A framework to guide strategic disinvestment in roadway infrastructure considering social vulnerability

Abstract

Abstract Strategic disinvestment involves a conscious reallocation of funds to prioritize transportation infrastructure assets in terms of their importance or criticality, and then deliberately shifting limited resources away from lower priority assets toward higher priority assets. While previous investment paradigms considered the economic implications of expanding or maintaining assets versus the alternative of no expansion or no maintenance, disinvestment considers whether it is realistic to attempt to maintain all assets according to their original standards, or if performance standards should be changed or ownership transferred. While the concept of disinvestment has received attention in recent years, there is no established framework for disinvestment actions, potential travel impacts associated with disinvestment actions have not been widely examined, and it is unclear how disinvestment may affect socially vulnerable populations. In this paper, we present a novel framework to guide disinvestment decisions. The framework identifies different disinvestment actions and illustrates the savings, costs, and control tradeoffs associated with those actions. Each action offers different cost-savings and is associated with varying levels of reduced responsibility or obligation. We next introduce a measure of social vulnerability referred to as the Disinvestment Vulnerability Index (DVI) to help identify socially vulnerable populations impacted by disinvestment. We then propose a methodology for identifying a set of least critical or “non-essential” roadway assets as initial candidates for disinvestment, and introduce an approach for quantifying the potential effect of asset-specific disinvestment actions on vulnerable populations. The suggested approach allows decision-makers to “take the first step” in selecting an initial set of potential disinvestment candidates by identifying assets that have a minimal disruptive effect on network-wide travel, while simultaneously considering accessibility and mobility issues related to socially vulnerable populations. We illustrate the approach in the state of Vermont using the state’s travel demand model and data obtained from the U.S. Census.