11026nam 2200529 450 99649556030331620230315144919.0981-19-5053-9(MiAaPQ)EBC7127058(Au-PeEL)EBL7127058(CKB)25208276000041(PPN)265862728(EXLCZ)992520827600004120230315d2022 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierAdvanced driver assistance systems and autonomous vehicles from fundamentals to applications /Yan Li and Hualiang Shi, editorsSingapore :Springer,[2022]©20221 online resource (628 pages)Print version: Li, Yan Advanced Driver Assistance Systems and Autonomous Vehicles Singapore : Springer,c2022 9789811950520 Includes bibliographical references.Intro -- Contents -- Introduction -- 1 Reshape the Future of Transportation -- 2 Challenges -- 2.1 New Technologies -- 2.2 Requalification of Non-Auto-Grade Components -- 2.3 New Mission Profiles for Existing Auto-Grade Components -- 3 Overview of Chapters -- 4 Summary -- References -- Basics and Applications of AI in ADAS and Autonomous Vehicles -- 1 Introduction -- 1.1 Advanced Driver-Assistance Systems (ADASs) -- 1.2 Autonomous Vehicles (AVs) and Automation Levels -- 1.3 Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) -- 2 Applications of AI in ADAS -- 2.1 Supervised Learning -- 2.2 Unsupervised Learning -- 2.3 Reinforcement Learning -- 2.4 Deep Learning (DL) -- 3 Safety in ADAS and AV Based on AI -- 3.1 Safety Standards and Methodologies -- 3.2 AI Safety Challenges: Edge Cases and Heavy Tail Distribution -- 3.3 Safety in AI System Design, Validation, Testing and Implementation -- 4 Datasets, Simulators, and Infrastructures for AI Systems -- 4.1 Publicly Available Training and Testing Datasets -- 4.2 Open-source Simulators -- 4.3 Infrastructures for AI Systems -- 5 Summary -- References -- Computing Technology in Autonomous Vehicle -- 1 Introduction -- 2 Compute and ADAS Technology -- 2.1 Levels of Autonomous Driving -- 2.2 Platform for Autonomous Driving System -- 2.3 Perception and Localization -- 2.4 Prediction, Planning, and Control -- 2.5 Functional Safety -- 3 Advanced Computer System -- 3.1 Architecture Solution and Comparisons -- 3.2 Environment Perception Sensors -- 3.3 System on Chip (SoC) -- 3.4 Memory -- 3.5 Storage -- 3.6 Network -- 3.7 Real-Time Operating System -- 3.8 Management, Failure Detection, and Diagnostics -- 3.9 Security and Middleware -- 4 Electrical Functional and Reliability Validation -- 4.1 Automotive Level EE Functional Tests.4.2 Reliability Validation Tests Based on AV Mission Profiles -- 4.3 EMC/ESD Validation -- 5 Challenges to Safe Deployment at Scale -- 5.1 Artificial Intelligence: Perception and Prediction -- 5.2 Power Consumption -- 5.3 Thermal Management -- 5.4 Manufacturing, Assembly, and Quality Control -- 5.5 Size and Cost -- 5.6 Quality and Reliability -- 5.7 Security and Safety -- 6 Summary -- References -- Overview of Packaging Technologies and Cooling Solutions in ADAS Market -- 1 Introduction -- 1.1 Market Opportunity and Trends -- 1.2 Road to Autonomy: ADAS Architecture -- 2 Package Technology and AD Requirements -- 2.1 Role of Advantage Packaging Technology in AD Market -- 2.2 Smaller System Level Footprints -- 3 Thermal Management -- 3.1 ECU Thermal Fundamentals -- 3.2 Component Level Fundamentals -- 3.3 Vehicle Operating Environment -- 3.4 ADAS ECU Thermal Management -- 4 ADAS Product Reliability Requirements -- 4.1 Qualification Requirements -- 4.2 ADAS Performance Requirements and Implications-ADAS