses. Based on
this criterion, ten respondents indicating diagnosis of ASD
and three respondents indicating no ASD diagnosis were
excluded from analyses.
The final study sample included 172 adults between 18
and 60 years of age (M = 34.3 years; SD = 10.5 years).
The ASD sample was composed of 44 men (56 %) and 34
women (44 %), while the non-ASD sample was composed
of 29 men (31 %) and 65 women (69 %). Seventy-eight
participants (45.3 %) reported diagnosis of an ASD, while
94 participants (54.7 %) reported no diagnosis. Of the 78
individuals in the ASD group, 61 (78.2 %) indicated a
diagnosis of Autism, 16 (20.5 %) reported a diagnosis of
Asperger’s Disorder, and one participant (1.3 %) noted a
diagnosis of Pervasive Developmental Disorder, Not
Otherwise Specified. The majority of ASD respondents
(68.0 %) indicated that they had been diagnosed by a
physician, whereas 30.7 % had received their diagnosis
from a psychologist. The mean age of diagnosis was
17.28 years (SD = 8.76 years).
Measures
Demographic Data Sheet
Individuals in the ASD and control group completed a
demographic form developed for this study that solicited
information such as gender, age, race, ethnicity, and edu-
cational attainment. In addition, participants were asked to
provide information regarding their ASD diagnoses,
including providing the specific diagnosis received, age of
diagnosis, and type of diagnosing clinician.
Driving History and Preferences
In order to ascertain the driving history of study partici-
pants, we developed and included questions that solicited
information about the status of their driver’s license, fre-
quency of driving, history of accidents or traffic violations,
reasons for driving, limitations on driving, and a rating of
their ability to drive.
Driving Behaviors
The current study utilized a slightly modified version of the
DBQ (Reason et al. 1990). The DBQ is a self-report measure
that assesses the frequency of problem driving behaviors in
individual drivers. As one of the most widely used measures
in driving and accident prevention research, the DBQ has
evidenced good reliability and validity in over 100 studies
and has been utilized with clinical populations including
those with developmental disorders (Constantinou et al.
2011; deWinter and Doudou 2010; Lajunen et al. 2004;
Lucidietal.2010;Shahar2009;Wåhlbergetal.2011).Onthe
DBQ, individuals rate 50 problem driving behaviors on a 1–6
Likert-type scale where 1 = never and 6 = nearly all the
time,suchthathigherscoresareassociatedwithgreaterlevels
of driving problems. Each item falls under a behavioral type
category according to whether behaviors represent: (1)
intentional violations; (2) unintentional violations; (3) mis-
takes; and, (4) slips/lapses. Examples of items on the DBQ
include, ‘‘Become distracted or preoccupied and realize too
late that the vehicle ahead of you has slowed down, then have
to slam on the breaks to avoid a collision’’, and, ‘‘Misjudge
speed of an oncoming vehicle when passing.’’ Items on the
DBQ are also assigned a risk category in terms of whether
J Autism Dev Disord (2014) 44:3119–3128 3121
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4. behaviors pose no risk (that is, behaviors that are mistakes,
but do not likely threaten the safety of pedestrians or other
drivers), possible risk (behaviors that may threaten the safety
of pedestrians or other drivers), or definite risk to others
(behaviors that definitely threaten the safety of pedestrians or
other drivers).
Because the DBQ was developed in the United King-
dom, several minor changes to the wording of certain items
were made to better match an American audience. For
example, because drivers from the United Kingdom drive
on the left side of the road, several items were changed to
reflect driving on the right-hand side of the road. Further-
more, four questions were removed because they did not
apply to an American audience, were outdated, or were
potentially offensive (removed items included those
applicable only to a manual transmission or stereotyping
the racial/ethnic identify of other drivers). Finally, two
items were added to the end of the survey that assessed
talking on a cell phone or sending text messages while
driving. Because using a cell phone while driving is not a
legal violation in all states, these behaviors were not
included in a behavioral type category. However, using a
cell phone while driving poses a definite risk to other
drivers (Klauer et al. 2006), and was therefore assigned to
the risk category of definite risk to others.
