• Convergence Security Journal
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• v.11 no.4
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• pp.59-66
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• 2011

Recently, it is very important to establish and predict a traffic policy for expanding social infra structure like road, because the number of cars is significantly increasing. In this paper, we propose and develop an automated system technology based on vision sensor (CCTV) which can provide an efficient information for the traffic policy establishment and expanding the social infra structure. First, the CCTV image is captured as an input of the developed system. With this image, we propose a scheme for extracting vehicles on the road and classifying small-type, large-type vehicles based on color, motion, and geometric features. Also, we develop a DB (database) system for supplying a whole information of traffic for a specified period. Based on the proposed system, we verify 90.1% of recognition ratio in real-time traffic monitering environment.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.16
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• pp.331-359
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• 2001

Uniform Electronic Transactions Act (1999) Drafted by the National Conference of Commissioners on Uniform State Laws. The Act allows the use of electronic records and electronic signatures in any transaction, except transactions subject to the Uniform Commercial Code. The fundamental purpose of this act is to remove perceived barriers to electronic commerce. The Act's a procedural statute. It does not mandate either electronic signatures or records, but provides a means to effectuate transactions when they are used. The primary objective is to establish the legal equivalence of electronic records and signatures with paper writings and manually-signed signatures. With regard to the general scope of the Act, the Act's coverage is inherently limited by the definition of "transaction." The Act does not apply to all writings and signatures, but only to electronic records and signatures relating to a transaction, defined as those interactions between people relating to business, commercial and governmental affairs. The exclusion of specific Articles of the Uniform Commercial Code reflects the recognition that, particularly in the case of Articles 5, 8 and revised Article 9, electronic transactions were addressed in the specific contexts of those revision processes. In the context of Articles 2 and 2A the UETA provides the vehicle for assuring that such transactions may be accomplished and effected via an electronic medium. At such time as Articles 2 and 2A are revised the extent of coverage in those Articles(Acts) may make application of this Act as a gap-filling law desirable. Similar considerations apply to the recently promulgated Uniform Computer Information Transactions Act (UCITA). Another fundamental premise of the Act is that it be minimalist and procedural. The general efficacy of existing law, in an electronic context, so long as biases and barriers to the medium are removed, confirms this approach. The Act defers to existing substantive law. Specific areas of deference to other law in this Act include: i) the meaning and effect of "sign" under existing law, ii) the method and manner of displaying, transmitting and formatting information in section 8, iii) rules of attribution in section 9, and iv) the law of mistake in section 10.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.4
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• pp.201-208
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• 2015

This paper proposes a method for detecting the direction indicator shown in the road surface efficiently from the black box system installed on the vehicle. In the proposed method, the direction indicators are detected by inverse perspective mapping(IPM) and bag of visual features(BOF)-based NN classifier. In order to apply the proposed method to real-time environments, the candidated regions of direction indicator in an image only performs IPM, and BOF-based NN is used for the classification of feature information from direction indicators. The results of applying the proposed method to the road surface direction indicators detection and recognition, the detection accuracy was presented at least about 89%, and the method presents a relatively high detection rate in the various road conditions. Thus it can be seen that the proposed method is applied to safe driving support systems available.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.481-484
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• 2011

Recent Automotive technology is driven from mechanical device to the electronic components which improve the vehicle's safety and convenience. The future competitiveness of the car will come from safety issues and energy efficiency, convenience and the application of the technologies. In this study, various techniques for driver drowsiness detection are introduced and compared with each others. The advantages and disadvantages of commercially available technologies and developed technologies are compared. To enhance the detection resolution, multiple sensing technologies are introduced in this paper. The feasibility of two drowsiness detection methods, that is, existing camera image recognition method and bio signal analysis method, are tested. The direct drowsiness detection by the camera image of eyes and driver's vital signs detected indirectly are combined and analyzed by the developed noble algorithm for stress, fatigue, drowsiness detection with a more accurate high-drowsiness detection.

• Journal of Korean Society of Transportation
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• v.32 no.5
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• pp.522-530
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• 2014

Spatio-temporal congestion evolution pattern can be reproduced using the VDS(Vehicle Detection System) historic speed dataset in the TMC(Traffic Management Center)s. Such dataset provides a pool of spatio-temporally experienced traffic conditions. Traffic flow pattern is known as spatio-temporally recurred, and even non-recurrent congestion caused by incidents has patterns according to the incident conditions. These imply that the information should be useful for traffic prediction and traffic management. Traffic flow predictions are generally performed using black-box approaches such as neural network, genetic algorithm, and etc. Black-box approaches are not designed to provide an explanation of their modeling and reasoning process and not to estimate the benefits and the risks of the implementation of such a solution. TMCs are reluctant to employ the black-box approaches even though there are numerous valuable articles. This research proposes a more readily understandable and intuitively appealing data-driven approach and developes an algorithm for identifying congestion patterns for recurrent and non-recurrent congestion management and information provision.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.230-236
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• 2015

