The technology for Advanced Driver Assistance System (ADAS) continues to evolve, largely driven by automotive regulations and consumer demand. ADAS helps drivers stay on top of the driving surroundings for an easier, safer and more comfortable ride. ADAS is the essential step between initial Driver Assistance (DA) systems and fully autonomous cars, and typical solutions include various digital sensors such as RADAR, LIDAR and digital CMOS cameras to capture, fuse and process data from the vehicle driving environment. The popular ADAS camera-based functions are:
|Figure 1: TySOM-3-ZU7EV||Figure 2: FMC-ADAS expansion card|
As ADAS technology continues to evolve, the need for high-performance re-programmable platforms has never been greater. Aldec provides ADAS development platforms including reference designs and tutorials based on the TySOM Embedded Development boards and FMC-ADAS extension card.
Figure 3: FMC-ADAS functionalities
The ADAS application contains the following features:
Figure 4: ADAS solution processing detail
ADAS Multi-Camera Surround View technology is a parking assistance system available in today’s mid- and high-cost vehicles. The key feature is a set of 4 HDR wide-lens cameras installed around the vehicle for a full 360 degree view of the surroundings in a single screen. The reference design grabs, processes and displays 4 simultaneous camera video streams in real-time. The most computational intensive parts of the code are offloaded from ARM Cortex-A9 to FPGA part of Xilinx® Zynq-7000 All-Programmable and Xilinx® Zynq Ultrascale+ MPSoC device using Xilinx SDSoC™ tool, achieving the goal for real-time processing performance. The accelerated part includes edge detection, colorspace conversion and frame merging tasks. The Edge detector is used to highlight the possible obstacles around the vehicle which cannot be easily noticed by the human eye.
Figure 5: Multi-camera surround view processing detail
Most of the car accidents nowadays occur because of the drowsiness of the driver, specially truck drivers. Nowadays, to prevent such a collision, a specific camera is used in smart vehicles to realize driver drowsiness in the early stages. Aldec’s ADAS solution also contains this feature by using one HDR camera allocated for the driver. The Pixel Intensity Comparison-based Object detection (PICO) algorithm is used for this application because of high processing speed and ease of modification. In this application, the most computational intensive parts of the code are offloaded from ARM Cortex-A9 to FPGA part of Xilinx® Zynq-7000 All-Programmable and Xilinx® Zynq Ultrascale+ MPSoC device using Xilinx SDSoC™ tool, achieving the goal for real-time processing performance. The accelerated parts contain colorspace conversion and Histogram Equalization. In the next step, face detection, eye detection and blink detection are processed. In the decision making section, a buzzer comes to play if the driver is detected to be sleepy. The following diagram shows the steps for the Driver Drowsiness Detection Application.
Figure 6: Driver Drowsiness Detection processing detail
Today’s modern vehicles include a rear-view camera as a basic feature which allows drivers to monitor the rear of the vehicle during reverse driving. Automotive grade megapixel HDR camera, ultrasonic sensor and the Human Interface Devices (HID) are the essential components that turn the rear license plate camera into a smart solution. The reference design is running on the TySOM-2 board under the control of embedded Linux OS, providing an easy way to collect, fuse and process multiple simultaneous data from several digital sensors using the best from ARM Processing System (PS) and the Programmable Logic/FPGA (PL) sides located on Xilinx Zynq-7000 All-Programmable device. The processed data is used to overlay the rear-view video stream with the visual warnings as well as for sonic alert generation in case of a possible obstacle close to the vehicle.
Figure 7: Smart rear-view processing details