The Evolution of Deep Learning for ADAS Applications

Embedded vision solutions will be a key enabler for making automobiles fully autonomous. Giving an automobile a set of eyes – in the form of multiple cameras and image sensors – is a first step, but it also will be critical for the automobile to interpret content from those images and react accordingly. To accomplish this, embedded vision processors must be hardware optimized for performance while achieving low power and small area, have tools to program the hardware efficiently, and have algorithms to run on these processors. The significant automotive safety improvements in the past (e.g., shatter-resistant glass, three-point seatbelts, airbags), were passive safety measures designed to minimize damage during an accident. We now have technology that can actively help the driver avoid crashing in the first place.