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    An intelligent system to enhance traffic safety analysis

    Access Status
    Fulltext not available
    Authors
    Gregoriades, A.
    Mouskos, K.
    Ruiz-Juri, N.
    Parker, N.
    Hadjilambrou, I.
    Krishna, Aneesh
    Date
    2011
    Type
    Conference Paper
    
    Metadata
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    Citation
    Gregoriades, A. and Mouskos, K. and Ruiz-Juri, N. and Parker, N. and Hadjilambrou, I. and Krishna, A. 2011. An intelligent system to enhance traffic safety analysis, in Eugen Borcoci, Petre Dini (ed), PESARO 2011: The First International Conference on Performance, Safety and Robustness in Complex Systems and Applications, Apr 17 2011, pp. 42-47. Budapest, Hungary: IARIA.
    Source Title
    PESARO 2011 Proceedings
    Source Conference
    PESARO 2011: The First International Conference on Performance, Safety and Robustness in Complex Systems and Applications
    ISBN
    9781612081328
    Faculty
    Faculty of Engineering
    URI
    http://hdl.handle.net/20.500.11937/49220
    Collection
    • Curtin Research Publications
    Abstract

    Traffic phenomena are characterized by complexity and uncertainty, hence require sophisticated information management to identify patterns relevant to safety. Traffic information systems have emerged with the aim to ease traffic congestion and improve road safety. However, assessment of traffic safety and congestion requires significant amount of data which in most cases is not available. This work illustrates an approach that aims to alleviate this problem through the integration of two mature technologies namely, simulation basedDynamic Traffic Assignment (DTA) and Bayesian Belief Networks (BBN). The former generates traffic information that is utilised by a Bayesian engine to quantify accident risk. Dynamic compilation of accident risks is used to gives rise to overall traffic safety. Preliminary results from this research have been validated.

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