/ Corporate / Microsoft’s Vision Zero Project Aims to Combat Traffic Congestion

Microsoft’s Vision Zero Project Aims to Combat Traffic Congestion

Matt Ball on March 11, 2016 - in Corporate, Planning, Sensors, Transportation

We all come together in the streets, and often at significant speeds. The laws of physics tell us that collisions would be a minor concern if no one went faster than 3 miles per hour. But at real world speeds, intersection visibility, signs, rules and rights of way need to be designed to allow movements like left turns to work for pedestrians, cars, and cyclists.

That is why Microsoft is excited to partner with DataKind on a special project to support the Vision Zero movement to improve traffic safety.

DataKind is a global nonprofit that aims to harness the power of data science in the service of humanity. The organization engages data science and social sector experts on projects addressing critical humanitarian problems, with this being the first project to come out of their newly established program, DataKind Labs.

Vision Zero is an international initiative that aims to reduce traffic-related deaths and serious injuries to zero. A growing number of cities in the U.S. have signed on to this initiative and begun the process of analyzing their safety conditions and identifying opportunities to improve their environments through changes to policy and infrastructure.

Microsoft’s Technology & Civic Engagement team was created for exactly this purpose: to build partnerships that bring the company’s technologies and talent to bear on the shared challenges we face in cities around the planet (see examples from our work in New Yorkhere). Together with DataKind, the Vision Zero Network and a broad community of partners and collaborators, we will apply the latest advances in data analysis to one of humanity’s oldest inventions: the street.

City streets and sidewalks teem with a beautiful chaos. Jane Jacobs wrote, “We may fancifully call it the art form of the city and liken it to the dance – not to a simple-minded precision dance with everyone kicking up at the same time, twirling in unison and bowing off en masse, but to an intricate ballet in which the individual dancers and ensembles all have distinctive parts which miraculously reinforce each other and compose an orderly whole.” To study this movement, the DataKind Vision Zero project will gather and analyze data from multiple sources, including governmental agencies, citizens, and the private sector. The goal is to identify behaviors and patterns that will help cities make decisions about what changes might be useful, which modifications should receive resources first, and how to determine if interventions are effective.

These are the sorts of questions that apply to many challenges today in civic and business settings: what to do, how to do it, did it help? As this project will demonstrate, new data gathering and analysis techniques are presenting new opportunities. Sensors, connectivity and the Internet of Things allow us to gather detailed data on the ground, the cloud allows us to combine data from different sources, and techniques like machine learning allow us to discern patterns and model and test changes.

The DataKind Vision Zero project is a terrific demonstration of the possibilities created by bringing diverse sources of data and expertise together. From transportation expertise on how people move around cities, to health expertise on which collisions lead to the most severe outcomes, from community expertise on shared values and advocacy to engineering and design expertise on evolving urban layouts, data analysis can inform and strengthen cross-cutting discussions and decisions.

Read more about the project and how to get involved here, and follow the project on Twitter using #VisionZeroData.

Microsoft is thrilled to support the DataKind Vision Zero project, and we look forward to working with governments, community organizations, transportation experts and data scientists on insights and interventions that make all of our cities safer.

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