Ensuring safety in highly automated vehicles : a review of testing and validation methods for robustness and reliability

Frischknecht-Gruber, Carmen; Heuberger, Benjamin; Reif, Monika Ulrike; Weng, Joanna; Senn, Christoph

doi:10.3850/978-981-18-8071-1_P414-cd

Publication type:	Conference paper
Type of review:	Peer review (publication)
Title:	Ensuring safety in highly automated vehicles : a review of testing and validation methods for robustness and reliability
Authors:	Frischknecht-Gruber, Carmen Heuberger, Benjamin Reif, Monika Ulrike Weng, Joanna Senn, Christoph
et. al:	No
DOI:	10.3850/978-981-18-8071-1_P414-cd
Proceedings:	Proceeding of the 33rd European Safety and Reliability Conference
Editors of the parent work:	Brito, Mário P. Aven, Terje Baraldi, Piero Čepin, Marko Zio, Enrico
Page(s):	257
Pages to:	264
Conference details:	33rd European Safety and Reliability Conference (ESREL), Southampton, United Kingdom, 3-7 September 2023
Issue Date:	2023
Publisher / Ed. Institution:	Research Publishing
Publisher / Ed. Institution:	Singapore
ISBN:	978-981-18-8071-1
Language:	English
Subjects:	Safe AI; Trustworthy AI; Safety critical systems; Autonomous driving
Subject (DDC):	629: Aeronautical, automotive engineering
Abstract:	The future of mobility is set to be reformed as the rapidly increasing use of driver assistance systems and highly automated vehicles (HAVs) show their great potential. The use of deep neural networks in autonomous driving systems has led to significant progress in this area. However, the increase in accidents involving HAVs highlights the need for effective testing and validation methods to increase the overall safety of these vehicles. With many technology companies and manufacturers aiming to put Level 4 and 5 vehicles into operation soon, the safety of HAVs remains a major concern. Rigorous testing and validation against potential failures and misbehaviour are required to ensure the reliability and robustness of these systems. This paper provides an overview of state of the art in testing and evaluation methods for machine learning-based HAVs. A literature review on these topics is provided to give valuable insights to researchers, practitioners and policymakers. As such, the review describes different types of validation, verification and testing methods, including real-world testing, simulation testing, hardware-in-the loop testing, adversarial robustness, and methods used for explainability and interpretability in AI. The advantages and limitations are discussed and current challenges are highlighted. Finally, open research questions and future directions in the field are identified.
URI:	https://digitalcollection.zhaw.ch/handle/11475/29451
Fulltext version:	Published version
License (according to publishing contract):	Licence according to publishing contract
Departement:	School of Engineering
Organisational Unit:	Institute of Applied Mathematics and Physics (IAMP)
Appears in collections:	Publikationen School of Engineering

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Frischknecht-Gruber, C., Heuberger, B., Reif, M. U., Weng, J., & Senn, C. (2023). Ensuring safety in highly automated vehicles : a review of testing and validation methods for robustness and reliability [Conference paper]. In M. P. Brito, T. Aven, P. Baraldi, M. Čepin, & E. Zio (Eds.), Proceeding of the 33rd European Safety and Reliability Conference (pp. 257–264). Research Publishing. https://doi.org/10.3850/978-981-18-8071-1_P414-cd

Frischknecht-Gruber, C. et al. (2023) ‘Ensuring safety in highly automated vehicles : a review of testing and validation methods for robustness and reliability’, in M.P. Brito et al. (eds) Proceeding of the 33rd European Safety and Reliability Conference. Singapore: Research Publishing, pp. 257–264. Available at: https://doi.org/10.3850/978-981-18-8071-1_P414-cd.

C. Frischknecht-Gruber, B. Heuberger, M. U. Reif, J. Weng, and C. Senn, “Ensuring safety in highly automated vehicles : a review of testing and validation methods for robustness and reliability,” in Proceeding of the 33rd European Safety and Reliability Conference, 2023, pp. 257–264. doi: 10.3850/978-981-18-8071-1_P414-cd.

FRISCHKNECHT-GRUBER, Carmen, Benjamin HEUBERGER, Monika Ulrike REIF, Joanna WENG und Christoph SENN, 2023. Ensuring safety in highly automated vehicles : a review of testing and validation methods for robustness and reliability. In: Mário P. BRITO, Terje AVEN, Piero BARALDI, Marko ČEPIN und Enrico ZIO (Hrsg.), Proceeding of the 33rd European Safety and Reliability Conference. Conference paper. Singapore: Research Publishing. 2023. S. 257–264. ISBN 978-981-18-8071-1

Frischknecht-Gruber, Carmen, Benjamin Heuberger, Monika Ulrike Reif, Joanna Weng, and Christoph Senn. 2023. “Ensuring Safety in Highly Automated Vehicles : A Review of Testing and Validation Methods for Robustness and Reliability.” Conference paper. In Proceeding of the 33rd European Safety and Reliability Conference, edited by Mário P. Brito, Terje Aven, Piero Baraldi, Marko Čepin, and Enrico Zio, 257–64. Singapore: Research Publishing. https://doi.org/10.3850/978-981-18-8071-1_P414-cd.

Frischknecht-Gruber, Carmen, et al. “Ensuring Safety in Highly Automated Vehicles : A Review of Testing and Validation Methods for Robustness and Reliability.” Proceeding of the 33rd European Safety and Reliability Conference, edited by Mário P. Brito et al., Research Publishing, 2023, pp. 257–64, https://doi.org/10.3850/978-981-18-8071-1_P414-cd.