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  • A tree-structured crash surrogate measure for freeways

    Author(s)
    Kuang, Yan
    Qu, Xiaobo
    Wang, Shuaian
    Griffith University Author(s)
    Qu, Xiaobo
    Kuang, Yan
    Year published
    2015
    Metadata
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    Abstract
    In this paper, we propose a novel methodology to define and estimate a surrogate measure. By imposing a hypothetical disturbance to the leading vehicle, the following vehicle's action is represented as a probabilistic causal model. After that, a tree is built to describe the eight possible conflict types under the model. The surrogate measure, named Aggregated Crash Index (ACI), is thus proposed to measure the crash risk. This index reflects the accommodability of freeway traffic state to a traffic disturbance. We further apply this measure to evaluate the crash risks in a freeway section of Pacific Motorway, Australia. The ...
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    In this paper, we propose a novel methodology to define and estimate a surrogate measure. By imposing a hypothetical disturbance to the leading vehicle, the following vehicle's action is represented as a probabilistic causal model. After that, a tree is built to describe the eight possible conflict types under the model. The surrogate measure, named Aggregated Crash Index (ACI), is thus proposed to measure the crash risk. This index reflects the accommodability of freeway traffic state to a traffic disturbance. We further apply this measure to evaluate the crash risks in a freeway section of Pacific Motorway, Australia. The results show that the proposed indicator outperforms the three traditional crash surrogate measures (i.e., Time to Collision, Proportion of Stopping Distance, and Crash Potential Index) in representing rear-end crash risks. The applications of this measure are also discussed.
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    Journal Title
    Accident Analysis and Prevention
    Volume
    77
    DOI
    https://doi.org/10.1016/j.aap.2015.02.007
    Subject
    Transport engineering
    Transportation, logistics and supply chains
    Publication URI
    http://hdl.handle.net/10072/69401
    Collection
    • Journal articles

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