Autonomous and Connected Heavy Vehicle Technology

1st Edition - January 18, 2022
Editors: Rajalakshmi Krishnamurthi, Fatos Xhafa, Adarsh Kumar, Sukhpal Singh Gill
Language: English
Paperback ISBN:
9 7 8 - 0 - 3 2 3 - 9 0 5 9 2 - 3
eBook ISBN:
9 7 8 - 0 - 3 2 3 - 9 0 7 1 5 - 6

Autonomous and Connected Heavy Vehicle Technology presents the fundamentals, definitions, technologies, standards and future developments of autonomous and connected heavy veh… Read more

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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.

Cover
Title page
Table of Contents
Copyright
Contributors
Preface
Section 1: Review articles
Chapter 1: Lightweight and heavyweight technologies for autonomous vehicles: A survey
Abstract
1: Lightweight sensor technology for automated and connected heavy vehicles
2: Lightweight and heavyweight road safety issues for automated vehicles
3: Impact of heavy vehicle technologies with industry 4.0 standards
4: Conclusion and future scope
References
Chapter 2: Cybercrimes and defense approaches in vehicular networks
Abstract
1: Introduction
2: Literature review of cybersecurity and cyberattacks in defense networks
3: Methodology for securing data from cyberattacks
4: Data security measures
5: Cybersecurity in defense networks
6: Conclusion and future scope
References
Chapter 3: Autonomous driving systems and experiences: A comprehensive survey
Abstract
1: Introduction
2: Autonomous vehicle’s datasets and features
3: Lane detection system in autonomous vehicles
4: Autonomous vehicle movement systems
5: Conclusion
References
Chapter 4: Applications of blockchain in automated heavy vehicles: Yesterday, today, and tomorrow
Abstract
1: Introduction
2: IoT devices and automated vehicles
3: Security verification and analysis process
4: Use case for blockchain-based automated vehicle management
5: Conclusion
References
Chapter 5: Eco-routing navigation systems in electric vehicles: A comprehensive survey
Abstract
Acknowledgment
1: Introduction
2: Eco-routing of electric vehicles
3: Survey of literature
4: Range determination in electric vehicles
5: Existing eco-routing system prototypes
6: Major challenges
7: Proposed eco-routing system
8: Future scope
9: Conclusion
References
Section 2: Implementation or Simulation-based study for heavy vehicles technologies
Chapter 6: Automatic vehicle number plate detection and recognition systems: Survey and implementation
Abstract
1: Introduction
2: Survey of automated vehicle number detection systems
3: Number detection system methodology
4: Distributed computing platform for automated number detection
5: Proposed automated vehicle number detection systems
6: Conclusion and future scope
References
Chapter 7: A secured IoT parking system based on smart sensor communication with two-step user verification
Abstract
1: Introduction
2: Existing system
3: EcoSystem: Internet of Things
4: Proposed smart parking system
5: Cloud computing
6: Privacy-preserving smart parking system
7: Networks and security
8: Discussion
9: Conclusion
References
Further reading
Chapter 8: Man-and-wife coupling and need for artificially intelligent heavy vehicle technology in The Long, Long Trailer
Abstract
1: Argument and comparative methodology
2: Ethical and moral imperatives
3: Film at the intersection of technology, art, and material culture
4: Imaginary characters, real stars
5: Film adaptation of literary biography
6: Marriage as a connected vehicle
7: Rocky Mountain imagery in film art and AI for HVT
8: Missing: A catalytic converter
9: State of the art in artificial intelligence
10: Narratological framework and imagery
11: High technology and middle class daydreamers
12: Connected HVT, disconnected civilians
13: Measuring space and time
14: At the intersection: The artificiality of AI
15: Climbing to the top in a connected heavy vehicle
16: Romantic comedy of descent
17: Collision and disaster at the family reunion
18: Coupling and connectivity
19: Love’s chemistry, life’s gravity
20: Love’s Rocky overload: Dangerous deception
21: Conclusion
References
Further reading
Chapter 9: Pulse oximeter-based machine learning models for sleep apnea detection in heavy vehicle drivers
