What are the components in the vision system of ADAS?

What are the components in the vision system of ADAS?
More and more, ADAS or advanced driver-assistance system has become a popular and widespread term as researchers, automakers and other stakeholders seek to automate the driving experience. In this regard, the vision system in ADAS plays a critical role and includes various components that make it work.
ADAS is a term that we will hear more and more of in the future. Indeed, amid efforts to make driving more autonomous, ADAS, which combines various sensors including cameras, thermal cameras, LIDAR and radar to help vehicles detect objects and decide what action to take accordingly, will be in higher demand.
In fact, this growth trend is corroborated by statistics. In a report, MarketsandMarkets noted that the ADAS market was estimated to be US$24.24 billion in 2018 and is projected to reach $91.83 billion by 2025 at a compound annual growth rate of 20.96 percent. “The market is principally driven by the increasing demand for a safe, efficient, and convenient driving experience,” it said.
Within ADAS, the vision system in essence serves as the “eye” of the vehicle. “Embedded vision system … uses digital processing and intelligent algorithms to interpret meaning from real-time images or videos captured from the onboard cameras,” said a blog post by eInfochips. “Automotive cameras integrated with application-specific processors and image recognition technologies enable an embedded vision system to identify people, pedestrians, vehicles, traffic signs, and other objects in and around the vehicle while driving.”


According to the post, the vision system of ADAS is consisted of various components. They are summarized as follows.
Automotive cameras: Automotive cameras are the eyes of the vision-based advanced driver assistance systems in a vehicle, said the post. “While front cameras in vehicles are used to detect lane markings, pedestrian and traffic signs, the side and rear cameras help in cross-traffic alerts, blind spot detection, and parking assistance,” it said. “To optimally cover the front, rear and surround view of a vehicle, automotive companies use monocular and stereo cameras in vehicles.”
Camera modules: According to the post, camera modules are systems comprised of automotive cameras, image sensors and lens modules. “Image sensors in the camera module are used to convert images from cameras into electronic signals for processing. There are two types of image sensors available for ADAS applications, namely CCD (charge-coupled device) and CMOS (complementary metal-oxide semiconductor) sensors, of which CMOS sensors are highly preferred and used because of their low power consumption, easy integration, faster frame rate and low manufacturing cost,” it said. “The other part of the camera module is a lens module, which is responsible for the quality of light on the image sensor and defines the quality of the final output image for processing. A few things to consider in a camera module are smaller size, less power dissipation and digital signal communication to allow higher bandwidth.”
ADAS algorithms: Embedded vision systems in ADAS are incomplete without algorithms for specific functions, the post said. “Embedded system requires multiple sequential image frame processing and a set of complex and sophisticated algorithms to analyze the image and reach to a decision for the ADAS function. To achieve real-time performance in the system, these algorithms require specialized high-performance DSPs (digital signal processors) or GPUs (graphics processing units),” it said. “To develop any embedded vision application such as a lane departure warning system or automatic emergency braking system, a complex set process needs to be followed. At first, the application needs to be analyzed with a proper algorithm research, and then functional prototyping of the algorithm is done.”

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