Safety requirements are among the most ambitious challenges for autonomous guidance and control of automobiles. A human-like understanding of the surrounding traffic scene is a key element to fulfill these requirements, but is a still missing capability of today's intelligent vehicles. Few recent proposals for driver assistance systems approach this issue with methods from the AI research to allow for a reasonable situation evaluation and behavior generation. While the methods proposed in this contribution are lend from cognition in order to mimic human capabilities, we argue that in the long term automated cooperation among traffic participants bears the potential to improve traffic efficiency and safety beyond the level attainable by human drivers. Both issues are major objectives of the Transregional Collaborative Research Centre 28 'cognitive automobiles,' TCRC28 that is outlined in the paper. Within this project the partners focus on systematic and interdisciplinary research on machine cognition of mobile systems as the basis for a scientific theory of automated machine behavior.
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