The development of safety performance functions (SPFs) and crash modification factors (CMFs) requires data on traffic exposure. The analysis of motorcycle crashes can be especially challenging in this regard because few jurisdictions collect motorcycle traffic volume data systematically. To address this challenge, the project team conducted several analyses to explore (1) how much predictive power for an SPF is lost when motorcycle volumes are unknown and how this lack of information may affect the development of CMFs for motorcycle crashes, and (2) alternative methods for deriving accurate predictions of motorcycle crashes or motorcycle volumes.


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    Titel :

    Investigating the Impact of Lack of Motorcycle Annual Average Daily Traffic Data in Crash Modeling and the Estimation of Crash Modification Factors


    Beteiligte:
    C. Lyon (Autor:in) / B. Persaud (Autor:in) / R. Scopatz (Autor:in) / S. Himes (Autor:in) / M. Albee (Autor:in) / T. Le (Autor:in)

    Erscheinungsdatum :

    2016


    Format / Umfang :

    150 pages


    Medientyp :

    Report


    Format :

    Keine Angabe


    Sprache :

    Englisch





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