What are the basic principles of autonomous driving?

The basic principles of autonomous driving involve a combination of sensors, artificial intelligence (AI), and real-time data processing to enable vehicles to navigate and make decisions without human intervention. Here's a breakdown:

1. Perception: The vehicle uses sensors like LiDAR, radar, cameras, and ultrasonic sensors to detect and interpret its surroundings, including other vehicles, pedestrians, traffic signs, and road conditions.

   • Example: Cameras identify lane markings, while LiDAR measures distances to objects with high precision.

2. Localization: The system determines the vehicle's exact position on a map using GPS, inertial measurement units (IMUs), and sensor fusion.

   • Example: High-definition maps combined with real-time sensor data help the car pinpoint its location within centimeters.

3. Path Planning: AI algorithms calculate the safest and most efficient route, considering traffic rules, obstacles, and dynamic changes in the environment.

   • Example: The system adjusts the trajectory to avoid a suddenly stopping car ahead.

4. Control: The vehicle executes the planned path by controlling acceleration, braking, and steering through electronic control units (ECUs).

   • Example: The car smoothly slows down when approaching a red light.

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