FEDERAL MOTOR CARRIER SAFETY ADMINISTRATION

FMCSA Contact: Robert Carroll, MC-RRR, 202-385-2388

The 100-Car Naturalistic Driving Study:

A Descriptive Analysis of Light VehicleHeavy Vehicle Interactions from the Light

Vehicle Driver’s Perspective

BACKGROUND

In 2002, 434,000 large trucks (gross weight >10,000 lbs) were involved in vehicle crashes;

4,542 of these crashes resulted in fatalities. In these crashes, 4,897 people died and an

additional 210,000 were injured. Though accounting for 4% of all registered vehicles in

2002, large trucks represented 8% of all vehicles involved in fatal crashes. The

disproportionate number of vehicles to fatalities among large trucks may contribute to the

perception that truck drivers are irresponsible. However, these data do not necessarily signify

that truck drivers are the problem. In fact, truck drivers have lower crash rates per million

vehicle miles traveled than light vehicles. Nonetheless, light vehicles are extremely

vulnerable when they interact with trucks because trucks often weigh 20-30 times as much as

light vehicles, and trucks take 20-40% farther to stop than light vehicles. This is best

illustrated by the fact that over 75% of multiple vehicle fatal truck crashes resulted in the

occupant(s) of the other vehicle being killed. 

Project Goals

The data from the 100-Car Study were used to assess the Light Vehicle-Heavy Vehicle 

(LV-HV) interaction problem from the LV drivers’ perspective. There were four primary

goals: 1) gain a better understanding of LV-HV interactions on the nation’s roadways; 

2) continue to develop a classification scheme and corresponding Contributing Factors list for

LV-HV interactions and use the terminology and methodology described in the Large Truck

Crash Causation Study (LTCCS); 3) compare the current data to the data obtained in the

Contributing Factors list for LV-HV interactions study for a more complete picture of the 

LV-HV interaction problem; 4) provide background information that would serve as a

necessary prerequisite to the development of countermeasures for LV-HV interactions.

Method

One hundred participants who commute to and from the Washington, DC metro area were

initially recruited as drivers in the 100-Car Study. As some participants had to be replaced for

various reasons (e.g., dropped out of the study because they moved from the area), the final

number of participants was 109. One hundred LVs were instrumented for this study; 80

vehicles were owned by the participants, while 20 were leased vehicles. The data used in the

current effort consisted of video recordings of critical incidents. As such, the primary

methodological considerations are those related to the video systems. 

Five video cameras were used in the video recording system: (1) a forward-looking camera

that captured the forward roadway scene, traffic situation, and possible incidents; (2) a

driver’s face camera that was used to record facial expressions, eyelid closure, glance

position, and head turns; (3) a right-side camera that was mounted on the A-pillar of the

passenger side and faced outward; (4) a dome camera that was mounted from inside the

vehicle and faced over the drivers shoulder towards the steering wheel, hands, and feet; and

(5) a rear camera that was intended to capture the situation behind the vehicle. Infrared

lighting was used to illuminate the vehicle cab so that the driver’s face as well as their hands

could still be viewed by the camera during nighttime driving. The five camera images were

multiplexed into a single image as shown in the figure on the following page. The video

continuously recorded while the ignition was on, thereby allowing laboratory review and

selection of the video, which were selected and keyed to digitally-recorded data. 

Tech Bri e f

The goal of the Federal Motor Carrier

Safety Administration (FMCSA) is to

reduce the large truck fatality rate by

41 percent from 1996 to 2008. This

reduction translates into a rate of

1.65 fatalities in truck crashes per

100 million miles of truck travel.

FMCSA’s programs encompass a

range of issues and disciplines, all

related to motor carrier and bus

safety and security. FMCSA’s Office

of Research and Analysis, which

includes the Research and

Technology Divisions, 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” defines those programs

that adopt, develop, test, and/or

deploy innovative driver and/or

vehicle best practices, and

technologies that will improve safety

and reduce the number and severity

of commercial motor vehicle crashes. 

Currently, FMCSA’s Research and

Technology Divisions are 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 Research

and Technology Divisions’ 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. 

Tech Bri e f

Office of Research and Analysis

400 Virginia Ave., SW 

Suite 600 

Washington, DC 20024
Split-screen presentation of the five camera views

RESULT HIGHLIGHTS

Light Vehicle-Heavy Vehicle Interaction Data Set

The 100-Car Study captured 9,125 incidents, which were divided into four categories: (1) LV-LV Interactions; (2) LV-HV

Interactions; (3) Single Vehicle Conflicts; and (4) Other. Of the 9,125 events, 246 (2.7%) involved a LV-HV interaction. 

Incident Types

With the 246 LV-HV interactions recorded in the data set, the next step in the analysis was to determine the vehicles’ actions for

each incident. The video and relevant data for each incident were carefully reviewed and then classified according to “Incident

Type.” Twenty-seven different Incident Types were identified in the data set. 

The most frequent Incident Type involving a LV-HV interaction was Late Braking for Stopped/Stopping Traffic. Of all 246

incidents, this particular Incident Type occurred 66 times and accounted for 26.8% of the incidents captured. Most of the incidents

(48.8%) involved one of two different Incident Types: Late Braking for Stopped/Stopping Traffic, and Lane Change Without

Sufficient Gap.

