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Autonomous Vehicles Volume 1

Using Machine Intelligence
Edited by Romil Rawat, A. Mary Sowjanya, Syed Imran Patel, Varshali Jaiswal, Imran Khan, and Allam Balaram
Copyright: 2023   |   Status: Published
ISBN: 9781119871958  |  Hardcover  |  
350 pages
Price: $225 USD
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One Line Description
Addressing the current challenges, approaches and applications relating to autonomous vehicles, this groundbreaking new volume presents the research and techniques in this growing area, using Internet of Things, Machine Learning, Deep Learning, and Artificial Intelligence.

Audience
Academic researchers, research scholars, practitioners, students, traffic engineers, city planners, consultants, traffic planners, vehicle designers and all key stakeholders working on intelligent engineering solutions

Description
This book provides and addresses the current challenges, approaches and applications relating to autonomous vehicles, using Internet of Things (IoT), Machine Learning, Deep Learning, and Artificial Intelligence (AI) techniques. Several self-driving or autonomous (“driverless”) cars, trucks, and drones incorporate a variety of IoT devices and sensing technologies such as sensors, gyroscopes, cloud computing, and fog layer, allowing the vehicles to sense, process, and maintain massive amounts of data on traffic, routes, suitable times to travel, potholes, sharp turns, and robots for pipe inspection in the construction and mining industries.

Few books are available on the practical applications of unmanned aerial vehicles (UAVs) and autonomous vehicles from a multidisciplinary approach. Further, the books that are available only cover a few applications and designs in a very limited scope. This new, groundbreaking volume covers real life applications, business modeling, issues and solutions that the engineer or industry professional faces every day that can be transformed using intelligent systems design of autonomous systems. Whether for the student, veteran engineer, or other industry professional, this book, and its companion volume, are must haves for any library.

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Author / Editor Details
Romil Rawat, PhD, is an assistant professor at Shri Vaishnav Vidyapeeth Vishwavidyalaya, Indore. With over 12 years of teaching experience, he has published numerous papers in scholarly journals and conferences. He has also published book chapters and is a board member on two scientific journals. He has received several research grants and has hosted research events, workshops, and training programs. He also has several patents to his credit.

A. Mary Sowjanya, PhD, is a faculty member in the Department of Computer Science and Systems Engineering at Andhra University, India. She has three patents to her credit and has more than 70 research publications. She also received the "Young Faculty Research Fellowship Award" under the Viswerayya program by the government of India.

Syed Imran Patel is a lecturer, education program manager, and lead internal verifier at Bahrain Training Institute, HEC, EDUC-Information System Training Programs, Ministry of Education, Bahrain. With his expertise, he contributes to the Quality Assurance Committee, the Grade and Credit Transfer Committee, and the Curriculum Development Committee.

Varshali Jaiswal, PhD, is an assistant professor at Vellore Institute of Technology, Bhopal, India. She has over 12 years of experience in the field of academics. She has published more than seven papers in international journals and conferences.

Imran Khan is a faculty member at the Bahrain Training Institute, Higher Education Council, Ministry of Education, Bahrain. Before this, he was a lecturer at Sirt University, Ministry of Education, Libya and an assistant professor at Osmania University.

