
Developed an end-to-end autonomous driving control system in the OpenHUTB/nn repository, integrating YOLOv8-based real-time traffic sign detection with robust vehicle control logic in the CARLA simulator. Leveraged Python and deep learning to enable the vehicle to recognize and respond to traffic signs, while redesigning the controller for improved stability and responsiveness. Enhanced operator visibility by building a real-time dashboard that visualizes vehicle metrics and detected signs using Pygame. Improved project accessibility through deployment scripts, batch files, and localized documentation, including a Chinese README, streamlining onboarding and testing for new users and supporting cross-team collaboration and maintainability.
2026-04 OpenHUTB/nn monthly summary: Implemented end-to-end autonomy enablement in CARLA by combining perception (YOLOv8-based traffic sign detection) with robust control logic, enhanced operator visibility through a real-time vehicle status dashboard, and improved project accessibility via deployment scripts and localized documentation. These changes deliver safer, more observable autonomous behavior and accelerate onboarding and testing.
2026-04 OpenHUTB/nn monthly summary: Implemented end-to-end autonomy enablement in CARLA by combining perception (YOLOv8-based traffic sign detection) with robust control logic, enhanced operator visibility through a real-time vehicle status dashboard, and improved project accessibility via deployment scripts and localized documentation. These changes deliver safer, more observable autonomous behavior and accelerate onboarding and testing.

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