New-Tech Europe | March 2017 | Digital Edition

Automotive Special Edition

Considerations for Advanced Driver Awareness Systems why use an All Programmable SoC

Aaron Behman & Adam Taylor, XILINX

algorithms. These challenges range from the ability to implement the algorithms required for the application, to complyingwith the correct automotive standards. Many ADAS applications also require sensor fusion to combine the inputs from several sensors, significantly increasing the required processing power. Sensor fusion can be homogeneous where the multiple sensors of the same type are used, or heterogeneous where different sensor types are used to extract the information required. Many applications utilize an All Programmable SoC or FPGA to implement the system due to the flexibility provided. Both to implement the required algorithms but also due to the ability to interface with different sensors types and networks. Along with performance ADAS applications also come with several

Road benefited significantly from Moore’s law, increases in processing capability and the development of CMOS Image Sensors (CIS) and other sensor technologies have enabled vehicle manufacturers to introduce Advanced Driver Awareness Systems (ADAS). ADAS enhances the driver’s awareness of the environment around them reducing the chances of collision. Some systems are also capable of monitoring the driver and alerting them, should they become sleepy for instance. Increasingly ADAS also takes control (or provides information to autonomous driving systems), providing assistance to the driver with capabilities like parking assist, lane assist and adaptive cruise control. It is no surprise therefore the ADAS market is predicted to be worth $42 Billion a year by 2021 safety has

and is currently experiencing a 10% Compounded Annual Growth Rate (CAGR) (Source: http://www. marketsandmarkets.com/Market- Reports/driver-assistance-systems- market-1201.htm). ADAS use a wide spectrum of sensors encompassing embedded vision, RADAR and LIDAR, often to extract the information required they utilize a sensor fusion approach combining information from several sensors. Within the embedded vision sphere, ADAS can be split further into two categories, external monitoring which addresses aspects like lane departure, object detection, blind spot detection and traffic sign recognition. While internal systems monitor aspects such as driver drowsiness and eye detection. Both internal and external ADAS applications bring with them challenges to address in implementing the image processing

46 l New-Tech Magazine Europe