• Journal of Advanced Marine Engineering and Technology
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• v.21 no.4
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• pp.381-386
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• 1997

The offsetting method using geometric properties of B-spline control polygon is more faster than using of general normal vector in offset processing. But this method itself does not solve the prob¬lems of loop removal in normal offsetting. Generally the distance between neighborhood spans of B-spline control polygon is greater than the offset distance, the loops are occurred in offsetting. For generating of the more precision tool-path in NC machining, the loops of offset must be removed. In this paper, two methods for loop removal are introduced in offsetting of B-spline curve. One is using the intersection of B-spline control span which being occurred of the loop. The other is using two B-spline curve divisions divided from original B-spline curve or its offset curve. After the inter¬section point of loop was searched, the loop being removed to cusp. Also the method for filleting of cusp is inspected to more precision cutting. It is shown that the offsetting using B-spline control polygon is more effective in the sculptured surface machining.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.181-190
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• 2022

In this paper, we use a LiDAR sensor and an image camera to detect a left-turning waiting vehicle in two ways, unlike the existing image-type or loop-type left-turn detection system, and a left-turn traffic signal corresponding to the waiting length of the left-turning lane. A system that can efficiently assign a system is introduced. For the LiDAR signal transmitted and received by the LiDAR sensor, the left-turn waiting vehicle is detected in real time, and the image by the video camera is analyzed in real time or at regular intervals, thereby reducing unnecessary computational processing and enabling real-time sensitive processing. As a result of performing a performance test for 5 hours every day for one week with an intersection simulation using an actual signal processor, a detection rate of 99.9%, which was improved by 3% to 5% compared to the existing method, was recorded. The advantage is that 99.9% of vehicles waiting to turn left are detected by the LiDAR sensor, and even if an intentional omission of detection occurs, an immediate response is possible through self-correction using the video, so the excessive waiting time of vehicles waiting to turn left is controlled by all lanes in the intersection. was able to guide the flow of traffic smoothly. In addition, when applied to an intersection in the outskirts of which left-turning vehicles are rare, service reliability and efficiency can be improved by reducing unnecessary signal costs.