While other companies, like Waymo, have shared self-driving vehicle data in the past, the breadth and depth of Ford’s data is unusual. Because it was collected over an entire year, it includes a variety of weather conditions, including rain, sun, clouds and snow. The data was gathered in the Metro Detroit area, so the vehicles experienced dense urban areas, freeways, tunnels, residential neighborhoods, airports, construction zones and pedestrian activity. That should give research access to the kinds of diverse scenarios self-driving vehicles will find themselves in, Ford says.

Plus, while most datasets only offer data from a single vehicle, this data comes from multiple vehicles. That means researchers can explore, for instance, what happens when two vehicles encounter each other. One might be able to detect things that the other cannot “see,” which could lead to development around multi-vehicle communication, perception and path planning.
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