Advanced Driver Assistant System (ADAS) is a key application leading towards autonomous drive in the not distant future. Almost all car OEMs and tier 1s are developing and competing with each other with the aim to introduce semi-autonomous driving vehicles into market by 2020. ADAS requires much higher computing performance than existing other automotive applications. It needs sophisticated technologies such as mobile and consumer electronics tailored for automotive qualifications which are quite huge challenges for today’s automotive industries.
Under such circumstances, a great deal of attention is paid to ARM processors for their unparalleled performance with high power efficiency and broad ecosystem, which will help a lot for the automotive space.
Actually ADAS contains very wide applications but here we want to focus on camera, sensor and radar related applications and discuss how ARM processors will be used in the near future.
Simplified ADAS application workflow is described below: sensing, perception, decision making (sometimes displayed to the monitor/dashboard) and then actuated by chassis application like braking or steering system.
For sensing, a multitude of sensors such as radar, lidar, cameras, MEMS or ultrasonic sensors are used here.
ADAS will bring a lot of extra MCUs and SoCs into vehicles. They will start communicating or cooperating with chassis applications like braking system or steering system via domain controllers. Communication via automotive Ethernet, data fusion seems to be inevitable to happen to handle enormous amount of data but it is not clear yet what kind of new SoC will be needed or if improved Graphic SoC (for GPU compute) to handle the extra job. Perhaps real-time CPUs supporting functional safety related to ISO26262 will be needed to make decisions. Nevertheless, the performance requirements for the SoC for data fusion should be higher than ever. I’m thinking that if heterogeneous computing is to happen in automotive space in the future, this will be the place. We offer ARMv8-A processors supporting 64-bit, ARMv8-R architecture supporting virtualization by hardware with real-time response, and Mali GPU for GPU compute and ARM’s announced Open CL support for NEON for heterogeneous multiprocessing and parallel computation for performance and efficiency.
ADAS, which is definitely required to support automotive quality and safety, at the same is very similar to mobile and consumer application technologies with rapid development cycle. ARM’s solutions in terms of technologies and ecosystem address such complicated requirements. ADAS is a unique domain where cooperation or co-development with third-party of software companies is needed to remain competitive or to develop new algorithms for fast time to market. ARM’s ecosystem with its broadness and diversity, enables the automotive industry to overcome the difficulties it faces today by providing new partnerships and to leap into the next stage.