This book captures multidisciplinary research encompassing various facets of autonomous vehicle systems (AVS) research and developments. The AVS field is rapidly moving towards realization with numerous advances continually reported. The contributions to this field come from widely varying branches of knowledge, making it a truly multidisciplinary area of research and development. The topics covered in the book include:
- AI and deep learning for AVS
- Autonomous steering through deep neural networks
- Adversarial attacks and defenses on autonomous vehicles
- Gesture recognition for vehicle control
- Multi-sensor fusion in autonomous vehicles
- Teleoperation technologies for AVS
- Simulation and game theoretic decision making for AVS
- Path following control system design for AVS
- Hybrid cloud and edge solutions for AVS
- Ethics of AVS
This book captures multidisciplinary research encompassing various facets of autonomous vehicles systems research and developments.
1. Introduction
2. Deep Learning for Autonomous Vehicles and Systems
3.
Towards Autonomous Vehicles and Systems Potentials and Challenges of
Artificial Intelligence
4. Autonomous Vehicle Steering through Convolutional
and Recurrent Deep Learning
5. 2D and 3D Pose Estimation for Gesture
Recognition in Deep-Learning-Driven HumanVehicle LeaderFollower Systems
6.
Adversarial Attacks and Defenses on Autonomous Vehicle Systems
7.
Multi-sensor Fusion for Multi-target Detection and Tracking
8. Teleoperation
Technologies for Enhancing Connected and Autonomous Vehicles
9. Hybrid
Edge/cloud Solutions for Supporting Autonomous Vehicles
10. Game-Theoretic
Decision Making for Autonomous Driving Vehicles
11. State of Modeling and
Simulation in Autonomous Vehicles
12. Path Following Control System Design
and Analysis for Autonomous Vehicles
13. Public Transport Travel Time
Prediction using Sequential Forward Floating Selection Algorithm and Stacked
Autoencoder
14. A Look into the Ethics of Autonomous Vehicles Systems (AVS)
Ishwar K. Sethi is currently a professor in the Department of Computer Science and Engineering at Oakland University in Rochester, Michigan. He has over 45 years of experience in applying neural networks including deep learning, machine learning, pattern recognition, and image, video, and text analytics to a broad range of projects. He has authored or coauthored over 175 journal and conference articles and has graduated 25 doctoral students. He has served on the editorial boards of several prominent journals including IEEE Trans. Pattern Analysis and Machine Intelligence, and IEEE Multimedia. He was elected IEEE Fellow in 2001 for his contributions in artificial neural networks and statistical pattern recognition and achieved the status of Life Fellow in 2012. He most recently organized the 20th International Conference on Machine Learning and Applications (ICMLA) in December 2021.
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