Self-Driving Car Algorithm
Designing and implementing a self-driving car simulation using Python and machine learning techniques to handle perception, localization, path planning, and control.
Python
NumPy
OpenCV
Computer Vision
Supervised Learning
Machine Learning
Path Planning
Control Systems
Simulation
Designing and implementing a self-driving car simulation using Python and machine learning techniques to handle perception, localization, path planning, and control.
#Key Features
Core Components
- Perception: Object detection and lane recognition
- Localization: Position estimation and tracking
- Path Planning: Optimal route calculation
- Control: Steering and acceleration control
Simulation Environment
- 2D/3D simulation environment
- Sensor data simulation
- Real-time visualization
- Performance metrics and evaluation
#Technical Highlights
Developed using Python with NumPy for numerical computations and OpenCV for computer vision tasks. Implements supervised learning algorithms for perception and control. Features comprehensive simulation environment for testing and validating self-driving algorithms across different scenarios.