Predicted Spread of Vehicle Crashes Using Story Map in ArcGIS

Abstract: Motor vehicles are the primary mode of transportation in the United States, with individuals across all age groups relying heavily on automobiles due to their accessibility and availability, even when public transportation options exist. Intersections present a particularly high crash risk for drivers due to the complex nature of navigating multiple tasks and movements. This study examines the frequency of vehicle crashes that occurred in the state of Kansas in the year 2018, focusing on identifying accident clusters and the underlying causes of repeated crashes at specific locations. Using a story map in ArcGIS, the analysis explored vehicle crash data obtained from the Kansas Department of Transportation. The dataset comprised approximately 52,000 records, highlighting over 2,900 crashes within the year. The data were highlighted in a map representing the number of traffic units involved in crashes across different areas. Locations marked in red to yellow indicate high-risk zones, signifying a higher frequency of crashes over a twelve-month period. The spotted areas highlighted in red are concentration zones that require further investigation to identify effective measures for reducing vehicle crashes. The data also were highlighted in a map to display the Euclidean distance of crashes, helping to identify areas of concentration. Notably, the highest concentration of collisions occurs around populated urban areas. The Kansas City region, in particular, has experienced over 1,000 crashes within a single year. Other areas with significant crash densities include Reno County, Lyon County, and the city of Wichita. This significant number of vehicle crashes underscores the urgent need for targeted interventions. The results and proposed countermeasures aim to enhance safety for road users by addressing the factors contributing to these vehicle crashes.