Architecting Dependable Learning-enabled Autonomous Systems: A Survey

Chih-Hong Cheng; Dhiraj Gulati; Rongjie Yan

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arXiv · 1902.10590

Architecting Dependable Learning-enabled Autonomous Systems: A Survey

Chih-Hong Cheng·Dhiraj Gulati·Rongjie Yan

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Abstract

We provide a summary over architectural approaches that can be used to construct dependable learning-enabled autonomous systems, with a focus on automated driving. We consider three technology pillars for architecting dependable autonomy, namely diverse redundancy, information fusion, and runtime monitoring. For learning-enabled components, we additionally summarize recent architectural approaches to increase the dependability beyond standard convolutional neural networks. We conclude the study with a list of promising research directions addressing the challenges of existing approaches.

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Chih-Hong Cheng, Dhiraj Gulati, Rongjie Yan. 2019-02-27. Architecting Dependable Learning-enabled Autonomous Systems: A Survey. https://arxiv.org/abs/1902.10590

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