Autonomous Car Data: Going Driverless? Get Excited About Petabytes

How Self-Driving Cars Use Big Data and AI

Fully driverless cars require sophisticated artificial intelligence (AI), all of which is based on massive training efforts with potentially petabytes of source data. Driving around cones on an empty racetrack is one thing; navigating through dense urban streets with random pedestrian traffic and distracted adjacent drivers is something else.

Leveling Up — 5 Levels of Self-Driving Cars

On the road from fully manual cars to Total Recall’s Johnny Cabs, the Society of Automotive Engineers has defined six levels:

  • Radar: 10–100KB per second
  • Sonar: 10–100KB per second
  • GPS: 50KB per second
  • Lidar: 10–70MB per second

Handling the Load — How Do Self-Driving Cars Collect Data?

The mix of sensors may change. The algorithms may evolve.

Quobyte — A Solution for Efficient Autonomous Cars Data Processing

Yet yes, it is possible to achieve high-bandwidth, reliable, affordable storage for neural network training at the scale demanded by autonomous driving efforts.

Interested in Quobyte?

Schedule a call with us to learn more about Quobyte and our Editions.

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Quobyte empowers customers by providing real software storage so that they can keep up with the ever-increasing amounts of data in today’s data-driven world.

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Quobyte

Quobyte

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Quobyte empowers customers by providing real software storage so that they can keep up with the ever-increasing amounts of data in today’s data-driven world.