Effectiveness assessment of Cyber-Physical Systems

Autor: Nhan Le Thanh, Gérald Rocher, Jean-Yves Tigli, Stéphane Lavirotte
Přispěvatelé: Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Equipe RAINBOW, Scalable and Pervasive softwARe and Knowledge Systems (Laboratoire I3S - SPARKS), Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), Web-Instrumented Man-Machine Interactions, Communities and Semantics (WIMMICS), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Scalable and Pervasive softwARe and Knowledge Systems (Laboratoire I3S - SPARKS), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS)
Rok vydání: 2020
Předmět:
FOS: Computer and information sciences
Computer Science - Artificial Intelligence
Computer science
Input/Output Hidden Markov Model
Physical system
Context (language use)
[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]
02 engineering and technology
Transferable belief model
Theoretical Computer Science
[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing
Cyber Physical Systems
Transferable Belief Model
Artificial Intelligence
Control theory
020204 information systems
0202 electrical engineering
electronic engineering
information engineering
Dependability
Hidden Markov model
Applied Mathematics
Cyber-physical system
Industrial engineering
Artificial Intelligence (cs.AI)
Degree of Effectiveness
Zone of Viability
020201 artificial intelligence & image processing
Forward algorithm
Software
Zdroj: International Journal of Approximate Reasoning
International Journal of Approximate Reasoning, Elsevier, 2020, 118, pp.112-132. ⟨10.1016/j.ijar.2019.12.002⟩
International Journal of Approximate Reasoning, 2020, 118, pp.112-132. ⟨10.1016/j.ijar.2019.12.002⟩
ISSN: 0888-613X
DOI: 10.1016/j.ijar.2019.12.002
Popis: By achieving their purposes through interactions with the physical world, Cyber-Physical Systems (CPS) pose new challenges in terms of dependability. Indeed, the evolution of the physical systems they control with transducers can be affected by surrounding physical processes over which they have no control and which may potentially hamper the achievement of their purposes. While it is illusory to hope for a comprehensive model of the physical environment at design time to anticipate and remove faults that may occur once these systems are deployed, it becomes necessary to evaluate their degree of effectiveness in vivo. In this paper, the degree of effectiveness is formally defined and generalized in the context of the measure theory. The measure is developed in the context of the Transferable Belief Model (TBM), an elaboration on the Dempster-Shafer Theory (DST) of evidence so as to handle epistemic and aleatory uncertainties respectively pertaining the users' expectations and the natural variability of the physical environment. The TBM is used in conjunction with the Input/Output Hidden Markov Modeling framework (we denote by Ev-IOHMM) to specify the expected evolution of the physical system controlled by the CPS and the tolerances towards uncertainties. The measure of effectiveness is then obtained from the forward algorithm, leveraging the conflict entailed by the successive combinations of the beliefs obtained from observations of the physical system and the beliefs corresponding to its expected evolution. The proposed approach is applied to autonomous vehicles and show how the degree of effectiveness can be used for bench-marking their controller relative to the highway code speed limitations and passengers' well-being constraints, both modeled through an Ev-IOHMM.
Comment: Preprint submitted to International Journal of Approximate Reasoning
Databáze: OpenAIRE
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