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Description
While more and more progress is achieved and being reported in talks and press releases on the functional challenges on the road towards fully automated driving, there is little light on the challenge of proving that these automated driving functions are safe - a prerequisite for releasing automated driving functions to the market. This special session intends to bring together academics and practitioners from automotive industry in order to show recent advances made in different aspects of this challenge. These include a model-based automated analysis and optimization method to achieve system safety, a method to reason about safety of machine learning enabled components, and the use of formal property specification to generate runtime safety monitors.
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