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Development and evaluation of infrastructure strategies for safer cycling.

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English


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  • Abstract:
    In recent years there has been an increasing number of recreational and bicycle

    commuters in the United States. Although bicycle users still represent a very small mode

    share, municipalities have been attempting to further encourage the health, economic,

    and environmental benefits of cycling by implementing new and innovative bicycle

    infrastructure treatments. However, many of these treatments have only been recently

    implemented in a few locations and are often constructed with little or no understanding

    of their effects on user behavior. Currently, there is a substantial amount of research

    investigating bicyclist behavior, as well as operations and safety from the cyclists’

    perspective of such innovative treatments. However, there is little research conducted

    from the drivers’ perspective towards cyclists and bicycle infrastructure. With

    approximately 75 percent of all bicycle-vehicle crashes occurring at intersections, there

    especially is a need to investigate driver behavior at intersections with unfamiliar bicycle

    treatments. This project report provides an in-depth evaluation of driver behavior from

    the driver’s perspective when approaching new and unfamiliar bicycle infrastructure

    intersection treatments. It utilizes a driving simulator as well as participant

    questionnaires to determine whether any patterns or causalities exist between bicycle

    infrastructure treatments and driver behavior. The results of this study indicate that there

    is a correlation between driver behavior and the level of familiarity with bicycle

    infrastructure treatments as well as cycling experience. This in-depth study can help

    inform design, education, or other countermeasures for safer operations.

  • Format:
    PDF
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  • Main Document Checksum:
    urn:sha-512:824b8454e0ae9b233d4694ed4046792ee53f54f4ce96647fc148a3937f938badfe3f2b148975192155cb219d8bba6924ada19a7ea165d0fc685b79b233ca45cd
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    Filetype[PDF - 2.09 MB ]
File Language:
English
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