Employing Asset Management to Control Costs and Sustain Highway Levels of Service: Volumes I and II

Abstract

This project investigated the impact of varying two elements of pavement, bridge, and mobility asset management on the long term network‐level performance of those assets. The first element was the condition at which restorative treatments are triggered. The second element was the budget available to implement these treatments. For each of the pavement, bridge and mobility assets, three different management strategies in the form of treatment trigger values were investigated: a standard treatment trigger strategy, an early treatment trigger strategy, and a late treatment trigger strategy. For the pavement and bridge assets, the standard treatment trigger strategy simulates Indiana Department of Transportation's (INDOT’s) current treatment trigger policy. The early treatment trigger strategy simulates performing treatment at a better condition level than the standard treatment trigger strategy, while the late treatment trigger strategy simulates deferring treatment to a worse condition level than the standard treatment trigger strategy. For bridge assets, each treatment trigger strategy had six different treatments that can be applied to different bridge components. It was discovered that the standard (current) treatment trigger strategy outperforms other strategies. For pavement assets, the treatment trigger strategies pertained to pavement rehabilitation treatments. It was found that the long‐term pavement roughness condition at the network‐level is highly influenced by the policy being used to trigger pavement rehabilitation. The higher the trigger standard, the higher the percentage of miles in good condition and the lower the percentage of miles in poor condition. For mobility management, the treatment trigger strategies pertained to lane additions. It was discovered that neither restricting nor expanding the lane addition project candidate list (corresponding to the late and early treatment trigger strategies, respectively) provides more cost efficiency in the long‐term for reducing the percent of road miles or vehicle miles of travel (VMT) experiencing peak hour congestion. The report consists of two volumes; the first volume reports the analysis results for the bridge asset class and the second volume reports the analysis results for the pavement and mobility asset classes.