Autonomous Vehicle Systems

A Cyber-Physical Stack from Sensors to Motion
1. Auflage 2027
ISBN: 978-1-041-30143-1
Verlag: Taylor & Francis Ltd

Buch, Englisch, 400 Seiten, Format (B × H): 156 mm x 234 mm

This book offers a comprehensive, systems-level exploration of autonomous driving technology, framed through the lens of cyber-physical systems (CPS). Covering the full autonomy stack, sensing, perception, prediction, planning, control, and actuation, the book integrates computational, physical, and embedded control aspects essential for designing robust, real-time autonomous systems. With in-depth discussions on sensor modalities (LiDAR, RADAR, cameras, GNSS, IMUs), deep learning-based perception algorithms (YOLO, DETR, Mask R-CNN), multi-modal sensor fusion, and control strategies (PID, MPC, Stanley, Pure Pursuit), it bridges academic theory and industrial deployment. Practical insights into simulation tools like CARLA, drive-by-wire systems, and real-world deployment challenges make this book an essential resource for graduate students, researchers, and engineers seeking to understand and build intelligent, adaptive autonomous vehicle systems.

• Comprehensive coverage of the full autonomous vehicle stack: sensing, perception, prediction, planning, control, and actuation.

• In-depth analysis of sensor modalities, including LiDAR, RADAR, cameras, GNSS, and IMUs, with real-world benchmarks and datasets.

• State-of-the-art deep learning algorithms for perception, including YOLO, DETR, Mask R-CNN, and multi-object tracking methods like DeepSORT and ByteTrack.

• Detailed exploration of multi-modal sensor fusion strategies, addressing synchronization, redundancy, and alignment challenges.

• Comparative study of control algorithms, including PID, MPC, Stanley, and Pure Pursuit, with practical tuning strategies.

• Practical insights into simulation frameworks (e.g., CARLA), sensor calibration, and drive-by-wire systems using CAN protocols.

• Deployment-focused content, including sensor mounting, data logging, and validation workflows.

This book is for researchers and industry professionals in robotics, embedded systems, autonomous driving, and cyber-physical systems.

Zielgruppe

Academic

Autoren/Hrsg.

Rajalakshmi, P

S, Abhilash

Thakur, Abhishek

Fachgebiete

• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Kybernetik, Systemtheorie, Komplexe Systeme
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
• Technische Wissenschaften Technik Allgemein Mess- und Automatisierungstechnik
• Technische Wissenschaften Verkehrstechnik | Transportgewerbe Fahrzeugtechnik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik EDV | Informatik Technische Informatik
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik

Inhaltsverzeichnis

1. Introduction to Autonomous Vehicles. 2. Autonomy Stack: An Overview. 3. Camera. 4. LiDAR. 5. RADAR. 6. GNSS 7. Camera-Based Perception. 8. LiDAR-Based Perception. 9. RADAR-Based Perception. 10. Multi-Modal Sensor Fusion. 11. Path Planning and Decision Making. 12. Control Algorithms for Autonomous Driving. 13. Drive-by-Wire (DBW) Systems. 14. Safety, Ethics, and Industry Standards. 15. Data Collection Platforms and Sensor Mounting. 16. Simulation and Validation. 17. Challanges in Autonomous Driving. 18. Conclusion and Future Directions.

Über Autor(innen)

Dr. P Rajalakshmi is a Professor in the Department of Electrical Engineering at the Indian Institute of Technology Hyderabad, India, and the Project Director of Technology Innovation Hub on Autonomous Navigation (TIHAN), a Section 8 company established at IIT Hyderabad. She earned her Ph.D. from IIT Madras in 2008 and has published over 250 internationally reputed research articles. Her research interests include Autonomous Vehicles, Advanced Driver Assistance Systems (ADAS), drone-based sensing, IoT, AI, cyber-physical systems, sensor networks, and wireless networks. She has led 17 projects as PI and Co-PI, including TIHAN and DST's NM-ICPS initiatives. Dr. Rajalakshmi has been a member of various national and international committees, including the Expert Committee for Engineering Sciences. She has received several accolades, such as the CYIENT Chair Professor in Future Communications (2021–2024) and the Digital Trail Blazer Award (2016).

Abhilash S is a Ph.D. scholar in the Department of Artificial Intelligence at the Indian Institute of Technology Hyderabad, India. He holds a bachelor's degree in Computer Science and Engineering (2017) and a master's degree in the same field (2020). His primary research interests lie in computer vision applications for autonomous vehicles.

Abhishek Thakur is a Ph.D. scholar in the Department of Electrical Engineering at the Indian Institute of Technology Hyderabad, India, and a Prime Minister's Research Fellow. He completed his bachelor's degree in Electronics & Communication Engineering from IIIT Manipur in 2019. He is a member of the IEEE Intelligent Transportation Systems Society (ITSS) Committee on Young Professionals. His research focuses on LiDAR-based Mapping and Localization, LiDAR data processing, and sensor fusion for autonomous vehicles.