Autonomous and Connected Heavy Vehicle Technology presents the fundamentals, definitions, technologies, standards and future developments of autonomous and connected heavy vehicles. This book provides insights into various issues pertaining to heavy vehicle technology and helps users develop solutions towards autonomous, connected, cognitive solutions through the convergence of Big Data, IoT, cloud computing and cognition analysis. Various physical, cyber-physical and computational key points related to connected vehicles are covered, along with concepts such as edge computing, dynamic resource optimization, engineering process, methodology and future directions.
The book also contains a wide range of case studies that help to identify research problems and an analysis of the issues and synthesis solutions. This essential resource for graduate-level students from different engineering disciplines such as automotive and mechanical engineering, computer science, data science and business analytics combines both basic concepts and advanced level content from technical experts.
1. Autonomous and Connected Heavy Vehicle Technology - p. i 2. Cover - p. i 3. Title Page - p. i 4. Copyright Page - p. iv 5. Table of Contents - p. iv 6. Contributors - p. xix 7. Preface - p. xxiii 8. Chapter 1 Lightweight and heavyweight technologies for autonomous vehicles: A survey - p. 3 9. Chapter 2 Cybercrimes and defense approaches in vehicular networks - p. 37 10. Chapter 3 Autonomous driving systems and experiences: A comprehensive survey - p. 65 11. Chapter 4 Applications of blockchain in automated heavy vehicles: Yesterday, today, and tomorrow - p. 81 12. Chapter 5 Eco-routing navigation systems in electric vehicles: A comprehensive survey - p. 95 13. Chapter 6 Automatic vehicle number plate detection and recognition systems: Survey and implementation - p. 125 14. Chapter 7 A secured IoT parking system based on smart sensor communication with two-step user verification - p. 141 15. Chapter 8 Man-and-wife coupling and need for artificially intelligent heavy vehicle technology in The Long, Long Trailer - p. 161 16. Chapter 9 Pulse oximeter-based machine learning models for sleep apnea detection in heavy vehicle drivers - p. 183 17. Chapter 10 Using wavelet transformation for acoustic signal processing in heavy vehicle detection and classification - p. 199 18. Chapter 11 Congestion control mechanisms in vehicular networks: A perspective on Internet of vehicles (IoV) - p. 211 19. Chapter 12 Smart traffic light management system for heavy vehicles - p. 225 20. Chapter 13 Smart automated system for classification of emergency heavy vehicles and traffic light controlling - p. 245 21. Chapter 14 Implementation of a cooperative intelligent transport system utilizing weather and road observation data - p. 263 22. Chapter 15 Heavy vehicle defense procurement use cases and system design using blockchain technology - p. 287 23. Chapter 16 Cybercriminal approaches in big data models for automated heavy vehicles - p. 303 24. Chapter 17 Modeling fuel economy of connected vehicles using driving context - p. 335 25. Chapter 18 Conceptual design and computational investigations of fixed wing unmanned aerial vehicle for medium-range applications - p. 353 26. Chapter 19 Multi-sensor fusion in autonomous heavy vehicles - p. 375 27. Chapter 20 Smart vehicle accident detection for flash floods - p. 391 28. Index - p. 417
Autonomous and Connected Heavy Vehicle Technology presents the fundamentals, definitions, technologies, standards and future developments of autonomous and connected heavy vehicles. This book provides insights into various issues pertaining to heavy vehicle technology and helps users develop solutions towards autonomous, connected, cognitive solutions through the convergence of Big Data, IoT, cloud computing and cognition analysis. Various physical, cyber-physical and computational key points related to connected vehicles are covered, along with concepts such as edge computing, dynamic resource optimization, engineering process, methodology and future directions.
The book also contains a wide range of case studies that help to identify research problems and an analysis of the issues and synthesis solutions. This essential resource for graduate-level students from different engineering disciplines such as automotive and mechanical engineering, computer science, data science and business analytics combines both basic concepts and advanced level content from technical experts.
1. Autonomous and Connected Heavy Vehicle Technology - p. i 2. Cover - p. i 3. Title Page - p. i 4. Copyright Page - p. iv 5. Table of Contents - p. iv 6. Contributors - p. xix 7. Preface - p. xxiii 8. Chapter 1 Lightweight and heavyweight technologies for autonomous vehicles: A survey - p. 3 9. Chapter 2 Cybercrimes and defense approaches in vehicular networks - p. 37 10. Chapter 3 Autonomous driving systems and experiences: A comprehensive survey - p. 65 11. Chapter 4 Applications of blockchain in automated heavy vehicles: Yesterday, today, and tomorrow - p. 81 12. Chapter 5 Eco-routing navigation systems in electric vehicles: A comprehensive survey - p. 95 13. Chapter 6 Automatic vehicle number plate detection and recognition systems: Survey and implementation - p. 125 14. Chapter 7 A secured IoT parking system based on smart sensor communication with two-step user verification - p. 141 15. Chapter 8 Man-and-wife coupling and need for artificially intelligent heavy vehicle technology in The Long, Long Trailer - p. 161 16. Chapter 9 Pulse oximeter-based machine learning models for sleep apnea detection in heavy vehicle drivers - p. 183 17. Chapter 10 Using wavelet transformation for acoustic signal processing in heavy vehicle detection and classification - p. 199 18. Chapter 11 Congestion control mechanisms in vehicular networks: A perspective on Internet of vehicles (IoV) - p. 211 19. Chapter 12 Smart traffic light management system for heavy vehicles - p. 225 20. Chapter 13 Smart automated system for classification of emergency heavy vehicles and traffic light controlling - p. 245 21. Chapter 14 Implementation of a cooperative intelligent transport system utilizing weather and road observation data - p. 263 22. Chapter 15 Heavy vehicle defense procurement use cases and system design using blockchain technology - p. 287 23. Chapter 16 Cybercriminal approaches in big data models for automated heavy vehicles - p. 303 24. Chapter 17 Modeling fuel economy of connected vehicles using driving context - p. 335 25. Chapter 18 Conceptual design and computational investigations of fixed wing unmanned aerial vehicle for medium-range applications - p. 353 26. Chapter 19 Multi-sensor fusion in autonomous heavy vehicles - p. 375 27. Chapter 20 Smart vehicle accident detection for flash floods - p. 391 28. Index - p. 417
