Autonomous Driving and Advanced Driver-Assistance Systems (ADAS): Applications, Development, Legal Issues, and Testing (Chapman & Hall/CRC Artificial Intelligence and Robotics Series)

✍ Scribed by Lentin Joseph (editor), Amit Kumar Mondal (editor)

• Publisher: CRC Press
• Year: 2021
• Tongue: English
• Leaves: 540
• Edition: 1
• Category: Library

✦ Synopsis

Autonomous Driving and Advanced Driver Assistance Systems (ADAS) outlines the latest research relating to autonomous cars and advanced driver-assistance systems, including the development, testing and verification for real-time situations of sensor fusion, sensor placement, control algorithms, computer vision, and more.

Key Features:

• Co-edited by an experienced roboticist and author as well as an experienced academic.
• Addresses the legal aspect of autonomous driving and ADAS.
• Presents the application of ADAS in autonomous vehicle parking systems.

With an infinite number of real-time possibilities that need to be addressed, the methods and examples included make this book a valuable source of information for academic and industrial researchers, automotive companies and suppliers.

✦ Table of Contents

Cover
Half Title
Series Page
Title Page
Copyright Page
Contents
Preface
Acknowledgments
Editors
Contributors
Section I: Autonomous Vehicle Testing and Development
Chapter 1: Intelligent Decision-Making and Motion Planning for Automated Vehicles
Chapter 2: Control Strategies for Autonomous Vehicles
Chapter 3: A Comprehensive Review of Navigation System, Design, and Safety Issues for Autonomous Vehicle Development
Chapter 4: Object Detection, Tracking and Trajectory Prediction for Autonomous Driving
Chapter 5: ADAS Vision System with Video Super Resolution: Need and Scope
Chapter 6: Lane Detection, Prediction, and Path Planning
Chapter 7: PRN-SORB-SLAM: A Parallelized Region Proposal Network-Based Swift ORB SLAM System for Stereo Vision-Based Local Path Planning
Chapter 8: Ontology-Based Indoor Domain Model Representation and Reasoning for Robot Path Planning Using ROS
Chapter 9: Automated Guided Autonomous Car Using Deep Learning and Computer Vision
Chapter 10: Deep Learning for Obstacle Avoidance in Autonomous Driving
Chapter 11: An Array of Processed Channel for Multiple Object Detection and Distance Estimation in a Video Using a Homographic Mono Camera System
Chapter 12: Stackelberg: Hidden Markov Model Approach for Behavior Prediction of Surrounding Vehicles for Autonomous Driving
Chapter 13: Recent Verification and Validation Methodologies for Advanced Driver-Assistance Systems
Section II: ADAS and AV Legal Issues and Liabilities
Chapter 14: Human Factors of Automated Driving Systems
Chapter 15: Human Factors of Vehicle Automation
Chapter 16: Legal Issues Surrounding Cyber Security and Privacy on Automated Vehicle
Chapter 17: Human Factors in Autonomous Driving Systems: A User Perspective
Chapter 18: Anticipating Legal Issues Associated with the Cyber Security and Privacy of Automated Driving Systems in India
Chapter 19: ADAS Technology: A Review on Challenges, Legal Risk Mitigation and Solutions
Section III: Autonomous Vehicle Applications
Chapter 20: Localization and Mapping for Autonomous Driving
Chapter 21: GPS-Based Localization of Autonomous Vehicles
Chapter 22: Video-Based Accident Detection of Cars
Chapter 23: ADS and AVS: Its Cyber Security and Privacy Legal Issues
Chapter 24: Open-Pit Mine Autonomous Bot
INDEX