Developing Real-Time Object Detection Models with Reinforcement Learning in Autonomous Driving Systems

1. Introduction 1.1 Background and Motivation 1.2 Objective of the Research 1.3 Structure of the Thesis 2. Literature Review 2.1 Object Detection in Autonomous Driving 2.2 Reinforcement Learning: An Overview 2.3 Integration of RL and Object Detection 3. Theoretical Framework 3.1 Principles of Reinforcement Learning 3.2 Object Detection Models Explained 3.3 Challenges in Real-Time Detection 4. Methodology 4.1 Research Design 4.2 Data Collection and Preparation 4.3 Model Development Process 4.4 Evaluation Criteria 5. Implementation of Models 5.1 Training Environment Setup 5.2 Tech Stack and Tools Used 5.3 Model Training Techniques 6. Experimental Results 6.1 Evaluation Metrics 6.2 Performance Analysis 6.3 Comparisons with Existing Solutions 7. Discussion and Implications 7.1 Interpretation of Results 7.2 Implications for Autonomous Systems 7.3 Limitations of the Study 8. Conclusion 8.1 Summary of Findings 8.2 Future Research Directions 8.3 Final Thoughts and Recommendations