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This is a study to identify the contributing factors of crashes on road curves and understand the effect of various dependencies between these factors on crash severity. Data mining techniques are employed based on the ability to identify patterns and the various dependencies between the contributing factors among vague, uncertain and imprecise data that characterised the insurance incident records. Results are more meaningful when the dependencies between the contributing factors are determined. This technique complements existing statistically based tools approach to analyse road crashes.…mehr

Produktbeschreibung
This is a study to identify the contributing factors of crashes on road curves and understand the effect of various dependencies between these factors on crash severity. Data mining techniques are employed based on the ability to identify patterns and the various dependencies between the contributing factors among vague, uncertain and imprecise data that characterised the insurance incident records. Results are more meaningful when the dependencies between the contributing factors are determined. This technique complements existing statistically based tools approach to analyse road crashes. The data mining approach is supported with proven theory and will allow road safety practitioners to effectively understand the dependencies between contributing factors and the crash type with the view to design tailored countermeasures.
Autorenporträt
Shin Huey Chen graduated from The University of Western Australia with Masters in Computer Science. Following the completion of her Masters, Chen joined The Centre for Accident Research and Road Safety -Queensland (CARRS-Q) to commerce a multidisciplinary PhD that uses theories from traffic engineering, road safety and computer science.