Abstract
The verification and validation (V&V) of autonomous systems is a complex and difficult task, especially when artificial intelligence is used to achieve autonomy. However, without proper V&V, sufficient evidence to argue safety is not attainable. We propose in this work the use of a Safety Supervisor (SSV) to circumvent this issue. However, the design of an adequate SSV is a challenge in itself. To assist in this task, we present a conceptual framework and a corresponding metamodel, which are motivated and justified by existing work in the field. The conceptual framework supports the alignment of future research in the field of runtime safety monitoring. Our vision is for the different parts of the framework to be filled with exchangeable solutions so that a concrete SSV can be derived systematically and efficiently, and that new solutions can be embedded in it and get evaluated against existing approaches. To exemplify our vision, we present an SSV that is based on the ISO 22839 standard for forward collision mitigation.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Adler, R., Feth, P., Schneider, D.: Safety engineering for autonomous vehicles. In: Workshop on Safety and Security of Intelligent Vehicles (2016)
Adler, R., Schaefer, I., Schule, T.: Model-based development of an adaptive vehicle stability control system. Modellbasierte Entwicklung von eingebetteten Fahrzeugfunktionen (2008)
Bojarski, M., Testa, D.D., Dworakowski, D., Firner, B., Flepp, B., Goyal, P., Jackel, L.D., Monfort, M., Muller, U., Zhang, J., Zhang, X., Zhao, J., Zieba, K.: End to end learning for self-driving cars (2016)
Eidehall, A.: Multi-target threat assessment for automotive applications. In: IEEE International Conference on Intelligent Transportation Systems (2011)
Endsley, M.R.: Toward a theory of situation awareness in dynamic systems. Hum. Fact. J. Hum. Fact. Ergon. Soc. 37(1), 32–64 (1995)
Feth, P., Bauer, T., Kuhn, T.: Virtual validation of cyber physical systems. In: Software Engineering & Management (2015)
FKA: Pelops. http://www.fka.de/pdf/pelops_whitepaper.pdf
Hornung, A., Wurm, K.M., Bennewitz, M., Stachniss, C., Burgard, W.: An efficient probabilistic 3D mapping framework based on octrees. Auton. Robot. 34(3), 189–206 (2013)
ISO: 26262: Road vehicles - functional safety (2009)
ISO: 22839: Intelligent transport systems - forward vehicle collision mitigation systems - operation, performance, and verification requirements (2013)
Johansson, R., Nilsson, J.: The need for an environment perception block to address all asil levels simultaneously. In: IEEE Intelligent Vehicles Symposium (2016)
Jungnickel, R., Kohler, M., Korf, F.: Efficient automotive grid maps using a sensor ray based refinement process. In: IEEE Intelligent Vehicles Symposium (2016)
Koopman, P., Wagner, M.: Challenges in autonomous vehicle testing and validation. SAE Int. J. Transp. Saf. 4(1), 15–24 (2016)
Kuhn, T., Forster, T., Braun, T., Gotzhein, R.: FERAL - framework for simulator coupling on requirements and architecture level. In: IEEE/ACM International Conference on Formal Methods and Models for Codesign (MEMOCODE) (2013)
Kuhnt, F., Pfeiffer, M., Zimmer, P., Zimmerer, D., Gomer, J.M., Kaiser, V., Kohlhaas, R., Zollner, M.J.: Robust environment perception for the audi autonomous driving cup. In: IEEE International Conference on Intelligent Transportation Systems (2016)
Kurd, Z., Kelly, T., McDermid, J., Calinescu, R., Kwiatkowska, M.: Establishing a framework for dynamic risk management in ‘intelligent’ aero-egine control. In: International Conference on Computer Safety, Reliability and Security (2009)
Lefèvre, S., Vasquez, D., Laugier, C.: A survey on motion prediction and risk assessment for intelligent vehicles. ROBOMECH J. 1, 1 (2014)
Mekki-Mokhtar, A., Blanquart, J.P., Guiochet, J., Powell, D., Roy, M.: Safety trigger conditions for critical autonomous systems. In: IEEE Pacific Rim International Symposium on Dependable Computing (2012)
Pegasus: Pegasus research project (2017). http://www.pegasus-projekt.info/en/
Rohmer, E., Surya, P.N.S., Freese, M.: V-REP: a versatile and scalable robot simulation framework. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (2013)
Rushby, J.: Runtime certification. In: Leucker, M. (ed.) RV 2008. LNCS, vol. 5289, pp. 21–35. Springer, Heidelberg (2008). doi:10.1007/978-3-540-89247-2_2
SAE: J3016: Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles (2016)
Schreier, M., Willert, V., Adamy, J.: Bayesian, maneuver-based, long-term trajectory prediction and criticality assessment for driver assistance systems. In: IEEE Intelligent Vehicles Symposium (2014)
Sha, L.: Using simplicity to control complexity. IEEE Softw. 18(4), 20–28 (2001)
Stolte, T., Bagisch, G., Maurer, M.: Safety goals and functional safety requirements for actuation systems of automated vehicles. In: IEEE International Conference on Intelligent Transportation Systems (2016)
Tamke, A., Dang, T., Breuel, G.: A flexible method for criticality assessment in driver assistance systems. In: IEEE Intelligent Vehicles Symposium (2011)
Trapp, M., Schneider, D.: Safety assurance of open adaptive systems – a survey. In: Bencomo, N., France, R., Cheng, B.H.C., Aßmann, U. (eds.) Models@run.time. LNCS, vol. 8378, pp. 279–318. Springer, Cham (2014). doi:10.1007/978-3-319-08915-7_11
van Nunen, E., Tzempetzis, D., Koudijs, G., Nijmeijer, H., van den Brand, M.: Towards a safety mechanism for platooning. In: IEEE Intelligent Vehicles Symposium (2016)
Wachenfeld, W., Winner, H.: The release of autonomous vehicles. In: Maurer, M., Gerdes, C.J., Lenz, B., Winner, H. (eds.) Autonomous Driving. Springer, Heidelberg (2015). doi:10.1007/978-3-662-48847-8_21
Wiest, J., Karg, M., Kunz, F., Reuter, S., Kreßel, U., Dietmayer, K.: A probabilisitc maneuver prediction framework for self-learning vehicles with application to intersections. In: IEEE Intelligent Vehicles Symposium (2015)
Winner, H., Lotz, F., Bauer, E., Konigorski, U., Schreier, M., Adamy, J., Pfromm, M., Bruder, R., Lueke, S., Cieler, S.: PRORETA 3: comprehensive driver assistance by safety corridor and cooperative automation. In: Winner, H., Hakuli, S., Lotz, F., Singer, C. (eds.) Handbook of Driver Assistance Systems. Springer, Cham (2016). doi:10.1007/978-3-319-09840-1_19-1
Acknowledgments
The work presented in this paper was created in context of the Dependability Engineering Innovation for CPS - DEIS Project, which is funded by the European Commission.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Feth, P., Schneider, D., Adler, R. (2017). A Conceptual Safety Supervisor Definition and Evaluation Framework for Autonomous Systems. In: Tonetta, S., Schoitsch, E., Bitsch, F. (eds) Computer Safety, Reliability, and Security. SAFECOMP 2017. Lecture Notes in Computer Science(), vol 10488. Springer, Cham. https://doi.org/10.1007/978-3-319-66266-4_9
Download citation
DOI: https://doi.org/10.1007/978-3-319-66266-4_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-66265-7
Online ISBN: 978-3-319-66266-4
eBook Packages: Computer ScienceComputer Science (R0)