NHTSA’s Review of the National Automotive Sampling System: Report to Congress

  • April 12th, 2015

DOT HS 812 128

The National Highway Traffic Safety Administration’s traffic crash data provides the underpinning for informed highway safety decision-making at the Federal, State, and local levels. Accurate, accessible, timely, and standardized data allows decision-makers to:

  • determine the primary factors related to the sources of crashes and their outcomes
  • develop and evaluate effective safety countermeasures
  • support traffic safety operations
  • measure progress in reducing crashes and their severity
  • design effective vehicle safety regulations
  • target safety funding
  • support defects identification and investigation

NHTSA’s National Automotive Sampling System (NASS) has provided nationally representative traffic crash information to the highway safety community for over 30 years. However, the data needs of the traffic safety community have increased and significantly changed since NASS was initially designed. In addition, the population demographics of the United States have changed over the last three decades, affecting how nationally representative the NASS data collection sites are. NHTSA recently undertook a thorough review of the NASS Crashworthiness Data System (CDS) and the NASS General Estimates System (GES), evaluating the sample design, the data collected, and the underlying information technology.
In the 2012 appropriation, NHTSA received funding to modernize NASS. To ensure that the new NASS best meets the current and future needs of the highway safety community, NHTSA sought user input from government, academia, and industry on both NASS GES and NASS CDS.
Based on its internal review and input from outside stakeholders, NHTSA is designing a new system that is flexible and scalable to efficiently and effectively accommodate these many requirements. The new system will combine the aspects of the current system that will be needed in the future with the additional needs not met with the current system. The new system will be composed of multiple components to accommodate these needs. There will be an annual records-based sample of motor vehicle police-reported crashes, the Crash Report Sampling System (CRSS), and an annual investigation based sample of motor vehicle police-reported towed passenger vehicle crashes, the Crash Investigation Sampling System (CISS). The new system will also include periodic special studies on motorcycle, medium and heavy truck, or pedestrian and bicycle crashes. Operating the new system, including the periodic special studies, will result in better quality data now and for the future, but will require additional operating funds.

As discussed in this report, it is important to note that the Congress asked NHTSA to review several of its current data systems and describe what an optimal system would look like. This report meets the letter of that requirement, but NHTSA, like other Federal agencies, operates in a resource-constrained environment. NHTSA prioritizes its resources based on safety data and continually reviews its activities to ensure its funding is deployed in the most effective manner possible. As such, the optimal system described in this report may not be constructed precisely as detailed in this report.

NHTSA’s design for the modernized system will:

  • Support future analytical needs by conducting 15,000 passenger vehicle crash investigations per
    year in 73 newly selected CISS sites.
  • Enhance the collection of pre-crash data and information on crash avoidance technologies,
    while continuing to collect crashworthiness data.
  • Build a flexible system that could be adapted for periodic special crash studies, such as analyses
    of crashes involving pedestrians, motorcycles, or large trucks.
  • Support analyses of all vehicle types and all crash severities by coding 65,000 police accident
    reports in 75 newly selected CRSS sites.
  • Amplify the analytical potential of CRSS through linkage to other data sources.
  • Make data more accessible and more secure, and provide users with better tools for analyzing
    the data.
  • Process data in a more streamlined and consolidated information technology environment
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