Abstract
We live in the era of the advent of automated vehicles. These will bring dramatic changes in both the automotive industry and everyday life, revolutionizing the concept of passenger mobility. The issue of perception is crucial for an autonomous vehicle and presents important challenges, many of which still need to be addressed. In this context, the choice of sensors is pivotal, yet there is still no general consensus on what the potential “best” sensory equipment should consist of. Furthermore, perception-related information is then used to make timely decisions on path planning and vehicle dynamics control to ensure efficient and safe vehicle behavior. Here, machine learning algorithms are playing an increasingly important role, for example, in the generation of trajectories perceivable as “natural” by the car’s occupants or in object recognition.
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