Estimating Motorcycle Miles Traveled From State Vehicle Inspection Records

To follow trends in motorcycle safety, it is necessary to have high-quality data on motorcycle exposure, crashes, and crash outcomes. Of these, motorcycle exposure may be the most challenging to measure. However, the ability to evaluate safety countermeasures requires reliable and accurate exposure data. This ability is important, given that motorcyclists comprised 14 percent of all traffic fatalities and 17 percent of all occupant (driver and passenger) fatalities in 2019. Exposure data, combined with crash data, reveal trends over time, across locations, and allow comparisons to other vehicle types. Obtaining exposure measures is challenging for any vehicle types and motorcycles are no exception. In fact, quantifying motorcycle exposures may be more difficult than it is for most vehicle types given that motorcycles are smaller, lighter, and have smaller axles. Motorcyclist travel patterns are unique as well, having a higher percentage of weekend travel than do passenger vehicles. Commonly used measures of motorcycle exposure are the number of registered motorcycles and vehicle miles traveled (VMT). As exposure measures, each has its strengths and weaknesses. The number of registered motorcycles is a good indicator of the popularity of motorcycles but does not provide the number and types of trips, miles traveled, or traffic and road conditions. VMT is generated at the State level, based on vehicle and traffic counts, and adjusted by modeling to take into account overall traffic patterns; however, VMT may not capture motorcycle traffic as well as it does for larger vehicles.

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Tables;
  • Pagination: 2p
  • Serial:
  • Publication flags:

    Open Access (libre)

Subject/Index Terms

Filing Info

  • Accession Number: 01848369
  • Record Type: Publication
  • Report/Paper Numbers: DOT HS 813 289
  • Files: HSL, NTL, TRIS, ATRI, USDOT
  • Created Date: Jun 10 2022 3:45PM