N. G. Leveson, J. P. Thomas, and M. Primer, MIT Partnership for a Systems Approach to Safety (PSAS), 2015.

N. G. Leveson, J. P. Thomas, and . Handbook, MIT Partnership for a Systems Approach to Safety, 2018.

S. Lefèvre, Risk estimation at road intersections for connected vehicle safety applications, 2012.

T. Raste, H. B. Ali, and A. Houry, Fallback strategy for automated driving using stpa, 2015.

G. Bagschik, T. Stolte, and M. Maurer, Safety analysis based on systems theory applied to an unmanned protective vehicle, 4th European {STAMP} Workshop, vol.179, pp.61-71, 2016.

S. A. Cook, H. Fan, K. Pennar, and P. Sundaram, Building behavioral competency into stpa process models for automated driving systems, 2018.

S. M. Sulaman, A. Beer, M. Felderer, and M. Höst, Comparison of the fmea and stpa safety analysis methods-a case study, Software Quality Journal, 2017.

. Ford, A matter of trust fords approach to developing self-driving vehicles, Ford, techreport, 2018.

A. Abdulkhaleq, S. Wagner, D. Lammering, H. Boehmert, and P. Blueher, Using STPA in compliance with ISO 26262 for developing a safe architecture for fully automated vehicles, CoRR, 2017.

G. Sabaliauskaite, L. S. Liew, and J. Cui, Integrating autonomous vehicle safety and security analysis using stpa method and the six-step model, International Journal on Advances in Security, vol.11, pp.160-169, 2018.

M. A. Vernacchia, Gm presentation for introducing stamp/stpa tools into standards, mIT STAMP Workshop, 2018.

J. Kephart, D. Chess, C. Boutilier, R. Das, and W. E. Walsh, An architectural blueprint for autonomic computing, 2006.

M. Fowler and J. Lewis, Microservices: a definition of this new architectural term, 2014.

M. T. Martin and L. Abbott, The Art of Scalability, 2015.

R. Cuer, Démarche de conception sûre de la supervision de la fonction de conduite autonome, Ph.D. dissertation, 2018.

C. Diop, G. Dugué, C. Chassot, E. Exposito, and J. Gomez, QoS-aware and autonomic-oriented multi-path TCP extensions for mobile and multimedia applica-tions, International Journal of Pervasive Computing and Communications, vol.8, issue.4, pp.306-328, 2012.

R. Koh-dzul, M. Vargas-santiago, C. Diop, E. Exposito, and F. Moo-mena, A smart diagnostic model for an autonomic service bus based on a probabilistic rea-soning approach, 2013 IEEE 10th International Conference on Ubiquitous Intelligence and Computing and 2013 IEEE 10th International Conference on Autonomic and Trusted Computing, pp.416-421, 2013.

U. Aßmann, S. Götz, J. Jézéquel, B. Morin, and M. Trapp, A Reference Architecture and Roadmap for Models@run.time Systems¨, pp.1-18, 2014.

,

A. Armand, D. Filliat, and J. Ibañez-guzmán, Ontology-based context awareness for driving assistance systems, 2014 IEEE Intelligent Vehicles Symposium Proceedings, pp.227-233, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01012078

A. Armand, Situation Understanding and Risk Assessment Framework for Preventive Driver Assistance, 2016.
URL : https://hal.archives-ouvertes.fr/tel-01421917

G. Bagschik, T. Menzel, and M. Maurer, Ontology based scene creation for the development of automated vehicles, CoRR, 2017.

S. Ulbrich, T. Menzel, A. Reschka, F. Schuldt, and M. Maurer, Defining and substantiating the terms scene, situation, and scenario for automated driving, 2015 IEEE 18th International Conference on Intelligent Transportation Systems, pp.982-988, 2015.

S. Geyer, M. Baltzer, B. Franz, S. Hakuli, M. Kauer et al., Concept and development of a unified ontology for generating test and use-case catalogues for assisted and automated vehicle guidance, IET Intelligent Transport Systems, vol.8, issue.3, pp.183-189, 2014.

L. Zhao, R. Ichise, T. Yoshikawa, T. Naito, T. Kakinami et al., Ontology-based decision making on uncontrolled intersections and narrow roads, 2015 IEEE Intelligent Vehicles Symposium (IV)

, IEEE, pp.83-88, 2015.

X. Geng, H. Liang, B. Yu, P. Zhao, L. He et al., A scenario-adaptive driving behavior prediction approach to urban autonomous driving, Applied Sciences, vol.7, p.426, 2017.

A. Haller, K. Janowicz, S. J. Cox, M. Lefrançois, K. Taylor et al., The modular SSN ontology: A joint W3C and OGC standard specifying the semantics of sensors, observations, sampling, and actuation, Semantic Web, pp.1-24, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01885335

E. Gamma, Design patterns: elements of reusable object-oriented software. Pear-son Education India, 1995.

M. Törngren, X. Zhang, N. Mohan, M. Becker, X. Tao et al., Architecting safety supervisors for high levels of automated driving, the 21st IEEE Internal Conference on Intelligent Transportation Systems, 2018.

N. Alaya, S. B. Yahia, and M. Lamolle, What makes ontology reasoning so arduous?: Unveiling the key ontological features, Proceedings of the 5th International Conference on Web Intelligence, Mining and Semantics, ser. WIMS '15, vol.4, 2015.

, ISO 26262 -Road vehicles -Functional safety, International Organization for Standardization Norm ISO 26262, 2018.

A. Kane, O. Chowdhury, A. Datta, and P. Koopman, A case study on runtime monitoring of an autonomous research vehicle (arv) system, pp.102-117, 2015.

M. Trapp and D. Schneider, Safety Assurance of Open Adaptive Systems -A Survey, pp.279-318, 2014.

H. C. Betty, K. I. Cheng, M. Eder, L. Gogolla, M. Grunske et al., Using Models at Runtime to Address Assurance for Self-Adaptive Systems, pp.101-136, 2014.

T. Amorim, D. Ratasich, G. Macher, A. Ruiz, D. Schneider et al., Runtime safety assurance for adaptive cyber-physical systems: ConSerts M and ontology-based runtime reconfiguration applied to an automotive case study, Solutions for CyberPhysical Systems Ubiquity, pp.137-168, 2018.

I. Stoica, D. Song, A. Raluca, D. A. Popa, M. W. Patterson et al., A berkeley View of Systems Challenges for AI, 2017.