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· 제목 : ADAS and Automated Driving - Systems Engineering (Paperback) 
· 분류 : 외국도서 > 컴퓨터 > 소프트웨어 개발/엔지니어링 > 시스템 분석/설계
· ISBN : 9781468607444
· 쪽수 : 357쪽
· 출판일 : 2024-03-01
· 분류 : 외국도서 > 컴퓨터 > 소프트웨어 개발/엔지니어링 > 시스템 분석/설계
· ISBN : 9781468607444
· 쪽수 : 357쪽
· 출판일 : 2024-03-01
목차
- "viivii© 2024 SAE International
- Introduction xiv
- About This Book xv
- Assumptions xvi
- Foreword I xvii
- Foreword II xix
- Acknowledgments xxi
C H A P T E R 1: Introduction to Systems Engineering 11 - 1.Systems Engineering: An Overview 21
- 2. Why Do We Need Systems Engineering? 41
- 3. Evolution of Systems 61
- 4. ADAS and Automated Driving Systems 81
- 5. Definition of a System and Its Hierarchy 101
- 6. System of Systems (SoS) 131
- 7. Systems Engineering Myths 161
- 8. Summary 19
- References 20
C H A P T E R 2 - Systems Engineering Life Cycle and Processes 232
- 1. Systems Engineering Life Cycle 232
- 1.1. Concept Phase 252
- 1.2. Design and Development Phase 252
- 1.3. Production Phase 262
- 1.4. Operation Phase 262
- 1.5. Service and Maintenance Phase 272
- 1.6. Retirement Phase 272
- 1.7. Re-engineering Phase 27
- Contents
- Contentsviii
- 2.2. System Life Cycle Models 282
- 2.1. V-Model 282
- 2.2. Spiral Model 292
- 2.3. Iterative and Agile Development Model 312
- 3. Systems Engineering Processes 342
- 4. Systems Engineering Methods 382
- 5. Systems Engineering Life Cycle of an Automated Driving System 402
- 6. Overview of Software-Defined Vehicles and Systems Engineering 422
- 7. Summary 45
- References 46
C H A P T E R 3 - Agile Methodologies and Systems Engineering 493
- 1. Introduction to Agile 503
- 2. Need for Agility in ADAS and Automated Driving 513
- 3. Agile Methodologies and Their Application 543
- 3.1. Scrum 553
- 3.2. Large-Scale Scrum (LeSS) 553
- 3.3. Scaled Agile Framework® (SAFe®) 563
- 3.4. Feature-Driven Development (FDD) 573
- 3.5. Test-Driven Development (TDD) 593
- 4. Myths about Agile 613
- 5. Systems Engineering and Agile 633
- 6. Challenges of Applying Agile in Systems Engineering 683
- 7. Summary 70
- References 71
C H A P T E R 4 - Concept Phase 734
- 1. Needs and Requirement Analysis 744
- 1.1. Concept Generation for Highway Chauffer Function 784
- 1.2. McCall's Quality Model 80Contents ix4
- 1.3. Quality Function Deployment 824
- 1.4. Theory of Inventive Problem-Solving (TRIZ) 844
- 2. Concept Exploration and Feasibility Analysis 864
- 2.1. MOE and MOP 864
- 2.2. Golden Triangle of Concept Generation 874
- 2.3. How to Generate Concept Alternatives 904
- 2.4. Operational Concept (OpsCon) 944
- 3. Concept Definition and Finalization 964
- 3.1. Concept Selection 964
- 3.2. Mistakes in Concept Selection 984
- 3.3. Functional Analysis and Allocation 994
- 3.4. Concept Validation 1014
- 4. Summary 103
- References 103
C H A P T E R 5 - System Concept and Modeling 1075
- 1. System Model 1085
- 1.1. System Modeling and Its Advantages 1085
- 1.2. Types of Models 1095
- 2. System Simulation 1115
- 2.1. System Model and Simulations 1115
- 2.2. Operational Simulation 1125
- 2.3. Physical Simulation 1135
- 2.4. Environmental Simulation 1135
- 2.5. Digital Twin and Virtual Reality-Based Simulation 1145
- 2.6. Hybrid Simulation 1145
- 2.7. Co-Simulation 1155
- 2.8. General Requirements for Simulations 1165
- 3. Modeling System Concepts: A Case Study 1185
- 4. IDEF: Integrated DEFinition 1245
- 5. Functional Flow Block Diagrams 1265
- 6. Trade-Off Analysis, Evaluation, and Decision-Making 1265
- 7. Summary 131
- References 132
- Contentsx
C H A P T E R 6 - Predevelopment Phase and Prototyping 1356
- 1. Bridging Concept Phase and Development Phase 1366
- 2. Predevelopment of an Automated Driving System: A Case Study 1416
- 2.1. Preparation Phase 1416
- 2.2. Development Phase 1426
- 2.3. Integration Phase 1446
- 2.4. Testing Phase 1446
- 3. Measurements in Predevelopment and Prototyping Phase 1476
- 4. Challenges and Drawbacks in Prototyping 1506
- 5. Platform Development 1516
- 6. Summary 153
- References 154
C H A P T E R 7 - System Design and Development Phase 157
- Part 1: Requirement Analysis, Design, and Architecture 1587
- 1. Overview of Design and Development Phase 1587
- 2. Requirement Elicitation and Analysis 1597
- 3. Functional Analysis and Design 1627
- 4. System Definition and Component Design 1687
- 5. System Architecture Definition 1727
