Spatiotemporal Investigation of Road Traffic Accident Severity for Transportation Safety Planning in Missouri: A GIS-Based Hotspot Evolution Framework

Road traffic accidents (RTAs) are a complex crisis created by the combination of infrastructure, drivers, and varying traffic demand factors.While locating clusters of hotspots has been of prime importance in public safety, a research gap still exists in understanding the spatiotemporal evolution of accident severity in administrative hubs.This study fills this gap by focusing on the severity of RTAs in Missouri between 2020 and 2023.In a three-phased methodology, this research assesses sustained efficiency by leveraging a Geographic Information System (GIS)-based framework, involving systematic data integration, calculation of an Accident Severity Index (ASI), and sophisticated spatiotemporal statistics.For the assurance of statistical significance in the detection of clusters, the Getis-Ord Gi * (G * i ) was used for the localized detection of both hot and cold spots.The methodology outcomes depicted a precipitous decline in the number of accidents in April 2020, which was regarded as a direct consequence of the coronavirus impact.Besides, adults accounted for most fatalities (59%), while speeding was a contributing factor with 29%.Some variations in the occurrence of RTAs were identified during substantial seasons by indicating an optimum persistent occurrence throughout the fall months.Besides, over the main metropolitan areas, robust clustering of RTA density was observed, such as St. Louis and Jackson counties, whereas rural areas exhibited lower densities.The G * i identified persistent, high-confidence severity hot spots, indicating progressively clustered, temporally consistent, and persistent patterns of RTA severity in Missouri.The revealed outcomes reflected a granular, evidence-based foundation for urban planners and law-enforcement authorities to implement targeted safety interventions and optimise emergency response allocation.