TRAFFIC SAFETY FACTS
Research Note

DOT HS 812 517

Summary of Statistical Findings

April 2018

Distracted Driving 2016
The National Highway Traffic Safety Administration (NHTSA)
works to reduce the occurrence of distracted driving and raiseawareness of its dangers. This risky behavior poses a danger tovehicle occupants as well as pedestrians and bicyclists. Driver
distraction is a specific type of driver inattention. Distraction
occurs when drivers divert their attention from the driving
task to focus on some other activity. Often discussions regarding distracted driving center around cell phone use and texting, but distracted driving also includes other activities suchas eating, talking to other passengers, or adjusting the radioor climate controls. A distraction-affected crash is any crashin which a driver was identified as distracted at the time of
the crash.
■■ Nine percent of fatal crashes in 2016 were reported as­distraction-affected crashes.
■■ In 2016, there were 3,450 people killed in motor vehicle

crashes involving distracted drivers.
■■ Six percent of all drivers involved in fatal crashes werereported as distracted at the time of the crash. Nine percent
of drivers 15 to 19 years old involved in fatal crashes werereported as distracted. This age group has the largest proportion of drivers who were distracted at the time of thefatal crashes.
■■ In 2016, there were 562 nonoccupants (pedestrians, bicy-

clists, and others) killed in distraction-affected crashes.

Methodology
This fact sheet contains information on fatal motor vehicle
crashes and fatalities, based on data from the Fatality Analysis
Reporting System (FARS). FARS is a census of fatal crashes in
the 50 States, the District of Columbia, and Puerto Rico (Puerto
Rico is not included in U.S. totals). Crash and injury statistics
are based on data from the National Automotive Sampling
System (NASS) General Estimates System (GES). The NASS
GES is a probability-based sample of police-reported trafficcrashes, from 60 locations across the country, from which estimates of national totals for injury and property-damage-onlycrashes are derived.
NASS GES was discontinued in 2016 and replaced with a new
system called the Crash Report Sampling System (CRSS). The
NHTSA’s National Center for Statistics and Analysis

2016 data year is the first data collection year of CRSS. The 2016
CRSS data was released the last week of March 2018. Thus,
injury and property-damage-only crash estimates for 2016
will not be presented in this publication. For more information, read Crash Report Sampling System (CRSS) Replaces
the National Automotive Sampling System (NASS) General
Estimates System (GES) at the end of this publication.
As defined in the Overview of the National Highway Traffic Safety
Administration’s Driver Distraction Program (Report No. 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. The document
describes distraction as a subset of inattention (which also
includes fatigue, and physical and emotional conditions of
the driver). However, while NHTSA may define the terms inthis manner, inattention and distraction are often used interchangeably or simultaneously in other material, including
police crash reports. It is important that NHTSA and NHTSA’s
data users be aware of these differences in definitions. It isalso important to acknowledge the inherent limitations in thedata collection for distraction-affected crashes and the resulting injuries and fatalities. The appendix of this document contains a table that describes the coding for distraction-affectedcrashes for FARS and GES as well as a discussion regarding
limitations in the distracted driving data.

Data
Fatalities in Distraction-Affected Crashes
In 2016, there was a total of 34,439 fatal crashes in the UnitedStates involving 51,914 drivers. As a result of those fatal
crashes, 37,461 people were killed.
There were 3,157 fatal crashes that occurred on U.S. roadways
in 2016 that involved distraction (9% of all fatal crashes). These
crashes involved 3,210 distracted drivers, since some crashes
involved more than one distracted driver. Distraction wasreported for 6 percent (3,210 of 51,914) of the drivers involvedin fatal crashes. In these distraction-affected crashes, 3,450
fatalities (9% of overall fatalities) occurred. Table 1 provides
information on crashes, drivers, and fatalities involved in fatal
distraction-affected crashes in 2016.
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Table 1

Fatal Crashes, Drivers in Fatal Crashes, and Fatalities, 2016
Crashes

Drivers

Fatalities

34,43951,914

37,461

Distraction-Affected (D-A)

3,157(9% of total crashes)

3,210(6% of total drivers)

3,450(9% of total fatalities)

Cell Phone in Use

444(14% of D-A crashes)457(14% of distracted drivers)

486(14% of fatalities in D-A crashes)

Total

Source: FARS 2016 Annual Report File (ARF)

