Transportation data gets an upgrade
Exploring a new area? Chances are you’ll reach for a map at some point, or maybe ask a local for directions. But what would you do if you were in a self-driving car? In the world of autonomous driving, the map is digital and the “local” is big data. At least that’s the idea behind the newly formed SharedStreets platform. This public-private collaboration is the first of its kind in the area of transportation data, and it aims to solve complex problems that could bog down the mobility of the future.
So, what is SharedStreets, really, and why is it so important? In short, it’s a new standard for transportation data sets. The current model for transportation data is built on geographic information systems known as GIS. The problem with GIS is it has a non-universal global standard. Use of proprietary maps and identification systems makes comparison and analysis of collected data a challenge. The newly created SharedStreets platform attempts to eliminate this issue by creating a uniform standard everyone can use.
This baseline protocol is imperative for true collaboration to take place. The goal of the project is to better provide cities and private companies with the tools they need to help us understand what’s happening on city streets. Imagine real-time analysis of traffic patterns, parking availability, road closures and more. The idea behind automated driving is about more than just relieving us of the stresses of the road. The goal is to change our approach to transportation entirely.
This collaboration between Ford Motor Company, Uber, Lyft and the National Association of City Transportation officials, with the help of Bloomberg Philanthropies, seeks to create the maps of the future. The data points evaluated with SharedStreets could be the “local” we rely on for years to come.