U.S. Road Accident Insights: A Visual Analytics Approach with Tableau

Manda Vaishnavi1, Kala Santhosh2, Esampelli Hriday3 , Dr. Syed Azahad4

1Department of AI&DS, Methodist College of Engineering and Technology, Hyderabad

2Department of AI&DS, Methodist College of Engineering and Technology, Hyderabad

3Department of AI&DS, Methodist College of Engineering and Technology, Hyderabad

4Associate Professor CSE(AI), Methodist College of Engineering and Technology, Hyderabad

Abstract - Road safety in the US is a real, persistent problem, and researchers have been digging into large accident datasets to make sense of it. The one this study uses has 10,000 collision records from across the country — each with coordinates, timestamps, severity scores, weather readings, visibility data, road type, and whatever infrastructure happened to be nearby. It's a lot to work with. The time patterns alone are interesting. Crashes cluster around rush hour, as you'd expect. But weekends have their own texture, and winter months in certain regions skew the numbers significantly. None of this is shocking in isolation, but seeing it quantified and mapped gives safety planners something they can actually use — not just a general sense that roads are dangerous at night, but a breakdown of when intervention would matter most. The geographic side is where things get specific. Some dangerous corridors are already on planners' radar. Others show up in the data without much prior attention. Either way, spatial analysis cuts through the guesswork. It makes the case for putting resources in particular places rather than distributing them broadly and hoping for the best. For transportation agencies working with limited budgets, that distinction is the whole ballgame.

Key Words:  Traffic Accident Analysis, US Accidents Dataset, Tableau Visualization, Spatiotemporal Patterns, Accident Severity Analysis, Environmental Factors, Weather Impact, Road Infrastructure, Temporal Trends, Spatial Distribution, Hotspot Detection, Risk Assessment, Transportation Analytics.