Internal consistency for the modified DBQ total scores,
each behavioral category, and each risk category was
computed using Cronbach’s alpha, and results indicated
adequate to excellent internal consistency (a = .73–.99)
for each component. In terms of construct validity, binary
logistic regressions revealed that irrespective of group,
higher scores on the DBQ were predictive of self-reported
traffic violations, a = -2.74, SEa = .48, b = .01, SEb =
.004, p .01 and motor vehicle accidents, a = -2.64,
SEa = .47, b = .01, SEb = .004, p .01.
Statistical Analysis
Statistical analyses were conducted using Statistical Pack-
age for Social Sciences (SPSS) version 18.0. Means and
standard deviations were calculated for the demographic
variables (gender, age, race, ethnicity, education) and
between-group comparisons were performed using t tests
and Chi Square Tests of Independence. Next, Chi Square
Tests of Independence were used to compare the driving
history of individuals with ASD to controls across the
DBQ. Pearson’s correlations were run to examine the
relationship between driving history and DBQ scores for
each diagnostic group. Finally, ANCOVAs controlling for
demographic variables that significantly differed between
groups were used to compare DBQ total scores, behavior
category scores, and risk category scores between ASD and
non-ASD drivers.
Results
Complete demographic data for both groups are presented
in Table 1. As expected, the ASD group included signifi-
cantly more male respondents as compared to the non-ASD
group, [v2
(1, N = 172) = 11.40, p .001, V = .26],
which is consistent with the male preponderance in the
diagnosis of ASD relative to the normal population (CDC
2012). However, there were no differences in self-reported
driving behaviors between males and females for either the
ASD group or controls (all ps [ . 05). Although there were
no significant differences in race between diagnostic
groups, ASD drivers were more likely to be Hispanic,
[v2
(1, N = 172) = 15.69, p .001, V = .30]. In addition,
Table 1 Demographic characteristics
Characteristic ASD sample Non-ASD
sample
n = 78 n = 94
Gender*
Male 44 (56.4 %) 29 (30.9 %)
Female 34 (43.6 %) 65 (69.1 %)
Age 32.9 (± 8.1) 35.3 (± 12.0)
Self-reported diagnosis
Autism 61 (78.2 %) –
Asperger’s disorder 16 (20.5 %) –
Pervasive developmental
disorder
1 (1.3 %) –
Diagnosing clinician
Psychiatrist 29 (37.2 %) –
Primary care or family physician 24 (30.8 %) –
Psychologist 21 (26.9 %) –
School psychologist 3 (3.8 %) –
Other 1 (1.3 %) –
Race
American Indian or Alaskan
Native
2 (2.6 %) 0 (0 %)
Asian 6 (7.7 %) 15 (16.0 %)
Black or African American 8 (10.3 %) 3 (3.2 %)
Native Hawaiian or Pacific
Islander
2 (2.6 %) 0 (0 %)
White 56 (71.8 %) 70 (74.5 %)
Other 4 (5.1 %) 6 (6.4 %)
Hispanic ethnicity** 24 (30.8 %) 7 (7.4 %)
Highest level of education completed**
Certificate of high school
attendance
0 (0 %) 4 (5.1 %)
High school diploma or GED 21 (26.9 %) 19 (20.2 %)
Associate’s degree 20 (25.6 %) 8 (8.5 %)
Bachelor’s degree 29 (37.2 %) 28 (29.8 %)
Postgraduate degree 4 (5.1 %) 39 (41.5 %)
* p .01; ** p .001
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5. there were significant group differences in level of educa-
tion [v2
(4, N = 172) = 36.57, p .001, V = .46] pri-
marily due to the greater likelihood of non-ASD
respondents than ASD respondents to have received post-
graduate degrees. When asked to describe their employ-
ment status, 60.26 % of ASD respondents (n = 47) and
62.77 % of controls (n = 59) reported being employed
full-time; 19.23 % of ASD respondents (n = 15) and
12.77 % of controls (n = 12) reported being employed
part-time; 14.10 % of ASD respondents (n = 11) and
20.21 % of controls (n = 19) reported being in school; and
6.41 % of ASD respondents (n = 5) and 4.26 % of con-
trols (n = 4) indicated that they did not work. However,
between-group differences in terms of self-reported
employment status did not reach significance [v2
(3,
N = 172) = 2.47, p = .48, V = .12]. No other significant
group differences in demographic characteristics were
identified.