Much attention across the country has been focused on thedangers of using cell phones and other electronic devices
while driving. In 2016, there were 444 fatal crashes reported tohave involved cell phone use as a distraction (14% of all fatal
distraction-affected crashes). For these distraction-affectedcrashes, the police crash report stated that the driver wastalking on, listening to, or engaged in some other cell phone
activity at the time of the crash. A total of 486 people diedin fatal crashes that involved cell-phone-related activities as
distractions.
Table 2 presents data on drivers involved in fatal crashes in2016 by the driver’s age. Nine percent (303 of 3,323) of drivers 15
to 19 years old involved in fatal crashes were distracted at thetime of the crash. This age group has the largest proportion ofdrivers within each respective age group who were distracted(column titled “Distracted Drivers: % of Total Drivers in This
Age Group”).
Comparing the percentage of drivers of each age involved in
fatal crashes to the percentage involved in distraction-affectedfatal crashes points to overrepresentation of drivers under 30.
This is seen by comparing the columns titled “Total Drivers:% of Total Drivers” and “Distracted Drivers: % of Distracted
Drivers.” For all fatal crashes, 6 percent of the drivers involved
were 15 to 19 years old (3,323 of the 51,914). However, 9 percentof the distracted drivers were 15 to 19 years old (303 of the
3,210 distracted drivers in fatal crashes). Thirteen percent of

all the distracted drivers using cell phones were 15 to 19 years
old (58 of the 457 cell-phone distracted drivers in fatal crashes).
Similarly, drivers in their 20s make up 24 percent of drivers
in fatal crashes, but are 28 percent of the distracted drivers
and 35 percent of the distracted drivers who were using cell
phones in fatal crashes.
The distributions of drivers by age for all drivers involvedin fatal crashes, distracted drivers involved in fatal crashes,and distracted drivers on cell phones during fatal crashes, areshown graphically in Figure 1.
Figure 1

Percent Distribution of Drivers Involved in Fatal Crashes
By Age, Distraction, and Cell Phone Use, 201640%

Percent of Total Drivers
Percent of Distracted Drivers
Percent of Cell Phone Users

35%
30%
25%
20%
15%
10%
5%
0%

15–19 20–29 30–39 40–49 50–59 60–69

70+

Source: FARS 2016 ARF

Table 2

Drivers Involved in Fatal Crashes by Age, Distraction, and Cell Phone Use, 2016
Total Drivers
Age Group

NumberDistracted Drivers% of Total
Drivers

Number% of Total Drivers inThis Age Group

Drivers Using Cell Phones% of All Distracted
Drivers

Number% of Distracted % of Cell Phone
Drivers
Drivers

15–19

3,323

6%

303

9%

9%

58

2%

13%

20–29

12,335

24%

898

7%

28%

159

5%

35%

30–39

9,064

17%

586

6%

18%

96

3%

21%

40–49

7,797

15%

400

5%

12%

69

2%

15%

50–59

7,945

15%

415

5%

13%

48

1%

11%

60–69

5,591

11%

288

5%

9%

21

1%

5%

70+

4,628

9%

282

6%

9%

5

0%

1%

Total

51,914

100%

3,210

6%

100%

457

14%

100%

Source: FARS 2016 ARF; Note: The total includes 77 drivers 14 and younger, 8 of whom were noted as distracted. Additionally, the total includes 1,154 of unknown age, 30 ofwhom were noted as distracted.

NHTSA’s National Center for Statistics and Analysis

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Table 3 shows the role of the people killed in distractionaffected crashes in 2016. The large majority of fatalities in
distraction-affected crashes (and in all fatal crashes) weremotor vehicle occupants (including motorcyclists), 84 percent for distraction-affected fatal crashes and 81 percent for
all fatal crashes. The balance of victims were nonoccupants—
pedestrians, pedalcyclists, and others. Distracted drivers wereinvolved in the deaths of 562 nonoccupants during 2016. It is
unknown how many of these nonoccupants were potentiallydistracted as well. In general, looking at occupant type, thepercentage of fatalities in distraction-affected crashes is very
similar to that in all fatal crashes.
Table 3

Person Type
Total

All Fatalities
in Crashes
37,461100%

Estimated Number of People Injured in Crashes and People
Injured in Distraction-Affected Crashes, 2012–2016
Distraction
Estimated Number
Cell Phone Useof People Injured(% of People Injured in(% of Total Injured) Distraction-Affected Crashes)

Year

Total

2012

2,362,000

421,000 (18%)

28,000 (7%)

2013

2,313,000

424,000 (18%)

34,000 (8%)

2014

2,338,000

431,000 (18%)

33,000 (8%)

2015

2,443,000

391,000 (16%)

30,000 (8%)