Abstract
1: Introduction
2: Literature survey
3: Methodology
4: Experimental setup
5: Results and discussion
6: Conclusion and future scope
References
Chapter 10: Using wavelet transformation for acoustic signal processing in heavy vehicle detection and classification
Abstract
1: Introduction
2: Literature survey
3: Comparison of Morlet, Mexican hat, frequency B-spline wavelets in classification of vehicle sound
4: Conclusion
References
Chapter 11: Congestion control mechanisms in vehicular networks: A perspective on Internet of vehicles (IoV)
Abstract
1: DCC mechanisms
2: Centralized congestion control mechanisms
3: Conclusion
References
Chapter 12: Smart traffic light management system for heavy vehicles
Abstract
1: Introduction
2: Different techniques of traffic management systems for heavy vehicles
3: Literature review
4: Scope of study
5: Proposed methodology
6: Results and discussion
7: Conclusion and future scope
References
Chapter 13: Smart automated system for classification of emergency heavy vehicles and traffic light controlling
Abstract
1: Introduction
2: Literature survey
3: Methodology
4: Design and implementation
5: Results and findings
6: Conclusion
References
Chapter 14: Implementation of a cooperative intelligent transport system utilizing weather and road observation data
Abstract
Acknowledgment
1: Introduction
2: Related work
3: C-ITS communication and protocol
4: European framework of C-ITS
5: Validation framework and deployment of C-ITS pilot system
6: Results and discussion
7: Summary/conclusion
References
Section 3: Applications and case studies for heavy vehicles technologies
Chapter 15: Heavy vehicle defense procurement use cases and system design using blockchain technology
Abstract
Acknowledgments
1: Introduction
2: Blockchain technology in defense
3: Use cases of defense blockchain
4: Conclusion and future scope
References
Chapter 16: Cybercriminal approaches in big data models for automated heavy vehicles
Abstract
1: Introduction
2: Cybersecurity and cyberattacks in networks (wired and wireless) for automated heavy vehicle movements
3: Data security measures for big data
4: Big data analytics for heavy autonomous vehicles
5: Conclusion and future scope
References
Chapter 17: Modeling fuel economy of connected vehicles using driving context
Abstract
1: Introduction
2: Literature review
3: Proposed architecture for estimating fuel efficiency
4: Results and discussion
5: Conclusion
References
Chapter 18: Conceptual design and computational investigations of fixed wing unmanned aerial vehicle for medium-range applications
Abstract
1: Introduction
2: Literature survey
3: Symbols
4: Conceptual design
5: Conclusions
References
Chapter 19: Multi-sensor fusion in autonomous heavy vehicles
Abstract
1: Introduction
2: Autonomous heavy vehicle subsystems
3: Communication protocols in autonomous heavy vehicles
4: ECU in autonomous heavy vehicles
5: The sensors used in autonomous heavy vehicles
6: Essential sensors used in ADSs
7: Sensor fusion in autonomous heavy vehicles
8: Multi-sensor data fusion approaches
9: Advantages and challenges in multi-sensor data fusion in AHVs
10: Conclusion
11: Future directions
References
Chapter 20: Smart vehicle accident detection for flash floods
Abstract
1: Introduction
2: Literature review
3: Proposed methodology
4: Design and architecture
5: System implementation
6: Result
7: Discussion
8: Conclusion and future directions
References
Further reading
Index

Rajalakshmi Krishnamurthi

Rajalakshmi Krishnamurthi is a Senior Member of IEEE, Professional Member of ACM, SIAM, IET and CSI. She is serving as Treasurer, Delhi ACM-W chapter. She is currently working as Assistant Professor (Senior Grade), Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida, India. She has more than 17 year of teaching experience. She has more than 50 research publications in various reputed peer reviewed International Journal, Book Chapters, and International Conferences. Her research interest includes Internet of Things, Cloud Computing, optimization techniques in wireless mobile networks, e-learning applications using mobile platform and advanced fuzzy approaches.