Driving History and Preferences
A summary of the responses to the driving history ques-
tions are presented in Table 2. Drivers diagnosed with an
ASD reported obtaining their driver’s license approxi-
mately 2 years later (Mean age = 19.97, SD = 3.62) than
non-ASD drivers [M = 17.54, SD = 2.93, t(147.55) =
4.76, p .001, 95 % CI [1.42, 3.44], d = .74 (correction
applied for violation of equal variance)], and also drove
nearly one fewer day per week (M = 4.85, SD = 1.85)
than non-ASD drivers [M = 5.63, SD = 1.97,
t(170) = 2.66, p = .01, 95 % CI [-.20, -1.36], d = .41].
The majority of drivers in both the ASD and control group
(80.85 and 94.87 %, respectively) reported using a car as
their primary means of transportation. In terms of reasons
for driving, individuals with and without ASD most com-
monly reported driving for work and leisure. ASD
respondents were slightly, but not significantly, more likely
to drive to school as compared to non-ASD participants
(39.36 and 28.21 %, respectively), but ASD drivers were
significantly less likely than non-ASD drivers to drive for
errands [65.38 and 86.17 %, respectively; [v2
(1,
N = 172) = 10.32, p = .001, V = .25].
When presented with a 10-point Likert-type scale asking
participants to rate their overall driving ability, individuals
with ASD rated their ability as lower (M = 7.22,
SD = 2.06) as compared to non-ASD drivers (M = 8.67,
SD = 1.13), t(114.30) = -5.57, p .001, 95 % CI [-.94,
-1.97], d = .87 (correction applied for violation of equal
variance). In addition, individuals with ASD were more
likely than non-ASD drivers to place voluntary restrictions
on their driving (62.82 and 48.93 %, respectively) though
this difference was just below the threshold of statistical
significance, v2
(1, N = 172) = 3.32, p = .07, V = .14.
Table 2 Driving history and preferences
ASD drivers Non-ASD
drivers
p
n = 78 n = 94
Age at licensure 19.97 (±3.62) 17.54
(±2.93)
.001***
Primary mode of
transportation
.02*
Car 74 (94.87 %) 76 (80.85 %)
Bus 2 (2.56 %) 2 (2.12 %)
Train or subway 2 (2.56 %) 7 (7.44 %)
Walking 0 (0 %) 9 (9.60 %)
Days per week of
driving
4.85 (±1.85) 5.63 (±1.97) .01**
Average miles driven
per year
11,629.84
(±25,704.15)
7,626.17
(±9,115.84)
.24
Reasons for driving
Work 61 (91.00 %) 70 (97.20 %) .57
Leisure 59 (75.64 %) 74 (78.72 %) .63
Travel 38 (48.72 %) 63 (67.02 %) .02*
Medical
appointments
48 (61.54 %) 61 (64.89 %) .65
School 22 (28.21 %) 37 (39.36 %) .13
Errands 51 (65.38 %) 81 (86.17 %) .001***
Voluntary restrictions
on driving
49 (62.82 %) 46 (48.93 %) .07
In bad weather 38 (48.72 %) 40 (42.55 %)
During heavy traffic 30 (38.46 %) 18 (19.15 %)
During evening or
night
25 (32.05 %) 11 (11.70 %)
To avoid highway 13 (16.67 %) 6 (6.38 %)
To avoid city 11 (14.10 %) 14 (14.89 %)
Self-rated driving skill
(1–10 scale)
7.22 (±2.06) 8.67 (±1.13) .001***
Traffic violations, past
2 years (overall)
24 (30.77 %) 12 (12.77 %) .01**
Circumstances
Speeding 18 (23.07 %) 5 (5.32 %)
Ran a red light/stop
sign
19 (24.36 %) 2 (2.13 %)
Reckless driving 12 (15.38 %) 2 (2.13 %)
Illegal turn 8 (10.26 %) 1 (1.10 %)
Drinking and driving 4 (5.12 %) 1 (1.10 %)
Accidents, past 2 years 22 (28.21 %) 16 (17.02 %) .08
Circumstances
I hit another driver or
pedestrian with my
car
8 (36.36 %) 1 (6.25 %)
I hit something else
with my car
9 (40.91 %) 1 (6.25 %)
Someone else hit my
car
5 (22.73 %) 11 (68.75 %)
Other 0 (0 %) 3 (18.75 %)
* p .05; ** p .01; *** p .001
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6. Respondents in the ASD group were more likely than non-
ASD respondents to avoid driving during times when
heavy traffic was expected (38.46 and 19.15 %, respec-
tively), v2
(1, N = 172) = 7.90, p = .005, V = .21; in the
evening or nighttime (32.05 and 11.70 %, respectively),
v2
(1, N = 172) = 10.67, p = .001, V = .25; and on the
highway (16.67 and 6.38 %, respectively), v2
(1,
N = 172) = 4.59, p = .03, V = .16. However, drivers
with ASD were not more likely than non-ASD drivers to
avoid driving in bad weather or in the city.
