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Introduction

With the advancement of technology, autonomous vehicles have become a promising solution for improving road safety, reducing traffic congestion, and increasing mobility for individuals. These vehicles rely on a multitude of sensors and data processing capabilities to navigate and make decisions in real-time. However, the massive amount of data generated by these sensors poses a significant challenge for traditional cloud computing systems in terms of latency, reliability, and security.

Edge computing has emerged as a potential solution to address these challenges by bringing computation and data storage closer to the source of data generation. This thesis aims to explore the role of edge computing in enhancing the performance and efficiency of autonomous vehicles.

Chapter 1: Introduction
1.1 Introduction
1.2 Background of study
1.3 Problem Statement
1.4 Objective of study
1.5 Limitation of study
1.6 Scope of study
1.7 Significance of study
1.8 Structure of the Thesis
1.9 Definition of terms

Chapter 2: Literature Review
2.1 Overview of autonomous vehicles
2.2 Evolution of edge computing
2.3 Edge computing architecture
2.4 Applications of edge computing in autonomous vehicles
2.5 Challenges of implementing edge computing in autonomous vehicles
2.6 Comparison of edge computing and cloud computing
2.7 Security and privacy concerns in edge computing for autonomous vehicles
2.8 Edge computing technologies for autonomous vehicles
2.9 Case studies of edge computing implementation in autonomous vehicles
2.10 Future trends in edge computing for autonomous vehicles

Chapter 3: Research Methodology
3.1 Research design
3.2 Data collection methods
3.3 Data analysis techniques
3.4 Participant selection
3.5 Ethical considerations
3.6 Pilot study
3.7 Data validation
3.8 Limitations of the research

Chapter 4: Discussion of Findings
4.1 Overview of the findings
4.2 Analysis of the data
4.3 Comparison with existing literature
4.4 Implications of the findings
4.5 Recommendations for future research
4.6 Practical implications
4.7 Managerial implications
4.8 Policy recommendations

Chapter 5: Conclusion and Summary
5.1 Summary of the research
5.2 Contribution of the study
5.3 Implications for practice
5.4 Recommendations for further research
5.5 Conclusion

Thesis Overview on Edge Computing for Autonomous Vehicles

The rise of autonomous vehicles has brought forth a new era of transportation, promising safer roads and increased mobility for individuals. However, the success of autonomous vehicles hinges on their ability to process and analyze vast amounts of data in real-time, a task that traditional cloud computing systems struggle to handle efficiently.

Edge computing has emerged as a viable solution to this challenge by bringing computation and data storage closer to the source of data generation, reducing latency and improving reliability and security. This thesis seeks to investigate the role of edge computing in enhancing the performance and efficiency of autonomous vehicles.

In Chapter 1, the introduction provides an overview of the research topic, highlighting the background, problem statement, objectives, limitations, scope, significance, and structure of the thesis. Chapter 2 presents a comprehensive review of the literature on autonomous vehicles, edge computing, and their intersection, including applications, challenges, security concerns, technologies, and case studies.

Chapter 3 details the research methodology, outlining the design, data collection methods, analysis techniques, participant selection, ethical considerations, pilot study, data validation, and limitations. Chapter 4 discusses the findings of the research, analyzing the data, comparing with existing literature, and providing implications and recommendations for future research, practice, and policy.

Finally, Chapter 5 offers a conclusion and summary of the thesis, summarizing the research, highlighting its contribution, outlining implications for practice, and providing recommendations for further research. Through this comprehensive examination, this thesis aims to contribute to the understanding and development of edge computing for autonomous vehicles, paving the way for safer, more efficient, and more reliable autonomous transportation systems.

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