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  • A Comparative Study of Weather Effects on Black Spot Identification for Motorways and Urban Arterials Roads

    Author(s)
    Zhang, Jin
    Qu, XB
    Yan, YD
    Griffith University Author(s)
    Qu, Xiaobo
    Zhang, Jin
    Year published
    2018
    Metadata
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    Abstract
    It is well acknowledged that the seasonality (dry or rainy seasons) has significant impacts on crashes. Being able to differentiate the crashes that occur because of poor surface conditions (i.e., when the road is wet) is important for the economical use of available resources, as these segments of roads may only require signage and/or resurfacing. However, this effect is always ignored in the traditional black spot identification (BSID) techniques. This paper proposes an improved BSID model by taking into account the wet/dry crash rate ratio. Comparative study based on a high-speed motorway and a relatively low-speed urban ...
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    It is well acknowledged that the seasonality (dry or rainy seasons) has significant impacts on crashes. Being able to differentiate the crashes that occur because of poor surface conditions (i.e., when the road is wet) is important for the economical use of available resources, as these segments of roads may only require signage and/or resurfacing. However, this effect is always ignored in the traditional black spot identification (BSID) techniques. This paper proposes an improved BSID model by taking into account the wet/dry crash rate ratio. Comparative study based on a high-speed motorway and a relatively low-speed urban arterials road is carried out. Results indicate that the proposed model has good applicability. The impact of rainfall has been minimized on the results of a BSID analysis.
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    Conference Title
    CICTP 2018: Intelligence, Connectivity, and Mobility - Proceedings of the 18th COTA International Conference of Transportation Professionals
    DOI
    https://doi.org/10.1061/9780784481523.181
    Subject
    Civil engineering
    Publication URI
    http://hdl.handle.net/10072/385328
    Collection
    • Conference outputs

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