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Data-driven reduction targets for a highway safety plan

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  • Kweon, Young-Jun

Abstract

A safety plan or policy should have traffic safety targets. Setting the targets is challenging but is possible through data-driven approach. This paper describes a study that forecast fatalities and injuries under three scenarios, examined the probabilities of meeting different reduction targets, and proposed realistic targets for Virginia's safety plan. The study combined statistical forecasting approach, inputs from safety experts, and reported effects of safety improvement measures to come up with ambitious yet achievable targets. Realistic targets for the safety plan in Virginia by 2010 are a 10% reduction in fatalities and a 5% reduction in injuries. These targets assume enactment of a primary safety belt law and deployment of crash countermeasures comparable to 20-30% engineering treatments.

Suggested Citation

  • Kweon, Young-Jun, 2010. "Data-driven reduction targets for a highway safety plan," Transport Policy, Elsevier, vol. 17(4), pages 230-239, August.
    • Handle: RePEc:eee:trapol:v:17:y:2010:i:4:p:230-239
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    References listed on IDEAS

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    Cited by:

    1. Chang, Yu Sang, 2014. "Comparative analysis of long-term road fatality targets for individual states in the US—An application of experience curve models," Transport Policy, Elsevier, vol. 36(C), pages 53-69.

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