Quality assurance methodologies for automated driving-Reference-Cited by-同舟云学术

Quality assurance methodologies for automated driving

Published:2018-07-10 Issue:4-5 Volume:135 Page:322-327
ISSN:0932-383X
Container-title:e & i Elektrotechnik und Informationstechnik
language:en
Short-container-title:Elektrotech. Inftech.

Author:

Wotawa Franz,Peischl Bernhard,Klück Florian,Nica Mihai

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering

Link

http://link.springer.com/article/10.1007/s00502-018-0630-7/fulltext.html

Reference38 articles.

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3. Fayolle, G., Raffaëlli, L., Vallée, F., De Souza, P., Rouah, X., Pfeiffer, M., Géronimi, S., Petront, F., Ahiad, S. (2016): Facing ADAS validation complexity with usage-oriented testing. In 8th European congress embedded real time software.

4. Nvidianews.nvidia.com (2018): NVIDIA announces worlds first functionally safe ai self-driving platform, [online]. Available at: https://nvidianews.nvidia.com/news/nvidia-announces-worlds-first-functionally-safe-ai-self-driving-platform .2018. [Accessed, 28 Feb. 2018].

5. Esch, S., Lang, B. (2008): Elektronik- und Vernetzungsarchitektur mit gesteigerter Leistungsfähigkeit. In ATZextra (pp. 194–199).

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