El Cajon Boulevard is a key thoroughfare for San Diego with a legacy of automobile-centric design. Historically, the corridor's infrastructure has enabled high vehicle speeds and increased the risk of pedestrian injuries. Because the corridor is a major focal point for upcoming development projects and has the highest pedestrian fatality rate in the city, it is imperative that we are well equipped to create informed decisions about updating infrastructure to be more human-centric. This is a unique opportunity to engage both the community and the newly available sensor data to re-design this area.

What it does

Enables public planners to make informed choices about how new public infrastructure investments will impact the community. The tool does this by modeling on a number of variables provided by smart street light sensors and relates them to corridor data around vehicle speed, collisions, and pedestrian deaths.

How I built it

As a team :-) Python. Marrying the San Diego collisions data set and the smart light sensors data set to create an aggregated dataset that we can model on.

Challenges I ran into

Lack of engineering experience.

Accomplishments that I'm proud of

Starting to understand the stakeholders and developing a creative solution backed in data.

What I learned

Use Jupyter! Amazed by how much different data we have available.

What's next for Operation: The Boulevard

With the discovery phase complete, we will build out the model tying different variables to the ultimate goal: limiting pedestrian injuries and fatalities. To validate our model, we will do a series of analyses and conduct ethnographic field work on El Cajon Boulevard. Then, we will build out software that allows the user to change variables based on public planning initiatives to see what the overall impact will be on fatalities.

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