Recent federal regulations require states to develop risk-based transportation asset management (TAM) plans for bridge and pavement assets. These requirements are making TAM principles, and their related benefits and tools, familiar to a variety of sections within Departments of Transportation (DOTs) and prompting select DOTs to apply them to select geotechnical assets.

    The Montana Department of Transportation (MDT) recently completed a multi-year project to update its previous Rockfall Hazard Rating System (RHRS) into a Rock slope Asset Management Program (RAMP), incorporating some of these new tools. Incorporating risk into decision-making is important, but risk posed by deteriorating geotechnical assets is difficult for departments to quantify. Adverse event data are often collected in an ad-hoc fashion, with only the worst events attracting attention.

    As part of the RAMP project, an MDT-administered adverse event survey was combined with a statewide dataset of detailed rock slope assessments. These data were used to develop initial relationships between rock slope condition and adverse event likelihood per unit area of rock slope face. Annual likelihood of both service disrupting events and accidents was calculated for each rock slope in MDT’s database and used to identify high-risk corridors. Using established AASHTO methods, event likelihood was combined with traffic and detour data, generating site-specific estimates of annual safety and mobility risks, expressed in dollars, which can be incorporated into benefit/cost tools at various planning levels and permits dollar-to-dollar comparisons of the risks posed by rock slope assets to other actively managed assets.


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    Title :

    Estimating Event Likelihood for Rock Slope Assets on Transportation Networks


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2018-06-06




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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