Respondents in the ASD group were significantly more
likely to report having been charged with a traffic violation
during the past 2 years (30.77 %) as compared to controls
(12.77 %), v2
(1, N = 172) = 8.35, p = .004. V = .22.
More specifically, ASD drivers reported more violations in
the following areas compared to controls: speeding tickets
(23.08 vs. 5.32 %), running a red light/stop sign (24.36 vs.
2.13 %), engaging in reckless driving (15.38 vs. 2.13 %),
and completing an illegal turn (10.26 vs. 1.06 %). No
significant differences were found for reports of drinking
and driving between the ASD drivers (5.13 %) and controls
(1.06 %). Individuals with ASD were also more likely to
endorse involvement in a traffic accident during the past
2 years, but this comparison did not reach statistical sig-
nificance, v2
(1, N = 172) = 3.10, p = .08, V = .13. Of
drivers who reported involvement in an accident over the
past 2 years, ASD drivers were more likely than controls to
report having hit a car or person (36.36 vs. 6.25 %) and
having hit something (40.91 vs. 6.25 %) but they were less
likely than controls to report having their car hit by
someone else (0.00 vs. 18.75 %).
Driving Behaviors
Variables found to be significantly different between ASD
and non-ASD drivers (gender, ethnicity, and education
level) were included in analyses as covariates. Results
indicate that drivers with ASD obtained significantly
higher DBQ total scores (M = 132.71, SD = 52.23) as
compared to controls (M = 88.32, SD = 35.11), F(1,
162) = 8.83, p .003, gp
2
= .05. In terms of the behavioral
type categories, a Repeated Measures ANCOVA revealed
a significant interaction effect of diagnostic group and
DBQ subscale type on scores, F(1.48, 162) = 9.85,
p .001, gp
2
= .06 (Greenhouse-Geisser correction
applied). ASD respondents endorsed greater numbers of
problem driving behaviors as compared to control par-
ticipants on subscales assessing intentional violations,
F(1, 162) = 6.15, p = .01, gp
2
= .04; mistakes,
F(1,162) = 10.15, p = .002, gp
2
= .06; and slips/lapses,
F(1, 162) = 11.33, p = .001, gp
2
= .07. The groups did
not significantly differ on the unintentional violations
subscale, F(1, 162) = .67, p = .42, gp
2
= .004.
To examine whether driving experience related to self-
reported driving competency, we calculated a rough esti-
mate of total driving experience by multiplying the number
of days per week respondents reported driving by the
number of years they have been licensed. For non-ASD
drivers, total driving experience was negatively correlated
with total DBQ score (r = -.34, p = .001) as well as each
subscale score (rs = -.22 to -.36, ps .05). However,
for ASD drivers, there was no significant relationship
between total driving experience and total DBQ score
(r = .01, p = .95) or any of the subscale scores (rs = .01–
.05, ps = .70–.90). We also examined whether self-per-
ceived overall driving ability on a 1–10 scale related to
driving behaviors on the DBQ. For non-ASD drivers, self-
perceived driving ability was negatively correlated with
total DBQ score (r = -.25, p = .02) as well as subscale
scores for intentional driving violations (r = -.24,
p = .02), mistakes (r = -.27, p = .01), and slips/lapses
(r = -.25, p = .01); there was a negative relationship
between self-perceived driving ability and unintentional
violations as well but it did not reach statistical significance
(r = -.18, p = .08). For ASD drivers, there was no sig-
nificant relationship between self-perceived driving and
DBQ total score (r = -.003, p = .98) or any subscale
scores (rs = -.07 to .04, ps = .56–.89).
