1st Edition
Autonomous Vehicles and Systems A Technological and Societal Perspective
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
1. Introduction
Ishwar K. Sethi
2. Deep Learning for Autonomous Vehicles and Systems
Guimin Dong, Mingyue Tang, Runze Yan, Zeyu Mu, Lihua Cai, and B. Brian Park
3. Towards Autonomous Vehicles and Systems – Potentials and Challenges of Artificial Intelligence
C. Hürten, A. Stockem Novo, Dieter Schramm, and P. M. Sieberg
4. Autonomous Vehicle Steering through Convolutional and Recurrent Deep Learning
Mark Kocherovsky, Guiseppe DeRose, Nicholas Paul, Ian Timmis, and Chan-Jin Chung
5. 2D and 3D Pose Estimation for Gesture Recognition in Deep-Learning-Driven Human–Vehicle Leader–Follower Systems
Joseph Schulte, Mark Kocherovsky, Justin Dombecki, Nicholas Paul, Mitchell Pleune, and Chan-Jin Chung
6. Adversarial Attacks and Defenses on Autonomous Vehicle Systems
Sunny Raj
7. Multi-sensor Fusion for Multi-target Detection and Tracking
Li Liu, Jiang Tian, Zhongchao Shi, Jianping Fan, and Yong Rui
8. Teleoperation Technologies for Enhancing Connected and Autonomous Vehicles
Sidi Lu, Ren Zhong, and Weisong Shi
9. Hybrid Edge/cloud Solutions for Supporting Autonomous Vehicles
Loris Belcastro, Fabrizio Marozzo, and Alessio Orsino
10. Game-Theoretic Decision Making for Autonomous Driving Vehicles
Mingfeng Yuan and Jinjun Shan
11. State of Modeling and Simulation in Autonomous Vehicles
Arpan Kusari
12. Path Following Control System Design and Analysis for Autonomous Vehicles
Mümin Tolga Emirler
13. Public Transport Travel Time Prediction using Sequential Forward Floating Selection Algorithm and Stacked Autoencoder
Makram Soui, Ines Gasmi, Nesrine Mansouri, Imen Ben Rjeb, Marouane Kessentini, and Karthic Srinivasin
14. A Look into the Ethics of Autonomous Vehicles Systems (AVS)
Jia Hui (Sherry) Feng and Xiaoxin (Carol) Shen
Biography
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.
