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FEDERAL MOTOR CARRIER SAFETY ADMINISTRATION Tech Brief

Driver Distraction in 


Commercial Vehicle Operations
 

Programs of the Federal Motor Carrier 

Safety Administration (FMCSA) 

encompass a range of issues and 

disciplines, related to motor carrier 

safety and security. FMCSAs 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. 

Office of Analysis, Research and 

Technology 

1200 New Jersey Ave. SE 

Washington, DC 20590 

FMCSA Contact: Terri Hallquist, MC-RRR, 202-366-1064 

FMCSA has been addressing crucial driver issues such as distraction for years. 

Until 2006, driver distraction was widely believed to be a contributing factor in 

as many as 30 percent of all crashes as indicated by crash databases (comprised 

of police accident reports, which were the primary data source for 

understanding pre-crash driver behavior). In 2006, a naturalistic driving study 

conducted with 100 light vehicles (i.e., primarily passenger automobiles) found 

driver distraction in 78 percent of crashes. 

To gather naturalistic driving data, each vehicle typically contains several video 

cameras (e.g., recording views of the face, over-the-shoulder, front view, rearview, right/left side view, and foot pedals) and vehicle sensors to collect data on 

vehicle speed, global positioning system, braking intensity, steering input, forward 

range to a lead vehicle, and many additional measures. These data are generally 

collected continuously; that is, the data collection system is started as soon as the 

vehicle ignition starts and continues to record until the vehicle is turned off. 

For this investigation into the impact of driver distraction on commercial motor 

vehicle (CMV) operations, data from two earlier naturalistic CMV driving 

studies were analyzed to produce odds ratios to determine the odds of an 

outcome (such as a crash) occurring as compared with normal, non-event, 

baseline driving. From those odds ratios, population attributable risk (PAR) 

percentages were calculated to consider the frequency of occurrence of each task. 

One data set was collected in a 2004 field operational test of a drowsy driver 

warning system. The second data set was collected in 2007 for the Naturalistic 

Truck Driving Study. The combined data set consisted of 203 CMV drivers, 55 

instrumented trucks from seven trucking fleets, and about 3 million miles of 

continuously collected kinematic and video data. Analysts scanned the data to 

identify potential safety-critical events (crashes, near-crashes, crash-relevant 

conflicts, and unintentional lane deviations). Crashes involve contact with an 

object. Near-crashes are events that require a rapid evasive maneuver by one of 

the parties involved. Crash-relevant conflicts are similar to near-crashes, though 

the severity of the evasive maneuver is less than that in a near-crash. 

Unintentional lane deviations involve drifting outside of the driving lane. 

This scanning process—using kinematic data thresholds, and video review and 

validation—resulted in 4,452 safety-critical events: 21 crashes, 197 nearcrashes, 3,019 crash-relevant conflicts, and 1,215 unintentional lane deviations. 

In addition, 19,888 baseline epochs (non-events) of normal driving were 

randomly selected. The amount of time each driver was in the study was used to 

weight the frequency of baseline epochs per driver. Those who were in the study 

for a longer duration (e.g., 12 weeks) had more baseline epochs than drivers in 

the study for less time (e.g., 8 weeks). 

Driver behavior was sorted into three broad categories of tasks: primary tasks 

(required for vehicle control), secondary tasks (driving related, but not required 

for vehicle control, such as checking mirrors or the speedometer), and tertiary 

tasks (non-driving related, such as eating). For tertiary tasks, the level of 

complexity of the task (complex, moderate, simple) was used as a grouping factor. 
Key Findings 

Of the 4,452 safety-critical events noted in the combined data,  percent had some type of 

tertiary task listed as a potential contributing factor. Those tasks that drew the driver’s eyes 

away from the forward road led to a significant increase in risk. 