Mission Profile -- 4.3 Failure Regimes-Quality and Wear-Out Failures -- 4.4 Package Reliability Challenges -- 5 Summary -- References -- Flash Memory and NAND -- 1 NAND Flash-The Perfect Storage Medium -- 1.1 What is NAND Flash -- 1.2 NOR Versus NAND -- 1.3 Evolution of NAND Flash -- 2 NAND Fundamentals -- 2.1 NAND Arrays in 2D and 3D -- 2.2 Basic NAND Operations -- 2.3 Multi-Bit-Per-Cell Technologies -- 2.4 Anatomy of a NAND Product -- 2.5 3D NAND Technology Basics -- 3 3D NAND Technology and Design Challenges -- 3.1 Cost-Performance-Reliability Tradeoffs -- 3.2 3D NAND Technology Challenges -- 3.3 3D NAND Design Challenges -- 4 NAND Reliability Issues -- 4.1 Write Errors -- 4.2 Disturb Errors -- 4.3 Data Retention Errors -- 5 3D NAND Future Outlook -- References -- Interconnect -- 1 Interconnects for Applications Under the Hood.1.1 Nanoparticle Sintering Method -- 1.2 Transient Liquid Phase Bonding Technology -- 1.3 Electrochemical Migration Phenomenon -- 2 Solder Joint Technology for Applications Under the Hood -- 2.1 Low Melting Point Solders -- 2.2 Low-Temperature Assembly -- 3 Introduction for Low-Temperature Cu to Cu Direct Bonding -- 3.1 Cu-Cu Bonding by Surface-Activated Bonding Process -- 3.2 Cu-Cu Bonding by Chemical Pretreatment -- 3.3 Cu-Cu Bonding by Thermal Compressive Bonding -- 3.4 Low-Temperature Cu-Cu Bonding by (111) Nanotwinned Structure -- 3.5 Low-Temperature Cu to Cu Bonding with Ag Passivation Under Atmosphere -- 3.6 Hybrid Bonding -- References -- Cameras in Advanced Driver-Assistance Systems and Autonomous Driving Vehicles -- 1 Introduction -- 2 Camera System Overview -- 3 Camera System Hardware -- 3.1 Image Sensor -- 3.2 Optics -- 3.3 Electronics -- 3.4 Image Signal Processor (ISP) -- 4 Image Processing -- 4.1 Image Processing Pipeline -- 4.2 Calibration -- 4.3 ISP Tuning -- 5 Camera Product Development -- 5.1 Product Definition -- 5.2 Camera Design -- 5.3 Prototype -- 5.4 Validation -- 5.5 Manufacturing -- 5.6 Implementation -- 5.7 Support -- 6 Summary -- References -- Lidar Technology -- 1 Introduction -- 2 Overview of Current Lidar Technology for Automotive Application -- 3 Important Performance Metrics for Lidar -- 3.1 Range -- 3.2 Field of View -- 3.3 Angular Resolution/Accuracy -- 3.4 Frame Rate -- 3.5 Eye Safety -- 4 Transmitter and Receiver -- 5 Distance Calculation -- 5.1 Range of Time of Flight -- 5.2 Signal-To-Noise Ratio -- 5.3 Factors that Affect Range Detection -- 6 Future Direction of Lidar Developments -- 6.1 Frequency-Modulated Continuous Wave (FMCW) -- 7 Mapping Methods -- 7.1 Mechanical Spinning Scanner -- 7.2 Opto-Mechanical Scanning -- 7.3 MEMS Scanning -- 7.4 Flash -- 7.5 Optical Phased Array (OPA) -- 8 Discussion -- References.Radar Technology -- 1 Introduction -- 2 Radar Physical Design -- 2.1 Radar Architecture -- 2.2 Radar Categories -- 3 Waveform Design -- 3.1 Pulse Radar -- 3.2 Pulse Coded Radar -- 3.3 FMCW Radar -- 4 Link Budget Analysis for FMCW Radar -- 4.1 Radar Equation -- 4.2 Target Reflectivity -- 4.3 Processing Gain -- 5 Challenges and Solutions for Automotive Radars -- 5.1 Interference -- 5.2 Under- and Overclustering -- 5.3 Classification -- 5.4 Lack of Resolution -- 5.5 Data Fusion -- 5.6 Radar Integration -- 6 Summary -- References -- Electrochemical Power Systems for Advanced Driver-Assistant Vehicles -- 1 Introduction -- 2 Batteries -- 2.1 Introduction -- 2.2 Types of Battery Cells -- 2.3 Battery Cell Internal Structure -- 2.4 Battery Cell Manufacturing Process -- 2.5 Chemistry Choices for Li-Ion Battery for EV Applications -- 2.6 Next-Generation Li-Ion Battery for EV Applications -- 2.7 Battery Management System -- 2.8 Battery Testing Methods and Industrial Standards -- 2.9 Battery Failure Mode and Effects Analysis (FMEA) -- 3 Fuel Cells -- 3.1 Major Types of Fuel Cells -- 3.2 Fuel Cells for EV Application -- 4 Capacitors -- 5 Summary -- References -- In-Vehicle Display Technology -- 1 Introduction -- 2 In-Vehicle Display Technologies and Architectures -- 2.1 LCD -- 2.2 TFT LCD -- 2.3 OLED -- 2.4 LED, Mini-/Micro-LED -- 2.5 Head-Up Display -- 2.6 Flexible and Free-Form -- 2.7 Touch Technology -- 3 In-Vehicle Display Requirements -- 3.1 Optical Performance Requirement -- 3.2 Appearance -- 3.3 Integration and Fabrication -- 3.4 Color Measurement and Characterization -- 3.5 Mura, Defect, Inspection, and Demura -- 3.6 Visibility in Bright Light and Complete Darkness -- 3.7 Improvement of Image and Touch Quality -- 3.8 Reliability and Durability -- 3.9 Functional Safety -- 4 In-Vehicle Display Challenges -- 4.1 Specification and Functionality Challenges.4.2 Quality, Reliability, and Validation Challenges -- 4.3 EMC/EMI Challenges -- 4.4 ESD and High-Transient Voltage Challenges -- 5 Common LED LCD Reliability Testing Failure Modes and Effects Case Studies -- 5.1 FOS Spotlighting Failure Mechanism and Risk Assessment -- 5.2 BLU Film Buckling/Waving/Wrinkle Failure Mechanism Study -- 5.3 Metal Oxide TFT Panel-Level VGH and VGL Reliability Modeling -- 5.4 LCD Panel UV Irradiation Aging Reliability Modeling -- 5.5 Polarizer Edge Bleaching Failure Mechanism and Reliability Modeling -- 5.6 Free-Fall Object Impact Test and LCD Glass Crack Failure Risk Assessment -- 5.7 LED Lumen Degradation Reliability Modeling -- 6 Summary -- References -- Disk Drive for Data Center Storage -- 1 Introduction -- 2 Hard Disk Drive Application in Data Center -- 2.1 Data Storage for Autonomous Vehicle -- 2.2 Data Storage Configurations in Data Center -- 2.3 Hard Disk Drive Versus Solid-State Drive in Data Center -- 3 Hard Disk Drive Design -- 3.1 Hard Disk Drive System -- 3.2 Components in Recording Head -- 3.3 Next Generation Hard Disk Drive -- 4 Challenges in the Performance and Reliability -- 4.1 The Need for Higher Areal Data Density -- 4.2 Microwave-Assisted Magnetic Recording (MAMR) -- 4.3 Heat-Assisted Magnetic Recording (HAMR) -- 4.4 The Future of High-Volume Hard Disk Drive -- 5 Summary -- References -- Role and Responsibility of Hardware Reliability Engineer -- 1 Introduction -- 2 Risk Assessment Methodologies -- 2.1 Failure Mode and Effect Analysis (FMEA) -- 2.2 Fault Tree Analysis (FTA) -- 2.3 Stress-Strength Analysis -- 3 Accelerated Life Testing (ALT) and Highly Accelerated Life Testing (HALT) -- 3.1 Introduction -- 3.2 Identify Field Stress Factors -- 3.3 Determine Stress Levels -- 3.4 Acceleration Models and Acceleration Factor -- 3.5 Case Study -- 4 Reliability Statistics -- 4.1 Sample Size.4.2 Life Distribution Analysis.Automated vehiclesDriver assistance systemsArtificial intelligenceAutomated vehicles.Driver assistance systems.Artificial intelligence.629.2Li YanShi HualiangMiAaPQMiAaPQMiAaPQBOOK996495560303316Advanced driver assistance systems and autonomous vehicles3062554UNISA