With scarce funding for transportation network improvements and increasing demand for those limited funds, decision makers at state and regional planning organizations often face a challenge selecting, ranking and prioritizing investment projects. Transportation investments can be examined as a two-stage process. In the first stage the decision maker plans for network improvements and in the second stage the users react (not follow) to the improvement made by the decision maker. Often such problems are modeled using bi-level optimization formulations, and it is hard to find an optimal investment that satisfies both the decision maker and the users. An additional challenge is determining, with a given budget, when, where and how much to invest such that the benefit to the decision makers and users are maximized (or costs minimized). The problem becomes even more challenging when we consider multiple time periods and/or objectives (for both the decision maker and the users) of investments in a given planning horizon.
In this paper we present a methodology considering a network design framework with a travel behavioral approach that determines the amount of investment needed for specific links/corridors of a transportation network and their sequence of improvements over a planning horizon satisfying the objective of the decision maker and the users. We describe the use of iterative exact methods to analyze the investment decision making process. For application and implementation purposes we demonstrate the concept in four cities: Sioux Falls (ND), Anaheim (CA), Chicago (IL), and Montgomery County (MD). Results shows that network performance increases with the initial investment up to a specific threshold, but decreases thereafter; showing the influence of the law of diminishing returns. The proposed approach can be used as a tool to enhance the planning process by decision makers at cities, Metropolitan Planning Organizations (MPOs,) and state Departments of Transportation (DOTs) for identifying improvement options, and their sequence of implementation in a planning horizon with budget and other policy constraints.