Risk Associated with Distracting Tasks 

Odds ratios (OR) were calculated to identify tasks that were high risk. For a given task, an odds 

ratio of “1.0” indicated the outcome was equally likely to occur in the safety-critical event data as 

in the baseline, non-event data. An odds ratio greater than “1.0” indicated the outcome was more 

likely to occur, and odds ratios of less than “1.0” indicated the outcome was less likely to occur. 

Table 1 shows the results from the odds ratio analyses. 

The most risky behavior identified was “text message on cell phone,” with an odds ratio of 23.2. 

This means that the odds of being involved in a safety-critical event is 23.2 times greater for 

drivers who text message while driving than if they were not text messaging while driving. CMV 

drivers using a dispatching device while driving increased risk by 9.9 times. Other distracting 

activities included writing (increased risk of 9.0), using a calculator (increased risk of 8.2), 

looking at maps (increased risk of 7.0), dialing a cell phone (increased risk of 5.9), personal 

grooming (increased risk of 4.5), and reaching for an object in the vehicle (increased risk of 3.1). 

Other interesting results involve the protective effect (defined as decreasing the risk of a safety 

critical event) of some tasks. While reaching for or dialing a cell phone was a high risk task, 

talking or listening on a hands-free phone provided a significant protective effect (OR = 0.4), that 

is, engaging in the task or behavior provided a safety benefit. Talking or listening to a CB radio 

also provided a similar significant protective effect (OR = 0.6). One hypothesis for these results is 

that reaching for a phone and dialing a phone requires substantial visual attention to complete the 

task, taking the eyes away from the forward roadway. Listening and talking, on the other hand, 

engages the driver and may provide an alerting mechanism. 

Visual Demand for Distracting Tasks 

Eye glance analyses were conducted and provided the “why” for the findings in the odds ratio 

analysis. Put simply, tasks that draw the drivers’ eyes away from the forward roadway were those 

with high odds ratios. For example, texting, which had the highest odds ratio of 23.2, also had the 

longest duration of eyes off forward roadway (4.6 s over a 6-s interval). This equates to a driver 

travelling the length of a football field (end zones included), at 55 mi/h, without looking at the 

roadway. Other high visual attention tasks included those that involved the driver interacting with 

technology: calculator (4.4 s), dispatching device (4.1 s), and cell phone dialing (3.8 s). 

Technology-related tasks were not the only ones with high visual demands. Non-technology tasks, 

including mundane or common activities, with high visual demands (all over a 6 s time interval) 

included: writing (4.2 s), reading a book/newspaper/other (4.3 s), looking at a map (3.9 s), and 

reaching for an object (2.9 s). 

Population Risk for Distracting Tasks 

Odds ratios only inform part of the analysis findings (i.e., which tasks are shown to increase the 

risk of involvement in a safety-critical event). Other analysis efforts consider the frequency of 

occurrence of each task (i.e., which task, if removed, would increase safety most). Table 1 shows 

the results from the PAR analysis for tasks with an odds ratio greater than “1.0”. High PAR 

percentages occurred for commonly performed tasks. Specific tasks with the largest PAR 

percentage included: reaching for an object (PAR = 7.6), interacting with a dispatching device 

(PAR = 3.1), and dialing a cell phone (PAR = 2.5). The PAR percentages for these tasks were 
Table 1. Odds Ratio and Population Attributable Risk Percentage by Task 

Task Odds Ratio 

Population 

Attributable 

Risk 

Percentage* 

Complex Tertiary Task 

Text message on cell phone 23.2 0.7 

Other – Complex (e.g., clean side mirror) 10.1 0.2 

Interact with/look at dispatching device 9.9 3.1 

Write on pad, notebook, etc. 9.0 0.6 

Use calculator 8.2 0.2 

Look at map 7.0 1.1 

Dial cell phone 5.9 2.5 

Read book, newspaper, paperwork, etc. 4.0 1.7 

Moderate Tertiary Task 

Use/reach for other electronic device 6.7 0.2 

Other – Moderate (e.g, open medicine bottle) 5.9 0.3 

Personal grooming 4.5 0.2 

Reach for object in vehicle 3.1 7.6 

Look back in sleeper berth 2.3 0.2 

Talk or listen to hand-held phone 1.0 0.2 

Eating 1.0 0 

Talk or listen to CB radio 0.6 * 

Talk or listen to hands-free phone 0.4 * 

*Calculated for tasks where the odds ratio is greater than one. 

greater than for the other tasks because the drivers commonly performed them. 

