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Challenges in Using Neural Networks in Safety-Critical Applications

Authors:

Håkan Forsberg, Johan Hjorth, Masoud Daneshtalab, Joakim Lindén , Torbjörn Månefjord

Publication Type:

Conference/Workshop Paper

Venue:

The 39th Digital Avionics Systems Conference


Abstract

In this paper, we discuss challenges when using neural networks (NNs) in safety-critical applications. We address the challenges one by one, with aviation safety in mind. We then introduce a possible implementation to overcome the challenges. Only a small portion of the solution has been implemented physically and much work is considered as future work. Our current understanding is that a real implementation in a safety-critical system would be extremely difficult. Firstly, to design the intended function of the NN, and secondly, designing monitors needed to achieve a deterministic and fail-safe behavior of the system. We conclude that only the most valuable implementations of NNs should be considered as meaningful to implement in safety-critical systems.

Bibtex

@inproceedings{Forsberg5952,
author = {H{\aa}kan Forsberg and Johan Hjorth and Masoud Daneshtalab and Joakim Lind{\'e}n and Torbj{\"o}rn M{\aa}nefjord},
title = {Challenges in Using Neural Networks in Safety-Critical Applications},
month = {October},
year = {2020},
booktitle = {The 39th Digital Avionics Systems Conference},
url = {http://www.es.mdh.se/publications/5952-}
}