Think of it in human terms.
We perceive our surroundings through various sensory organs in our bodies. Although vision is the dominant sensor of daily life, the information acquired with this single sensor is extremely limited. Therefore, we must complete the information of our surroundings by using other sensors — including hearing and smell.
This concept is applicable to AVs. Currently, sensors used in AVs and advanced driver-assistance system technology range from cameras to lidars, radars and sonars. These sensors each have their own advantages, but each also have limited capabilities.
In the automotive field, which is so essential to allowing people to live their daily lives, safety is the most important value. This truth especially applies to AVs, where every mistake could lead to further distrust from the public about AVs. So the ultimate value that most companies aim for through autonomous driving technology is the realization of a safer driving environment.
With sensor fusion technology, each sensor is specialized in acquiring and analyzing specific information. Therefore, advantages and disadvantages are clear in recognizing the surrounding environment, and there are also limitations that are difficult to solve.
Cameras are very effective in classifying vehicles and pedestrians, or reading road signs and traffic lights. However, their abilities may be limited by fog, dust, darkness, snow and rain. Radar and lidar accurately detect the position and velocity of an object, but they lack the ability to classify objects in detail. They also cannot recognize various road signs because they are incapable of classifying colors.
Sensor fusion technology eliminates distortion or lack of data by integrating various types of data acquired. The sensor fusion software algorithm complements information about blind spots that a single sensor cannot detect, or integrates overlapping data detected by multiple sensors simultaneously and balances information. With this comprehensive information, this technology provides the most accurate and reliable environmental modeling and enables more intelligent driving.