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  • A Python Pygame environment for developing and testing reinforcement-learning autonomous driving agents on customizable tracks.
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    What is SelfDrivingCarSimulator?
    SelfDrivingCarSimulator is a lightweight Python framework built on Pygame that offers a 2D driving environment for training autonomous vehicle agents using reinforcement learning. It supports customizable track layouts, configurable sensor models (like LiDAR and camera emulation), real-time visualization, and data logging for performance analysis. Developers can integrate their RL algorithms, adjust physics parameters, and monitor metrics such as speed, collision rate, and reward functions to iterate quickly on self-driving research and educational projects.
    SelfDrivingCarSimulator Core Features
    • 2D self-driving car simulation via Pygame
    • Customizable track editor
    • Configurable sensor models (camera, LiDAR)
    • Reinforcement learning algorithm integration
    • Real-time visualization and metrics logging
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