News Release

Findings released on real-world driver behavior, distraction, crash factors

Peer-Reviewed Publication

Virginia Tech

Driver inattention is the leading factor in most crashes and near-crashes, according to a landmark research report released today by the National Highway Traffic Safety Administration (NHTSA) and the Virginia Tech Transportation Institute (VTTI).

Nearly 80 percent of crashes and 65 percent of near-crashes involved some form of driver inattention within three seconds before the event. Primary causes of driver inattention are distracting activities, such as cell phone use, and drowsiness.

"This important research illustrates the potentially dire consequences that can occur while driving distracted or drowsy. It's crucial that drivers always be alert when on the road," said Jacqueline Glassman, acting administrator of NHTSA. Her remarks were made during a news conference today at VTTI in Blacksburg, Va.

The 100-Car Naturalistic Driving Study tracked the behavior of the drivers of 100 vehicles equipped with video and sensor devices for more than one year. During that time, the vehicles were driven nearly 2,000,000 miles, yielding 42,300 hours of data. The 241 drivers of the vehicles were involved in 82 crashes, 761 near crashes, and 8,295 critical incidents.

"The huge database developed through this breakthrough study is enormously valuable in helping us to understand--and prevent--motor vehicle crashes," said Tom Dingus, director of VTTI.

In addition, a follow-on analysis to the 100-Car Study has also been released. Focused on the types of driver inattention and their associated risk, key findings include:

  • Drowsiness is a significant problem that increases a driver's risk of a crash or near-crash by at least a factor of four. But drowsy driving may be significantly under-reported in police crash investigations.
  • The most common distraction for drivers is the use of cell phones. However, the number of crashes and near-crashes attributable to dialing is nearly identical to the number associated with talking or listening. Dialing is more dangerous but occurs less often than talking or listening.
  • Reaching for a moving object increased the risk of a crash or near-crash by 9 times; looking at an external object by 3.7 times; reading by 3 times; applying makeup by 3 times; dialing a hand-held device (typically a cell phone) by almost 3 times; and talking or listening on a hand-held device by 1.3 times.
  • Drivers who engage frequently in distracting activities are more likely to be involved in an inattention-related crash or near-crash. However, drivers are often unable to predict when it is safe to look away from the road to multi-task because the situation can change abruptly leaving the driver no time to react even when looking away from the forward roadway for only a brief time.

The 100-Car Study and its follow-on analysis were co-sponsored by NHTSA, the Virginia Transportation Research Council (the research division of the Virginia Department of Transportation) and Virginia Tech.

The background and results of both studies are available on NHTSA's website under Research and Development.

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The 100-Car Naturalistic Driving Study Phase II – Results of the 100-Car Field Experiment

NHTSA Crash Avoidance Research Technical Publications
http://www-nrd.nhtsa.dot.gov/departments/nrd-12/pubs_rev.html

The Impact of Driver Inattention on Near-Crash/Crash Risk: An Analysis of 100-Car Naturalistic Driving Study Data (This report will be posted at two locations)

NHTSA Crash Avoidance Research Technical Publications
http://www-nrd.nhtsa.dot.gov/departments/nrd-12/pubs_rev.html and

Safety Implications of Driver Distraction When Using In-Vehicle Technologies
http://www-nrd.nhtsa.dot.gov/departments/nrd-13/DriverDistraction.html

100-Car Naturalistic Driving Study Fact Sheet

Setting up the Study

Study Sponsors:

  • National Highway Traffic Safety Administration (NHTSA)
  • Virginia Department of Transportation (VDOT)
  • Virginia Transportation Research Council (VTRC)
  • Virginia Tech (VT)

Study Parameters:

  • 109 primary drivers, 241 total drivers (primary plus secondary)
  • Northern Virginia/Metropolitan Washington, DC area
  • 12 – 13 months of data collection
  • Drivers' ages ranging from 18 to 73 years old; 60 percent male; 40 percent female

100-Car Study Features:

  • First large-scale instrumented-vehicle study undertaken with the primary purpose of collecting pre-crash and near-crash naturalistic driving data.
  • Captured a range of severity of crashes from airbag deployments to minor, low-force, no-property-damage crashes.
  • First study to collect detailed information on a large number of near-crash events.
  • Drivers were given no special instructions and no experimenter was present.
  • Vehicles were used for general purpose driving.
  • Data collection instrumentation was unobtrusive.

