Abstract
In autonomous driving, the goal of perception is to sense the surrounding dynamic environment, to build reliable and detailed representation based on sensory data. In order for autonomous driving vehicles to be safe and intelligent, perception modules must be able to detect any obstacle, to recognize road surface, lane dividers, traffic signs and lights, to track moving objects in 3D, etc. Since all subsequent driving decisions, planning, and control depend on a correct perception output, its importance cannot be overstated. In this chapter, major functionalities of perception are covered, along with public datasets, problem definitions, and typical algorithms. Algorithms based on neural networks are discussed in the next chapter.
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