Inspiration

A movement called "vision zero" has become an official goal by many cities and agencies around the world to eliminate all car crash fatalities. In the last 11 years, 27 children have died on Austin's roads. I wanted to explore in what ways are child serious and fatal crashes different than the general population, and ultimately help decision makers deliver solutions to these problems.

What it does

The visualization breaks down existing crash and demographic data in different ways. Ethnicity and race, by mode, time of day, and by location.

How we built it

The crash data was queried and grouped together in python, using the SodaPy library for collecting data from the city of Austin Open Data Portal. This was then copied over to excel for creating the visualizations. Mapbox Studio was used for creating the heatmap.

Challenges we ran into

I didn't have time to dive deeper into the other data that is also collected, such as: lighting condition, weather, and seatbelts/car seats.

Accomplishments that we're proud of

I have found a key conclusion that black children in Austin are three times more likely to be involved in a serious or fatal car crash than white children. Hispanic children are two times as likely as white children.

What we learned

I've learned a lot about the SodaPy extension and it allows me to re-do this analysis in the future easily!

What's next for Fatal and Serious Car Crashes Involving Children in Austin

Future updates when new crash data is posted.

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