Autonomous Driving and Advanced Driver-Assistance Systems (ADAS)
Applications, Development, Legal Issues, and Testing
- Available for pre-order. Item will ship after December 1, 2021
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.
- 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
About the Editors
List of Contributors
Section I: Autonomous Vehicle Test & Development
Intelligent Decision-Making and Motion Planning for Automated Vehicles
Rick Voßwinkel, Maximilian Gerwien, Alexander Jungmann and Frank Schrödel
Control Strategies for Autonomous Vehicles
Chinmay Samak, Tanmay Samak and Sivanathan Kandhasamy
A comprehensive review on navigation system, design and safety issues for autonomous vehicle development
Pranjal Paul and Abhishek Sharma
CNN based object detection, tracking and trajectory prediction for autonomous driving
Sridevi M, Sugirtha T, Hazem Rashed, Ravi Kiran and Senthil Yogamani
ADAS Vision System with Video Super Resolution:Need and Scope
Mrunmayee Daithankar and Sachin Ruikar
Lane detection, prediction and path planning
Any Gupta and Ayesha Choudhary
PRPN-SORB-SLAM: A Parallelized Region Proposal Network based Swift ORB SLAM system for a Stereo Vision based local path planning
Kishorjit Nongmeikapam, Wahengbam Kanan Kumar and Aheibam Dinamani Singh
Ontology-based Indoor Domain Model Representation and Reasoning for Robot Path Planning using ROS
Gayathri R, Uma V and Bettina O'Brien
Vision based Smart Autonomous Vehicle using Deep Learning
Anubha Parashar, Apoorva Parashar and Vidyadhar Aski
Deep learning for obstacle avoidance in autonomous driving
Mallika Garg, Jagpal Singh Ubhi and Ashwani Kumar Aggarwal
An Array of Processed Channel for Multiple Object detection and distance estimation in a video using a Homographic Monocamera system
Wahengbam Kanan Kumar, Aheibam Dinamani Singh and Kishorjit Nongmeikapam
Stackelberg – Hidden Markov Model Approach for Behavior Prediction of Surrounding Vehicles for Autonomous Driving
R Syama and C Mala
Recent Verification & Validation Methodologies for Advanced Driver Assistance Systems
Franz Wotawa, Mihai Nica, Hermann Felbinger, Yihao Li, Florian Klück, Martin Zimmermann and Jianbo Tao
Section II: ADAS & AV Legal Issues & Liabilities
Human Factors of automated driving systems
Human Factors of Vehicle Automation
Sunil Sharma, Sunil Singh and Subhash Panja
Legal Issues surrounding Cyber Security and Privacy on Automated Vehicle
Rakesh Kumar Chopra and Abhijeet Srivastava
Human factors in autonomous driving systems: User perspective
Neeta Maitre and Neeraj Hanumante
Anticipating Legal Issues associated with the Cyber Security and Privacy of Automated Driving Systems (ADS) in India
Sujata Bali and Shamneesh Sharma
Section III: Autonomous Vehicle Applications
ADAS Technology and Legal Risk Mitigation: A Review
Madhusmita Mishra and Abhishek Kumar
Localization and Mapping for Autonomous Driving
Sridevi M, Sugirtha T, Ravi Kiran and Senthil Yogamani
GPS Based Localization of Autonomous Vehicles
Video based accident detection of Cars
Earnest Paul Ijjina
ADS & AVS – Its Cyber security & Privacy legal Issues.
Ravishankar C V and Kavitha K S
Open Pit Mine Autonomous Bot
Apoorva Parashar, Anubha Parashar and Vidyadhar Aski
Lentin Joseph is an author, roboticist, and robotics entrepreneur from India. He runs a robotics software company called Qbotics Labs in Kochi/Kerala. He has 10 years of experience in the robotics domain primarily in Robot Operating System, OpenCV, and PCL.
He has authored 8 books in ROS, namely, Learning Robotics using Python first and second edition, Mastering ROS for Robotics Programming first and second edition, ROS Robotics Projects first and second edition, ROS Learning Path, and Robot Operating System for Absolute Beginners.
He has pursued his Masters in Robotics and Automation from India and also worked at Robotics Institute, CMU, USA. He is also a TEDx speaker.
Amit Kumar Mondal, PhD, is Assistant Professor in the Department of Mechatronics Engineering, Manipal Academy of Higher Education, Dubai, UAE. His area of research interest are Mobile Robotics, Autonomous System, Industrial Automation. He has published more than 30 papers in national and international journals and conferences. He has filed 3 patents and successfully completed 3 externally funded projects from SERB, IUSSTF.