Data drives the development of autonomous vehicles. During autonomous operation, an R&D vehicle gathers data from the sensors and produces logs. The raw sensor data, as well as onboard logs, is then used by engineers to improve onboard autonomy systems, including machine learning.
Onboard data is typically transferred to a large-scale storage device by fiber optics or by removable or swappable drives. Once the data is processed by engineers, it’s retained and used later for regression testing and engineering.
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Autonomous R&D vehicles are fitted with a variety of sensors, which are used by onboard autonomy systems and machine learning algorithms. The raw data from these sensors is used to improve and train the onboard machine learning algorithms. Cameras and LiDAR generate most of the data.