2016*

N/A

N/A

N/A

Source: NASS GES 2012–2015*Not Available

People Killed in All Crashes and Distraction-Affected
Crashes, By Person Type, 2016
Percentage
of AllFatalities

Table 4

Fatalities in Percentage ofDistraction- DistractionAffected
Affected
Crashes
Fatalities
3,450

100%

Occupants
Driver

23,560

63%

2,025

59%

Passenger

6,822

19%

863

25%

Total
Occupants

30,382

81%

2,888

84%

Crashes of All Severity
Table 5 provides information for fatal crashes from 2012
through 2016, and all police-reported injury and propertydamage-only (PDO) from 2012 through 2015. During thistime period, the percentages of crashes of all severities thatinvolve distractions fluctuated very little.
Table 5Motor Vehicle Traffic Crashes and Distraction-Affected
Crashes by Year, 2012–2016

Nonocccupants
Pedestrian

5,987

16%

462

13%

Pedalcyclist

840

2%

70

2%

Other

252

1%

30

1%

Total
Nonoccupants

7,079

19%

562

16%

2012

Source: FARS 2016 ARF

In 2016, 70 percent of the distracted drivers in fatal crashes
were male as compared to 74 percent of drivers in all fatal
crashes.

Estimates of People Injured in Distraction-Affected
Crashes
From 2012 to 2015, the estimated number of people injured in
distraction-affected crashes showed decreases and increases.
The percentage of injured people in distraction-affected crashes
as a proportion of all injured people remained relatively
constant.

2013

2014

2015

2016

DistractionD-A Crashes
Affected Crashes
Involving Cell(% of Total
Phone Use
Crashes)(% of D-A Crashes)

Crash
Severity

Overall
Crashes

Fatal Crash

31,006

3,098 (10%)

380 (12%)Injury Crash

1,634,000

286,000 (18%)

21,000 (7%)

PDO* Crash

3,950,000

619,000 (16%)

39,000 (6%)

Total

5,615,000

908,000 (16%)

60,000 (7%)

Fatal Crash

30,202

2,923 (10%)

411 (14%)

Injury Crash

1,591,000

284,000 (18%)

24,000 (8%)

PDO Crash

4,066,000

616,000 (15%)

47,000 (8%)

Total

5,687,000

904,000 (16%)

71,000 (8%)

Fatal Crash

30,056

2,972 (10%)

387 (13%)

Injury Crash

1,648,000

297,000 (18%)

22,000 (8%)

PDO Crash

4,387,000

667,000 (15%)

46,000 (7%)

Total

6,064,000

967,000 (16%)

69,000 (7%)

Fatal Crashes

32,5393,242 (10%)

453 (14%)

Injury Crash

1,715,000

265,000 (15%)

21,000 (8%)

PDO Crash

4,548,000

617,000 (14%)

48,000 (8%)

Total

6,296,000

885,000 (14%)

69,000 (8%)

Fatal Crashes

34,4393,157 (9%)

444 (14%)

Injury Crash

N/A

N/A

N/A

PDO Crash

N/A

N/A

N/A

Total

N/A

N/A

N/A

*PDO = Property-Damage-Only; D-A = Distraction-Affected
Sources: NCSA, FARS 2012–2015 Final File, FARS 2016 ARF, GES 2012–2015.

NHTSA’s National Center for Statistics and Analysis

1200 New Jersey Avenue SE., Washington, DC 20590

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Appendix — Coding of Distraction During Crashes
In keeping with its distraction plan (Overview of the National
Highway Traffic Safety Administration’s Driver Distraction
Program, April 2010, Report No. DOT HS 811 299), NHTSA
continues to refine collection of information about the role of
distracted driving in police-reported crashes. This includes
improvements to the coding of distraction in FARS. Prior to2010, FARS, which contains data about fatal motor vehicle
crashes, and the NASS GES, which contains data about asample of all severities of police-reported crashes, coded distraction information in different formats. FARS was more general and inclusive of generally inattentive behavior, whereas
GES identified specific distracted-driving behaviors. In 2010,
the two systems’ methods of coding distraction were unified. Beginning in 2010 for both systems, when looking at
distraction-affected crashes, 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 specificactivity that was distracting the driver. This was not a change
for data coding for GES, but was in FARS. The data collectedon the Police Accident Report (PAR) did not change; rather, itis the way the data is classified in FARS to focus the fatal crashdata 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 thedriver as coded on the PAR were combined and categorizedas “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. With only 7 years of fatal crash information
for distraction under the new coding, the reader should takecaution in making conclusions of trends in these data. 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 crashin which a driver was identified as distracted at the time of thecrash is referred to as a distraction-affected crash. Discussionof cell phones is also more specific starting with the 2010 data.
Starting in 2010, FARS no longer offers “cell phone present invehicle” as a coding option; thus this code cannot be considered a distraction within the dataset. From discussion withlaw enforcement officers, this code in years past was used
when it was believed that the driver was using a cell phone
at the time of the crash and thus contributed to the crash, but
proof was not available. The use of a cell phone is more specificwith the current coding and if the specific involvement cannot
be determined, law enforcement has other options available todiscuss the role of the cell phone and thus the coding would
reflect such. Because of these changes, the current language
NHTSA’s National Center for Statistics and Analysis

