Tesla Begins Crowdsourcing Camera Data to Improve Autonomous Functions

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By James Hodgson | 2Q 2017 | IN-4589


Harnessing Crowdsourced Data


The crowdsourcing of car sensor data represents the “next step” in the role that connectivity plays in automotive, moving from use cases that support convenience and entertainment toward more mission-critical functions. The aggregation of camera, radar, LiDAR, and ultrasonic data from connected cars can enable a range of new services, including smart parking guidance, real-time traffic, and hyper-local weather information. The crowdsourcing paradigm will also play a key role in autonomous driving—firstly in the building and maintenance of 3D maps for relative positioning, and secondly for the training of deep learning networks to improve the performance of autonomous systems software.

Tesla has always been ahead of the competition in terms of how effectively it leverages connectivity to deliver a unique and improved user experience, particularly with its pioneering use of over-the-top (OTA) software and firmware updates to remotely fix bugs and add significantly new functionality. Once again, Tesla is pushing the boundaries of what connectivity means…

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