Industry Expert Blogs
Memory Trends for Automotive MarketsCadence IP Blog - Priya Balasubramanian, CadenceMar. 09, 2017 |
Remember automobiles from a few years ago? They were pretty simple machines with lots of small microprocessors distributed across the whole vehicle and doing fairly simple tasks. Semiconductors have been in automobiles for several years, of course, with simple 8- and 16-bit microcontrollers performing functions like Anti-lock Braking (ABS).
But today’s automobiles are a different beast. They incorporate several compute-heavy applications like Advanced Driver Assistance Systems (ADAS) systems, infotainment systems, and in some cases, even the ultimate goal that everyone is working toward—autonomous driving. All these applications need very heavy computing. For instance, in the case of ADAS, the system will need to process several images in real time, analyze them and make crucial decisions accordingly. The vision sub-system of the ADAS will need to process images from a variety of sources—RADAR, LIDAR, or standard image sensors. These pictures could be of speed signs, obstacles on the road, etc. Depending on the decisions arrived at after processing these images, the ADAS will need to control the steering and braking in a timely manner in order to achieve safe driving.