Distraction in Commercial Trucks and Buses:

Assessing Prevalence and Risk in Conjunction

with Crashes and Near-Crashes

FEDERAL MOTOR CARRIER SAFETY ADMINISTRATION

FMCSA Contact: Albert Alvarez (MC-RRR) 202-385-2387

Office of Analysis, Research and

Technology

1200 New Jersey Ave. SE 

Washington, DC 20590

The aim of this project was to use an existing naturalistic data set to

document the prevalence and risk of commercial truck and bus drivers’

activities or actions that distract their attention away from the driving task.

This naturalistic data set involved thousands of commercial motor vehicles

(including trucks and buses) and provided a wealth of data, including driver

behavior during safety-critical events. The data set was provided by

DriveCam® a vendor of onboard safety monitoring systems (OBMS) aimed

at reducing risky driving behaviors. The OBMS contains video recordings

and data from kinematic sensors (e.g., vehicle speed) in order to study

driver behavior in driving conditions in the presence of real world daily

pressures. These video recordings and kinematic data are used by fleet

safety managers to provide feedback on safe and at-risk driving behaviors.

Note that the authors of this study did not receive any video recordings, but

rather kinematic data and driver behavior data that did not identify the

driver.

Summary of the Data Sets

The vendor provided two data sets collected over a consecutive 1-year

period: data set A, the first 273 days, and data set B, the last 92 days. The

data sets did not include continuous data, but only recorded events that met

or exceeded a kinematic threshold (i.e., greater than or equal to |0.5 g|).

These recorded triggers included both safety-critical events (e.g., hard

braking in response to another vehicle) and non-safety triggered events

(e.g., vehicle traveled over train tracks, which exceeded the kinematic

threshold). The non-safety triggered events served as baselines in the

analyses. Note that only data set B, collected June 6, 2009–September 5,

2009, contained baseline events that allowed the calculation of odds ratios.

Data set B was derived from 183 truck and bus fleets comprising 13,306

vehicles. A total of 1,085 crashes, 8,375 near-crashes, 30,661 crash-relevant

conflicts, and 211,171 baselines were captured in data set B.

Key Results 

Texting/e-mailing/accessing the Internet was associated with a very high

odds ratio. An odds ratio is a measure of association (not unlike a

correlation). In this case, the odds ratio was high due to the finding that 90

of the 93 instances where truck and bus drivers were using a mobile device

for texting/e-mailing/accessing the Internet while driving were involved in a

safety-critical event. The results of the odds ratio analysis for data set B are

shown in Table 1. 

A second noteworthy finding was that when “cell phone use” was treated as

a “yes” or “no” variable, the odds of being involved in a safety-critical

event were 1.14 times greater while the driver was using a cell phone than

Tech Brief

Programs of the Federal Motor Carrier

Safety Administration (FMCSA)

encompass a range of issues and

disciplines related to motor carrier

safety and security. FMCSA’s Office of

Analysis, Research and Technology

defines a “research program” as any

systematic study directed toward fuller

scientific discovery, knowledge, or

understanding that will improve safety,

and reduce the number and severity of

commercial motor vehicle crashes.

Similarly, a “technology program” is a

program that adopts, develops, tests,

and/or deploys innovative driver and/or

vehicle best safety practices and

technologies that will improve safety

and reduce the number and severity of

commercial motor vehicle crashes. An

“analysis program” is defined as

economic and environmental analyses

done for agency rulemakings, as well

as program effectiveness studies,

state-reported data quality initiatives,

and special crash and other motor

carrier safety performance-related

analyses. A “large truck” is any truck

with a Gross Vehicle Weight rating or

Gross Combination Weight rating of

10,001 pounds or greater. 

