TRAFFIC SAFETY FACTS
Research Note

DOT HS 811 737

Summary of Statistical Findings

April 2013

Distracted Driving 2011
Distracted driving is a behavior dangerous to drivers, passengers, and nonoccupants alike. Distraction is a specific
type of inattention that occurs when drivers divert theirattention from the driving task to focus on some other activity. A distraction-affected crash is any crash in which a driver
was identified as distracted at the time of the crash.
■■ Ten percent of fatal crashes in 2011 were reported as distraction-affected crashes.
■■ Seventeen percent of injury crashes in 2011 were reported
as distraction-affected crashes.
■■ In 2011, 3,331 people were killed in crashes involving distracted drivers and an estimated additional 387,000 were
injured in motor vehicle crashes involving distracted
drivers.
■■ Of those people killed in distraction-affected crashes, 385
died in crashes in which at least one of the drivers wasusing a cell phone (12% of fatalities in distraction-affectedcrashes) at the time of the crash. Use of a cell phoneincludes talking/listening to a cell phone, dialing/texting
a cell phone, or other cell-phone-related activities.
■■ Of those injured in distraction-affected crashes, an estimated 21,000 were injured in crashes that involved theuse of cell phones at the time of the crashes (5% of injured
people in distraction-affected crashes).
■■ Eleven percent of all drivers 15-19 years old involved in
fatal crashes were reported as distracted at the time of thecrashes. This age group has the largest proportion of drivers who were distracted.
■■ For drivers 15-19 years old involved in fatal crashes, 21
percent of the distracted drivers were distracted by theuse of cell phones.
■■ In 2011, 495 nonoccupants were killed in distractionaffected crashes.

Distraction in Fatal Crashes: New Measure in 2010
In a continuing effort towards data improvement, NHTSA
changed the coding for distracted driving in the Fatality
Analysis Reporting System (FARS) beginning with the 2010
FARS data. For this reason, this document will only include
NHTSA’s National Center for Statistics and Analysis

distraction-affected fatal crash data for 2010 and 2011. With
only two years of fatal crash information for distraction
under the new coding, the reader should take caution in
making conclusions of trends in these data.
The coding for distraction in the National Automotive
Sampling System (NASS) General Estimates System (GES)
was not revised and therefore GES data is available for years
prior to 2010.
Appendix A contains further detail on the change in coding for FARS beginning in 2010. The Research Note containing distracted-driving data for 2010 is available through the
NHTSA Web site (Distracted Driving 2010, DOT HS 811 650).

Methodology
The data sources include NHTSA’s FARS and NASS GES
systems. FARS annually collects fatal crash data from all 50
States, the District of Columbia, and Puerto Rico, and is a census of all fatal crashes that occur on the Nation’s roadways.
NASS GES contains data from a nationally ­representative
sample of police-reported crashes of all severities, including those that result in death, injury, or property damage. The national estimates produced from GES data are
based on a probability sample of crashes and are subject tosampling errors.
As defined in the Overview of the National Highway Traffic
Safety Administration’s Driver Distraction Program (DOT HS
811 299), distraction is a specific type of inattention that
occurs when drivers divert their attention from the driving task to focus on some other activity instead. It is worth
noting that distraction is a subset of inattention (which also
includes fatigue, physical, and emotional conditions of thedriver) as referenced in the Overview.
Appendix B contains a table to describe the coding for distraction-affected crashes for FARS and GES.
There are inherent limitations in the data for distractionaffected crashes and the resulting injuries and fatalities. Theselimitations are being addressed through efforts within andoutside of NHTSA as detailed in the Overview. Appendix C
describes limitations in the distracted driving data.
1200 New Jersey Avenue SE., Washington, DC 20590

2

Data

Table 2 describes 2011 fatal crash data for distractionaffected crashes by driver age. Eleven percent of all drivers
15-19 years old involved in fatal crashes were distracted at
the time of the crashes. This age group is the group with thelargest proportion of drivers who were distracted. An additional way to look at the age groups is how large a percentage of the total number of drivers involved was in each age
group. For all fatal crashes, only 7 percent of the drivers in
the fatal crashes were 15-19 years old. However, for distraction, 11 percent of the drivers in fatal distraction-affectedcrashes were 15-19 years old. Likewise, drivers in their 20s
were overrepresented in distraction-affected crashes relative to their proportion in total drivers — 23 percent of all
drivers in fatal crashes were in their 20s, but 26 percent of
distracted drivers were in their 20s. Both methods of looking at age illustrate the increased prevalence of distracted
younger drivers in fatal crashes.

