• 한국군사과학기술학회지
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• 제12권2호
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• pp.236-247
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• 2009

In Korea, the driving system restriction criteria is strictly applied(gross weight 400kN, axial load 100kN). Especially after the Seoungsu Bridge accident, safety factor has been strictly applied. The Safety factor is applied to the cumulative results for each steps like design, construction, maintenance of the Bridge. Because of it, the bridge is undervalued compared to its capacity. So, this generates loss for both private and military sector(eg. logistical delays, structural damage, etc.). But analyzing data from many existing researches we have confirmed that the military heavy vehicle may pass through the first class bridges. In consequence, this study have focused on determining whether HETS vehicles can pass over the first class bridge, without safety issues, using MIDAS structural analysis program. The results have confirmed that the military heavy vehicle may pass over the bridge.

• 한국군사과학기술학회지
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• 제10권3호
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• pp.139-147
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• 2007

In military transportation, the use of wide trailer for transporting the large and heavy weight equipments such as tank, armoured vehicle, and mobile gunnery is quite common. So, the vulnerability of causing traffic accidents for these wide military trailer to bump or collide with another car in adjacent lane is very high due to its broad width in excess of its own lane's width. Also, the possibility of these strayed accidents can be increased especially by the careless driver. In this paper, the recognition system of lane and vehicle headway direction is developed to detect the possible collision and warn the driver to prevent the fatal accident. In the system development, Kalman filtering is used first to extract the border of driving lane from the video images supplied by the CCD camera attached to the vehicle and the driving lane detection is completed with regression analysis. Next, the vehicle headway direction is recognized by using neural network scheme with the extracted parameters of the detected driving lane feature. The practical experiments for the developed system are also carried out in the real traffic road of Seoul city area and the results show us the more than 90% accuracy in recognizing the driving lane and vehicle headway direction.