Risk Profiles
We next examined differences in driving behaviors for
drivers with and without ASD based on driving risk,
meaning driving behaviors that pose no risk, those that
pose possible risk, and those that pose definite risk.
A Repeated Measures ANCOVA revealed a significant
interaction effect of diagnostic group and DBQ risk cate-
gory on scores, F(1.12, 162) = 8.14, p = .004, gp
2
= .05,
with the largest difference in scores between ASD and non-
ASD drivers occurring in the high risk category and smaller
differences in scores for no risk and possible risk categories.
However, drivers with ASD had significantly higher scores
in all three risk categories: no risk, F(1, 162) = 11.13,
p = .001, gp
2
= .06; possible risk, F(1,162) = 4.0,
p = .047; and definite risk, F(1,162) = 8.47, p = .004,
gp
2
= .05. For non-ASD participants, total driving
experience was significantly correlated with scores for all
three risk subscales (rs = -.28 to -.36, ps .01). How-
ever, for ASD participants, there was no relationship
between total driving experience and scores for any of
the risk categories (rs = -.02 to .04, ps = .75–.92). Simi-
larly, self-perception of overall driving ability was signi-
ficantly related to scores on all three risk subscales for
non-ASD drivers (rs = -.23 to -.28, ps = .01–.02) but
were not related for ASD drivers (rs = -.03 to .01,
ps = .79–.91).
3124 J Autism Dev Disord (2014) 44:3119–3128
123

7. Discussion
Although there is a developing literature on the driving
behavior of individuals with ASD, these studies exclu-
sively focus on teenagers or young adults, which may not
adequately account for currently licensed adult drivers with
ASD and may not fully represent driving difficulties among
this population. As such, the current study employed a
commonly used method in the driving literature to examine
driving behaviors among adult drivers with ASD. Specifi-
cally, this study which is the first to examine perceived
driving behaviors among licensed ASD adult drivers,
examined self-reported driving history, driving behaviors,
and risk profiles using a standardized driver behavior
questionnaire. The results indicate that ASD drivers
acquired licenses significantly later, drove significantly
fewer days per week, and reported more traffic violations
than non-ASD drivers. The finding that individuals with
ASD obtain their driving license more than 2 years later
than their non-ASD counterparts is in accord with the
extant literature that reveals the skill of learning to drive is
significantly challenging for individuals with ASD (Cox
et al. 2012), which may result in a delay for taking the
licensing exam and then ultimately obtaining a driver’s
license. Moreover, because no formal guidelines exist for
assessment of fitness to drive among teenagers with ASD
(Huang et al. 2012), it is also possible that parents of youth
with ASD place more restrictive limits on the timeline for
obtaining the initial driving permit and subsequent driver’s
license as compared to the parents of non-ASD youth.
The study also found that ASD drivers were more likely
to report themselves as ‘‘poor drivers’’ when compared to
their non-ASD counterparts. This is notable given the more
common observations in the driving literature that suggests
individuals are more likely to overrate their driving skills
and ability (Delhomme 1991; Goszcynska and Roslan
1989). Behaviorally, the ASD drivers were also more likely
to place restrictions on their driving such as avoiding
driving during times of heavy traffic, during evening or
nighttime hours, and on the highway. At face value, this
finding may be indicative of possible parental restrictions
during their early driving years and increased awareness
about limitations that together resulted in a cautious
approach to driving. In this sense, these results are aligned
with those of Huang et al. (2012) in which parents of
teenagers with ASD rated their child as more ‘‘rule-bound’’
and less ‘‘reckless’’.
However, our results also reveal that self-reported poor
driving ability for ASD drivers did not relate to self-
reported driving behavior on the DBQ, suggesting that
these individuals may be inaccurate in their self-appraisal
of driving ability. Several studies that have utilized self-
report questionnaires in youth or adults with ASD also
caution about the accuracy of self-appraisals in this popu-
lation for endorsement of psychiatric symptoms (Mazefsky
et al. 2011; White et al. 2009) or emotional responses
(Berthoz and Hill 2005; Ben Shalom et al. 2006). In
addition, given the high prevalence rate of depression in
adults with ASD (Bakken et al. 2010; Hofvander et al.
