Traffic Exposure Model • Re-engineering New Yorks' Streets

In August 2015, the New York city teamed up with Datakind to build a tool capable of projecting the impact of any given engineering intervention, on any given New York City street. This traffic “exposure” model uses AI to estimate the volume of cars coursing any road, at any time. Spots with high crash rates but low traffic volumes, for instance, could hint at a flaw in the street’s engineering and design; conversely, places with high volumes and low crash rates might teach officials something about what makes a safe street. Data-driven models may never be perfect, but in an era of limited funds and rising pedestrian fatalities, city leaders need all the help they can get to figure out why some street designs save lives.


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