ADAS and Automated Driving Systems Engineering / Plato Pathrose.

Format:

Book

Author/Creator:

Pathrose, Plato, author.

Language:

English

Subjects (All):

Automated vehicles--Technological innovations.

Automated vehicles.

Technological innovations--Engineering and construction.

Technological innovations.

Automobile industry and trade.

Driver assistance systems--Technological innovations.

Driver assistance systems.

Systems engineering.

Physical Description:

1 online resource (381 pages)

Edition:

First edition.

Place of Publication:

Warrendale, PA : SAE International, [2024]

Summary:

This book provides a comprehensive overview of Advanced Driver Assistance Systems (ADAS) and automated driving, emphasizing the role of systems engineering in the automotive industry's technological evolution. It explores the lifecycle, processes, and methods essential for developing these systems, influenced by artificial intelligence and technological advancements. Authored by an industry expert, the text is designed for engineers and students seeking to gain insights into designing and implementing ADAS and automated systems. It includes real-world examples to bridge theory with practical applications, preparing readers for complex projects in automotive technology. The book also addresses the challenges and methodologies, such as Agile, used in systems engineering to manage the complexities of modern vehicle systems. Generated by AI.

Contents:

Front Cover

Title Page

Copyright Page

Dedication Page

Contents

Introduction

About This Book

Assumptions

Foreword I

Foreword II

Acknowledgments

1 Introduction to Systems Engineering

1.1 Systems Engineering: An Overview

1.2 Why Do We Need Systems Engineering?

1.3 Evolution of Systems

1.4 ADAS and Automated Driving Systems

1.5 Definition of a System and Its Hierarchy

1.6 System of Systems (SoS)

1.7 Systems Engineering Myths

1.8 Summary

References

2 Systems Engineering Life Cycle and Processes

Chapter 2: Systems Engineering Life Cycle and Processes

2.1 Systems Engineering Life Cycle

2.1.1 Concept Phase

2.1.2 Design and Development Phase

2.1.3 Production Phase

2.1.4 Operation Phase

2.1.5 Service and Maintenance Phase

2.1.6 Retirement Phase

2.1.7 Re-engineering Phase

2.2 System Life Cycle Models

2.2.1 V-Model

2.2.2 Spiral Model

2.2.3 Iterative and Agile Development Model

2.3 Systems Engineering Processes

2.4 Systems Engineering Methods

2.5 Systems Engineering Life Cycle of an Automated Driving System

2.6 Overview of Software-Defined Vehicles and Systems Engineering

2.7 Summary

3 Agile Methodologies and Systems Engineering

Chapter 3: Agile Methodologies and Systems Engineering

3.1 Introduction to Agile

3.2 Need for Agility in ADAS and Automated Driving

3.3 Agile Methodologies and Their Application

3.3.1 Scrum

3.3.2 Large-Scale Scrum (LeSS)

3.3.3 Scaled Agile Framework® (SAFe®)

3.3.4 Feature-Driven Development (FDD)

3.3.5 Test-Driven Development (TDD)

3.4 Myths about Agile

3.5 Systems Engineering and Agile

3.6 Challenges of Applying Agile in Systems Engineering

3.7 Summary

4 Concept Phase

Chapter 4: Concept Phase

4.1 Needs and Requirement Analysis.

4.1.1 Concept Generation for Highway Chauffer Function

4.1.2 McCall's Quality Model

4.1.3 Quality Function Deployment

4.1.4 Theory of Inventive Problem-Solving (TRIZ)

4.2 Concept Exploration and Feasibility Analysis

4.2.1 MOE and MOP

4.2.2 Golden Triangle of Concept Generation

4.2.3 How to Generate Concept Alternatives

4.2.4 Operational Concept (OpsCon)

4.3 Concept Definition and Finalization

4.3.1 Concept Selection

4.3.2 Mistakes in Concept Selection

4.3.3 Functional Analysis and Allocation

4.3.4 Concept Validation

4.4 Summary

5 System Concept and Modeling

Chapter 5: System Concept and Modeling

5.1 System Model

5.1.1 System Modeling and Its Advantages

5.1.2 Types of Models

5.2 System Simulation

5.2.1 System Model and Simulations

5.2.2 Operational Simulation

5.2.3 Physical Simulation

5.2.4 Environmental Simulation

5.2.5 Digital Twin and Virtual Reality-Based Simulation

5.2.6 Hybrid Simulation

5.2.7 Co-Simulation

5.2.8 General Requirements for Simulations

5.3 Modeling System Concepts: A Case Study

5.4 IDEF: Integrated DEFinition

5.5 Functional Flow Block Diagrams

5.6 Trade-Off Analysis, Evaluation, and Decision-Making

5.7 Summary

6 Predevelopment Phase and Prototyping

Chapter 6: Predevelopment Phase and Prototyping

6.1 Bridging Concept Phase and Development Phase

6.2 Predevelopment of an Automated Driving System: A Case Study

6.2.1 Preparation Phase

6.2.2 Development Phase

6.2.3 Integration Phase

6.2.4 Testing Phase

6.3 Measurements in Predevelopment and Prototyping Phase

6.4 Challenges and Drawbacks in Prototyping

6.5 Platform Development

6.6 Summary

7 System Design and Development Phase

Chapter 7: System Design and Development Phase.

