In this chapter, we propose a novel reliability estimation concept for ego-lane detection. By that, the reliabilities of the participating sensors are learned and estimated using multiple classification approaches, whose input data consists of different types of information, such as contextual data, sensor measurements. Afterward, we demonstrate the feasibility of our introduced concept by applying it to real data.
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