Fatalities in Distraction-Affected Crashes
In 2011, there were a total of 29,757 fatal crashes in the UnitedStates involving 43,668 drivers. In those crashes, 32,367
people were killed. In 2011, 3,020 fatal crashes occurred thatinvolved distraction (10% of all fatal crashes). These crashes
involved 3,085 distracted drivers, as some crashes involved
more than one distracted driver. Distraction was reported
for 7 percent (3,085) of the drivers involved in fatal crashes.
In these distraction-affected crashes, 3,331 fatalities (10%of overall fatalities) occurred. Table 1 provides information
on crashes, drivers, and fatalities involved in distractionaffected crashes.
Of those drivers distracted during fatal crashes, cell phones
are often a leading distraction (of those identified). In 2011,
350 fatal crashes were reported to have involved the useof cell phones as a distraction (12% of all fatal distractionaffected crashes). For these distraction-affected crashes, thepolice accident report stated the driver used a cell phone totalk, listen, dial, or text (or other cell phone activity) at thetime of the crash. Cell phones were reported as a distraction
for 12 percent of the distracted drivers in fatal crashes. A
total of 385 people died in fatal crashes that involved the useof cell phones as distractions.

For drivers 15-19 years old, 21 percent of the distracted drivers were distracted by the use of cell phones at the time of thecrash. This was the age group that had the highest portionof distracted drivers identified as using cell phones. Among
all distracted drivers in fatal crashes using cell phones,
those drivers ages 20 to 29 represent 32 percent, which isan overrepresentation of this age group when compared todrivers overall.

Table 1

Fatal Crashes, Drivers in Fatal Crashes, and ­Fatalities, 2011
Crashes

Drivers

Fatalities

29,75743,66832,367

Distraction-Affected (D-A)

3,020(10% of total crashes)

3,085(7% of total drivers)

3,331(10% of total fatalities)

Cell Phone in Use

350(12% of D-A crashes)

368(12% of distracted drivers)

385(12% of fatalities in D-A crashes)

Total

Source: National Center for Statistics and Analysis (NCSA), FARS 2011 (ARF)

Table 2

Drivers Involved in Fatal Crashes by Age, 2011
Total Drivers

Distracted Drivers

Drivers Using Cell Phone#% of total#% total drivers% distracted
drivers#

Total

43,668

100

3,085

7

100

368

12

100

15-19

3,212

7

344

11

11

72

21

20

20-29

10,160

23

790

8

26

117

15

32

30-39

7,401

17

505

7

16

79

16

21

40-49

7,376

17

464

6

15

49

11

13

50-59

6,783

16

434

6

14

34

8

9

60-69

4,144

9

251

6

8

12

5

3

70+

3,815

9

270

9

9

5

2

1

Age Group% of distracted % of cell phone
drivers
drivers

Source: NCSA, FARS 2011 (ARF); Note: Total includes 60 drivers aged 14 and under, 4 of whom were noted as distracted.

NHTSA’s National Center for Statistics and Analysis

1200 New Jersey Avenue SE., Washington, DC 20590

3

Estimates of People Injured in Distraction-Affected Crashes

With respect to the vehicles driven by distracted drivers, thedistribution of vehicles among distracted drivers is similar
to the distribution of vehicles among all drivers (Table 3). For
example, 43 percent of distracted drivers were operating apassenger car at the time of the fatal crash, which is similar
to 40 percent of all drivers in fatal crashes were driving apassenger car.

In 2011, an estimated 2,217,000 people were injured in motor
vehicle traffic crashes (Table 5). The number of people
injured in a distraction-affected crash in 2011 was estimatedat 387,000 (17% of all the injured people). An estimated 21,000
people were injured in distraction-affected crashes in 2011
involving cell phones. These injured people comprised 5 percent of all people injured in distraction-affected crashes.

In 2011, 85 percent of the fatalities in distraction-affectedcrashes involved motor vehicle occupants or motorcyclists.
This compares to 84 percent of all motor vehicle crash fatalities involving occupants. Thus, the victims of distractionaffected crashes vary little from the victims of crashes overall.
Table 4 describes the role of the people killed in distractionaffected crashes in 2011. Distracted drivers were involved in
the deaths of 495 nonoccupants during 2011.

Over the past five years, the estimated number of people
injured in distraction-affected crashes has fallen from
448,000 to 387,000, a 14-percent decline (compared to an 11%
decline in the number of people injured overall during thistime period). However, the percentage of injured people indistraction-affected crashes as a portion of all injured people
has remained relatively constant (a high of 20% in 2008 and2009 to a low of 17% in 2011).

