Simulation-Based Approaches for Verification of Embedded Control Systems: An Overview of Traditional and Advanced Modeling, Testing, and Verification Techniques

doi:10.1109/mcs.2016.2602089

Cited by 98 publications

(11 citation statements)

References 49 publications

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“…These formulas are using negation, Boolean combinations, or temporal operators to define the requirements with a standard logical notation. 32…”

Section: Control System Design and Methodsmentioning

confidence: 99%

“…These formulas are using negation, Boolean combinations, or temporal operators to define the requirements with a standard logical notation. 32 LTL is different from STL in the way that there is assumed a relationship between the sensor and the system behavior. That means that for a given input, certain actuator output is expected.…”

Section: Control Approaches and Algorithmsmentioning

confidence: 99%

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Risk-informed control systems for improved operational performance and decision-making

Thieme

Rokseth

Utne

2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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Autonomous systems, including airborne, land-based, marine, and underwater vehicles, are increasingly present in the world. One important aspect of autonomy is the capability to process information and to make independent decisions for achieving a mission goal. Information on the level of risk related to the operation may improve the decision-making process of autonomous systems. This article describes the integration of risk analysis methods with the control system of autonomous and highly automated systems that are evaluated during operation. Four main areas of implementation are identified; (i) risk models used to directly make decisions, (ii) use of the output of risk models as input to decision-making and optimization algorithms, (iii) the output of risk models may be used as a constraint in or modifying constraints of algorithms, and (iv) the output of risk models may be used to inform representations or maps of the environment to be used in path planning. A case study on a dynamic positioning controller of an offshore supply vessel exemplifies the concepts described in this article. In addition, it demonstrates how risk model output may be used within a hybrid controller.

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“…These formulas are using negation, Boolean combinations, or temporal operators to define the requirements with a standard logical notation. 32…”

Section: Control System Design and Methodsmentioning

confidence: 99%

Section: Control Approaches and Algorithmsmentioning

confidence: 99%

Risk-informed control systems for improved operational performance and decision-making

Thieme

Rokseth

Utne

2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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“…Rouder noticed that the calibration hypothesis should hold as a mathematical theorem, without giving an explicit proof; he demonstrated it by computer simulation in a simple parametric setting. Deng et al (2016) gave a proof for a somewhat more extended setting yet still with proper priors. In Section 4.2 we show that a version of the calibration hypothesis continues to hold for general measures based on improper priors, and in Section 5.4 we extend this further to strong calibration for group invariance settings as discussed below.…”

Section: Second Sense Of Handling Optional Stopping: Calibrationmentioning

confidence: 99%

Optional Stopping with Bayes Factors: A Categorization and Extension of Folklore Results, with an Application to Invariant Situations

2021

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It is often claimed that Bayesian methods, in particular Bayes factor methods for hypothesis testing, can deal with optional stopping. We first give an overview, using elementary probability theory, of three different mathematical meanings that various authors give to this claim: (1) stopping rule independence, (2) posterior calibration and (3) (semi-) frequentist robustness to optional stopping. We then prove theorems to the effect that these claims do indeed hold in a general measure-theoretic setting. For claims of type ( 2) and ( 3), such results are new. By allowing for non-integrable measures based on improper priors, we obtain particularly strong results for the practically important case of models with nuisance parameters satisfying a group invariance (such as location or scale). We also discuss the practical relevance of ( 1)-( 3), and conclude that whether Bayes factor methods actually perform well under optional stopping crucially depends on details of models, priors and the goal of the analysis.

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“…The complex interactions between various components, the unpredictability of human-machine interfaces, and the diversity of environmental conditions all contribute to this complexity. To mitigate these difficulties, simulation-driven validation has emerged as a formidable tool, providing a risk-free environment for the comprehensive evaluation of LECs across a spectrum of scenarios (Kapinski et al 2016). This methodology allows for in-depth analysis of autonomous systems' behavior, facilitating the identification of potential safety violations, and offering an avenue for developing proactive countermeasures.…”

Section: Introductionmentioning

confidence: 99%

Exploring the role of simulator fidelity in the safety validation of learning‐enabled autonomous systems

Baheri

2023

AI Magazine

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This article presents key insights from the New Faculty Highlights talk given at AAAI 2023, focusing on the crucial role of fidelity simulators in the safety evaluation of learning‐enabled components (LECs) within safety‐critical systems. With the rising integration of LECs in safety‐critical systems, the imperative for rigorous safety and reliability verification has intensified. Safety assurance goes beyond mere compliance, forming a foundational element in the deployment of LECs to reduce risks and ensure robust operation. In this evolving field, simulations have become an indispensable tool, and fidelity's role as a critical parameter is increasingly recognized. By employing multifidelity simulations that balance the needs for accuracy and computational efficiency, new paths toward comprehensive safety validation are emerging. This article delves into our recent research, emphasizing the role of simulation fidelity in the validation of LECs in safety‐critical systems.

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Simulation-Based Approaches for Verification of Embedded Control Systems: An Overview of Traditional and Advanced Modeling, Testing, and Verification Techniques

Abstract: Hardware Platform + Plant figure 1 The model-based development design V. This process is used to develop reliable embedded control systems.

Cited by 98 publications

References 49 publications

Risk-informed control systems for improved operational performance and decision-making

Risk-informed control systems for improved operational performance and decision-making

Optional Stopping with Bayes Factors: A Categorization and Extension of Folklore Results, with an Application to Invariant Situations

Exploring the role of simulator fidelity in the safety validation of learning‐enabled autonomous systems

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