Assessing Spatial Accessibility and Socio-Demographic Disparities in EV Charging Infrastructure

Abstract: Ensuring equitable access to Electric Vehicle (EV) charging infrastructure is essential for the widespread adoption of sustainable transportation. This study examines the spatial accessibility of EV charging stations, focusing on socio-demographic disparities across both urban and rural areas. We used Geographic Information System (GIS) tools and the network analysis feature in ArcGIS Pro to calculate travel times and distances from the centroid of each census tract to the nearest EV charging stations. Accessibility scores were determined using a gravity-based method, considering the top five closest charging stations to each centroid to approximate average travel times and distances. Local Indicators of Spatial Association (LISA) were applied to identify spatial clusters and outliers in accessibility, and to categorize census tracts based on income, race, and education levels. Additionally, Lorenz curves and Gini coefficients were used to quantify disparities, providing a measure of inequality across communities. Using data on the opening dates of EV charging stations, we assessed how accessibility has changed over the past six years, highlighting regions where access has improved or remained constant. Our approach reveals significant disparities, particularly in socioeconomically disadvantaged communities. The findings underscore the need for targeted infrastructure development and offer insights for policymakers and planners on strategically placing new charging stations to promote equitable access. This research provides a framework that can be applied to other regions, supporting broader EV adoption and fostering sustainable, inclusive transportation systems.