OpenHUTB/nn
Apr 2026 – Apr 2026
1 Month active
Languages Used
Python
Technical Skills
Game DevelopmentPID controlPythonPython programmingSimulation Developmentautomated driving
soyo0001
PROFILE
Soyo0001
Developed a comprehensive Driving Assist System (ADAS) for the OpenHUTB/nn repository, delivering automated and assisted driving features such as adaptive cruise control, lane keeping, and pedestrian detection with automatic emergency braking. Leveraged Python and simulation development skills to implement perception, decision, and control layers, integrating computer vision techniques for traffic light and sign recognition, as well as weather-adaptive lighting. Enhanced safety and automation-readiness by supporting both manual and autonomous driving modes. Improved developer productivity through detailed CARLA-native documentation and architecture overviews, enabling easier onboarding and collaboration. The work established a robust foundation for future automotive system deployments.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
9Total
Bugs
0
Commits
9
Features
2
Lines of code
1,428
Activity Months1
Your Network
263 peopleWork History
April 2026
9 Commits • 2 Features
Apr 1, 2026April 2026 monthly summary for OpenHUTB/nn: Delivered a comprehensive Driving Assist System (ADAS) enabling automated and assisted driving modes across perception, decision, and control layers. Implemented end-to-end features including adaptive cruise control, lane keeping, traffic light and sign recognition, lane departure warnings, forward collision warning, pedestrian detection with automatic emergency braking, and weather-based adaptive lighting. Strengthened safety, reliability, and developer productivity through parallel feature work, extensive README coverage, and CARLA-native documentation. The work demonstrates business value in safety, compliance, and automation-readiness, and lays groundwork for broader deployment.
9 Commits • 2 Features
Apr 1, 2026April 2026 monthly summary for OpenHUTB/nn: Delivered a comprehensive Driving Assist System (ADAS) enabling automated and assisted driving modes across perception, decision, and control layers. Implemented end-to-end features including adaptive cruise control, lane keeping, traffic light and sign recognition, lane departure warnings, forward collision warning, pedestrian detection with automatic emergency braking, and weather-based adaptive lighting. Strengthened safety, reliability, and developer productivity through parallel feature work, extensive README coverage, and CARLA-native documentation. The work demonstrates business value in safety, compliance, and automation-readiness, and lays groundwork for broader deployment.
April 2026
Activity
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Quality Metrics
Correctness89.0%
Maintainability82.2%
Architecture82.2%
Performance82.2%
AI Usage49.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Game DevelopmentPID controlPythonPython programmingSimulation Developmentautomated drivingautomated driving systemsautomotive engineeringautomotive systemsautonomous drivingcollision detectioncomputer visionfull stack developmentgame developmentimage processing
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