Table 3

Drivers Involved in Fatal Crashes by Vehicle Type, 2011
Total Drivers

Distracted Drivers

Drivers Using Cell Phone#% of total#% total drivers% distracted
drivers#

Total

43,668

100

3,085

7

100

368

12

100

Passenger Car

17,335

40

1,316

8

43

178

14

48

Light Truck

16,643

38

1,235

7

40

164

13

45

Motorcycle

4,741

11

265

6

9

3

1

2

Large Truck

3,568

8

202

6

7

22

11

6

243

1

20

8

1

0

0

0

Vehicle TypeBus

% of distracted % of cell phone
drivers
drivers

Source: NCSA, FARS 2011 (ARF)

Table 4People Killed in Distraction-Affected Crashes, by Person Type, 2011
Occupant

Nonoccupant

DriverPassenger

Total

Pedestrian

Pedalcyclist

Other

Total

2,024 (61%)

812 (24%)

2,836 (85%)

408 (12%)58 (2%)

29 (1%)

495 (15%)

Source: NCSA, FARS 2011 (ARF)

Table 5

Estimated Number of People Injured in Crashes andPeople Injured in Distraction-Affected Crashes
Distraction

Table 6

Estimates of Distraction-Affected Injury Crashes, Drivers,
and Injured People, 2011
Distraction-Affected
Injury Crashes

Distracted Drivers inDistraction-Affected
Injury Crashes

People Injured inDistraction-Affected
Injury Crashes

266,000(10% of all drivers ininjury crashes)

387,000(17% of all injured
people)Year

Overall

Estimate (% of Total
Injured)Cell Phone Use (%of People Injured inDistraction-Affected
Crashes)

2007

2,491,000

448,000 (18%)

24,000 (5%)

260,000(17% of all injury
crashes)

2008

2,346,000

466,000 (20%)

29,000 (6%)

Source: NCSA, GES 20112009

2,217,000

448,000 (20%)

24,000 (5%)

2010

2,239,000

416,000 (19%)

24,000 (6%)

2011

2,217,000

387,000 (17%)

21,000 (5%)

Source: NCSA, GES 2007-2011

NHTSA’s National Center for Statistics and Analysis

1200 New Jersey Avenue SE., Washington, DC 20590

4

Crashes of All Severity
Table 7 provides information for all police-reported crashes
from 2007 through 2011 including injury crashes, and property-damage-only (PDO) crashes for the year. During thistime period, the percentage of injury crashes that were distraction-affected fluctuated slightly, but remained relatively

constant. The percentage of PDO crashes that were distraction-affected remained at 16 percent for from 2007 through2010 and dropped to 15 percent in 2011 years. The percentage of total crashes that were distraction-affected crashes
also fell to 15 percent after remaining at 17 percent from 2007
through 2010.

Table 7

Motor Vehicle Traffic Crashes and Distraction-Affected Crashes by Year
Crash by Crash Severity
Non-Fatal Crashes
Injury Crash2007
PDO Crash
Total
Non-Fatal Crashes
Injury Crash2008
PDO Crash
Total
Non-Fatal Crashes
Injury Crash2009
PDO Crash
Total
Non-Fatal Crashes
Injury Crash2010
PDO Crash
Total
Non-Fatal Crashes
Injury Crash
2011
PDO Crash
Total

Overall Crashes

Distraction-Affected Crashes

D-A Crashes Involving
Cell Phone Use

1,711,000
4,275,000
6,024,000

309,000 (18%)
689,000 (16%)
1,003,000 (17%)

17,000 (6%)
31,000 (4%)
49,000 (5%)

1,630,000
4,146,000
5,811,000

314,000 (19%)
650,000 (16%)
969,000 (17%)

19,000 (6%)
30,000 (5%)
49,000 (5%)

1,517,000
3,957,000
5,505,000

307,000 (20%)
647,000 (16%)
959,000 (17%)

16,000 (5%)
29,000 (5%)
46,000 (5%)

1,542,000
3,847,000
5,419,000

279,000 (18%)
618,000 (16%)
900,000 (17%)

16,000 (6%)
30,000 (5%)
47,000 (5%)

1,530,000
3,778,000
5,338,000

260,000 (17%)
563,000 (15%)
826,000 (15%)

15,000 (6%)
35,000 (6%)
50,000 (6%)

