Highlights Spatial influence on the frequency and severity of vehicle crashes by driving in distraction is examined. A multivariate Bayesian approach captures the unobserved spatial impacts on the relative risk of distraction-affected vehicle crashes. Location of census tracts with elevated risks has been identified and this can provide guidance to where to allocate scarce safety resources. Census tracts providing more jobs and having a higher share of commercial land use are likely to have higher risk in both severity levels. Findings about the risks of teenagers allow policymakers to devise proper strategies to reduce the risk of distracted driving.

    Abstract This study investigates spatial dependencies between frequency and within severity of vehicle crashes caused by distracted driving, along with the role of the built and socio-demographic environments in the Columbus Metropolitan Area, Ohio. We adopt a full Bayesian hierarchical framework with Multivariate Conditional Autoregressive Priors to account for the complex spatial correlation structure as well as the unobserved heterogeneity. Using aggregated crash count data (Property Damage Only and Bodily Injuries) for the 414 census tracts, the analysis outcomes reveal that census tracts providing more jobs and having a higher proportion of commercial land use would have higher likelihood of relative crash risks in both severity levels. Inclusion of correlation structure between frequency as well as within crash-severity-level has proven a significant increase on the performance of the model, verifying influences of space on the frequency and severity of distraction-affected vehicle crashes. In addition, this research presents areas of higher relative risks (spatial clusters) that have 1.5 times elevated risk of collision than other census tracts. The identification of areas of excessive risks informs us to devise policies to mitigate negative consequences of distraction-affected crashes.


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    Titel :

    Does space influence on the frequency and severity of the distraction-affected vehicle crashes? An empirical evidence from the Central Ohio


    Beteiligte:
    Lym, Youngbin (Autor:in) / Chen, Zhenhua (Autor:in)


    Erscheinungsdatum :

    2020-05-15




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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