Autonomous and Connected Heavy Vehicle Technology
FIRST EDITION
Rajalakshmi Krishnamurthi
Associate Professor, Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida, India
Adarsh Kumar
Senior Associate Professor, Department of Systemics, School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India
Sukhpal Singh Gill
Assistant Professor, School of Electronic Engineering and Computer Science, Queen Mary University of London, UK
Series Editor Fatos Xhafa
Technical University of Catalonia (UPC), Barcelona, Spain
Table of Contents
Cover
Title page
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
y g g
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
Copyright
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Contributors
R. Arul Prakash Department of Aeronautical Engineering, Kumaraguru College of Technology, Coimbatore, Tamil Nadu, India
Gourav Bathla Department of Informatics; Department of Cybernetics; School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India
Priyanka Chawla School of Computer Science and Engineering, Lovely Professional University, Phagwara, Punjab, India
J. Darshan Kumar Department of Aeronautical Engineering, Kumaraguru College of Technology, Coimbatore, Tamil Nadu, India
Kritanjali Das Department of Electronics and Communication Engineering, Tezpur University, Napaam, Assam, India
Sukhpal Singh Gill School of Electronic Engineering and Computer Science, Queen Mary University of London, London, United Kingdom
Dhanalekshmi Gopinathan Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida, U ar Pradesh, India
Naman Gupta Department of Computer science and Engineering, Jaypee Institute of Information Technology, Noida, U ar Pradesh, India
Sakshi Gupta Department of Computer Science and Engg., Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India
Vatsal Gupta Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida, U ar Pradesh, India
N. Jagadeesh Department of Computer Science & Applications, St. Peter’s Institute of Higher Education & Research, Chennai, Tamilnadu, India
Neetika Jain Department of Computer Science & Engineering and Information Technology, Jaypee Institute of Information Technology, Noida, India
Saurabh Jain Department of Systemics, School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India
M. Kannan Department of Computer Science, Vels Institute of Science, Technology and Advanced Studies (VISTAS), Chennai, Tamilnadu, India
Marcos Ka University of Oulu, Oulu, Finland
Keshav Kaushik
Department of Systemics
Department of Informatics, School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India
K.M. Krishna Kumar Department of Aeronautical Engineering, Kumaraguru College of Technology, Coimbatore, Tamil Nadu, India
Rajalakshmi Krishnamurthi Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida, U ar Pradesh, India
Adarsh Kumar
Department of Systemics
Department of Informatics, School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India
Vaibhav Mishra Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida,
U ar Pradesh, India
Sangeeta Mi al Department of Computer Science & Engineering and Information Technology, Jaypee Institute of Information Technology, Noida, India
Usha Mi al School of Computer Science and Engineering, Lovely Professional University, Phagwara, Punjab, India
P. Muthuchidambaranathan Electronics and Communication Engineering Department, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India
Usman Naeem School of Electronic Engineering and Computer Science, Queen Mary University of London, London, United Kingdom
Farhin Faiza Neha Department of Computer Science & Engineering, Chi agong University of Engineering & Technology, Cha ogram, Bangladesh
Kushagra Pathak Department of Computer science and Engineering, Jaypee Institute of Information Technology, Noida, U ar Pradesh, India
Ashish Patil Electronics and Communication Engineering Department, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India
C. Priya Department of Information Technology, School of Computing Science, Vels Institute of Science, Technology and Advanced Studies (VISTAS), Chennai, Tamilnadu, India
R. Rajkumar Department of Science and Humanities Maths Division, Kumaraguru College of Technology, Coimbatore, Tamil Nadu, India
Muhammad Saad Saud University of Oulu, Oulu, Finland
M. Senthil Kumar Department of Aeronautical Engineering, Kumaraguru College of Technology, Coimbatore, Tamil Nadu, India
S. Senthilkumar Department of Aeronautical Engineering, Kumaraguru College of Technology, Coimbatore, Tamil Nadu, India
Kazi Hassan Shakib Department of Computer Science & Engineering, Chi agong University of Engineering & Technology, Cha ogram, Bangladesh
Deepak Kumar Sharma Department of Informatics, School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India
Gaurav Sharma Department of Systemics, School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India
Kriti Sharma Department of Systemics, School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India
Santanu Sharma Department of Electronics and Communication Engineering, Tezpur University, Napaam, Assam, India
