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Autonomous Vehicles, Volume 2: Smart Vehicles

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AUTONOMOUS VEHICLES

The companion to Autonomous Vehicles Volume 1: Using Machine Intelligence, this second volume in the two-volume set covers intelligent techniques utilized for designing, controlling, and managing vehicular systems based on advanced algorithms of computing like machine learning, artificial intelligence, data analytics, and Internet of Things (IoT) with prediction approaches to avoid accidental damages, security threats, and theft.

Besides communicating with other vehicles, self-driving cars connected to a 5G network will also be able to communicate with different infrastructure elements that make up our roads and other transportation and communication systems. Similarly, an unmanned aerial vehicle (UAV), an aircraft without any human pilot, crew, or passengers on board, can operate under remote control by a human operator, as a remotely-piloted aircraft (RPA), or with various degrees of autonomy. These include autopilot assistance and fully autonomous aircraft that have no provision for human intervention. Transportation is a necessary, but often painful process. With fully autonomous driving, passengers will be freed to accomplish their own goals, turning the dead hours of driving into fruitful hours of learning, working, engaging, and relaxing. Similarly, UAVs can perform functions that human-operated aircraft cannot, whether because of the environment or high-risk situations.

The purpose of the book is to present the needs, designs, and applications of autonomous vehicles. The topics covered range from mechanical engineering to computer science engineering, both areas playing vital roles in programming, managing, generating alerts, and GPS position, artificial intelligence-based prediction of path and events, as well as other high-tech tools, are covered in this book, as well. Whether for the student, veteran engineer, or another industry professional, this book, and its companion volume, are must-haves for any library.

Author(s): Romil Rawat, Purvee Bhardwaj, Upinder Kaur, Shrikant Telang, Mukesh Chouhan, K. Sakthidasan Sankaran
Publisher: Wiley-Scrivener
Year: 2023

