Today there are two paths towards autonomous vehicles. Mass-market automobiles continue to add more sensors and more compute power to enable increasingly sophisticated ADAS functionality. Separately, developers of robotic vehicles utilize high-end, industrial-grade sensors (lidar, cameras and radars) along with massive centralized computing. Either way, the push towards autonomy demands more and more computational power as increasingly demanding algorithms process increasing amounts of sensor data. In this presentation, we share Yole’s analysis and forecast of the ADAS and autonomous vehicle perception market. When will cars with L2 to L5 level automation become mainstream? What sorts of processing power will they require? What alternative innovation scenarios might disrupt current trends?