referring to cell phones is that the crash involved the use ofa cell phone as opposed to the generic cell-phone-involvement
used previously.
In a continuing effort towards uniformity in data collection
among states, the Model Minimum Uniform Crash Criteria(MMUCC) was updated in June 2012. MMUCC is a guideline
for collection of crash characteristics in PARs. In this updated
edition, MMUCC Guideline, 4th Edition, the reporting elementfor distraction was improved after consultation with law
enforcement, safety advocates, first responders, and industry
representatives. The States are increasingly becoming compliant with these MMUCC guidelines.

Attribute Selection
As discussed in the Methodology section of this ResearchNote, FARS and GES were accessed to retrieve distractionaffected crashes. Table A-1 contains every variable attributeavailable for coding for driver distraction along with examples to illustrate the meaning of the attribute. This is the coding scheme available for FARS and GES. Table A-1 further
indicates whether that attribute was included in the analysis
for distraction-affected crashes.
In 2012, the variable attributes changed to account for different ways that State police accident reports describe generalcategories of distraction, inattention, and careless driving.
These additional attributes provide a more accurate classification of the behavior indicated on the police accident report.
If there are no indications of usage for distraction-affectedcrashes, the attribute was not considered as a type of distraction behavior and therefore not included in the analysis.

Data Limitations
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 information gathered after the crashes have occurred.
One noteworthy challenge for collection of distracted driving
data is the PAR itself. Police crash reports vary across jurisdictions, thus creating potential inconsistencies in reporting.
Many variables on the police accident report are nearly universal, but distraction is not one of those variables. Some PARs
identify distraction as a distinct reporting field, while others
do not have such a field and identification of distraction isbased upon the narrative portion of the report. The variationin reporting forms contributes to variation in the reported
number of distraction-affected crashes. Any national or State
count of distraction-affected crashes should be interpretedwith this limitation in mind due to potential underreportingin some States and overreporting in others.
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Table A-1

Attributes Included in “Driver Distracted by” Element and Indication of Inclusion in Distraction-Affected Definitions,
GES and FARSDistraction-Affected
Crashes
Attribute

2012–2016

ExamplesNot distracted

Completely attentive to driving; no indication of distraction or noted as Not Distracted

Looked but did not see

Driver paying attention to driving but does not see relevant vehicle, object, etc.

By other occupant

Distracted by occupant in driver’s vehicle; includes conversing with or looking at otheroccupant

X

By a moving object in vehicle

Distracted by moving object in driver’s vehicle; includes dropped object, moving pet,
insect, cargo.

X

While talking or listening tocellular phone

Talking or listening on cellular phone; includes talking or listening on a “hands-free” orBluetooth-enabled phone

X

While manipulating cellular
phone

Dialing or text messaging on cell phone or any wireless email device; any manual button/
control actuation on phone qualifies

X

Other cellular phone-related

Used when the police report indicated the driver is distracted from the driving task due tocellular phone involvement, but none of the specified codes are applicable (reaching forcellular phone, etc.). This code is also applied when specific details regarding cellular phone
distraction/usage are not provided

X

While adjusting audio and/or
climate controls

While adjusting air conditioner, heater, radio, cassette, using the radio, using the cassette or
CD mounted into vehicle

X

While using other component/
controls integral to vehicle

Manipulating a control in the vehicle including adjusting headlamps, interior lights,
controlling windows, door locks, mirrors, seats, steering wheels, on-board navigational
devices, etc.

