Capturing and managing big data for autonomous driving (AD)

ADAS/AD providers use artificial intelligence as one key component. Researchers and developers who can deliver insights faster while managing rapid infrastructure growth will be poised to be industry leaders. Following the process of data acquisition from test drives via ingest to the data center and processing of big data, many challenges occur. To handle this unstructured data, seamless scaling systems and toolsets are necessary from the sensor to the data center with storage and computing systems. This combined presentation provides a case study of how synchronized data capturing in test drives, big data computing, storage and archiving are integrated in today’s ADAS/AD development workflow.