• Journal of the Korean Institute of Gas
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• v.13 no.2
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• pp.49-56
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• 2009

This thesis suggests ways for ensuring the safety of domestic autogas (liquefied petroleum gas) vehicles by conducting comparison and analysis on the status of market diffusion and safety management scheme in foreign countries as well as in Korea. According to the result of the survey on the status of domestic autogas safety management, the national scheme to secure the safety of autogas vehicles seems neither well-organized nor sufficiently-controlled. Actually, the gas leakage check-ups conducted for 5,000 autogas cars revealed that about 4 percent of them had leakage problems. As a result, it was acknowledged that the autogas safety regulations being operated in advanced countries need to be selectively introduced for the domestic autogas industry. Consequently, in line with the recent permission to use autogas as a fuel for subcompact cars etc., this thesis is recommending some methods to enhance the safety management scheme for autogas cars such as the amendment of facility regulations including the ventilation of underground parking lots, mandatory attachment of labels claiming autogas cars and indicating periodical inspections etc.

• Journal of KSNVE
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• v.10 no.2
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• pp.254-260
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• 2000

the reduction of the interior nosie level has been the main interest of NVH engineers in the development of vehicles. However, the consumer's perception on the car noise is affected largely by the psychoacoustic characteristics of the noise, as well as the sound pressure level. In this study, the quality of the vehicle interior nosie is analyzed by employing the subjective evaluations and by representing them in temrs of the objective quantities. The subjective evaluatins were performed for the seven vehicles in the range of subcompact to luxury cars. The methods of paired comparisons and semantic differential were used to study the preference, the quality of interior noise and their correlation. The linear regression models were obtained for the subjective evaluation and the sound quality metrics.

• Journal of Korean Society of Transportation
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• v.36 no.2
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• pp.129-140
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• 2018

In this study, we analyzed the electric vehicle (EV) purchasing behavior with market segmentation in Seoul using the binary logit model. For the model estimation, the experimental design of SP survey generated 24 scenarios with purchase price, charging station availability, and driving range of EVs. The results of market segmentation analysis indicated that the owners of subcompact and compact size cars were primarily affected by the purchasing price while those of mid and full size cars were more sensitive to the charging station availability. By housing type, the charging station availability was the most important factor for the residents of apartment while the purchase price was the most important factor to choose the EVs. These results presented that the EV supply strategy of the automobile manufacturer should be diversified according to the marketing target and the expansion of the public charging infrastructure should be the top priority in the government policy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.469-472
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• 2022

With the recent development of intelligent transportation systems, various technologies applying deep learning technology are being used. To crackdown on illegal vehicles and criminal vehicles driving on the road, a vehicle type classification system capable of accurately determining the type of vehicle is required. This study proposes a vehicle type classification system optimized for mobile traffic control systems using YOLO(You Only Look Once). The system uses a one-stage object detection algorithm YOLOv5 to detect vehicles into six classes: passenger cars, subcompact, compact, and midsize vans, full-size vans, trucks, motorcycles, special vehicles, and construction machinery. About 5,000 pieces of domestic vehicle image data built by the Korea Institute of Science and Technology for the development of artificial intelligence technology were used as learning data. It proposes a lane designation control system that applies a vehicle type classification algorithm capable of recognizing both front and side angles with one camera.