Currently, the FMCSA Office of

Analysis, Research and Technology is

conducting programs in order to

produce safer drivers, improve safety

of commercial motor vehicles, produce

safer carriers, advance safety through

information-based initiatives, and

improve security through safety

initiatives. The study described in this

Tech Brief was designed and

developed to support the strategic

objective to produce safer drivers. The

primary goals of this initiative are to

ensure that commercial drivers are

physically qualified, trained to perform

safely, and mentally alert. 
Tertiary Task Odds

Ratio LCL UCL

Frequency of

Safety-Critical

Events

Frequency of

Baselines

Any Cell Phone Usage 1.14* 1.06 1.23 895 4,262

Dialing Cell Phone 3.51* 2.89 4.27 165 256

Talking/Listening Hands

Free Cell Phone 0.65* 0.56 0.76 194 1,626

Talking/Listening Hand

Held Cell Phone 0.89 0.80 1.00 372 2,266

Reaching for

Headset/Earpiece Device 3.38* 2.64 4.31 104 168

Reaching for Cell Phone 3.74* 2.97 4.71 122 178

Texting/E-mailing/

Accessing the Internet 163.59* 51.77 516.73 90 3

Consuming Food/Drink 1.11 0.97 1.26 268 1,320

Other Distraction 511.64* 296.20 883.79 1,220 13

Passenger Distraction – – – 30 0

Table 1. Odds ratios for each tertiary task in data set B.

* Asterisk indicates a significant odds ratio. 

when the driver was not using a cell phone. However, the results indicated the talk/listen

cell phone sub-tasks alone did not have a significant odds ratio. In fact, in this analysis,

talking/listening on a hand-held or hands-free cell phone had a protective effect. Although

talking on the cell phone did not show an increased risk, a driver must take several riskincreasing steps such as reaching for and dialing the cell phone in order to use the

electronic device for conversation. The use of a cell phone, however, involves a variety of

sub-tasks, including reaching for and holding the phone, dialing the phone, and talking.

Reaching for the phone and dialing the phone do show increased odds of involvement in a

safety-critical event. In other words, although talking on the cell phone did not show an

increased risk, a driver must take several risk-increasing steps in order to use the

electronic device for conversation.

Odds ratios were also calculated to approximate the effectiveness of a fleet cell phone

policy and State cell phone law regarding cell phone use while driving. These odds

ratios did not look at odds of involvement in a safety-critical event, but rather evaluated

the odds of cell phone usage given a fleet cell phone policy or State cell phone law

versus the odds of cell phone usage given no fleet cell phone policy or State cell phone

law. Table 2 shows the odds ratios for cell phone use while driving in each cell phone

policy/law variable in the combined data set A and B. For truck and bus drivers the odds

of using a cell phone while driving under a fleet cell phone policy were .83 times less,

compared to no fleet cell phone policy. However, the existence of a State cell phone law

did not significantly impact drivers’ likelihood of using their cell phone while driving

compared to usage in a State that did not have a law prohibiting cell phone use 

(odds ratio = 0.97). 
Table 2. Odds ratios for cell phone use while driving in each cell phone policy in the

365 day data set (safety-critical events).

Cell Phone Policy Odds

Ratio LCL UCL

Frequency of

Cell Phone Use

with Policy/Law

Frequency of No

Cell Phone Use with

Policy/Law

Fleet Cell Phone Policy 0.83* 0.78 0.87 8,787 1,897

State Cell Phone Law 0.97 0.94 1.01 4,526 2,987

* Asterisk indicates a significant odds ratio. 

Discussion

It is important to note this was an observational study that evaluated associations between

various tertiary tasks (non-driving related tasks) and safety-critical event occurrence. The

study did not evaluate cause and effect (i.e., whether cell phone use caused a safetycritical event), but rather showed which tertiary tasks increased the odds of commercial

truck and bus drivers being involved in a safety-critical event if they engaged in those

tertiary tasks while driving. 

Tertiary tasks associated with the presumed greatest visual attention had the greatest risk

(e.g., texting/e-mailing/accessing the Internet, dialing a cell phone, reaching for cell phone,

and reaching for a headset/earpiece), while those tertiary tasks associated with the

presumed least visual attention had no impact on the odds of being involved in a safetycritical event. It appears that a key difference between these high-risk and low-risk tertiary

tasks involves the amount of visual distraction. Tertiary tasks associated with high visual

attention have the highest odds of involvement in a safety-critical event. 

