Perception is a safety-critical function of autonomous vehicles and machine learning (ML) plays a key role in its implementation. This position paper identifies (1) perceptual uncertainty as a performance measure used to define safety requirements and (2) its influence factors when using supervised ML. This work is a first step towards a framework for measuring and controling the effects of these factors and supplying evidence to support claims about perceptual uncertainty.
CITATION STYLE
Czarnecki, K., & Salay, R. (2018). Towards a framework to manage perceptual uncertainty for safe automated driving. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11094 LNCS, pp. 439–445). Springer Verlag. https://doi.org/10.1007/978-3-319-99229-7_37
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