This study presents a spatial framework to evaluate the readiness of rural Florida counties for autonomous vehicle (AV) shuttle deployment, focusing on physical infrastructure, digital infrastructure, and social vulnerability index. Leveraging publicly available data sets, including pavement and bridge conditions, broadband access, and social vulnerability index indicators, the study integrates geospatial techniques and statistical methods to produce high-resolution readiness assessments at the granular level. To capture conditions at a granular level, a spatial interpolation was applied to fill gaps and provide a more detailed understanding of infrastructure quality. An important aspect of this study is entropy-based weighting, which objectively assigns importance to each indicator based on its spatial variability, reducing the subjectivity often found in expert-driven approaches. The results revealed wide variation in readiness across counties. The counties of Jefferson, Hardee, Dixie, and Madison ranked highest in overall readiness. Clustering analysis was used to group areas with similar readiness profiles at a granular level, helping stakeholders identify spatially similar areas in terms of readiness for accepting new technology. Although some areas are well-positioned for early AV deployment, others require targeted interventions to improve infrastructure. Conversely, counties with higher social vulnerability index values indicate a potential need for autonomous shuttle interventions to enhance the livelihood of populations needing these services. Sensitivity analysis using Gaussian perturbations confirmed the stability of the entropy-weighted scores under small changes in input data. This framework offers practical insights for transportation planners and policymakers to guide data-driven infrastructure investments and facilitate successful AV integration in rural areas.
Saeidi et al. (Mon,) studied this question.