Source: NCSA, GES 2007-2011; PDO – Property Damage Only

Appendix A
In keeping with the National Highway Traffic Safety
Administration’s distraction plan (Overview of the National
Highway Traffic Safety Administration’s Driver Distraction
Program, April 2010, DOT HS 811 299), the agency continues to refine collection of information about the role of distracted driving in police-reported crashes. This includes
an improvement to the coding of distraction in the Fatality
Analysis Reporting System (FARS). Prior to 2010, FARS,
which contains data about fatal motor vehicle crashes, andthe National Automotive Sampling System (NASS) General
Estimates System (GES), which contains data about a sample
of all severities of police-reported crashes, coded distraction
information in different formats. FARS was more generaland inclusive of generally inattentive behavior, whereas GES
identified specific distracted driving behaviors. In 2010, thetwo systems’ coding of distraction was unified. Beginning in2010 for both systems, when looking at distraction-affectedcrashes, the driver in both FARS and GES is identified as“Yes-Distracted,” “No-Not distracted,” or “Unknown if distracted.” If the driver is identified as distracted, further coding is performed to distinguish the specific activity that was
distracting the driver. This was not a change for data codNHTSA’s National Center for Statistics and Analysis

ing for GES, but was in FARS. The data collected on the PAR
did not change; rather, it is the way the data is classified in
FARS to focus the fatal crash data on the set of distractions
most likely to affect the crash. Prior to 2010 in FARS, distraction was not first identified in a Yes/No/Unknown manner.
Rather, specific behaviors of the driver as coded on the PAR
were combined and categorized as “distracted.”
Because of this change in data coding in FARS, distractionaffected crash data from FARS beginning in 2010 cannot becompared to distracted-driving-related data from FARS fromprevious years. GES data can be compared over the years, as
the data coding did not change in this system.
Of additional note is the terminology regarding distraction. For FARS and GES data, beginning with 2010 data, any
crash in which a driver was identified as distracted at thetime of the crash is referred to as a distraction-affected crash.
Discussion of cell phones is also more specific starting withthe 2010 data. Starting in 2010, FARS no longer offers “cellphone present in vehicle” as a coding option, thus this code
cannot be considered a distraction within the data set. Fromdiscussion with law enforcement officers, this code in years
past was used when it was believed that the driver was using
1200 New Jersey Avenue SE., Washington, DC 20590

5

a cell phone at the time of the crash and thus contributed tothe crash, but proof was not available. The use of a cell phone
is more specific with the current coding and if the specificinvolvement cannot be determined, law enforcement hasother options available to discuss the role of the cell phone
and thus the coding would reflect such. Because of thesechanges, the current language referring to cell phones is thatthe crash involved the use of a cell phone as opposed to thegeneric cell-phone-involvement used previously.

Appendix B
As discussed in the Methodology section of this ResearchNote, FARS and GES were accessed to retrieve distractionaffected crashes. Table B1 contains every variable attribute

Table B1

Attributes Included in “Driver Distracted By” Element and Indication of Inclusion in Distraction-Affected Definitions, GES
and FARS; Frequency of Distraction Attributes for FARS 2011

Attribute
Not distracted

ExamplesCompletely attentive to driving; no indication of distraction
or noted as Not Distracted
Looked but did
Driver paying attention to driving but does not see relevant
not seevehicle, object, etc.
By other occupant Distracted by occupant in driver’s vehicle; includes
conversing with or looking at other occupant
By moving object in Distracted by moving object in driver’s vehicle; includes
vehicledropped object, moving pet, insect, cargo.
While talking or
Talking or listening on cellular phone
listening to cellular
phone
While dialing cellular Dialing or text messaging on cell phone or any wirelessphone
email device
Other cellular
Used when the Police Report indicated the driver isphone-related
distracted from the driving task due to cellular phone(2007 and later)
involvement, but none of the specified codes are applicable(e.g., reaching for cellular phone, etc.). This code is also
applied when specific details regarding cellular phone
distraction/usage are not provided.
Adjusting audio and/ While adjusting air conditioner, heater, radio, cassette, using
or climate controls the radio, using the cassette or CD mounted into vehicle
While using other
Adjusting windows, door locks, rear/side view mirrors, seat,
devices/controls
steering wheel, seat belts, on-board navigational devices,integral to vehicle
etc.
While using or
Radar detector, CDs, razors, portable CD player,
reaching for device/ headphones, a navigational device, cigarette lighter, etc.;
object brought into if unknown if device is brought into vehicle or integral, use
vehicleObject Brought Into Vehicle
Distracted by
Animals on roadside or previous crash. Do not use whenoutside person,
driver has recognized object/event and driver has taken
object, or event
evasive action
Eating or drinking
Eating or drinking or actively related to these actions
Smoking related
Smoking or involved in activity related to smoking
No driver present
When no driver is in this vehicle
Distraction/
Distraction and/or inattention are noted on the PAR but the
inattention, details specifics are unknown
unknown
Not reported
No field available on PAR; field on PAR left blank; no otherinformation available
Inattentive or lost in Driver is thinking about items other than the driving task
thought(e.g., daydreaming)
Other distraction
Details regarding the driver’s distraction are known but
none of the specified codes are applicable
Unknown if
PAR specifically states unknown
distracted
NHTSA’s National Center for Statistics and Analysis

