Built as an A-Level OCR Computer Science programming project, this Unity simulation trained cars to navigate around a track using custom-built feed-forward neural networks and reinforcement learning rather than third-party ML libraries. The project combined car physics, sensor-style inputs, reward feedback, model loading and saving, training controls and visual feedback. It was accompanied by an approximately 50,000-word project report explaining the system design, development process and evaluation.
OCR A-Level CS
Course
Unity
Engine
C#
Language
50k words
Writeup
Key details
- Built the car physics, driving simulation and track-navigation environment in Unity.
- Implemented feed-forward neural networks and reinforcement learning logic manually in C# using default Unity libraries.
- Added model loading and saving so trained networks could be reused between sessions.
- Built training controls and visual feedback for inspecting whether cars were learning valid track behaviour.
- Produced a substantial written A-Level project report explaining the system and development process.