Using Naturalistic Driving Data to Develop a Typology of Speeding Episodes

Speeding-related crashes continue to be a serious problem in the United States. A recently completed NHTSA project, Motivations for Speeding, collected data to address questions about driver speeding behavior. This naturalistic driving study used 1-Hz GPS units to collect data from 88 drivers in Seattle, Washington, to record how fast vehicles traveled on different roadways. The current project further developed this data set to redefine speeding in terms of speeding episodes, which were continuous periods in which drivers exceeded the posted speed limit by at least 10 mph. More than half of all study participants averaged less than one speeding episode per trip taken. Various characteristics of speeding episodes representing aspects such as duration, magnitude, variability, and overall form of speeding were examined. Cluster analyses conducted using these characteristics of speeding episodes identified six types of speeding. These included two types of speeding that occurred around speed-zone transitions (speeding up and slowing down), incidental speeding, casual speeding, cruising speeding, and aggressive speeding. Qualitative examination of the speeding types indicated that these types also differed in terms of the prevalence of additional risky situational characteristics.

• Record URL:
  https://doi.org/10.3141/2659-10
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780309442107
• Authors:
  • Richard, Christian M
  • Brown, James L
  • Atkins, Randolph
  • Divekar, Gautam
• Publication Date: 2017

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: pp 91–97
• Monograph Title: Statistical Methods and Safety Data and Analysis
• Serial:
  • Transportation Research Record: Journal of the Transportation Research Board
  • Issue Number: 2659
  • Publisher: Transportation Research Board
  • ISSN: 0361-1981

Subject/Index Terms

• TRT Terms: Automatic data collection systems; Behavior; Crash causes; Drivers; Motivation; Risk assessment; Speeding
• Geographic Terms: Seattle (Washington); Texas
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors;

Filing Info

• Accession Number: 01623748
• Record Type: Publication
• ISBN: 9780309442107
• Report/Paper Numbers: 17-00544
• Files: TRIS, TRB, ATRI
• Created Date: Jan 25 2017 3:08PM