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Table of Contents
Preface
1. Anomalous Activity Detection Using Deep Learning Techniques in Autonomous Vehicles
Amit Juyal, Sachin Sharma and Priya Matta
1.1 Introduction
1.1.1 Organization of Chapter
1.2 Literature Review
1.3 Artificial Intelligence in Autonomous Vehicles
1.4 Technologies Inside Autonomous Vehicle
1.5 Major Tasks in Autonomous Vehicle Using AI
1.6 Benefits of Autonomous Vehicle
1.7 Applications of Autonomous Vehicle
1.8 Anomalous Activities and Their Categorization
1.9 Deep Learning Methods in Autonomous Vehicle
1.10 Working of Yolo
1.11 Proposed Methodology
1.12 Proposed Algorithms
1.13 Comparative Study and Discussion
1.14 Conclusion
References
2. Algorithms and Difficulties for Autonomous Cars Based on Artificial Intelligence
Sumit Dhariwal, Avani Sharma and Avinash Raipuria
2.1 Introduction
2.1.1 Algorithms for Machine Learning in Autonomous Driving
2.1.2 Regression Algorithms
2.1.3 Design Identification Systems (Classification)
2.1.4 Grouping Concept
2.1.5 Decision Matrix Algorithms
2.2 In Autonomous Cars, AI Algorithms are Applied
2.2.1 Algorithms for Route Planning and Control
2.2.2 Method for Detecting Items
2.2.3 Algorithmic Decision-Making
2.3 AI’s Challenges with Self-Driving Vehicles
2.3.1 Feedback in Real Time
2.3.2 Complexity of Computation
2.3.3 Black Box Behavior
2.3.4 Precision and Dependability
2.3.5 The Safeguarding
2.3.6 AI and Security
2.3.7 AI and Ethics
2.4 Conclusion
References
3. Trusted Multipath Routing for Internet of Vehicles against DDoS Assault Using Brink Controller in Road Awareness (TMRBC-IOV
Piyush Chouhan and Swapnil Jain
3.1 Introduction
3.2 Related Work
3.3 VANET Grouping Algorithm (VGA)
3.4 Extension of Trusted Multipath Distance Vector Routing (TMDR-Ext)
3.5 Conclusion
References
4. Technological Transformation of Middleware and Heuristic Approaches for Intelligent Transport System
Rajender Kumar, Ravinder Khanna and Surender Kumar
4.1 Introduction
4.2 Evolution of VANET
4.3 Middleware Approach
4.4 Heuristic Search
4.5 Reviews of Middleware Approaches
4.6 Reviews of Heuristic Approaches
4.7 Conclusion and Future Scope
References
5. Recent Advancements and Research Challenges in Design and Implementation of Autonomous Vehicles
Mohit Kumar and V. M. Manikandan
5.1 Introduction
5.1.1 History and Motivation
5.1.2 Present Scenario and Need for Autonomous Vehicles
5.1.3 Features of Autonomous Vehicles
5.1.4 Challenges Faced by Autonomous Vehicles
5.2 Modules/Major Components of Autonomous Vehicles
5.2.1 Levels of Autonomous Vehicles
5.2.2 Functional Components of An Autonomous Vehicle
5.2.3 Traffic Control System of Autonomous Vehicles
5.2.4 Safety Features Followed by Autonomous Vehicles
5.3 Testing and Analysis of An Autonomous Vehicle in a Virtual Prototyping Environment
5.4 Application Areas of Autonomous Vehicles
5.5 Artificial Intelligence (AI) Approaches for Autonomous Vehicles
5.5.1 Pedestrian Detection Algorithm (PDA)
5.5.2 Road Signs and Traffic Signal Detection
5.5.3 Lane Detection System
5.6 Challenges to Design Autonomous Vehicles
5.7 Conclusion
References
6. Review on Security Vulnerabilities and Defense Mechanism in Drone Technology
Chaitanya Singh and Deepika Chauhan
6.1 Introduction
6.2 Background
6.3 Security Threats in Drones
6.3.1 Electronics Attacks
6.3.1.1 GPS and Communication Jamming Attacks
6.3.1.2 GPS and Communication Spoofing Attacks
6.3.1.3 Eavesdropping
6.3.1.4 Electromagnetic Interference
6.3.1.5 Laser Attacks
6.3.2 Cyber-Attacks
6.3.2.1 Man-in-Middle Attacks
6.3.2.2 Black Hole and Grey Hole
6.3.2.3 False Node Injection
6.3.2.4 False Communication Data Injection
6.3.2.5 Firmware’s Manipulations
6.3.2.6 Sleep Deprivation
6.3.2.7 Malware Infection
6.3.2.8 Packet Sniffing
6.3.2.9 False Database Injection
6.3.2.10 Replay Attack
6.3.2.11 Network Isolations
6.3.2.12 Code Injection
6.3.3 Physical Attacks
6.3.3.1 Key Logger Attacks
6.3.3.2 Camera Spoofing
6.4 Defense Mechanism and Countermeasure Against Attacks
6.4.1 Defense Techniques for GPS Spoofing
6.4.2 Defense Technique for Man-in-Middle Attacks
6.4.3 Defense against Keylogger Attacks
6.4.4 Defense against Camera Spoofing Attacks
6.4.5 Defense against Buffer Overflow Attacks
6.4.6 Defense against Jamming Attack
6.5 Conclusion
References
7. Review of IoT-Based Smart City and Smart Homes Security Standards in Smart Cities and Home Automation
Dnyaneshwar Vitthal Kudande, Chaitanya Singh and Deepika Chauhan
7.1 Introduction
