• Journal of the korean Society of Automotive Engineers
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• v.24 no.2
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• pp.62-65
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• 2002

• Journal of the korean Society of Automotive Engineers
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• v.27 no.6
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• pp.4-8
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• 2005

• Journal of the korean Society of Automotive Engineers
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• v.25 no.5
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• pp.43-47
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• 2003

• Journal of Advanced Navigation Technology
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• v.15 no.1
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• pp.130-139
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• 2011

In this paper, vehicle tracking algorithm using hue transformation in HIS color model is proposed. the proposed algorithm is installed on the road of the two horizontal virtual data sampling lines. The difference images are detected between the frame and the frame, respectively and also detected in the vehicle by using the hue color distribution to determine identity and lane changes. To examine the effectiveness of proposed algorithm, identification and velocity measurement for driving vehicle are evaluated. this evaluated results is shown by hue data of vehicle passing of two virtual data sample lines, and the velocity measurement for driving vehicle is less than 0.4% comparing with existing vehicle speed meter system.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.5
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• pp.325-333
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• 2015

Vision based night-time vehicle detection has been an emerging research field in various advanced driver assistance systems(ADAS) and automotive vehicle as well as automatic head-lamp control. In this paper, we propose night-time vehicle detection method based on multi-class support vector machine(SVM) that consists of thresholding, labeling, feature extraction, and multi-class SVM. Vehicle light candidate blobs are extracted by local mean based thresholding following by labeling process. Seven geometric and stochastic features are extracted from each candidate through the feature extraction step. Each candidate blob is classified into vehicle light or not by multi-class SVM. Four different multi-class SVM including one-against-all(OAA), one-against-one(OAO), top-down tree structured and bottom-up tree structured SVM classifiers are implemented and evaluated in terms of vehicle detection performances. Through the simulations tested on road video sequences, we prove that top-down tree structured and bottom-up tree structured SVM have relatively better performances than the others.

• Journal of Auto-vehicle Safety Association
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• v.10 no.4
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• pp.40-49
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• 2018

Currently, a lot of researches about high risk test scenarios for autonomous vehicle and advanced driver assistance systems have been carried out to evaluate driving safety. This study proposes new type of test scenario that evaluate the driving safety for autonomous vehicle by reconstructing accident database of national automotive sampling system crashworthiness data system (NASS-CDS). NASS-CDS has a lot of detailed accident data in real fields, but there is no data of accurate velocity in accident moments. So in order to propose scenario generation method from accident database, we try to reconstruct accident moment from accident sketch diagram. At the same step, we propose an accident of occurrence frequency which is based on accident codes and road shapes. The reconstruction paths from accident database are integrated into evaluation of simulation environment. Our proposed methods and processor are applied to MILS (Model In the Loop Simulation) and VILS (Vehicle In the Loop Simulation) test environments. In this paper, a reasonable method of accident reconstruction typology for autonomous vehicle evaluation of feasibility is proposed.

• Journal of Auto-vehicle Safety Association
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• v.11 no.2
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• pp.17-22
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• 2019

This paper describes the tracking algorithm performance evaluation for autonomous vehicle using a safety envelope based path. As the level of autonomous vehicle technologies evolves along with the development of relevant supporting modules including sensors, more advanced methodologies for path generation and tracking are needed. A safety envelope zone, designated as the obstacle free regions between the roadway edges, would be introduced and refined for further application with more detailed specifications. In this paper, the performance of the path tracking algorithm based on the generated path would be evaluated under safety envelop environment. In this process, static obstacle map for safety envelope was created using Lidar based vehicle information such as current vehicle location, speed and yaw rate that were collected under various driving setups at Seoul National University roadways. A level of safety was evaluated through CarSim simulation based on paths generated with two different references: a safety envelope based path and a GPS data based one. A better performance was observed for tracking with the safety envelop based path than that with the GPS based one.

• Journal of Welding and Joining
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• v.26 no.1
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• pp.69-75
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• 2008

Spot welding which use the main process for side block production of stainless steel railway vehicle is legged behind in laser welding about a quality and productivity. Although the laser welding has many potential advantages such as low heat input and aspect ratio of weld bead, its application to a new structural component still is required many engineering data including mechanical properties such as tensile, fatigue strength, etc on. Therefore, experimental analysis was carried out to understand the fatigue phenomena of different thickness stainless steel overlap joining panels by Nd:YAG laser welding. The fatigue life curves were obtained through fatigue tests with the various levels of applied load. The fatigue life is related with the parameters such as gap size and penetration depth through experiment. As the results, tensile strength and fatigue life were proportional in heat input level and gap was identified the major factor for fatigue life. Also we could know that deferent a-ferrite content at HAZ depend on welding heat input was important factor to determine a formation of initial crack and total fatigue life cycle.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.3
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• pp.65-77
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• 2013

Recent advanced sensors and communication technologies have been widely applied to advanced safety vehicle (ASV) for reducing traffic accident and injury severity. To apply the advanced safety vehicle technologies, it is important to quantify the safety benefits, which is a fundamental for justifying application. This study proposed a methodology for quantifying the effectiveness of the advanced driver assistant system (ADAS), and applied the methodology to lane departure warning system (LDWS) and automatic emergency braking system (AEBS) which are typical advanced driver assistant systems. When the proposed methodology is applied to 2008-2010 gyeonggi-province crash data, LDWS would reduce about 10~14% of relevant crashes such as head-on, run-off-the road, rollover and fixed-object collisions on the road. In addition, AEBS could potentially prevent about 50% of total rear-end crashes. The outcomes of this study support decision making for developing not only vehicular technology but also relevant safety policies.

• Journal of the Korean Society for Railway
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• v.18 no.3
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• pp.203-211
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• 2015

Ride comfort of a vehicle can be utilized to maintain the track geometry and track irregularities because ride comfort of the rolling stock is affected by the characteristics of the vehicle and track. Ride comfort was evaluated according to the measured floor acceleration data of vehicles for a Korean high speed line as well as European high speed lines using Continuous comfort method which can be applied to track maintenance. The exceedance distribution of the ride comfort was quantitatively analyzed by the vehicle speed, the ride comfort of the Korean high speed line was compared with that of European high speed lines. It is shown that the ride comfort of Korean high speed line is better than that of European high speed lines, which indicates that the Korean track geometry and track irregularities are properly maintained.