X

While using or reaching for
device/object brought into
vehicleRadar detector, CDs, razors, music portable CD player, headphones, a navigational device, alaptop or tablet PC, etc.; if unknown if device is brought into vehicle or integral, use Object
Brought Into Vehicle

X

Distracted by outside person,
object, or event

Animals on roadside or previous crash, non-traffic related signs. Do not use when driver has
recognized object/event and driver has taken evasive action

X

Eating or drinking

Eating or drinking or actively related to these actions

X

Smoking related

Smoking or involved in activity related to smoking

X

No driver present/unknown if
driver present

When no driver is in this vehicle or when it is unknown if there is a driver present in thisvehicle at the time of the crashDistraction/Inattention

Used exclusively when “distraction/inattention” or “inattention/distraction” are noted in casematerials as one combined attribute

X

Distraction/CarelessUsed exclusively when “distraction/careless” or “careless/distraction” are noted in casematerials as one combined attribute

X

Careless/Inattentive

Used exclusively when “careless/inattentive” or “inattentive/careless” are noted in casematerials as one combined attribute

X

Distraction (distracted), details
unknown

Used when “distraction” or “distracted” are noted in case materials but specific distractions
cannot be identified

X

Inattention (inattentive), details
unknown

Used when “inattention” or “inattentive” are noted in the case materials but it cannot be
identified if this refers to a distractionX

Not reported

No field available on PAR; field on PAR left blank; no other information available

Lost in thought/Daydreaming

Used when the driver is not completely attentive to driving because he/she is thinking about
items other than the driving task

Unknown if distracted

PAR specified states unknown

The following are potential reasons for underreporting of
distraction-affected crashes.
■■ 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.
NHTSA’s National Center for Statistics and Analysis

X

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 duringcrashes 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 on
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whether driver distraction was involved. Law enforcement
may not have information to indicate distraction. These
investigations may rely on witness account and oftentimes
these accounts may not be available either.
■■ Technologies are changing at a rapid speed and it is dif-ficult to update the PAR to accommodate these changes.
Without broad-sweeping changes to the PAR to incorporate new technologies and features of technologies, it is difficult to capture the data that involve interaction with thesedevices.
The following is a challenge in quantifying external distractions.
■■ 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 fromother external distractions (looking at previous crash or
billboard). Currently, the category of external distractions
is included in the counts of distraction-affected crashes.
Limitations in the data can be seen in a quantifiable mannerin a research paper titled Precrash Data Collection in NHTSA’s
Databases by Mark Mynatt and Greg Radja, published in 2013
for the ESV Conference. In this research paper, Mynatt andRadja reviewed crashes that were common in the National
Motor Vehicle Crash Causation Survey (NMVCCS), an on- site
investigations crash survey; the GES (police report data); andthe Crashworthiness Data System (CDS), data from followon vehicle and crash scene inspections and driver interviews
along with the police report. A total of 379 crashes involving 653 vehicles were determined to be present in all threeprograms. Mynatt and Radja looked at specific data for distraction in the common cases to quantify the difference inreporting of distracted driving behaviors due to additionalsources of information as can be seen in the following excerpt
from the paper:
Table A-2 shows the percentage of the common vehicles witha coded Distraction in each of the programs.
Table A-2

Common Vehicles With a Distraction Present(Percentages Rounded)
Distraction
Yes
No
Unknown

NASS-GES
11%
60%
30%

NASS-CDS
14%
46%
40%

NMVCCS
28%
48%
24%

As Table A-2 indicates, in these same vehicles a distraction
was coded in the on-scene program twice as often as in thefollow-on program; and 2.5 times more often than in the PARbased program. The on-scene based program also had a lower
percentage of Unknown Distraction coding.
While these findings cannot be expanded to quantify thepotential underreporting in FARS and GES, they are valuable
in understanding the potential underreporting that the FARS
and GES data may experience for driver distraction.

Crash Report Sampling System (CRSS) Replaces the National Automotive Sampling System(NASS) General Estimates System (GES)NHTSA’s National Center for Statistics and Analysis (NCSA)
redesigned the nationally representative sample of policereported traffic crashes, which estimates the number ofpolice-reported injury and property-damage-only crashes
in the United States. The new system, called CRSS, replaced

NASS GES in 2016. The 2016 CRSS data was released thelast week of March 2018. For more information, see theAdditional Resources section of the CRSS web page at: www.
nhtsa.gov/national-center-statistics-and-analysis-ncsa/
crash-report-sampling-system-crss.

Suggested APA Format Citation for This Document:
National Center for Statistics and Analysis. (2018, April). Distracted
driving 2016. (Traffic Safety Facts Research Note. Report No. DOT
HS 812 517). Washington, DC: National Highway Traffic Safety
Administration.

This research note and other general information on
highway traffic safety may be accessed at: https://crashstats.nhtsa.dot.gov.
NHTSA’s National Center for Statistics and Analysis

1200 New Jersey Avenue SE., Washington, DC 20590
13495-040918-v6