7.2 Overview and Motivation
7.3 Existing Research Work
7.4 Different Security Threats Identified in IoT-Used Smart Cities and Smart Homes
7.4.1 Security Threats at Sensor Layer
7.4.1.1 Eavesdropping Attacks
7.4.1.2 Node Capturing Attacks
7.4.1.3 Sleep Deprivation Attacks
7.4.1.4 Malicious Code Injection Attacks
7.4.2 Security Threats at Network Layer
7.4.2.1 Distributed Denial of Service (DDOS) Attack
7.4.2.2 Sniffing Attack
7.4.2.3 Routing Attack
7.4.2.4 Traffic Examination Attacks
7.4.3 Security Threats at Platform Layer
7.4.3.1 SQL Injection
7.4.3.2 Cloud Malware Injection
7.4.3.3 Storage Attacks
7.4.3.4 Side Channel Attacks
7.4.4 Security Threats at Application Layer
7.4.4.1 Sniffing Attack
7.4.4.2 Reprogram Attack
7.4.4.3 Data Theft
7.4.4.4 Malicious Script Attack
7.5 Security Solutions For IoT-Based Environment in Smart Cities and Smart Homes
7.5.1 Blockchain
7.5.2 Lightweight Cryptography
7.5.3 Biometrics
7.5.4 Machine Learning
7.6 Conclusion
References
8. Traffic Management for Smart City Using Deep Learning
Puja Gupta and Upendra Singh
8.1 Introduction
8.2 Literature Review
8.3 Proposed Method
8.4 Experimental Evaluation
8.4.1 Hardware and Software Configuration
8.4.2 About Dataset
8.4.3 Implementation
8.4.4 Result
8.5 Conclusion
References
9. Cyber Security and Threat Analysis in Autonomous Vehicles
Siddhant Dash and Chandrashekhar Azad
9.1 Introduction
9.2 Autonomous Vehicles
9.2.1 Autonomous vs. Automated
9.2.2 Significance of Autonomous Vehicles
9.2.3 Challenges in Autonomous Vehicles
9.2.4 Future Aspects
9.3 Related Works
9.4 Security Problems in Autonomous Vehicles
9.4.1 Different Attack Surfaces and Resulting Attacks
9.5 Possible Attacks in Autonomous Vehicles
9.5.1 Internal Network Attacks
9.5.2 External Attacks
9.6 Defence Strategies against Autonomous Vehicle Attacks
9.6.1 Against Internal Network Attacks
9.6.2 Against External Attack
9.7 Cyber Threat Analysis
9.8 Security and Safety Standards in AVs
9.9 Conclusion
References
10. Big Data Technologies in UAV’s Traffic Management System: Importance, Benefits, Challenges and Applications
Piyush Agarwal, Sachin Sharma and Priya Matta
10.1 Introduction
10.2 Literature Review
10.3 Overview of UAV’s Traffic Management System
10.4 Importance of Big Data Technologies and Algorithm
10.5 Benefits of Big Data Techniques in UTM
10.6 Challenges of Big Data Techniques in UTM
10.7 Applications of Big Data Techniques in UTM
10.8 Case Study and Future Aspects
10.9 Conclusion
References
11. Reliable Machine Learning-Based Detection for Cyber Security Attacks on Connected and Autonomous Vehicles
Ambika N.
11.1 Introduction
11.2 Literature Survey
11.3 Proposed Architecture
11.4 Experimental Results
11.5 Analysis of the Proposal
11.6 Conclusion
References
12. Multitask Learning for Security and Privacy in IoV (Internet of Vehicles
Malik Mustafa, Ahmed Mateen Buttar, Guna Sekhar Sajja, Sanjeev Gour, Mohd Naved and P. William
12.1 Introduction
12.2 IoT Architecture
12.3 Taxonomy of Various Security Attacks in Internet of Things
12.3.1 Perception Layer Attacks
12.3.2 Network Layer Attacks
12.3.3 Application Layer Attacks
12.4 Machine Learning Algorithms for Security and Privacy in IoV
12.5 A Machine Learning-Based Learning Analytics Methodology for Security and Privacy in Internet of Vehicles
12.5.1 Methodology
12.5.2 Result Analysis
12.6 Conclusion
References
13. ML Techniques for Attack and Anomaly Detection in Internet of Things Networks
Vinod Mahor, Sadhna Bijrothiya, Rina Mishra and Romil Rawat
13.1 Introduction
13.2 Internet of Things
13.3 Cyber-Attack in IoT
13.4 IoT Attack Detection in ML Technics
13.5 Conclusion
References
14. Applying Nature-Inspired Algorithms for Threat Modeling in Autonomous Vehicles
Manas Kumar Yogi, Siva Satya Prasad Pennada, Sreeja Devisetti and Sri Siva Lakshmana Reddy Dwarampudi
14.1 Introduction
14.2 Related Work
14.3 Proposed Mechanism
14.4 Performance Results
14.5 Future Directions
14.6 Conclusion
References
15. The Smart City Based on AI and Infrastructure: A New Mobility Concepts and Realities
Vinod Mahor, Sadhna Bijrothiya, Rina Mishra, Romil Rawat and Alpesh Soni
15.1 Introduction
15.2 Research Method
15.3 Vehicles that are Both Networked and Autonomous
15.4 Personal Aerial Automobile Vehicles and Unmanned Aerial Automobile Vehicles
15.5 Mobile Connectivity as a Service
15.6 Major Role for Smart City Development with IoT and Industry 4.0
15.7 Conclusion
References
Index

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