<p>1. Introduction<br> 1.1 Background<br> 1.2 Motivation<br> 1.3 Objectives<br>2. Literature Review<br> 2.1 Computer Vision in Autonomous Vehicles<br> 2.2 Sensor Fusion and Perception Algorithms<br> 2.3 Safety and Regulatory Considerations<br>3. Sensor Integration and Calibration<br> 3.1 Camera and LiDAR Sensor Selection<br> 3.2 Sensor Fusion Techniques<br> 3.3 Calibration and Synchronization<br>4. Perception and Decision-Making Algorithms<br> 4.1 Object Detection and Classification<br> 4.2 Lane Detection and Tracking<br> 4.3 Path Planning and Collision Avoidance<br>5. Control Interface Design<br> 5.1 Human-Machine Interface for Autonomous Driving<br> 5.2 Emergency Response and Fail-Safe Mechanisms<br></p>
This project aims to develop a computer vision system for autonomous vehicles, enabling real-time perception and decision-making capabilities for safe and efficient navigation. The system will utilize cameras, LiDAR, and radar sensors to capture and process environmental data, enabling object detection, lane tracking, and obstacle avoidance. The project will involve sensor integration, algorithm development, and the implementation of a control interface for autonomous driving.
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