Language: English
Pages: 352
City: Beverly

Cover
Title Page
Copyright Page
Contents
Preface
Chapter 1 A Best Fit Strategic Approach for Sample Selections of a Carrier to Minimizing Quantization Error
1.1 Introduction
1.1.1 Cryptography
1.1.2 Steganography
1.1.3 Watermarking
1.2 Background History
1.3 Literature Survey
1.4 Proposed Methodology
1.4.1 Carrier Selection
1.4.2 Carrier Classification
1.4.3 Searching Best Fit Sample from Class
1.4.4 Updating Result Carrier with Newly Found Best-Fit Sample
1.5 Result Analysis
1.6 Conclusion
1.7 Future Scope
References
Chapter 2 A Dual-Polarized Antenna With Circular Parasitic Element for Autonomous Vehicle
2.1 Introduction
2.2 Autonomous-Vehicle Antenna Design and Principle
2.3 Simulated Parameter Study
2.4 Simulated Results
2.5 Conclusion
References
Chapter 3 A Smart Vehicle Antenna for Defence and Satellite Communication
3.1 Introduction
3.2 Design Principle and Structure
3.3 Stages of Development
3.4 Simulated Parameter Study
3.5 Simulated and Measured Results
3.6 Conclusion
References
Chapter 4 Visual Place Recognition for Simultaneous Localization and Mapping
4.1 Introduction
4.2 The Structure for a Visual Place Recognition System
4.2.1 Image Processing
4.2.1.1 Global Descriptor Extraction
4.2.1.2 Local Descriptors Extraction
4.2.2 Map
4.2.2.1 Single Image-Based
4.2.2.2 Sequence of Images-Based
4.2.3 Belief Generator
4.2.3.1 Pixel-Wise Similarity
4.2.3.2 Euclidean or Cosine Distance
4.2.3.3 Vote Density
4.2.3.4 Temporal Consistency
4.2.3.5 Geometrical Verification
4.3 Evaluation
4.3.1 Ground Truth
4.3.2 Datasets
4.3.3 Evaluation Metrics
4.4 Paradigms
4.4.1 Sequence of Images-Based Visual Word Histograms
4.4.2 Dynamic Sequence Segmentation
4.4.3 Hierarchical Mapping Through an Incremental Visual Vocabulary
4.4.4 Bag of Tracked Words for Incremental Visual Place Recognition
4.5 Experimental Results
4.6 Future Trends and Conclusion
References
Chapter 5 Trust Verification Class (TVCRO) Based Communication for Enhanced of QoS in VANET Environment
5.1 Introduction
5.2 Related Work
5.3 Theoretical Framework
5.4 TVCRO Procedure
5.5 Simulation Setup
5.6 Results and Discussion
5.7 Conclusion
References
Chapter 6 Effective Congestion Control Mechanism for Smart Vehicles Using Edge Computing in VANET
6.1 Introduction
6.2 Related Study
6.3 Proposed Algorithm
6.4 Conclusion
Appendix
References
Chapter 7 Longitudinally Variant 4W4D Robot Slipagge-Based Path Tracking Control
7.1 Introduction
7.2 Related Work
7.3 Vehicle Physical Model
7.4 4W4D Z-Turn Control Law
7.5 Sensing Models
7.6 Path-Tracking Control
7.7 Conclusion
Acknowledgement
References
Chapter 8 Intelligent Autonomous Electric Car
8.1 Introduction
8.2 Related Work
8.3 Intelligent Autonomous System
8.3.1 Object Detection
8.3.1.1 Object Detection Using IR Sensor
8.3.2 Automatic Cooling
8.3.3 Speed Control While Raining
8.3.4 Automatic Charging
8.3.5 Hardware Requirement
8.3.6 Software Requirements
8.4 Results
8.4.1 Object Detection and Tracking
8.4.2 Automatic Cooling
8.4.3 Speed Control While Raining
8.4.4 Automatic Charging
8.5 Conclusions
References
Chapter 9 Cluster Optimization Using Metaheuristic JAYA Algorithm for Secure VANETs
9.1 Introduction
9.1.1 VANET Architecture
9.1.2 VANET Topology
9.1.3 Challenges in VANETs
9.1.4 Security Issues in VANETs
9.1.5 Organization of Chapter
9.2 Literature Review
9.2.1 Available Security Solutions for VANETs
9.2.2 On Trust-Based Security Models
9.2.3 Gaps in Existing Trust Model-Based Security Solutions
9.2.4 On Clustering in VANETs Using Metaheuristic Techniques
9.3 Proposed Work
9.3.1 Overview
9.3.2 Assumptions
9.3.3 Constraints
9.3.4 Proposed Methodology
9.4 Conclusion
References
Chapter 10 Analysis of Domestic Cars in India for Middle-Income Group Using TOPSIS
10.1 Introduction
10.2 Methodology
10.3 Result and Discussion
10.4 Conclusion
References
Chapter 11 A Secure Data Authentication-Based Aerial Intelligent Relay Road Side Unit (AIR-RSU) Framework for Intelligent Transportation System Applications
11.1 Introduction
11.1.1 The Need for Data Authentication
11.1.2 The Objective of the Proposed Model
11.2 Related Works
11.3 Application Scenario of The Working Model
11.4 Working Process
11.4.1 Network Measurement Subsystem
11.4.2 Data Authentication Subsystem
11.4.3 Service Classification Subsystem
11.5 Experimental Process
11.6 Conclusion and Future Works
References
Chapter 12 Evaluation of Vulnerabilities in IoT-Based Intelligent Agriculture Systems
12.1 Introduction
12.1.1 Precision Agriculture
12.1.2 Internet of Things and Machine Learning for Smart Agriculture and Related Security Concerns
12.2 Building Blocks of Internet of Things
12.2.1 Sensors
12.2.2 Control Unit
12.2.3 Communication Module
12.3 Literature Survey
12.4 Security Issues
12.4.1 Heterogeneous Devices and Communication
12.4.2 Integrating Physical Devices
12.4.3 Constrained Devices
12.4.4 Large Scale
12.4.5 Privacy
12.5 Attacks and Vulnerabilities in Internet of Things Related to Agriculture Field
12.6 Conclusion
References
Chapter 13 Q Learning Algorithm for Network Resource Management in Vehicular Communication Network
13.1 Introduction
13.2 Literature Review
13.3 Overview of Network Resource Management in Vehicular Communication Networks
13.4 Reinforcement Learning Techniques for Network Resource Management
13.5 Applications of Q Learning
13.6 Comparative Study and Result Analysis
13.7 Impact of Q-Learning
13.8 Conclusion
References
Chapter 14 Reliable Transportation Solution for Urban Planning: VANET
14.1 Introduction
14.1.1 VANET Architecture
14.1.2 VANET Characteristics
14.1.3 VANET Standards
14.1.4 VANET Communication
14.1.5 Implementation of Optimisation Algorithm for VANETs
14.2 Cryptography
14.2.1 Salient Features of Cryptography
14.2.2 Classification of Cryptography (as shown in Figure 14.2)
14.3 Common Security Attacks
14.4 Gaps in Present Cryptography
14.5 Lightweight Cryptography
14.5.1 Vital Security Aspects in Lightweight Cryptography
14.5.2 Advantages of Lightweight Protocols
14.5.3 Objectives of Lightweight Protocols are Classified as
14.5.4 Lightweight Cryptography Algorithms
14.5.5 Software and Hardware Implementation
14.5.5.1 Hardware Lightweight Cryptography
14.5.5.2 Software Lightweight Cryptography
14.5.6 Division of Lightweight Cryptography
14.5.6.1 Symmetric Key Algorithm
14.5.6.2 Asymmetric Key
14.6 Conclusion
14.7 Future Work
References
Chapter 15 Implementation of Veco-Taxis in Turbulent Environment for Gas Source Localization
15.1 Introduction
15.2 Literature Survey
15.3 Methodology
15.4 Results and Discussions
15.5 Conclusions
References
Chapter 16 A Technique for Monitoring Cyber-Attacks on Self-Driving Automobiles-Based VANET
16.1 Introduction
16.2 Related Work
16.3 Examining the Proposed Framework
16.4 Conclusion
References
About the Editors
Index
EULA