Highway Development Decision-Making under Uncertainty: A Real Options Approach

Abstract

A highway system development involves huge irreversible investments, and requires rigorous modeling and analysis before the implementation decision is made. This decision-making process is embedded with multiple uncertainties due to changes in political, social, and environmental contexts. In this paper, we present a multistage stochastic model for decision making in highway development, operation, expansion, and rehabilitation. This model accounts for the evolution of three uncertainties, namely, traffic demand, land price, and highway deterioration, as well as their interdependence. Real options in both development and operation phases of a highway are also incorporated in the model. A solution algorithm based on the Monte Carlo simulation and least-squares regression is developed. Numerical results show that the proposed model and solution algorithm are promising. This model makes a radical and conceptual step towards optimal decision making in highway engineering, which achieves decision-making optimality that is generally not well defined in traditional policy-based approaches for highway planning.

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