Conference Paper

Making Evidence-based Crash Risk Estimation Routine by using the SESA Process (updated and to be published in JACRS)

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Abstract

Achieving safe system or vision zero outcomes at high-risk urban intersections, especially priority cross-roads and high-volume traffic signals is a major challenge for most cities. Even after decades of crash analysis and improvement works many of these intersections still perform poorly. While best practice for optimising the efficiency of intersections requires the use of modelling tools, like Sidra, this is rarely the case with optimising safety outcomes. This is despite the large number of evidence-based safety analysis models and tools that are now available to understand intersection crash risk. This paper outlines the SESAP (Site-specific Evidence-based Safety Analysis Process) that has been developed to enable road safety professionals to estimate and predict the safety of intersections and potential upgrades in New Zealand and Australia. This process utilises existing safety analysis tools (based on crash prediction models and crash reduction factors), relevant road safety research, crash severity factors, professional judgement and crash data to predict the underlying crash risk at intersections (and other sites) and the effectiveness of improvement options. The output includes both the number and return period of ‘all injury’ and ‘fatal and serious injury (FSI)’ crashes for each option. The paper includes three applications of the process to high risk intersections in four New Zealand cities, consisting of two priority cross-roads and one high speed roundabout. The case studies demonstrate how the process can be used to assess intersection features and design options that are not covered within the available crash prediction tools.

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Conference Paper
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Crash data continues to be a key input to the way in which high-risk locations are identified, and interventions prioritised and funded by many transport authorities. In large part, this is attributable to processes and procedures developed by funding authorities over many decades being slow to adjust to proactive approaches that adopt a more ethical standpoint to road safety; one where people do not need to be injured or killed before safety improvements can be justified. Whilst proactive approaches to measuring safety, such as crash prediction modelling, Star Rating and Infrastructure Risk Rating are becoming more widely accepted by transportation professionals, there remains a reluctance to fully embrace these proactive risk techniques in preference to reactive crash-based approaches. If we are to reach the Vision Zero goal where no lives are lost on our roads, then a paradigm shift is required in the way we approach many aspects of road safety. This paper examines the predictive robustness of using historic crash to forecast future crash occurrence and compares it to a proactive risk approach. The findings provide compelling evidence that reactive approaches relying on crash history should be a secondary consideration to proactive risk-based approaches in the identification of high-risk locations and the prioritisation of interventions.
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