Statistical and Spatial Analysis of Precipitation-Related Crashes in Hennepin County, Minnesota from 2018 to 2022

This paper presents a comprehensive study on the statistical and spatial analysis of precipitation-related (rain and snow) crashes in Hennepin County, Minnesota, from 2018 to 2022. The objective is to identify surface and radar patterns that contribute to high crash rate days. The analysis entails proving statistical significance at a 95% confidence interval and identifying the 99th percentile crashes using a threshold of more than three standard deviations for case studies.

Density maps are utilized to pinpoint areas with high crash rates based on precipitation type, and patterns and trends are examined through surface and radar analyses. Additionally, case studies are conducted for the top three crashes in the 99th percentile for both precipitation types to further investigate the surface and radar patterns associated with high crash days.

Findings indicate a robust correlation between precipitation and crashes, while a weak inverse relationship between crashes and temperature is observed. The density maps reveal that high crash rates occur in downtown Minneapolis for rain, with intersections and interchanges also affected. For snow, downtown Minneapolis experiences a significant number of crashes as well, but highways and interstates display a higher concentration compared to rain-related crashes.

Among the six case studies conducted, four showed the presence of surface troughs associated with low pressure in the vicinity of Minnesota, while two displayed triple point set-ups. Radar loops highlighted either long duration storms or waves of precipitating systems.

This study contributes to an improved understanding of the relationship between precipitation patterns and crash rates. The findings offer valuable insights for policymakers and transportation authorities to develop targeted strategies and implement appropriate infrastructure modifications to mitigate crashes during precipitation events.