Data Collection Instrumentation Included:

  • Five channels of digital, compressed video
  • Front and rear radar sensors
  • Accelerometers
  • Machine vision-based lane tracker
  • GPS
  • Vehicle speed sensor

The Database:

  • Contains many extreme driving cases, including severe drowsiness, impairment, judgment error, risk taking, secondary task engagement, aggressive driving and traffic violations
  • Each safety-related conflict was classified as one of the following:
  • Crash – any physical contact between the subject vehicle and another vehicle, fixed object, pedestrian, pedalcyclist or animal
  • Near-Crash – situations requiring a rapid, severe evasive maneuver to avoid a crash
  • Incident – situations requiring an evasive maneuver occurring at less magnitude than a near-crash

Top Level Database Statistics

  • Approximately 2,000,000 vehicle miles of driving
  • 42,300 hours of driving data
  • 15 police-reported and 67 non-police-reported crashes
  • 761 near-crashes
  • 8,295 incidents

Types of Driving Behavior Recorded:

  • Drowsiness
  • Driver Inattention
  • Traffic violations
  • Aggressive driving and "road rage"
  • Seat belt usage

Discoveries

  • Driver Inattention:

  • Nearly 80 percent of all crashes and 65 percent of all near-crashes involved driver inattention (due to distraction, fatigue, or just looking away) just prior to (i.e., within 3 seconds) the onset of the conflict.

Rear-End-Striking Crashes:

  • Visual inattention was a contributing factor for 93 percent of rear-end-striking crashes.
  • In 86 percent of rear-end-striking crashes, the headway at the onset of the event was greater than 2.0 s.
  • Most near crashes involving conflict with a lead vehicle occurred while the lead vehicle was moving, while 100 percent of the crashes (14 total) occurred when the lead vehicle was stopped. This indicates that drivers are sufficiently aware and able to perform evasive maneuvers when closing rates are lower and/or expectancies about traffic are not violated.
  • Age-Related:

    • Judgment error, including secondary task performance in higher risk situations, driving while impaired, and other instances of aggressive driving, was much more prevalent in the youngest age group (i.e., 18 to 20 years) relative to the older age groups.
    • The rate of inattention-related crash and near-crash events decreased dramatically with age, with the rate being as much as four times higher for the 18- to 20-year-old age group relative to the older groups (i.e., 35+ years).

    Hand-Held Wireless Devices:

    • Primarily cellular telephones, but included a small amount of PDA use.
    • Associated with the highest frequency of distraction-related events for both incidents and near-crashes.

    Driver Drowsiness:

    • Contributing factor in 20 percent of all crashes and 16 percent of all near-crashes, while most current database estimates place fatigue-related crashes at a much lower percent (i.e., under 10 percent) of total crashes.

    Driver Inattention Analysis Fact Sheet

    Inattention Analysis Purpose

    • To conduct an in-depth analysis of driver inattention using the driving data collected in the 100-Car Naturalistic Driving Study.
    • To establish direct relationships between driving inattention and crash/near-crash involvement.

    Two Calculations

    • Relative crash/near-crash risk: defined as the increased risk for an individual driver to be involved in a crash or near-crash.
    • Population Attributable Risk Percentage: defined as an estimate of the percentage of crashes and near-crashes occurring in the general population that are occurring due to increased crash/near-crash risk associated with specific factors.

    Method

    Driver Inattention:

    • Defined as one of the following:
    • Driver engagement in secondary tasks (e.g. eating, talking on a cell phone)
    • Moderate to severe driver drowsiness
    • Driving-related inattention to the forward roadway (e.g. glance to rear-view mirror)
    • Non-specific eye glance away from the forward roadway (e.g. inopportune glance away from forward roadway)

    Discoveries
    Risks

    Relative Risk Findings:

    • Driving drowsy increases an individual's near-crash or crash risk by four to six times.
    • Engaging in secondary tasks that require multiple steps or eye glances away from the forward roadway increases risk by two to three times.
    • Certain behaviors increased the risk of involvement in a near-crash or crash. Reaching for a moving objects increased risk nine times, looking at an external object 3.7 times, reading 3.4 times, applying makeup 3 times, and dialing a hand-held device 2.8 times. Talking or listening to a hand-held device increased risk by 1.3 times, but this result was not statistically different than normal driving.
    • Looking away from the forward roadway for long glances at inopportune moments increase crash risk by two times that of an alert driver.

    Population Attributable Risk Percentage Findings:

    • Driving while drowsy was a contributing factor for 22 to 24 percent of the crashes and near-crashes.
    • Secondary-task distraction contributed to over 22 percent of all crashes and near-crashes.
    • Some inattention-related activities had high risk increases but low population attributable risk percentages because of their infrequent occurrence (i.e. reading).
    • On the other hand, other activities had high population attributable risk percentages but lower individual risk increases because of their frequent occurrence (i.e. talking on a wireless phone).
    • Findings suggest a clear relationship between involvement in inattention-related crashes and near-crashes and engaging in inattention-related activities during normal driving. Those who frequently chose to engage in inattention-related activities in general are more often involved in inattention-related near-crashes and crashes.


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