Using Spatial Analysis to Identify High-Risk Driver Residential Areas in South Carolina

Addressing safety issues at high crash incidence locations through crash countermeasures or better geometric design helps to make roadways safer, however, the most influential and ever-present factor in most crashes, the driver, is still not addressed. This paper investigated the socio-economic and demographic characteristics of residential locations (found using 9-digit zip code data) of drivers involved in crashes in South Carolina aggregated to census block groups. The spatial (block group and cluster analysis) and statistical (negative binomial) analyses results showed significant relationships and correlations between drivers involved in fatal and injury crashes within the state and demographic and socio-economic variables of the residential locations of these drivers. To mention a few, the results suggest that drivers with high median household income and within the 35 to 44 age group are less likely to be involved in fatal and injury crashes than other groups. This research has spatially and statistically shown the relationship between risky-driver clusters and some socio-economic and demographic characteristics of these drivers. Thus, providing justification for state decision makers and officials to support safety programs and research that target drivers while providing a method for prioritizing areas of the state with greatest need from a high-risk driver standpoint