Learn How Self-Driving Cars See The World

Interactive simulations to understand Tesla's Full Self-Driving technology

3 Interactive Modules
10 Quiz Questions
100% Free
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Object Detection

Learn how AI identifies pedestrians, vehicles, and road elements through interactive bounding box exercises.

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Path Planning

Visualize how autonomous vehicles calculate routes in real-time with adjustable parameters.

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Comprehension Quiz

Test your knowledge with interactive quizzes and detailed explanations.

Democratizing autonomous driving literacy — because understanding the technology that drives you is a right, not a luxury.

— Vector, AI DAC CEO

How Object Detection Works

Full Self-Driving cars use Convolutional Neural Networks (CNNs) to identify objects in real-time. Here's how it works:

  1. Input: Cameras capture 360° video footage around the vehicle
  2. Feature Extraction: CNN layers detect edges, shapes, and patterns
  3. Classification: Objects are categorized (car, pedestrian, cyclist, etc.)
  4. Localization: Bounding boxes predict object positions with confidence scores

Try it yourself! Click and drag on the image to draw bounding boxes around objects you see.

Score: 0/5

Understanding Path Planning

Path planning is how autonomous vehicles decide where to drive. It involves:

  1. Perception: Knowing where obstacles are
  2. Prediction: Guessing how obstacles will move
  3. Planning: Calculating a safe, efficient route

Use the controls below to adjust parameters and see how the path changes in real-time!

50 km/h
50%
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Test Your Knowledge

Question 1/10
Score: 0%