Autonomous and Connected Heavy Vehicle Technology

Title: Autonomous and Connected Heavy Vehicle Technology
Author: Adarsh Kumar, Fatos Xhafa, Rajalakshmi Krishnamurthi, Sukhpal Singh Gill
ISBN: 0323905927 / 9780323905923
Format: Soft Cover
Pages: 454
Publisher: Elsevier
Year: 2022
Availability: 20-30 days

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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.

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Chapter 1 : Lightweight and heavyweight technologies for autonomous 
Chapter 2 : Cybercrimes and defense approaches in vehicular networks
Chapter 3 : Autonomous driving systems and experiences: A comprehensive survey
Chapter 4 : Applications of blockchain in automated heavy vehicles: Yesterday, today, and tomorrow
Chapter 5 : Eco-routing navigation systems in electric vehicles: A comprehensive survey
Chapter 6 : Automatic vehicle number plate detection and recognition systems: Survey and implementation
Chapter 7 : A secured IoT parking system based on smart sensor communication with two-step user verification
Chapter 8 : Man-and-wife coupling and need for artificially intelligent heavy vehicle technology in The Long, Long Trailer
Chapter 9 : Pulse oximeter-based machine learning models for sleep apnea detection in heavy vehicle drivers
Chapter 10 : Using wavelet transformation for acoustic signal processing in heavy vehicle detection and classification
Chapter 11 : Congestion control mechanisms in vehicular networks: A perspective on Internet of vehicles (IoV)
Chapter 12 : Smart traffic light management system for heavy vehicles
Chapter 13 : Smart automated system for classification of emergency heavy vehicles and traffic light controlling
Chapter 14 : Implementation of a cooperative intelligent transport system utilizing weather and road observation data
Chapter 15 : Heavy vehicle defense procurement use cases and system design using blockchain technology
Chapter 16 : Cybercriminal approaches in big data models for automated heavy vehicles
Chapter 17 : Modeling fuel economy of connected vehicles using driving context
Chapter 18 : Conceptual design and computational investigations of fixed wing unmanned aerial vehicle for medium-range applications
Chapter 19 : Multi-sensor fusion in autonomous heavy vehicles
Chapter 20 : Smart vehicle accident detection for flash floods