Kazi Hassan Shazib Department of Electrical & Electronics Engineering, Shahjalal University of Science & Technology, Sylhet, Bangladesh
N. Shekar V. Shet Electronics and Communication Engineering Department, National Institute of Technology Karnataka, Surathkal, Mangalore, Karnataka, India
Anuraj Singh Department of Systemics, School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India
Itu Snigdh Department of Computer Science and Engg., Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India
Akash Soni Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida, U ar Pradesh, India
P. Srikanth Department of Systemics, School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India
Muhammad Naeem Tahir University of Oulu, Oulu, Finland
Aayush Tiwari Department of Computer science and Engineering, Jaypee Institute of Information Technology, Noida, U ar Pradesh, India
Suyash Verma Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida, U ar Pradesh, India
R. Vijayanandh Department of Aeronautical Engineering, Kumaraguru College of Technology, Coimbatore, Tamil Nadu, India
Nancy Ann Watanabe University of Oklahoma, Norman, OK, United States
L. William Mary Department of Computer Science, Alpha Arts and Science College, Chennai, Tamilnadu, India
Preface
The main technological areas that are facilitating today’s autonomous and connected heavy vehicle technology (AC-HVT) are vehicle sensor technology, vehicle communication technology, and vehicle software and hardware integration. The applications emerging from AC-HVT include driver alert systems, lane guidance, collision avoidance systems, automatic braking systems, platooning, eco-driving, blind spot detection, and cruise control. However, serious technical challenges have arisen related to sensor quality, data handling, bandwidth allocation, communication protocols and standards, resource constraints, data processing, and controlling software systems. These challenges are being met through enabling technologies such as cyberphysical systems, cloud computing, big data, fog computing, blockchain, data analytics, artificial intelligence, and pervasive computing. In the past decades, vehicle technologies were more focused on passenger-based vehicles, but in recent years the development and enhancement of heavy vehicle technologies (HVTs), including heavy freight vehicles and commercial truck vehicles, have gained more a ention. The reasons behind this are that these heavy vehicles significantly contribute to economic growth and have a high return on investment (ROI). In addition, adverse environmental impacts like air pollution, carbon footprint, fuel economy, and fatal accidents necessitate more research and development in HVT. Thus autonomous and connected vehicle technologies are emerging opportunities in the heavy vehicle industry, complicated by issues related to greater urbanization, insurance, security, and privacy.
This book provides a comprehensive text and reference covering the fundamentals, definitions, approaches, standards, and future developments in autonomous and connected heavy vehicle technology. It provides up-to-date knowledge of various issues in heavy vehicle technology and discusses solutions for autonomous, connected, and cognitive applications through the convergence of big data, IoT, cloud computing, cyberphysical systems, and cognitive analysis.
The objective of this book is to provide a one-volume source of technical insight into autonomous and connected heavy vehicle technology, including current state-of-the-art requirements, performance, evaluation, and challenges. The book is organized as follows: Chapter 1, “Light and Heavy Vehicle Technologies for Autonomous Vehicles: A Survey,” presents information on technological advancements for vehicles, including internet connectivity with four-wheel drives and steering, automated locks, petrol and diesel operation control through IoT devices, automated vehicle performance measurements, and operational measurements and control for vehicle systems including ignition and starter, emission control, suspension, and gearboxes. Chapter 2, “Identification of Cybercriminals Through Investigation and Reverse Engineering in Wired and Wireless Networks for Vehicular Technologies in the Defence Landscape,” lists cybera acks and identifies those a acks with their statistics found to be common in defense networks. Chapter 3, “Autonomous Driving Systems and Experiences: A Comprehensive Survey,” studies frameworks from an algorithmic standpoint in which computationally efficient routing and rebalancing concepts are evaluated numerically and case studies are prepared for theoretical insights. Chapter 4, “Applications of Blockchain in Automated Heavy Vehicles: Yesterday, Today, and Tomorrow,” emphasizes the recent blockchain-based approaches for integrating perception and planning for end-to-end communication, verification, and safety processes and managing fleets of autonomous vehicles. Chapter 5, “Eco-routing Navigation Systems in Electric Vehicles: A Comprehensive Survey,” explains how the use of renewable energy in electric vehicles can outweigh the limitations
