A federal rule requires state transportation agencies to conduct a Life-Cycle Cost Analysis (LCCA) for major highway pavement rehabilitation projects, accounting for agency and future maintenance costs. For instance, TxDOT mandates the use of an LCCA for significant highway pavement construction projects with more than 30 percent truck traffic or 100,000 average daily traffic volumes. The following three critical problems in current LCCA practice are observed: 1) existing methods, such as RealCost, rely on too many intuitive assumptions; 2) existing methods are time-consuming; and 3) the accuracy of analyses performed under numerous unrealistic assumptions is highly questionable.

We aim to develop a groundbreaking decision-support computer model for quantifying the most realistic, reliable life-cycle costs that account for total project cost, future maintenance cost, and road user cost within a viable integration analysis framework, using a series of machine learning stochastic simulations based on high-fidelity big data gathered through the PMIS pavement condition database.

This research effort is the first of its kind, as existing tools, including RealCost, require many intuitive assumptions and judgments. Our LCCA model has great potential to assist state transportation agencies in conducting LCCA by providing reliable estimates of agency and road-user costs. More accurate life-cycle cost estimates can help agencies make better-informed decisions when selecting the most feasible project scenarios, thereby improving the use of public funds. Estimating long-term maintenance and road user costs is the cornerstone of the LCCA. Therefore, the methods we develop at TTI have great potential to improve the accuracy of LCCA.

• GIS-based urban sustainability model to assess the impact of LEED sustainable site credits.

• Economic impact analysis of LEED public transportation accessibility.

• Modeling future highway maintenance costs to support a life-cycle cost analysis for major infrastructure improvement projects.

• Economic Input-Output Life-Cycle Assessment (EIO-LCA) of highway pavement rehabilitation alternatives to assess sustainable energy use, external costs, and toxic emissions.