• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.559-562
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• 2017

In city, tracing of power transmission lines is difficult due to compound installation of overhead and underground lines, transposition, bad view caused by trees or big buildings. It is hard problem for electrical technician on site to trace power transformers or power lines to serve customers in 3 phase -4 wires power distribution systems. It is necessary that the correct and fast tracing method is required for load balancing among distribution lines. Old technology use to trace off-lines with high power impulse injection. Our proposed method use to trace live lines with very small power high frequency signal injection. Typical power transformers in the distribution system prevent propagating the higher frequency carrier signal. The proposed method uses the limited propagation ability to identify the power transformer to serve customers. Two end communication terminals are required to be synchronized between them for determination on electrically same phases. Challenging issue is to achieve synchronization without GPS providing synchronizing time. A novel power transformer and wire identification system is designed and implemented. The system consists of a transmitter and a receiver with power-line communication module. Some experiments are conducted to verify the theoretical concepts in a big commercial building. Also some simulations are done to help and understand the concepts by using MATLAB Simulink simulator.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.4
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• pp.110-126
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• 2024

Several studies have focused on developing the safest and most efficient path from the current location to the available parking area for vehicles entering a parking lot. In the present study, the parking lot structure and parking environment such as the lane width, width, and length of the parking space, were vaired by referring to the actual parking lot with vertical and horizontal parking. An automatic parking path planning model was proposed by collecting path data by various setting angles and environments such as a starting point and an arrival point, by putting the collected data into a deep learning model. The existing algorithm(Hybrid A-star, Reeds-Shepp Curve) and the deep learning model generate similar paths without colliding with obstacles. The distance and the consumption time were reduced by 0.59% and 0.61%, respectively, resulting in more efficient paths. The switching point could be decreased from 1.3 to 1.2 to reduce driver fatigue by maximizing straight and backward movement. Finally, the path generation time is reduced by 42.76%, enabling efficient and rapid path generation, which can be used to create a path plan for autonomous parking during autonomous driving in the future, and it is expected to be used to create a path for parking robots that move according to vehicle construction.