AUSMAH Specialists on the Development of Autonomous Vehicles

Further progress in areas such as data management, object detection, map-based navigation and decision-making depends heavily on continued advances in machine learning and artificial intelligence models.

The main challenge facing automakers going forward is to keep refining these machine learning models.

At the same time, the underlying architecture of autonomous vehicles is being optimized. Fewer manufacturers are opting for large networks of microcontrollers, each tailored to a specific application, and instead favoring a single powerful processor with greater overall computing capacity. This shift away from a distributed network of microcontrollers (MCUs) toward a centralized MCU is likely to become one of the biggest changes in the cars of the future.