Traffic experts met last week at Spaces NoMA for the fourth Playing with Traffic event of Transportation Techies. A handful presented their latest work in a rapid-fire show-and-tell of the wide array of open-source mapping and imaging that can now inform how streets are planned for both current users and future technology. Mapillary's Janine Yoong explained how combining computer vision – using digital images to train computers to understand objects – with human collaboration can inform the development of autonomous vehicles. Yoong and her team hope to use street-view images from across the internet to help driverless cars better categorize items that they "see" while also creating fresher, more accurate, and complete maps that can help computers understand their location. With this, Mapillary pulls images of streetscapes from around the world, including remote arctic research bases, that can train AV programs by processing as many objects and situations as possible.