2009; Lugnegard et al. 2011), it is possible that respon-
dents’ perception of their driving ability was influenced by
negative affect. Ratings of driving ability also may have
been impacted by lack of a referent group as many adults
with ASD experience limited social contact (Barnhill 2007;
Engstrom et al. 2003), which likely includes contact with
drivers of the same age. Taken together, consideration for
differences in the information collected is warranted—for
example, factual information (e.g., days driving per week,
age licensed) may be more accurate than information that
requires self-appraisal (e.g., rate your driving ability) in
this population.
In terms of traffic violations, ASD drivers were signifi-
cantly more likely to have reported committing a violation
in the past 2 years relative to the control group. When
examined by circumstance of violation, ASD drivers
reported more parking violations, speeding tickets, running
a red light/stop sign, driving recklessly, and completing an
illegal turn. These findings are discrepant from those of
Huang et al. (2012) in which, according to parent/caregiver
report, driving teenagers in their survey study were less
likely to receive a driving citation when compared to the
general teen population. In addition, Cox et al. (2012)
found that parent ratings of teenage ASD drivers revealed
that they were adequate in simple driving skills such as
adhering to speed restrictions and staying in their driving
lane. It is notable, though, that the samples in these studies
were composed of teenagers and therefore considered early
drivers. Thus, it is possible that while teenage drivers with
ASD may be more cautious when initially engaging in
driving behaviors such as maintaining speed control, these
more experienced drivers habituate to the act of driving
over time and are then less conservative in their driving
actions. Alternatively, it may be that the ASD individuals
were more honest in their response style as compared to the
non-ASD individuals who may have been more likely to
provide socially desirable responses.
Group differences approached, but did not reach sig-
nificance, for reported involvement in a traffic accident.
However, the circumstances of the reported accidents
varied such that ASD respondents were significantly more
likely to endorse accidents in which they hit someone or
something, whereas control participants more frequently
reported having been hit by another driver. One possible
explanation is that the cause of some of these accidents is
attributable to situations that required increased cognitive
demand or more complex skills (e.g., merging onto a
J Autism Dev Disord (2014) 44:3119–3128 3125
123

8. highway), areas that are reported to be impaired in drivers
with ASD (Cox et al. 2012; Reimer et al. 2013). It is also
possible that the driving situations preceding some of these
accidents required the effective processing of social
information, another cognitive skill that has been shown to
be compromised in ASD drivers (Sheppard et al. 2010). As
noted before, another possible explanation is that the non-
ASD group may have self-reported fewer traffic collisions
due to their preference to be seen as good drivers, a finding
that has been demonstrated in previous research on the
relationship between social desirability and driving
behaviors (Wåhlberg 2010).
Of importance in this investigation is the finding that
individuals with ASD endorsed greater numbers of prob-
lem driving behaviors as compared to control participants
for most of the behavioral categories defined by the DBQ,
including intentional violations, mistakes, and slips/lapses.
These results suggest the possibility of global neurocog-
nitive and social processing challenges in driving behaviors
for individuals with ASD as opposed to a limited set of
specific skill deficits (e.g., hazard perception). For exam-
ple, neurocognitive skills that have been found to be
compromised in individuals with ASD including attention
modulation (Bird et al. 2006), social processing (Piggot
et al. 2004), motor coordination and motion perception
(Whyatt and Craig 2013) may be associated with the cat-
egories of driving mistakes and slips/lapses as conceptu-
alized by the DBQ. For instance, an item on the DBQ
questionnaire that is conceptualized as a driving mistake,
‘‘Turn onto a main road into the path of an incoming
vehicle that you haven’t seen, or whose speed you mis-
judged’’ could be accounted for by challenges associated
with attention modulation and/or motion perception. Sim-
ilarly, a question that falls under slips/lapses, ‘‘Lost in
thought or distracted, you fail to notice someone waiting at
a crosswalk’’ also could be related to problems with
attention modulation and perhaps social processing.
The finding that ASD drivers were comparable on
unintentional violations, but endorsed significantly greater
numbers of intentional driving violations on the DBQ (e.g.,
‘‘Deliberately disregard the speed limit late at night or very
early in the morning’’) as compared to the non-ASD group
is surprising. On the one hand, these results are in accord
with our finding that drivers with ASD are more likely to
have reported committing a violation such as receiving a
speeding ticket, running a red light/stop sign, driving
recklessly, and completing an illegal turn. Alternatively,
several previous studies suggest that, in the absence of
increased cognitive demand, ASD drivers are generally
able to legally maintain the speed limit and stay within
their driving lane (Cox et al. 2012; Reimer et al. 2013).
