Artificial Intelligence in Autonomous Vehicles – Complete Phd and Masters Thesis

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Table of Contents:

Chapter One: Introduction
1.1 Background of the Study
1.2 Research Problem
1.3 Research Questions
1.4 Objectives of the Study
1.5 Significance of the Study
1.6 Scope of the Study
1.7 Limitations of the Study

Chapter Two: Literature Review
2.1 Introduction to Artificial Intelligence in Autonomous Vehicles
2.2 Evolution of Autonomous Vehicles
2.3 Current trends in AI for Autonomous Vehicles
2.4 Challenges and Opportunities in AI for Autonomous Vehicles
2.5 Impact of AI on the Future of Autonomous Vehicles

Chapter Three: Research Methodology
3.1 Research Design
3.2 Data Collection Methods
3.3 Data Analysis Techniques
3.4 Sampling and Sample Size
3.5 Ethical Considerations

Chapter Four: Discussion of Findings
4.1 Overview of Findings
4.2 Analysis of Data
4.3 Comparison with Existing Literature
4.4 Implications of Findings
4.5 Recommendations for Future Research

Chapter Five: Conclusion and Summary
5.1 Summary of Key Findings
5.2 Conclusion
5.3 Contributions to the Field
5.4 Limitations of the Study
5.5 Recommendations for Practitioners

Brief Overview:

Artificial Intelligence in Autonomous Vehicles is a rapidly evolving field that holds great promise for revolutionizing the transportation industry. This thesis explores the application of AI in autonomous vehicles, examining its impact on safety, efficiency, and overall driving experience. The study aims to provide insights into current trends, challenges, and opportunities in AI for autonomous vehicles, with a focus on the future implications in the field.

The literature review delves into the evolution of autonomous vehicles, highlighting key advancements and breakthroughs in AI technology. It also discusses the current state of the art in AI for autonomous vehicles, including the use of machine learning, deep learning, and computer vision algorithms. The research methodology section outlines the design and approach used in the study, including data collection methods, analysis techniques, and ethical considerations.

The discussion of findings presents an analysis of the data collected, comparing it with existing literature and identifying implications for the future of AI in autonomous vehicles. The conclusion and summary section summarizes the key findings, highlights the contributions of the study, and provides recommendations for practitioners and future research directions. Overall, this thesis provides a comprehensive overview of the role of AI in autonomous vehicles and its potential to shape the future of transportation.

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