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  • 标题:Evidence-based and data-driven road safety management
  • 本地全文:下载
  • 作者:Fred Wegman ; Hans-Yngve Berg ; Iain Cameron
  • 期刊名称:IATSS Research
  • 印刷版ISSN:0386-1112
  • 出版年度:2015
  • 卷号:39
  • 期号:1
  • 页码:19-25
  • DOI:10.1016/j.iatssr.2015.04.001
  • 出版社:Elsevier
  • 摘要:Over the past decades, road safety in highly-motorised countries has made significant progress. Although we have a fair understanding of the reasons for this progress, we don't have conclusive evidence for this. A new generation of road safety management approaches has entered road safety, starting when countries decided to guide themselves by setting quantitative targets (e.g. 50% less casualties in ten years' time). Setting realistic targets, designing strategies and action plans to achieve these targets and monitoring progress have resulted in more scientific research to support decision-making on these topics. Three subjects are key in this new approach of evidence-based and data-driven road safety management: ex-post and ex-ante evaluation of both individual interventions and intervention packages in road safety strategies, and transferability (external validity) of the research results. In this article, we explore these subjects based on recent experiences in four jurisdictions (Western Australia, the Netherlands, Sweden and Switzerland). All four apply similar approaches and tools; differences are considered marginal. It is concluded that policy-making and political decisions were influenced to a great extent by the results of analysis and research. Nevertheless, to compensate for a relatively weak theoretical basis and to improve the power of this new approach, a number of issues will need further research. This includes ex-post and ex-ante evaluation, a better understanding of extrapolation of historical trends and the transferability of research results. This new approach cannot be realized without high-quality road safety data. Good data and knowledge are indispensable for this new and very promising approach.
  • 关键词:Road safety management; Evidence; based; Data; driven; Case studies
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