Formal Methods for Safe Autonomy: Data-driven Verification, Synthesis, and Applications

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Title: Formal Methods for Safe Autonomy: Data-driven Verification, Synthesis, and Applications
Description: There are significant financial and legal implications for ensuring design correctness and safety in autonomous systems. This book introduces new verification and synthesis algorithms to provide certifiable trusts for real-world autonomous systems. On the theoretical front, the techniques are armed with soundness, precision, and relative completeness guarantees. On the experimental side, this book shows that techniques can be successfully applied on a sequence of real-world problems, including a suite of Toyota engine control modules verified for the first time, satellite control systems, and autonomous driving and ADAS-based maneuvers. Insights throughout the book provide a level of assurance that can be provided by formal methods for today's autonomous systems. Verification and synthesis for typical models of real-world autonomous systems are challenging due to their high dimensionality, nonlinearities, and nondeterministic and hybrid nature. In addressing these challenges, several chapters present data-driven algorithmic verification via reachability analysis of complex hybrid systems as well as controller synthesis for dynamic systems under disturbance. The book includes the first algorithm for over-approximating reach sets of general nonlinear models with locally optimal tightness guarantees as well as algorithms to find correct-by-construction controllers for nonlinear dynamical systems. It is written for researchers in the corporate world, academia, government, and practitioners in autonomous systems.
Authors: Chuchu Fan
Resource Type: eBook.
Subjects: Computational intelligence, Formal methods (Computer science), Control theory
Categories: COMPUTERS / Data Science / Machine Learning, COMPUTERS / Artificial Intelligence / General, TECHNOLOGY & ENGINEERING / Automotive
Database: eBook Collection (EBSCOhost)
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  Availability: 0
Header DbId: nlebk
DbLabel: eBook Collection (EBSCOhost)
An: 4043709
RelevancyScore: 1123
AccessLevel: 6
PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 1122.83581542969
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  Data: Formal Methods for Safe Autonomy: Data-driven Verification, Synthesis, and Applications
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  Data: There are significant financial and legal implications for ensuring design correctness and safety in autonomous systems. This book introduces new verification and synthesis algorithms to provide certifiable trusts for real-world autonomous systems. On the theoretical front, the techniques are armed with soundness, precision, and relative completeness guarantees. On the experimental side, this book shows that techniques can be successfully applied on a sequence of real-world problems, including a suite of Toyota engine control modules verified for the first time, satellite control systems, and autonomous driving and ADAS-based maneuvers. Insights throughout the book provide a level of assurance that can be provided by formal methods for today's autonomous systems. Verification and synthesis for typical models of real-world autonomous systems are challenging due to their high dimensionality, nonlinearities, and nondeterministic and hybrid nature. In addressing these challenges, several chapters present data-driven algorithmic verification via reachability analysis of complex hybrid systems as well as controller synthesis for dynamic systems under disturbance. The book includes the first algorithm for over-approximating reach sets of general nonlinear models with locally optimal tightness guarantees as well as algorithms to find correct-by-construction controllers for nonlinear dynamical systems. It is written for researchers in the corporate world, academia, government, and practitioners in autonomous systems.
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RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Computational intelligence
        Type: general
      – SubjectFull: Formal methods (Computer science)
        Type: general
      – SubjectFull: Control theory
        Type: general
    Titles:
      – TitleFull: Formal Methods for Safe Autonomy: Data-driven Verification, Synthesis, and Applications
        Type: main
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          Name:
            NameFull: Chuchu Fan
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            NameFull: Chuchu Fan
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2024
            – D: 12
              M: 12
              Type: profile
              Y: 2025
          Identifiers:
            – Type: isbn-print
              Value: 9798400708633
            – Type: isbn-electronic
              Value: 9798400708640
            – Type: isbn-electronic
              Value: 9798400708664
          Titles:
            – TitleFull: Formal Methods for Safe Autonomy: Data-driven Verification, Synthesis, and Applications
              Type: main
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