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The automotive industry is transforming to a greater degree that has occurred since Henry Ford introduced mass production of the automobile with the Model T in 1913. Advances in computing, data processing, and artificial intelligence (deep learning in particular) are driving the development of new levels of automation that will impact all aspects of our lives including our vehicles. What are Connected and Automated Vehicles (CAVs)? What are the underlying technologies that need to mature and converge for them to be widely deployed? Fundamentals of Connected and Automated Vehicles is written to answer these questions, educating the reader with the information required to make informed predictions of how and when CAVs will impact their lives. Topics covered include: History of Connected and Automated Vehicles, Localization, Connectivity, Sensor and Actuator Hardware, Computer Vision, Sensor Fusion, Path Planning and Motion Control, Verification and Validation, and Outlook for future of CAVs.

• Front Cover
• Title Page
• Copyright Page
• Contents
• Foreword
• Preface
• CHAPTER 1 Introduction and History of Connected and Automated Vehicles
  • CAV History and Origins
  • CAVs Today
  • Current Status
    • Positive Impacts
    • Negative Impacts
  • Societal Impacts
  • CAV Taxonomy and Definitions
  • Scope of the Book
  • References
• CHAPTER 2 Localization
  • Localization Need
  • Mapping
  • Sensing
  • Localization Challenges
  • Localization Techniques
  • References
• CHAPTER 3 Connectivity
  • Connectivity Defined
  • Connectivity Origins
  • Motivations: The Case for Connectivity
    • Motivations: Crash Avoidance
      • Motivations: Mobility Enhancement
      • Motivations: Environmental Impact
  • Connectivity Case Study: ACC versus CACC
  • Connectivity Technology
    • Connectivity Technology: DSRC
    • Connectivity Technology: C-V2X
    • Connectivity Technology: DSRC versus 5G
    • Connectivity Technology: CV Costs
  • Deployment Challenges versus Potential Benefits
  • References
• CHAPTER 4 Sensor and Actuator Hardware
  • Principles and Characteristics of Sensor Hardware
    • Cameras
      • Definition and Description
      • Characteristics and Capabilities
    • RADAR
      • Definition and Description
      • Characteristics and Capabilities
    • LIDAR
      • Definition and Description
      • Working Principles
      • Types of LIDAR
      • Characteristics
    • Ultrasonic SONAR
      • Definition and Description
      • Characteristics
    • Other Important Sensors and Measurement Sources
      • HD Maps
      • High-Precision GPS
  • Sensor Suites
    • Overview
    • Sensor Suite: Functionality
  • Actuation and Propulsion Hardware
    • Steer-By-Wire
    • Rear-Wheel Steering
    • Electric Propulsion and In-Wheel Motors
  • References
• CHAPTER 5 Computer Vision
  • Image and 3D Point Cloud
    • Image Formation
    • Image Processing
    • 3D Point Cloud Formation
  • Deep Learning
    • Deep Neural Networks
    • Training Deep Neural Networks
    • Convolutional Neural Networks
  • Perception Tasks for CAV
    • Object Detection
    • Tracking
    • Segmentation
    • 3D Depth Estimation
  • Perception System Development for CAV
    • Case Study: Google/Waymo CAV
    • Case Study: Tesla Autopilot
    • Case Study: CAROM
  • References
• CHAPTER 6 Sensor Fusion
  • Sensor Fusion Definition and Requirements
    • Sensor Fusion Definition and CAV Data Sources
    • Sensor Fusion Requirements
  • Sensor Fusion Origins
    • JDL Model
    • Dasarathy Model
    • Boyd Control Loop
    • Intelligence Cycle
    • Omnibus Model
    • Object-Oriented Model
    • Frankel-Bedworth Architecture
  • Sensor Fusion Architecture
    • Centralized Fusion Architecture
    • Distributed Fusion Architecture
    • Hybrid Fusion Architecture
  • Sensor Interaction
  • Object and Situation Refinement ­Examples
    • Feature Extraction
    • Multi-Target Tracking
    • Evaluation Metrics
  • Sensor Fusion Applications: Active ­Safety Systems
    • Safe Speed and Distance
    • Lane-Keeping Assist
    • Intersection Navigation
  • Sensor Fusion Examples from ­Developmental CAVs
    • Waymo Sensor Fusion Applications
    • Lyft Self-Driving Platform with Level 5
    • Cruise Application of Late Fusion Techniques
  • Sensor Fusion Challenges
    • Lessons from Active Safety Systems and CAVs
  • Summary
  • References
• CHAPTER 7 Path Planning and Motion Control
  • Definition and Hierarchy
    • Path Planning Objectives
    • Structured Environments
      • Deviations from Reference Paths
    • Unstructured Environments
  • Behavioral Decision-Making
    • Finite-State Machines
    • Probabilistic Methods
    • Learning-Based Methods
    • Behavioral Ethics
      • Moral Dilemmas
      • The Moral Machine Project
      • Regulatory Guidance
  • Trajectory Planning
    • Optimization-Based Methods
    • Graph Search and Sampling Methods
  • Motion Control
    • Kinematic Path Tracking
    • Trajectory Tracking
      • Model Predictive Control
    • Actuation and Actuator Delay
  • End-to-End Automated Driving
  • Summary and Outlook
  • References
• CHAPTER 8 Verification and Validation
  • Definition
    • Design and Development Methods
    • Test and Validation Methods
  • Challenges
  • Test and Validation Methodology
    • Operational Safety Metrics
    • Test Methods
      • Simulation Testing
      • Closed Course Testing
      • Public Road Testing
    • Evaluation Methods
    • Evaluation Criteria
  • Safety Case
  • References
• CHAPTER 9 Outlook
  • State of the Industry—Technology
  • State of the Industry—Deployments
  • State of the Industry—Regulation and Legislation
    • State Legislation and Regulation
  • Standards Activities
  • Public Perception
  • CAV-Related Research and Activities
    • Advanced Vehicle Tracking through Infrastructure—IAM and ASU
    • Deployment of Infrastructure-Based CAV Solutions—NAU and UofA
    • Scenario-Based Testing of CAVs—Mcity and UMTRI
    • CAV Interactions with Emergency Vehicles—VTTI
  • What’s Next?
  • References
• Appendix B: Acronyms
• About the Authors
• Index
• Back Cover