Affiliations and expertise

Assistant Professor (Senior Grade), Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida, India

Fatos Xhafa

Fatos Xhafa, PhD in Computer Science, is Full Professor at the Technical University of Catalonia (UPC), Barcelona, Spain. He has held various tenured and visiting professorship positions. He was a Visiting Professor at the University of Surrey, UK (2019/2020), Visiting Professor at the Birkbeck College, University of London, UK (2009/2010) and a Research Associate at Drexel University, Philadelphia, USA (2004/2005). He was a Distinguished Guest Professor at Hubei University of Technology, China, for the duration of three years (2016-2019). Prof. Xhafa has widely published in peer reviewed international journals, conferences/workshops, book chapters, edited books and proceedings in the field (H-index 55). He has been awarded teaching and research merits by the Spanish Ministry of Science and Education, by IEEE conferences and best paper awards. Prof. Xhafa has an extensive editorial service. He is founder and Editor-In-Chief of Internet of Things - Journal - Elsevier (Scopus and Clarivate WoS Science Citation Index) and of International Journal of Grid and Utility Computing, (Emerging Sources Citation Index), and AE/EB Member of several indexed Int'l Journals. Prof. Xhafa is a member of IEEE Communications Society, IEEE Systems, Man & Cybernetics Society and Founder Member of Emerging Technical Subcommittee of Internet of Things. His research interests include IoT and Cloud-to-thing continuum computing, massive data processing and collective intelligence, optimization, security and trustworthy computing and machine learning, among others. He can be reached at [email protected]. Please visit also http://www.cs.upc.edu/~fatos/ and at http://dblp.uni-trier.de/pers/hd/x/Xhafa:Fatos

Affiliations and expertise

Full Professor of Computer Science, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain

Adarsh Kumar

Dr. Adarsh Kumar is an Professor in the School of Computer Science with University of Petroleum & Energy Studies, Dehradun, India. He received his Master degree (M. Tech) in Software Engineering from Thapar University, Patiala, Punjab, India and earned his PhD degree from Jaypee Institute of Information Technology University, Noida, India followed by Post-Doc from Software Research Institute, Athlone Institute of Technology, Ireland. From 2005 to 2016, he has been associated with the Department of Computer Science Engineering & Information Technology, Jaypee Institute of Information Technology, Noida, Uttar-Pardesh, India, where he worked as Assistant Professor. His main research interests are cybersecurity, cryptography, network security, and ad-hoc networks. He has many research papers in reputed journals, conferences and workshops. He participated in one European Union H2020 sponsored research project and he is currently executing two research projects sponsored from UPES SEED division and one sponsored from Lancaster University.

Affiliations and expertise

Professor, School of Computer Science University of Petroleum and Energy Studies, Dehradun, India

Sukhpal Singh Gill

Dr. Sukhpal Singh Gill is a Lecturer and Assistant Professor in Cloud Computing at the School of Electronic Engineering and Computer Science, Queen Mary University of London, UK. Prior to his present stint, Dr. Gill has held positions as a Research Associate at the School of Computing and Communications, Lancaster University, UK and also as a Postdoctoral Research Fellow at CLOUDS Laboratory, The University of Melbourne, Australia. Dr. Gill is serving as an Associate Editor for Wiley ETT and IET Networks Journal. He has co-authored 100+ peer-reviewed papers and has published in prominent international journals and conferences such as IEEE TCC, IEEE TSC, IEEE TII, IEEE TNSM, IEEE IoT Journal, Elsevier JSS/FGCS, IEEE/ACM UCC, and IEEE CCGRID. He has received several awards, including the Distinguished Reviewer Award from SPE (Wiley), Best Paper Award AusPDC at ACSW 2021, and has also served as the PC member for venues such as PerCom, UCC, CCGRID, CLOUDS, ICFEC, AusPDC. He has edited research books for Springer, Elsevier and CRC Press. His research interests include Cloud Computing, Fog Computing, Software Engineering, Internet of Things and Energy Efficiency.

Affiliations and expertise

Queen Mary University of London, UK.