Determining the sampling time frame for In-Vehicle Data Recorder measurement in assessing drivers

Rachel Shichrur, Adi Sarid, Navah Z. Ratzon

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


The present paper describes a method for choosing a sampling time frame for an In-Vehicle Data Recorder (IVDR) as an assessment tool in analyzing driving patterns and changes in the behavior of drivers over time. The study was a short-term follow-up to assess the driving patterns of 64 cab drivers. IVDRs installed in the vehicle of each participant recorded detailed information about undesirable events that occurred during the trip regarding the position of the vehicle, its speed, vertical and horizontal acceleration, and maneuvers. A statistical analysis was carried out on the IVDR data to identify the time at which the rate of driving events stabilizes in order to find a reasonable sampling time frame. The analysis indicates that collecting a sample of ≈300. h per driver should result in a relatively stable and reliable measure for assessing the driver's average event rate, and that sampling less than 100 driving hours per driver does not result in a reliable measure. Sampling between 100-300. h may also result in a stable measure but it is less recommended. The advantage of IVDR monitoring technology is that it makes it possible to evaluate changes over time and use the results to create custom-tailored interventions that can be implemented on different driving populations such as professional drivers, drivers with ADHD, new drivers, and others.

Original languageEnglish
Pages (from-to)99-106
Number of pages8
JournalTransportation Research Part C: Emerging Technologies
StatePublished - 1 Jan 2014
Externally publishedYes


  • Driving assessments
  • Driving behavior patterns
  • In-vehicle data recorder

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Automotive Engineering
  • Transportation
  • Computer Science Applications


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