Descriptive statistics for the Incident Types were also calculated for incidents as a function of the at-fault driver. The at-fault driver

is the driver that was assessed, by the analyst, to have been responsible for causing the event. Of the 246 LV-HV interaction

incidents recorded, 138 (56%) were judged to have been the fault of the LV driver, while 79 (32%) were attributed to the HV driver.

For the remaining 29 incidents (12%), it was unclear which driver was at-fault. By removing the “unknown” cases from the LV-HV

driver at-fault analyses, it was found that the LV driver was at-fault in 64% (138/217) of the LV-HV interaction incidents, while the

HV driver was at fault in 36% (79/217) of the incidents. 

The most frequent Incident Type for HV driver at-fault incidents was Lane Change Without Sufficient Gap (26.6%), followed by

Lateral Deviation of Through Vehicle (21.5%), and Left Turn Without Clearance (13.9%). The most frequent Incident Type for LV

driver at-fault incidents was Late Braking for Stopped/Stopping Traffic (41.3%), followed by Lane Change Without Sufficient Gap

(21.7%), and Aborted Lane Change (8%). The most frequent Incident Type for Unknown at-fault incidents was Late Braking for

Stopped/Stopping Traffic (27.6%), followed by Conflict With Oncoming Traffic (13.8%), Lane Change Without Sufficient Gap

(10.3%), and Unable to Determine (10.3%). 

Driver Distraction

A substantial number of the LV-HV incidents had Distraction listed as a Contributing Factor. As indicated above, the incidents

where Driver Distraction was mentioned refer to the behavior of the LV driver. The Distraction Contributing Factor was sub-divided

into more distinct categories. The table on the following page shows the frequency, percentage, and rank ordering for each subcategory in the Distraction Contributing Factor. As can be seen in the following table, the most frequent sub-category for the

Distraction Contributing Factor was Talking/Listening on Cell Phone (21.7%), followed by Passenger in Adjacent Seat (13%), and

Dialing Hand-Held Phone (8.7%). 
Availability: The report “The 100-

Car Naturalistic Driving Study: A

Descriptive Analysis of Light

Vehicle-Heavy Vehicle Interactions

from the Light Vehicle Driver's

Perspective” will be available from

NTIS at www.ntis.gov.

Key Words: Driver Distraction,

Fatigue, LV-HV, Truck Driving,

Vehicle Distraction, Vehicle

Interaction

Notice: This Tech Brief is

disseminated under the

sponsorship of the Department of

Transportation in the interest of

information exchange. The Tech

Brief provides a synopsis of the

study’s final publication. The Tech

Brief does not establish policies or

regulations, nor does it imply

USDOT endorsement of the

conclusions or recommendations.

The U.S. Government assumes

no liability for its contents or their

use.

Web Site: FMCSA Tech and

Analysis Briefs may be accessed

at www.fmcsa.dot.gov.

Technical Writer: 

Michael Lang

C2 Technologies, Inc.

December 2005

Publication No. FMCSA-MC-RRR-06-004

Frequency, percentage, and rank ordering of each sub-category in the

distraction contributing factor (n = 46)

CONCLUSIONS

The analyses that were conducted with the LV-HV interactions captured in the 100-Car

Study provide convincing evidence to support the contention that LV-HV interactions are a

serious problem. 

Based on these findings, the authors suggested that focusing on the LV driver and their

errors may provide the largest area of opportunity for reducing such events. Listed below

are several suggestions from the authors that should be considered for reducing LV-HV

interactions:

Distraction 

Frequency 

of 

Distraction 

Incidents 

Percentage 

of 

Distraction 

Incidents 

Combined 

Rank of 

Distraction 

Incidents 

Talking/listening on cell phone 10 21.7% 1 

Passenger in adjacent seat 6 13.0% 2 

Dialing hand-held cell phone 4 8.7% 3 

Looking out center mirror 3 6.5% 4.5 

Looking out left mirror 3 6.5% 4.5 

Other external distraction 2 4.3% 9 

Adjusting radio 2 4.3% 9 

Cognitive – Other 2 4.3% 9 

Combing or fixing hair 2 4.3% 9 

Lost in thought 2 4.3% 9 

Smoking cigar/cigarette 2 4.3% 9 

Talking/singing/dancing 

(not on cell phone) 2 4.3% 9 

Eating with utensils 1 2.2% 15.5 

Lighting cigar/cigarette 1 2.2% 15.5 

Operating PDA 1 2.2% 15.5 

Reaching for object 

(not cell phone) 1 2.2% 15.5 

Reading 1 2.2% 15.5 

Looking out right window 1 2.2% 15.5 

• Addressing the LV-HV interaction problem should focus on the driving 

behaviors of the LV driver.

• The primary area for LV that should be addressed involves their driving 

techniques and aggressive driving behaviors. 

• The primary area for HV drivers that should be addressed involves 

driving techniques. 

• Drivers and/or company dispatchers should be cognizant of problematic 

sections of routes, and avoid such locations to the greatest extent possible. 

• More research studies should use data collection in a naturalistic 

environment to identify potential crash countermeasures.