Distracted driving is an important topic and many State and Federal organizations have

passed and/or proposed bans on using cell phones while driving. A key question is, is it

safe to use a cell phone while driving? If the question concerns the use of the cell phone

in any manner, then the data in this study suggest that cell phone use in the commercial

driver population significantly increases the odds of involvement in a safety-critical

event by 1.14 times. However, if cell phone use is classified into specific cell phone

tasks or sub-tasks, this changes. Certain cell phone sub-tasks are shown to increase

significantly the odds of involvement in a safety-critical event (e.g., text/e-mail/web,

dial a cell phone, reach for cell phone, and reach for a headset/earpiece), while others

are not, and may, in fact, significantly decrease the odds of involvement in a safetycritical event (e.g., talking/listening on a hands-free phone). This approach, in addition

to providing a more complete picture of driving safety issues associated with cell phone

interaction, also provides important information to system designers pertaining to driversystem interface development.

Possible Limitations

There are six possible caveats or limitations in interpreting the results of this study:

 The purpose of collecting the data is to reduce risky driving behaviors. These data

are used by fleet safety managers to provide feedback to drivers with the goal of

changing risky behaviors to increase safety. Thus, the data sets may be skewed from
normative driving data as safety managers have attempted to alter

unsafe driver behaviors. This translates into potentially less risky

behavior being recorded in this study, which would imply higher

tertiary task involvement in the larger population.

 The fact that the truck and bus fleets in the data sets purchased an

onboard safety monitoring system reflects a group of safety conscious

carrier companies; thus, the prevalence of tertiary tasks may, in fact,

be more pronounced in the larger population. 

 The lack of continuous data collection or randomly collected video

segments means there were no “true” baseline or control data.

Baselines were used as a proxy measure of control data; however, the

similarity in the odds ratios with Olson et al. (2009), which did use

true baselines, suggests this likely had little or no influence on the

findings. 

 Data set B was collected during a time frame when intense media

attention was devoted to the dangers of distracted driving. This media

attention may have influenced safety manager and/or driver behavior.

However, again, this would translate into potentially less risky

behavior being recorded in this study, which would imply higher

tertiary task involvement in the larger population. 

 Driver exposure was not controlled in the study; thus, extremely

unsafe drivers may have contributed far more safety-critical events

than baselines. However, as the study included at least 13,000 drivers

(from more than 13,000 trucks and buses), the affect of any outliers

was minimized. 

 The length of the video window during safety-critical events and

baseline epochs was longer than in other naturalistic studies 

(8 seconds before the trigger and 4 seconds after the trigger). It is

possible that some tertiary tasks coded as an associative factor during

the safety-critical events had no influence on safety-critical event

occurrence (if the truck or bus driver engaged in the tertiary task at

the very beginning of the video window). However, and as noted

previously, the similarity of the odds ratios with the Olson et al. study,

which used a 6-second window, suggests this likely had minimal

influence on the results.

The full final report may be found online: 

www.fmcsa.dot.gov/facts-research/art-public-reports.aspx.

Reference

Olson, R.L., Hanowski, R.J., Hickman, J.S., & Bocanegra, J. (2009). Driver

Distraction in Commercial Vehicle Operations (Report no. FMCSA-RRR09-042).Washington, DC: U.S. Department of Transportation, Federal Motor

Carrier Safety Administration. Retrieved May 24, 2010:

www.fmcsa.dot.gov/facts-research/research-technology/report/FMCSARRR-09-042.pdf

Full report title:

Distraction in Commercial Trucks

and Buses: Assessing Prevalence

and Risk in Conjunction with

Crashes and Near-Crashes 

(Report No. FMCSA-RRA-10-049)

Report Authors:

J.S. Hickman, R.J. Hanowski, and

J. Bocanegra

Performing Organization:

Virginia Tech Transportation

Institute 

Center for Truck and Bus Safety 

3500 Transportation Research

Plaza

Blacksburg, VA 24061

Key Words:

buses, cell phone, cell phone

policy, commercial motor vehicle,

CMV, crash avoidance, distraction,

driver behavior, naturalistic, odds

ratio, population attributable risk,

trucks

Notice:

Tech Briefs are disseminated

under the sponsorship of the U.S.

Department of Transportation

(USDOT) in the interest of

information exchange. Tech Briefs

provide a synopsis of the study’s

final publication. Tech Briefs do not

establish policies or regulations,

nor do they imply USDOT

endorsement of the conclusions or

recommendations. The U.S.

Government assumes no liability

for its contents or their use.

Web Site:

All FMCSA Tech and Analysis

Briefs may be accessed at

www.fmcsa.dot.gov.

September 2010

Publication No. FMCSA-RRR-10-055