• 자동차안전학회지
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• 제14권4호
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• pp.6-15
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• 2022

In this study, a traffic light recognition algorithm was implemented and validated for low-speed special purpose vehicles in an urban environment. Real-time image data using a camera and YOLO algorithm were applied. Two methods were presented to increase the accuracy of the traffic light recognition algorithm, and it was confirmed that the second method had the higher accuracy according to the traffic light type. In addition, it was confirmed that the optimal YOLO algorithm was YOLO v5m, which has over 98% mAP values and higher efficiency. In the future, it is thought that the traffic light recognition algorithm can be used as a dual system to secure the platform safety in the traffic information error of C-ITS.

• 드라이브 ㆍ 컨트롤
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• 제19권3호
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• pp.32-38
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• 2022

The in-wheel drive gearbox for military special vehicles converts the high-speed & low-torque output generated by the electric servomotor, into low-speed & high-torque mechanical power. As the vehicle is remotely maneuvered in mountainous terrain, wet fields, rough terrain, etc., the gearbox must generate a maximum input speed exceeding 5,000 rpm, a maximum torque of 245 Nm, and MTBF of 9,600 km. The purpose of this study was to analyze the failure mode of the gearbox, to ensure the durability of the in-wheel drive gearbox. Also, the field load test data of the vehicle was analyzed, the acceleration durability test standards were established, the acceleration durability test was conducted, and the durability test results were analyzed as well.