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GM could crowdsource your car's data to make better maps for self-driving cars

Today at CES, GM announced that it's "exploring" the use of cameras on board its cars to automatically build high-definition mapping data — the kind of data needed for fully autonomous driving. The company would use the cellular connection in its OnStar modules, already built into most vehicles it sells, to upload a relatively low-bandwidth stream of differential mapping data back to the mothership, updating a master database of information like lane markings and precise location information.

High-def maps are key for autonomous cars

The project is in collaboration with Mobileye, a large supplier of semi-autonomous sensors and systems to the automotive industry; GM already uses Mobileye sensors for features like lane departure warning and collision alert, so firing up a system like this in new cars — which can generate the data using existing camera systems — is a relatively minor undertaking. Mark Reuss, GM's product boss, says it could be integrated into new model launches as soon as "later this year."

Anonymized, crowdsourced mapping data is seen as a possible boon for autonomous systems, which require higher-definition roadmaps than humans do in order to operate correctly in a broad spectrum of scenarios. In rolling out its Autopilot feature, Tesla announced that it would be collecting mapping data from its customers; for GM, which dwarfs Tesla, high-quality mapping from customers in the field could roll in and be continuously refreshed far more rapidly.

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