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Safety benefits of stability control systems for tractor-semitrailers.

File Language:
English


Details

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  • Edition:
    Final report; Sept. 2006-May 2008.
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  • Abstract:
    This study was conducted by the University of Michigan Transportation Research Institute

    (UMTRI) under a Cooperative Agreement between NHTSA and Meritor WABCO to examine

    the performance of electronic stability control (ESC) systems, and roll stability control (RSC)

    systems for heavy-truck tractor-semitrailers. The study is based on the analysis of independent

    crash datasets using engineering and statistical techniques to estimate the probable safety

    benefits of stability control technologies for 5-axle tractor-semitrailer vehicles. The

    conventional approach for assessing the safety benefits of vehicle technologies is to analyze

    crash datasets containing data on the safety performance of vehicles equipped with the

    technology of interest. Because the deployment of the stability technologies for large trucks is

    in its infancy, national crash databases do not yet have a sufficient amount of factual data that

    can be directly linked to the performance of the technology. Therefore a novel method of

    examining the potential benefits of these systems was used. Crash scenarios that could likely

    benefit from the technologies were selected from national crash databases and the probable

    effectiveness of each technology was estimated. The analysis in this study did not have the

    advantage of examining representative crash datasets that contain identifiable data from vehicles

    equipped with the technology. Therefore, the analysis was based on probable outcome

    estimates derived from hardware-in-the-loop simulation, field test experience, expert panel

    assessment, and fleet crash data and these methods were used to estimate the safety benefits

    from the national crash data population.

  • Format:
    PDF
  • Funding:
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  • Main Document Checksum:
    urn:sha256:8d6e8b0b54c1bb91bda0c793bd91119e4ebb182a949b33343d06f3099a12cb42
  • Download URL:
  • File Type:
    Filetype[PDF - 2.05 MB ]
File Language:
English
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