Investment in new transportation infrastructure is capital-intensive and irreversible in nature. Uncertainty and risk are two inherent problems associated with such investments, and must be analyzed prudently. Though these two terms are often used interchangeably, their implications from investment viewpoint are somewhat different. While uncertainties stem from lack of knowledge about the state of future affairs, risks are associated with some understanding of the likelihood of the future outcomes. Private sector participation in infrastructure investment has gained popularity in recent times because of scarcity of resources at the public sector, and because of the ability of the private sector to build, operate, maintain such facilities, and share future risk. Transportation infrastructures investment is of interest to three principal entities: (1) the private, (2) the public, and (3) the user, each having a different set of objectives/expectations. It is imperative to determine the economic viability of the investment from single and multiple entity perspective.;A bi-level programming is proposed to address uncertainty in decision making for these entities. At the upper level, the objective of each entity is optimized while at the lower level, optimal demand is obtained by elastic traffic assignment. Randomness in travel demand reflects uncertainty and used in the elastic traffic assignment procedure. The bi-level process results in the feasibility of each single entity perspective. A set of relaxation policies is proposed to form Ownership, Tenure, and Governance (OTG) strategies reflecting the nature and level of participation of the three entities. The uncertainty analysis output serves as input to the risk analysis. Monte Carlo Simulation is used to address risks for feasible policy options selected from uncertainty analysis. The concept of Value at Risk (VaR) is used to quantify risk. A methodology is proposed to integrate uncertainty and risk.;Finally, a multi-objective optimization (MOO) reflecting the perspectives of all three entities are proposed. MOO resulted in pareto optimal solutions to serve as tradeoff between the participation levels of the multiple entities. To obtain the relative importance of each entity within an OTG strategy, a questionnaire survey was conducted among knowledgeable transportation professionals in the states of Michigan and Ohio. Analytic Hierarchy Process (AHP) is used as a tool to determine the relative importance of entities obtained from survey responses. AHP and MOO are integrated to determine the feasibility of OTG strategies from multi entity perspectives. The framework is tested on the proposed multibillion dollar international river crossing connecting the city of Detroit in the U.S. and the city of Windsor in Canada. The combination of both uncertainty and risk reveals insights to the probable outcomes for a transportation infrastructure investment. This methodology can be used as a tool for transportation infrastructure investment decision making process.
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