Given the preliminary nature of this finding, further
research should seek to assess the actual or simulated
driving ability of ASD drivers who have a history of unsafe
driving (e.g., multiple violations, license suspension) to
better determine the differential contribution of ‘‘inten-
tionality’’ as compared to mistakes or slips/lapses in regard
to their reckless driving.
Limitations
The contribution of our investigation must be interpreted
within the limitations of the study design. First, this pilot
study relied on anonymous self-report. Use of self-report
may be particularly problematic with individuals with ASD
because they may have different response patterns than
those without ASD. For instance, ASD-related social def-
icits and literal thinking patterns may make them more
honest in their responses and less prone to social desir-
ability bias than controls. Although several studies suggest
that individuals with ASD are able to accurately report
their own thoughts and emotions (Ozsivadjian et al. 2013)
and behaviors (Karlsson et al. 2013; Posserud et al. 2013),
other research findings indicate that individuals with ASD
may underreport their own symptoms and behaviors
(Bishop and Seltzer 2012; Johnson et al. 2009; Mazefsky
et al. 2011), possibly due to poor insight or difficulty
comparing their own behavior to that of others. Another
possible limitation is that participants from the control
group may have overrated their true driving ability, a
finding that is common in the driving literature in which
drivers rate themselves as more competent than the average
driver (Delhomme 1991; Goszcynska and Roslan 1989).
Although there are clear limitations to self-report, assess-
ment of driving behaviors through the use of standardized
self-report measures such as the DBQ nonetheless repre-
sent an important first step to ascertaining perceptions of
driving behaviors among adults with ASD.
Second, because our survey link was distributed on
various Internet outlets, only individuals with Internet
access could complete the survey, and therefore our sample
was not representative of the entire licensed driver adult
ASD population. Third, we relied on self-report of ASD
diagnosis, meaning we were unable to objectively verify
participants’ ASD diagnosis. Thus, the possibility remains
that some individuals who identified as having an ASD
may not have received an official diagnosis of ASD by a
licensed professional or may no longer meet criteria for a
diagnosis. Similarly, because we relied on self-report, we
could not verify that participants were licensed drivers or
that they were currently driving on a regular basis. In
addition, because the survey was anonymous, we were
unable to systematically verify the status of the partici-
pant’s driver’s license, leaving open the possibility that
some respondents did not have a current and valid license
3126 J Autism Dev Disord (2014) 44:3119–3128
123

9. or possessed a suspended license. Moreover, because
questions regarding potential comorbid psychiatric or
medical conditions were not included in the survey, we
cannot rule out the possibility that features of these con-
ditions also impacted self-reported driving behaviors.
Finally, the generally comparable gender ratio in the ASD
group in the current study is different from that reported in
large epidemiological studies in which males with a diag-
nosis of ASD vastly outnumber ASD females (Newschaffer
et al. 2007), suggesting that our findings may not gener-
alize to the larger ASD population. One potential expla-
nation for the higher prevalence of females in our study is
that women are more likely to respond to surveys as
compared to men (Curtin et al. 2000; Singer et al. 2000).
Given the limitations of the sample in the current study,
future research efforts that investigate driving in adults
with ASD should target a more representative sample to
increase the external validity of these results.
Despite these limitations, this study, to our knowledge,
is the first to examine a variety of driving behaviors in
licensed adult drivers with ASD using a validated measure.
Individuals with ASDs represent a large and growing
subset of the population, and it is imperative that
researchers explore the potential difficulties these individ-
uals encounter when driving. This is especially important
given the link between driving a car and independent
functioning in the community. Currently, no educational
materials or programming specific to the ASD population
have been developed to assist individuals in learning to
drive or driving safely. As such, identifying specific chal-
lenges drivers with ASDs experience is a preliminary step
to developing research-informed educational program-
ming. Future research should also investigate the rela-
tionship between common neurocognitive impairments
associated with ASD and specific problem driving behav-
iors, such as speeding and lane violations. Ultimately, this
type of research can help determine what types of driving
supports are warranted for the ASD community.
Acknowledgments The authors gratefully acknowledge Connor
Kerns, Ph.D. for her helpful comments in reviewing this manuscript.
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