Car accidents are a crucial issue currently present in our world today. Road crashes are the leading cause of death for people under 30. While poor driving is an issue, this can be largely attributed to poorly designed roads and infrastructure.
Significant factors that affect where crashes occur include both static and continous factors. Static features include the sizes of roads, speed limits, road curvature, and billboards. Continous features include traffic congestion and the weather.
It is important to be able to track which conditions make a road dangerous and where potential hotspots for crashes are in order to help city planners adjust in the future. Knowing what is causing hotspots is also important as it allows for smarter design.
People should also be able to know which roads and paths are the safest so that they can prepare ahead of time before driving. This ultimately promotes smarter travel. Allowing residents to quickly report accidents would also improve data collection.
Using ML, we are able to detect crash hotspots by taking in features such as the size of the road, stop signs, and billboards. We also look at constantly changing features such as weather and concentration of cars. This outputs coordinates on the roads, and we render a graphical heatmap, making it simple for residents and city officials to understand where hotspots are.
Governments (both city and state) also are able to use this to upload their city data in order to help them discover collision hotspots and figure out how to adjust for the future. We will use their data to generate heatmaps for them, allowing them to better understand the problems in their road infrastructure.
Users can view where in their city the hotspots are, allowing them to adjust before driving. This gives drivers a peace of mind, and allows them to make safer and more informed decisions. This is especially key for new drivers who don’t have a strong understanding of their roads. They can also help governments collect data by reporting crashes which gets processed in our database, overall helping the data collection process, and adding to our heatmaps.