Screen LibrarySafe, autonomous and intelligent vehicles /
This book covers the start-of-the-art research and development for the emerging area of autonomous and intelligent systems. In particular, the authors emphasize design and validation methodologies to address the grand challenges related to safety. This book offers a holistic view of a broad range of...
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| Group Author: | ; ; ; ; |
|---|---|
| Published: |
Springer,
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| Publisher Address: | Cham, Switzerland : |
| Publication Dates: | [2019] |
| Literature type: | Book |
| Language: | English |
| Series: |
Unmanned System Technologies,
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| Subjects: | |
| Summary: |
This book covers the start-of-the-art research and development for the emerging area of autonomous and intelligent systems. In particular, the authors emphasize design and validation methodologies to address the grand challenges related to safety. This book offers a holistic view of a broad range of technical aspects (including perception, localization and navigation, motion control, etc.) and application domains (including automobile, aerospace, etc.), presents major challenges and discusses possible solutions. Provides a single-source guide to the practical challenges in designing autonomo |
| Item Description: | 6.5.3 Realizability of LK Contract. |
| Carrier Form: | xiii, 204 pages : illustrations (some color), color maps ; 25 cm. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: |
9783319973005 3319973002 9783319973029 3319973029 |
| Index Number: | TL152 |
| CLC: | U471.1 |
| Call Number: | U471.1/S128 |
| Contents: |
Intro; Preface; Contents; About the Editors; 1 Introduction; 2 Efficient Statistical Validation of Autonomous Driving Systems; 2.1 Introduction; 2.2 Background; 2.2.1 Image Sensing; 2.2.2 Image Processing; 2.2.3 Visual Perception; 2.3 Test Data Generation; 2.3.1 Temperature Variation; 2.3.2 Circuit Aging; 2.3.3 Corner Case Generation; 2.3.4 Numerical Experiments; 2.3.4.1 Experimental Setup; 2.3.4.2 Temperature Variation; 2.3.4.3 Circuit Aging; 2.4 Subset Simulation; 2.4.1 Mathematical Formulation; 2.4.2 Random Sampling; 2.4.3 Summary; 2.4.4 Numerical Experiments; 2.4.4.1 Experimental Setup. 2.4.4.2 Experimental Results2.5 Conclusions; References; 3 Cyberattack-Resilient Hybrid Controller Design with Application to UAS; 3.1 Introduction; 3.2 Problem Formulation; 3.2.1 System and Cyberattack Models; 3.2.2 Cyberattack Mitigation Problem; 3.3 Hybrid Controller Design; 3.4 Analytical Performance Verification; 3.5 Extension to Infinite Time Horizon: Receding Horizon Controller; 3.6 Illustrative Example; 3.6.1 H2 Optimal Controller; 3.6.2 H∞ Optimal Controller; 3.6.3 UAS Model; 3.6.4 Simulation Results; 3.7 Conclusions; References 4 Control and Safety of Autonomous Vehicles with Learning-Enabled Components4.1 Hamilton-Jacobi Reachability; 4.1.1 Backward Reachable Set (BRS); 4.1.2 Application: Provably Safe Multi-Vehicle Trajectory Planning; 4.1.3 Limitations of HJ Reachability; 4.2 Learning-Based Model Refinement; 4.2.1 Function Approximator-Based Model Learning; 4.2.2 Goal-Driven Model Learning; 4.3 Safety Analysis of Learned Models; 4.3.1 Safety During Model Learning; 4.3.2 Model Validation Before Deployment; 4.4 Learning in Partially Observable environments; References. 5 Adaptive Stress Testing of Safety-Critical Systems5.1 Introduction; 5.2 Related Work; 5.3 Background; 5.3.1 Definitions; 5.3.2 Sequential Decision Process; 5.3.3 Monte Carlo Tree Search; 5.4 Adaptive Stress Testing; 5.4.1 Full Observability; 5.4.2 Partial Observability; 5.5 Aircraft Collision Avoidance Application; 5.5.1 Experimental Setup; 5.5.2 Results; 5.5.3 Performance Comparison; 5.6 Conclusion; References; 6 Provably-Correct Compositional Synthesis of VehicleSafety Systems; 6.1 Introduction; 6.2 Autonomous Driving Functions; 6.2.1 Adaptive Cruise Control; 6.2.2 Lane Keeping. 6.2.3 Challenges in Composition6.3 Composition of Invariant Sets Via Contracts; 6.3.1 Contract Realizability Problem; 6.3.2 Contract Refinement Heuristic; 6.4 Contract Realizability Via Polyhedral Controlled-Invariant Sets; 6.4.1 Computation of Polyhedral Controlled-Invariant Sets; 6.4.2 Over-Approximation of Nonlinear Parametrizations; 6.4.3 Removal of Nonlinearities via Convexification; 6.4.3.1 Convex-Hull Computation With Monotone Functions; 6.4.3.2 Convex-Hull Computation With Convex Projections; 6.5 Design Flow for the Case Study; 6.5.1 Constraints; 6.5.2 Contracts. |