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Introduction

Edge computing has emerged as a key technology in the realm of connected and autonomous vehicles, offering the potential to enhance the performance and efficiency of next-generation automotive systems. By enabling data processing and storage to take place closer to the source of data generation, edge computing reduces latency and improves real-time decision-making capabilities. This thesis explores the role of edge computing in the context of connected and autonomous vehicles, with a focus on its benefits, challenges, and implications for the future of transportation.

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 Two: Literature Review

2.1 Overview of Edge Computing in the Automotive Industry

2.2 Benefits of Edge Computing for Connected and Autonomous Vehicles

2.3 Challenges and Limitations of Edge Computing in Automotive Applications

2.4 Edge Computing Technologies and Architectures

2.5 Edge-Cloud Integration for Automotive Systems

2.6 Security and Privacy Considerations in Edge Computing for Connected Vehicles

2.7 Standards and Regulations for Edge Computing in Automotive Industry

2.8 Case Studies on Edge Computing Implementation in Connected and Autonomous Vehicles

2.9 Future Trends and Research Directions in Edge Computing for Automotive Applications

2.10 Summary of Literature Review

Chapter Three: Research Methodology

3.1 Research Design

3.2 Data Collection Methods

3.3 Data Analysis Techniques

3.4 Sampling Approach

3.5 Research Instruments

3.6 Ethical Considerations

3.7 Case Study Approach

3.8 Limitations of Research Methodology

Chapter Four: Discussion of Findings

4.1 Overview of Data Analysis Results

4.2 Interpretation of Findings

4.3 Comparison with Existing Literature

4.4 Implications for Connected and Autonomous Vehicles Industry

4.5 Recommendations for Future Research

4.6 Practical Implications for Automotive Industry

4.7 Challenges and Opportunities

Chapter Five: Conclusion and Summary

5.1 Summary of Research Findings

5.2 Contributions to the Field

5.3 Implications for Practice

5.4 Recommendations for Industry Stakeholders

5.5 Conclusion and Future Directions

Thesis Overview: Edge Computing for Connected and Autonomous Vehicles

The rapid advancement of connected and autonomous vehicles has revolutionized the automotive industry, paving the way for safer, more efficient, and environmentally friendly transportation solutions. In the era of smart mobility, edge computing has emerged as a critical enabler of real-time data processing and decision-making capabilities for connected vehicles. This thesis explores the role of edge computing in enhancing the performance and efficiency of connected and autonomous vehicles, with a focus on its benefits, challenges, and implications for the future of transportation.

Chapter One provides an introduction to the research topic, offering a background of the study, problem statement, objectives, limitations, scope, significance, structure of the thesis, and definitions of key terms in the field of edge computing for connected and autonomous vehicles.

Chapter Two presents a comprehensive literature review on edge computing in the automotive industry, including its benefits, challenges, technologies, security considerations, standards, case studies, and future trends. This chapter sets the theoretical foundation for the research study and identifies gaps in existing knowledge.

Chapter Three details the research methodology employed in the study, including research design, data collection methods, analysis techniques, sampling approach, instruments, ethical considerations, case study approach, and limitations. This chapter provides insights into the research process and the rationale behind the chosen methodology.

Chapter Four discusses the findings of the research study, offering an overview of data analysis results, interpretation of findings, comparisons with existing literature, implications for the automotive industry, recommendations for future research, practical implications, challenges, and opportunities. This chapter presents a critical analysis of the research findings and their significance for the field.

Chapter Five concludes the thesis by summarizing the research findings, highlighting the contributions to the field, implications for practice, recommendations for industry stakeholders, and future directions for research. This chapter provides a comprehensive overview of the key insights gained from the study and outlines avenues for further exploration in the domain of edge computing for connected and autonomous vehicles.

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