Incorporating highway asset life expectancy into long-term fiscal planning - a risk-based, probabilistic approach
Abstract
A vital aspect of cost-effective highway asset management is the estimation of asset life expectancies. Using reliable estimates of asset service life, agencies can modify replacement intervals, plan physical and financial work, and identify those designs that are best suited to a region. To aid agencies in these tasks, this dissertation presents a proposed general, overarching framework for asset life estimation. Also, while the typical practice in planning is to apply life estimates deterministically, this dissertation demonstrates, with evidence, the benefits of using risk-based, probabilistic approaches. In demonstrating the developed methodologies, life expectancy models were calibrated for a number of asset classes and sensitivity and risk analyses were conducted to quantify the uncertainties associated with asset life. Further, the propagation of such uncertainty was quantified through its consequences on long-term, capital needs assessments. It was determined that in order to mitigate the uncertainty associated with Indiana's bridge replacement needs over a 15-year planning horizon, a contingency amount of $30-$58 million is needed to have 90% confidence in having sufficient funds. It was further found that if expert opinion or deterministic applications of the developed models had been applied, this need would likely have been underestimated their needs by 25-162%. This result demonstrates the inadequacies of needs assessment approaches that are not risk-based and probabilistic.
Degree
Ph.D.
Advisors
Sinha, Purdue University.
Subject Area
Civil engineering|Transportation planning|Urban planning
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