Vision Zero Labs: Using Data Science to Improve Traffic Safety

Jun 29, 2017   |   MSNY Staff

The central idea behind the global Vision Zero movement is that traffic crashes are preventable.

At Microsoft, we believe that data science and complex machine learning can aid cities in their life-saving Vision Zero commitment. That’s why we partnered with Datakind in 2015, and since then, we’ve worked with them to use city-specific data to identify where traffic safety conditions could be improved to ease traffic and protect citizens.

Today, we are releasing this video case study to showcase the project, its learnings, and its future potential. Take a look below:

As you can see in the video, the project was initially focused on New York, Seattle, and New Orleans. This allowed us to consider each city’s unique needs and tailor our analysis accordingly. By utilizing new and existing data from each city, we built an exposure model to determine block-by-block traffic congestion levels. This exposure model is an essential tool for city decision makers tasked with targeting policy and projects to meet their Vision Zero goal.

Ultimately, this collaborative project provided municipal transportation departments with resources that they would not have had access to otherwise and helped bring Microsoft together with community organizations and local governments in a public-private partnership model that has the potential to be utilized in other cities across the globe.

Learn more about our work with DataKind and Vision Zero and follow-up activities:

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