Autonomous vehicles navigate and make decisions using a combination of computer vision, sensor data, and machine learning. Cameras, LiDAR, and radar capture the surroundings, while AI models process this data to detect objects like pedestrians, vehicles, and traffic signs.
Path planning algorithms calculate safe routes based on real-time inputs, considering road conditions and traffic. Deep learning models, particularly CNNs, are crucial for tasks like lane detection and obstacle recognition.
The integration of sensor fusion and AI allows vehicles to adapt to dynamic environments, ensuring safety and efficiency in navigation.