Abstract
Autonomous Systems (e.g., self-driving vehicles) and autonomous systems network are becoming increasingly more feasible for real-world deployment with the advent of the Internet-of-Things (IoTs) and advances in sensing and machine reasoning technologies. Autonomous vehicle networks are system-of-systems and are amenable to model-based analysis and design. This paper presents a model-based approach for analyzing and designing resilient SoS subject to a variety of disruptions. The specific SoS addressed in this paper is an autonomous (i.e., self-driving) vehicle network. The approach employs deterministic and probabilistic modeling, and use-case patterns to model SoS behavior and explore mechanisms for introducing resilience into systems and SoS. Exemplar use cases for self-driving vehicles are provided to illustrate key aspects of the overall approach.
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Acknowledgment
The authors acknowledge the inputs of CPT Kurt Klingensmith who provided exemplar use cases.
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Madni, A.M., Sievers, M.W., Humann, J., Ordoukhanian, E., D’Ambrosio, J., Sundaram, P. (2018). Model-Based Approach for Engineering Resilient System-of-Systems: Application to Autonomous Vehicle Networks. In: Madni, A., Boehm, B., Ghanem, R., Erwin, D., Wheaton, M. (eds) Disciplinary Convergence in Systems Engineering Research. Springer, Cham. https://doi.org/10.1007/978-3-319-62217-0_26
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DOI: https://doi.org/10.1007/978-3-319-62217-0_26
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