Abstract
We address the question of feasibility of tests to verify highly automated driving functions by optimizing the trade-off between virtual tests for verifying safety properties and physical tests for validating the models used for such verification. We follow a quantitative approach based on a probabilistic treatment of the different quantities in question. That is, we quantify the accuracy of a model in terms of its probabilistic prediction ability. Similarly, we quantify the compliance of a system with its requirements in terms of the probability of satisfying these requirements. Depending on the costs of an individual virtual and physical test we are then able to calculate an optimal trade-off between physical and virtual tests, yet guaranteeing a probability of satisfying all requirements.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
Besides the prohibitively large computational complexity, this also requires an accurate, formal description of possible environments.
- 2.
- 3.
References
Winner, H.: Quo vadis, FAS? In: Winner, H., Hakuli, S., Lotz, F., Singer, C. (eds.) Handbuch Fahrerassistenzsysteme. ATZ/MTZ-Fachbuch, pp. 1167–1186. Springer, Wiesbaden (2015). https://doi.org/10.1007/978-3-658-05734-3_62
Kalra, N., Paddock, S.M.: Driving to safety: How many miles of driving would it take to demonstrate autonomous vehicle reliability? RAND Corp. 94, 182–193 (2016)
Stellet, J.E., Zofka, M.R., Schumacher, J., Schamm, T., Niewels, F., Zollner, J.M.: Testing of advanced driver assistance towards automated driving: a survey and taxonomy on existing approaches and open questions. In: 2015 IEEE 18th International Conference on Intelligent Transportation Systems (ITSC), pp. 1455–1462. IEEE (2015)
Hallerbach, S., Eberle, U., Köster, F.: Absicherungs- und Bewertungsmethoden für kooperative hochautomatisierte Fahrzeuge. In: AAET 2017, Braunschweig (2017) 369
Hakuli, S., Krug, M.: Virtuelle integration. In: Winner, H., Hakuli, S., Lotz, F., Singer, C. (eds.) Handbuch Fahrerassistenzsysteme. A, pp. 125–138. Springer, Wiesbaden (2015). https://doi.org/10.1007/978-3-658-05734-3_8
Nentwig, M.: Untersuchungen zur Anwendung von computergenerierten Kamerabildern für die Entwicklung und den Test von Fahrerassistenzsystemen. Ph.D. thesis, Friedrich-Alexander-Universität Erlangen-Nürnberg (2014)
Mauritz, M., Rausch, A., Schaefer, I.: Dependable ADAS by combining design time testing and runtime monitoring. In: 10th International Symposium on Formal Methods, FORMS/FORMAT 2014, pp. 28–37 (2014)
Schuldt, F., Menzel, T., Maurer, M.: Eine Methode für die Zuordnung von Testfällen für automatisierte Fahrfunktionen auf X-in-the-Loop Verfahren im modularen virtuellen Testbaukasten. In: 10. Workshop Fahrerassistenzsysteme, p. 171 (2015)
Clopper, C.J., Pearson, E.S.: The use of confidence or fiducial limits illustrated in the case of the binomial. Biometrika 26(4), 404–413 (1934)
Ammersbach, C., Winner, H.: Functional decomposition: an approach to reduce the approval effort for highly automated driving. In: 8. Tagung Fahrerassistenz (2017)
Hallerbach, S., Xia, Y., Eberle, U., Koester, F.: Simulation-based identification of critical scenarios for cooperative and automated vehicles. In: SAE International WCX World Congress Experience, April 2018
Giles, M.B.: Multi-level Monte Carlo path simulation. Oper. Res. 56(3), 607–617 (2008)
Acknowledgments
This study was partially supported and financed by Opel Automobile within the context of PEGASUS (Project for the Establishment of Generally Accepted quality criteria, tools and methods as well as Scenarios and Situations for the release of highly-automated driving functions), a project funded by the German Federal Ministry for Economic Affairs and Energy.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Böde, E., Büker, M., Eberle, U., Fränzle, M., Gerwinn, S., Kramer, B. (2018). Efficient Splitting of Test and Simulation Cases for the Verification of Highly Automated Driving Functions. In: Gallina, B., Skavhaug, A., Bitsch, F. (eds) Computer Safety, Reliability, and Security. SAFECOMP 2018. Lecture Notes in Computer Science(), vol 11093. Springer, Cham. https://doi.org/10.1007/978-3-319-99130-6_10
Download citation
DOI: https://doi.org/10.1007/978-3-319-99130-6_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-99129-0
Online ISBN: 978-3-319-99130-6
eBook Packages: Computer ScienceComputer Science (R0)