On the other hand, although text messaging had a very high odds ratio, this task was performed 

infrequently by drivers, thus it does not have a high PAR percentage. However, this does not mean 

that it should be ignored. On the contrary, it suggests that as texting while driving becomes more 

prevalent, the frequency of safety-critical events is likely to increase. 

Some tasks have both high odds ratios and high PARs. Specifically, driver interaction with a 

dispatching device was a risky, commonly performed task, as indicated in the high odds ratio (OR 

= 9.9) and PAR percentage (PAR = 3.1) for this task. Reaching for an object was another task with 

a high odds ratio (OR = 3.1) and PAR percentage (PAR = 7.6). Dialing a cell phone also had a high 

odds ratio (OR = 5.9) and PAR (PAR = 2.5). 
Environmental Conditions 

Task involvement as a function of environmental conditions was also 

analyzed. An odds ratio analysis was performed to approximate the increased 

risk of being involved in a safety-critical event, as compared to baseline 

epoch, while engaging in various tasks in eight environmental conditions, 

including lighting levels, weather, and traffic density. While some interesting 

findings resulted from this analysis, no obvious conclusions could be made 

from relationships between tasks and different environmental conditions. 

Summary Findings and Recommendations 

The following findings and recommendations by the authors to address 

driver distraction in CMV operations were formulated through a review of 

this study. These findings and recommendations provide a summarized list of 

critical issues and are ordered from general recommendations (e.g., maintain 

eyes on forward roadway) to more specific recommendations (e.g., no 

texting). These recommendations focus on improving CMV safety by 

reducing driver distraction and are intended to provide key take-aways for 

fleet-safety managers on how they might improve safety by applying the 

findings from the current study. The authors found and recommended that: 

• Fleet safety managers educate their drivers on the importance of being 

attentive and not engaging in distracting tasks or behaviors while 

driving. 

• Fleet safety managers develop policies that minimize or eliminate the 

use of in-vehicle devices (e.g., a calculator) while driving. 

• Drivers not use dispatching devices while driving. 

• Drivers not text while driving. 

• Drivers not manually dial cell phones while driving. 

• Activities such as reading, writing, and looking at maps never be 

performed while driving. 

• Talking, either on a cell phone or CB radio, be allowed as it was not 

found to increase risk. 

• Designers of dispatching devices work to develop more user-friendly 

interfaces that do not draw the driver’s eyes from the forward roadway. 

One possible solution is a hands-free dispatching device or blocking 

use while the vehicle is on and in motion. 

• Designs of instrument panels be intuitive, user-friendly and not require 

long glances away from the forward roadway. 

• Further research be undertaken to investigate the protective effects of 

performing certain tasks. If certain tasks or behaviors provide an 

alerting component, this could lead to countermeasures aimed at 

reducing drowsiness or inattentiveness. 

Full report title:
 

Driver Distraction in 


Commercial Vehicle Operations
 

(Doc. No. FMCSA-RRR-09-042)
 

Performed by:
 

Center for Truck and Bus Safety
 

Virginia Tech Transportation
 

Institute
 

3500 Transportation Research
 

Plaza (0536)
 

Blacksburg, VA 24061
 

Authored by:
 

Rebecca L. Olson, Richard J.
 

Hanowski, Jeffrey S. Hickman, and
 

Joseph Bocanegra
 

Key Words:
 

CMV, commercial motor vehicle,
 

distraction, naturalistic data, safety-


critical events
 

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.
 

Technical Editor:
 

Karen Robin
 

C2 Technologies, Inc.
 

September 2009 

Publication No. FMCSA-RRR-09-045