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Experience Safe and Smart Driving with Vision-based Advanced Driver Assistance Systems (ADAS)

According to Markets and Markets, the advanced driver assistance system (ADAS) market is projected to reach USD 91.83 billion by 2025 (From USD 24.24 billion in 2018). This trend clearly signifies the rising popularity and market acceptance of the innovative ADAS systems. The technological advancements in the sensor components, specifically in vision-based ADAS, are the major drivers that have propelled a huge interest in ADAS systems for the automotive market. With assisted and automated driving features, vision-based ADAS systems help experience safe and smart driving.

Let us discuss the Vision-based ADAS system, its components, and applications in assisted and automated driving.

What is Vision-based Advanced Driver Assistance System?

Vision-based ADAS uses embedded vision or computer vision systems to identify and track potential hazards on the road and provide a real-time vision-based analytics to the driver. Embedded vision system typically comprises of a compact board level camera and a single board computer (SBC) or system on module (SOM). It uses digital processing and intelligent algorithms to interpret meaning from real-time images or videos captured from the onboard cameras.  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.

Components of Vision-based ADAS Systems

  • Automotive Cameras: Automotive cameras are the eyes of the vision-based advanced driver assistance systems in a vehicle. 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. To optimally cover the front, rear and surround view of a vehicle, automotive companies use monocular and stereo cameras in vehicles. Where monocular camera (with single camera sensor) is primarily used for object detection, stereo cameras (with two camera sensors) provide an additional feature to calculate distance-to-object for the system.
  • Camera Modules: 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. 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. 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).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. After that, the code is optimized for embedded system and finally ported to the target system.

Applications of Vision-based ADAS Systems

Embedded vision in ADAS and its applications are dependent on the camera location in the vehicle. There are four sides in a vehicle where cameras can be installed for ADAS applications i.e. front, rear, and on both the sides of the vehicle. Front cameras are deployed in front of the vehicle behind rear view mirror, rear cameras are mounted near the vehicle number plate and side cameras are mounted near the side mirrors. All these cameras perform multiple ADAS tasks, which are as follows:

  • Front Cameras: Front cameras in a vision-based ADAS are monocular cameras, which run algorithms like forward collision warning, traffic sign recognition, pedestrian recognition, lane departure warning and vehicle detection.
  • Rear Cameras: Rear view cameras are usually used for parking assistance and object detection. In some vehicles, parking assistance is supported by four fish eyes cameras or wide-angle cameras, which provides a bird’s eye view to assist in parking.
  • Driver Monitoring Systems: A dash cam mounted in vehicle’s cabin supports the driver monitoring system for ADAS, which are assisted by advanced facial analysis algorithms to track eye gaze, head-pose, and mouth status of the driver. Driver monitoring system in ADAS recognizes and authenticates driver, detect drowsiness and distraction and provides real-time alerts to reduce possibilities of on-road accidents.
  • Surround View System: Surround view system in vehicles supports with left-right turn awareness, blind spot detection, lane change assistance, obstacle and pedestrian detection in the sideways of the vehicle and top-view parking assistance.

CASE STUDY: Advanced Driver Assistance System SW Development Download Now

Vision-based ADAS systems supported by embedded vision are cost-effective as compared to other sensor-based Advanced Driver Assistance Systems. However, the future of ADAS lies in more advanced and sophisticated ADAS systems supported by LIDAR and RADAR sensors (in addition to vision-based ADAS) to provide many more applications for assisted and automated driving.

eInfochips as an automotive engineering solutions provider assists tier 1 and semiconductor companies in the high-resolution camera design, video solution and vision based algorithms for advanced driver assistance systems. Know more about eInfochips’ capabilities in automotive and ADAS solutions.

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