Included in:
Devices/
DistractionControls Integral Electronic
Frequency of
Affected Crashes to the Vehicle Device Use Driver Distraction

X

135

X

16

X

X

114

X

X

39

X

X

218

X

X

47

X

X

30

X

53

X

188

X
X

52
15

X

1,398

X

586

X

267

1200 New Jersey Avenue SE., Washington, DC 20590

6

available for coding for driver distraction along with examples to illustrate the meaning of the attribute. This is thecoding scheme available for FARS and GES. Table B1 further
indicates whether that attribute was included in the analysis
for distraction-affected crashes.

to variation in the reported number of distraction-affectedcrashes. Any national or State count of distraction-affectedcrashes should be interpreted with this limitation in mind
due to potential under-reporting in some States/primary
sampling units and over-reporting in others.

In some NHTSA distracted driving discussions and publications, there is reference to electronic device use as well as
use of devices integral to the vehicle. Table B1 includes indication of which attributes are used when referencing either
electronic device use or use of devices integral to the vehicle.

The following are potential reasons for underreporting of
distraction-affected crashes.

If there are no indications of usage for either the distractionaffected crashes, devices/controls integral to the vehicle, or
electronic device use, the attribute was not considered as a
type of distraction behavior and therefore not included in
the analysis.
Data users often request information regarding the frequencyof each attribute with respect to distracted drivers. Table B1
provides the frequency of driver distraction reported for distracted drivers in FARS 2011. Each driver could potentiallyhave multiple distraction behaviors noted in the PAR andthus these attributes are not mutually exclusive. This column
will not sum to the number of distracted drivers in 2011.

■■ There are negative implications associated with distracted
driving—especially in conjunction with a crash. Survey
research shows that self-reporting of negative behavior
is lower than actual occurrence of that negative behavior.
There is no reason to believe that self-reporting of distracted driving to a law enforcement officer would differ.
The inference is that the reported driver distraction during crashes is lower than the actual occurrence.
■■ If a driver fatality occurs in the crash, law enforcement
must rely on the crash investigation in order to report onwhether driver distraction was involved. Law enforcement may not have information to indicate distraction.
These investigations may rely on witness account andoftentimes these accounts may not be available either.

NHTSA recognizes that there are limitations to the collection
and reporting of FARS and GES data with regard to driver
distraction. The data for FARS and GES are based on PARsand investigations conducted after the crash has occurred.

Also to be taken into consideration is the speed at which
technologies are changing and the difficulty in updating the
PAR to accommodate these changes. Without broad-sweeping changes to the PAR to incorporate new technologies andfeatures of technologies, it is difficult to capture the data thatinvolve interaction with these devices.

One significant challenge for collection of distracted driving data is the PAR itself. Police accident reports vary acrossjurisdictions, thus creating potential inconsistencies inreporting. Many variables on the police accident report arenearly universal, but distraction is not one of those variables.
Some police accident reports identify distraction as a distinct
reporting field, while others do not have such a field and identification of distraction is based upon the narrative portionof the report. The variation in reporting forms contributes

In the reporting of distraction-affected crashes, oftentimes
external distractions are identified as a distinct type of distraction. Some of the scenarios captured under external
distractions might actually be related to the task of driving(e.g., looking at a street sign). However, the crash reports
may not differentiate these driving-related tasks from otherexternal distractions (looking at previous crash or billboard).
Currently, the category of external distractions is included in
the counts of distraction-affected crashes.

Appendix C

This research note and other general information on
highway traffic safety may be accessed by Internet
users at: www-nrd.nhtsa.dot.gov/CATS/index.aspx
NHTSA’s National Center for Statistics and Analysis

1200 New Jersey Avenue SE., Washington, DC 20590
9596-040313-v2