Integrating social equity in highway maintenance and rehabilitation programming: A quantitative approach

With limited funds and an aging highway infrastructure network, agency decision-makers are tasked with making the most cost-effective decisions while accounting for the environment and social equity. Several studies have accounted for the economic and environmental considerations in infrastructure management decisions. However, there have been limited studies which have proposed quantitative approaches for integrating social equity as part of the highway Maintenance and Rehabilitation (M&R) decision-making process. To address this gap in the literature, this paper proposes four optimization models (corresponding to policies) for achieving social equity in highway M&R programming. The underlying rationales behind these models include combinations of egalitarian, utilitarian, socialism, and Rawlsian equity theories. The developed models were then implemented in a numerical case study consisting of a network of 500 pavement sections. The case study results were evaluated using average condition scores and adaptations of the Gini Coefficient and the Theil Index. An inter-policy analysis suggests that for a similar performance in network condition, different policies yield varying inequity levels over time. Furthermore, step changes in the budget size also suggest that a higher budget size generally leads to a reduction in inequity although some policies perform better than others.