Part 1: Requirement Analysis, Design, and Architecture

7.1 Overview of Design and Development Phase

7.2 Requirement Elicitation and Analysis

7.3 Functional Analysis and Design

7.4 System Definition and Component Design

7.5 System Architecture Definition

7.5.1 Physical Architecture

7.5.2 Software Architecture

7.5.3 Mechanical Architecture

7.5.4 Functional Architecture

7.5.5 Electrical and Electronic Architecture

7.5.6 Network and Communication Architecture

7.5.7 Safety Architecture

7.5.8 Security Architecture

7.6 Characteristics of a Good System Architecture

Part 2: System Integration, Verification, and Validation

7.7 System Integration

7.7.1 System Integration Strategy

7.7.2 Different Phases of Integration in Automated Driving Systems

7.8 Integration, Calibration, and Tuning of Automated Driving Systems

7.9 System Verification and Validation

7.10 Homologation of ADAS and Automated Driving Systems

7.11 Summary

8 System Production, Operation, and Maintenance Phases

Chapter 8: System Production, Operation, and Maintenance Phases

8.1 Production Phase of an Automated Driving System

8.1.1 Production Process and FMEA

8.1.2 Production Systems and Assembly

8.1.2.1 Serial Production Line

8.1.2.2 Assembly Systems

8.1.3 Production Preparation

8.1.4 Calibration of Sensors at the End-of-Line in Production

8.1.4.1 Static EoL Calibration

8.1.4.2 Dynamic EoL Calibration

8.1.5 Acceptance Testing in the Production and Shipment

8.2 Importance of Acquiring Production Knowledge

8.3 System Operation Phase

8.3.1 System Installation Approaches

8.3.2 Challenges in the System Operation Phase

8.4 System Maintenance Phase

8.4.1 Service and Maintenance of Automated Driving Systems

8.4.2 Importance of Maintenance History.

8.5 System Upgrade and Re-engineering

8.6 Summary

9 Systems Engineering for Artificial Intelligence Components

Chapter 9: Systems Engineering for Artificial Intelligence Components

9.1 Introduction to AI in Automated Driving Systems

9.1.1 An Overview of Neural Networks

9.2 Data-Driven Software Development in Automated Driving

9.3 Criteria for Using AI Software Components in a System

9.4 Requirement Definition and Design of AI Software Components

9.4.1 Detection Quality Measurements and Requirements for an Object Detection Model

9.5 Overview of Failure Analysis in Artificial Neural Networks

9.5.1 Neural Networks Fault Modeling

9.5.2 Overview of Neural Network Faults

9.5.3 Failures of Object Detection Model at the System Level

9.6 Integration, Verification, and Validation of AI Software Components

9.6.1 Verification and Validation of Functions Utilizing AI Models

9.6.2 Functional Quality and Performance Evaluation of Object Detection Algorithms

9.7 AI Software Components in the Operation Phase of a System

9.7.1 Challenges in Using Self-learning AI Models in Automotive

9.8 Summary

10 Systems Engineering Management

Chapter 10: Systems Engineering Management

10.1 Introduction to Systems Engineering Management (SEM)

10.1.1 SEM Tasks and Challenges

10.2 Systems Engineering Management Plan (SEMP)

10.2.1 Work Breakdown Structure (WBS)

10.2.2 Structure and Components of a SEMP

10.3 Risk Management in Systems Engineering

10.3.1 Risk Assessment and Analysis

10.3.2 Risk Abatement

10.4 Systems Engineering and Decision-Making Process

10.4.1 Strategies for Decision-Making

10.4.2 Case Study of Selecting a Domain Controller by Value-Focused Thinking

Step 1: Define the Objectives, Needs, and Values

Step 2: Develop Alternatives for Decision.

Step 3: Alternative Evaluation

Step 4: Value Function Analysis

Step 5: Selection of the Alternative Based on Analysis Results

10.4.3 Decision Process in Systems Engineering

Step 1: Problem Definition

Step 2: Solution Design

Step 3: Decision-Making

Step 4: Solution Implementation

10.5 Cost Estimation and Techniques

10.5.1 Cost Estimation

10.5.2 Techniques for Cost Estimation

10.5.3 Cost Breakdown Structure (CBS) in Systems Engineering

10.6 Summary

11 Methods and Tools for Problem-Solving

Chapter 11: Methods and Tools for Problem-Solving

11.1 Introduction to Processes, Methods, and Tools

11.2 Methods and Techniques for Problem-Solving

11.2.1 Eight Disciplines of Problem-Solving (8D)

D1: Create a Team

D2: Describe the Problem

D3: Implement Interim Containment Action

D4: Identify Root Cause

D5: Identify Permanent Corrective Action

D6: Implement and Validate Permanent Corrective Action

D7: Prevent Recurrence or Implement Preventive Action

D8: Close and Celebrate with the Team

11.2.2 Root Cause Analysis (RCA)

11.2.3 Five (5) Whys?

11.2.4 Fault Tree Analysis (FTA)

11.2.5 Failure Mode and Effects Analysis (FMEA)

11.2.6 3C Methodology

11.2.7 Plan-Do-Check-Act (PDCA) and Observe-Orient-Decide-Act (OODA)

11.2.8 Lean Six Sigma Methodology-DMAIC

11.2.9 Critical Thinking

11.2.10 Theory of Inventive Problem-Solving (TRIZ)

11.3 Summary

12 Systems Engineering for Next-Generation Systems

Chapter 12: Systems Engineering for Next-Generation Systems

12.1 Systems: Changes from Past to Present

12.2 Future Trends in ADAS and Automated Driving Systems

12.3 Systems Engineering in Software-Defined Vehicles (SDVs)

12.3.1 Automated Driving System as a Software-Defined System (SDS)

12.3.2 Role of Software in SDVs.

12.4 Digital Twins in Systems Engineering.

Notes:

Description based on publisher supplied metadata and other sources.

Part of the metadata in this record was created by AI, based on the text of the resource.

Description based on print version record.

ISBN:

9781468607451

1468607456

9781468607468

1468607464

OCLC:

1425513397