- 6. Characteristics of a Good System Architecture 176
- Part 2: System Integration, Verification, and Validation 1777
- 7. System Integration 1777
- 8. Integration, Calibration, and Tuning of Automated Driving Systems 1837
- 9. System Verification and Validation 1877
- 10. Homologation of ADAS and Automated Driving Systems 1917
- 11. Summary 194
- References 195
- Contents xi
C H A P T E R 8 - System Production, Operation, and Maintenance Phases 1998
- 1. Production Phase of an Automated Driving System 2008
- 1.1. Production Process and FMEA 2028
- 1.2. Production Systems and Assembly 2048
- 1.3. Production Preparation 2078
- 1.4. Calibration of Sensors at the End-of-Line in Production 2098
- 1.5. Acceptance Testing in the Production and Shipment 2158
- 2. Importance of Acquiring Production Knowledge 2168
- 3. System Operation Phase 2178
- 3.1. System Installation Approaches 2188
- 3.2. Challenges in the System Operation Phase 2198
- 4. System Maintenance Phase 2228
- 4.1. Service and Maintenance of Automated Driving Systems 2248
- 4.2. Importance of Maintenance History 2268
- 5. System Upgrade and Re-engineering 2268
- 6. Summary 228
- References 228
C H A P T E R 9 - Systems Engineering for Artificial Intelligence Components 2319
- 1. Introduction to AI in Automated Driving Systems 2329
- 1.1. An Overview of Neural Networks 2349.
- 2. Data-Driven Software Development in Automated Driving 2369
- 3. Criteria for Using AI Software Components in a System 2389
- 4. Requirement Definition and Design of AI Software Components 2409
- 4.1. Detection Quality Measurements and Requirements for an Object Detection Model 2419
- 5. Overview of Failure Analysis in Artificial Neural Networks 2449
- 5.1. Neural Networks Fault Modeling 244
- 5.2. Overview of Neural Network Faults 2469
- 5.3. Failures of Object Detection Model at the System Level 248
- Contentsxii
- 9.6. Integration, Verification, and Validation of AI Software Components 2489
- 6.1. Verification and Validation of Functions Utilizing AI Models 2529
- 6.2. Functional Quality and Performance Evaluation of Object Detection Algorithms 2559
- 7. AI Software Components in the Operation Phase of a System 2579
- 7.1. Challenges in Using Self-learning AI Models in Automotive 2589
- 8. Summary 259
- References 260
C H A P T E R 1 0 - Systems Engineering Management 26310
- 1. Introduction to Systems Engineering Management (SEM) 26410
- 1.1. SEM Tasks and Challenges 26510
- 2. Systems Engineering Management Plan (SEMP) 26610
- 2.1. Work Breakdown Structure (WBS) 26610
- 2.2. Structure and Components of a SEMP 26810
- 3. Risk Management in Systems Engineering 27110
- 3.1. Risk Assessment and Analysis 27310
- 3.2. Risk Abatement 27510
- 4. Systems Engineering and Decision-Making Process 27710
- 4.1. Strategies for Decision-Making 27810
- 4.2. Case Study of Selecting a Domain Controllerby Value-Focused Thinking 28010
- 4.3. Decision Process in Systems Engineering 28310
- 5. Cost Estimation and Techniques 28610
- 5.1. Cost Estimation 28610
- 5.2. Techniques for Cost Estimation 28810
- 5.3. Cost Breakdown Structure (CBS) in Systems Engineering 28910
- 6. Summary 290
- References 292
- Contents xiii
C H A P T E R 1 1 - Methods and Tools for Problem-Solving 29511
- 1. Introduction to Processes, Methods, and Tools 29611
- 2. Methods and Techniques for Problem-Solving 29711
- 2.1. Eight Disciplines of Problem-Solving (8D) 29711
- 2.2. Root Cause Analysis (RCA) 30311
- 2.3. Five (5) Whys? 30511
- 2.4. Fault Tree Analysis (FTA) 30811
- 2.5. Failure Mode and Effects Analysis (FMEA) 31011
- 2.6. 3C Methodology 31611
- 2.7. Plan–Do–Check–Act (PDCA) and Observe–Orient–Decide–Act (OODA) 31711
- 2.8. Lean Six Sigma Methodology—DMAIC 32011
- 2.9. Critical Thinking 32111
- 2.10. Theory of Inventive Problem-Solving (TRIZ) 32311
- 3. Summary 326
- References 326
C H A P T E R 1 2 - Systems Engineering for Next-Generation Systems 32912
- 1. Systems: Changes from Past to Present 33012
- 2. Future Trends in ADAS and Automated Driving Systems 33312
- 3. Systems Engineering in Software-Defined Vehicles (SDVs) 33712
- 3.1. Automated Driving System as a Software-Defined System(SDS) 33912
- 3.2. Role of Software in SDVs 34012
- 4. Digital Twins in Systems Engineering 34512
- 5. Skills for the Future 34812
- 6. Summary 349
- References 350
- Index 351
- About the Author 357
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