In these digital times, the image signal processing is being used in various areas like vehicle recognition, security, and robotics. Generally, the image deterioration occurs by salt & pepper noise in the procedures of image transmission, storage, and processing. Methods to remove this noise are SMF, CWMF, and SWMF and these methods have few unsatisfactory noise reduction characteristics in salt & pepper noise environment. Therefore, in order to mitigate salt & pepper noise which is added in the image, this study suggested an algorithm which subdivides the masks in the image into four areas and processes using non-noise pixel numbers in each area. Additionally, in order to prove the excellence of the proposed algorithm, relevant performances were compared with existing methods using PSNR.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.257-258
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• 2020

기존의 드론 조작은 초보자에게 어려웠다. 초보자의 경우 드론을 조종하다가 드론이 추락하거나 장애물에 걸려 프로펠러 등의 부품들이 손상되는 경우를 빈번하게 마주한다. 본 연구에서는 초보자 또한 드론 파손의 걱정 없이 드론의 조작을 더욱 쉽게 개선시키는 것을 전제로 뇌파와 보조입력인 음성인식을 이용한 드론 컨트롤러 기술을 적용하고자 한다. 현재 대중적으로 출시되어 있는 드론의 경우 호버링 기능을 포함시켜 드론의 추락 위험을 줄여주는 기능을 탑재하고 있다. 하지만 속도가 빠른 드론의 조작에 있어 미숙한 초보자들은 장애물과의 충돌 그리고 드론 착륙 시 기체손상 등의 위험에 대비하기 힘들다. 본 논문은 이러한 문제점들을 개선하기 위해 기존의 드론 컨트롤러 대신 특정한 동작을 상상할 때 발현되는 동작상상뇌파와 음성입력을 적용한 '동작상상뇌파와 음성인식을 이용한 드론 컨트롤러' 기술을 제안한다. 기존의 드론 컨트롤러와는 다르게 빅 데이터 처리기술인 머신러닝을 이용하여 뇌파 데이터를 처리하고 그 데이터들과 입력되는 뇌파 값을 비교하여 드론을 제어한다. 또한 뇌파의 발현이 안정적이지 못하는 상황을 대비한 보조입력인 음성인식을 이용하여 드론의 기체손상을 최소화 시킬 수 있다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.239-241
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• 2022

Currently, in Korea, a multi-seater lane (HOV) and a designated lane system are being implemented to solve traffic congestion. However, in both systems, it is difficult to crack down on cases of violations without permission, so people are required to be assigned to areas that want to crack down. In this process, manpower and budget are inefficiently consumed. To compensate for these shortcomings, we propose the development of an integrated enforcement system through YOLO, a deep learning object recognition model. If the two systems are implemented and integrated using YOLO, they will have advantages in terms of manpower and budget over existing systems because only data learning and system maintenance are considered. In addition, in the case of violations in which it is difficult for the existing unmanned system to crack down, the effect of increasing the crackdown rate through continuous learning can be expected.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.12
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• pp.507-516
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• 2019

Costs invested in road maintenance and road development are on the rise. However, due to accidents such as portholes and ground subsidence, the risks to the drivers' safety and the material damage caused by accidents are also increasing. Following this trend, we have developed a system that determines road damage, according to the magnitude of vibration generated without directly intervening the driver when driving. In this paper, we implemented the system using a remote control car (RC car) simulator due to the limitation of the environment in which the actual vehicle is not available in the process of developing the system. In addition, we attached a vibration sensor and GPS sensor to the body of the RC car simulator to measure the vibration value and location information generated by the movement of the vehicle in real-time while driving, and transmitting the corresponding data to the server. In this way, we implemented a system that allows external users to check the damage of roads and the maintenance of the repaired roads based on data more easily than the existing systems. By using this system, we can perform early prediction of road breakage and pattern prediction based on the data. Further, for the RC car simulator, commercialization will be possible by combining it with business in other fields that require flatness.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.123-128
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• 2014

This paper presents the study about MGV(Magnetic guidance vehicle) with up-and-down rotating type differential drive unit. Previous MGV needs the landmarks to get the driving information and additional sensor to recognize the landmarks except for localization sensor. Previous MGV requires at least 2 drive units when common fixed differential drive unit is used because it occurs the problems with driving control and localization error from imbalance of the MGV's weight. To solve such problems, we propose the MGV using up-and-down rotating type differential drive unit. Proposed MGV recognizes the driving information from the pattern which is consisted of both pole of magnet without landmarks and additional sensors, and it control the backward movement using up-and-down rotating type differential drive unit instead of common drive units. Proposed MGV considers KF(Kalman filter) to improve the localization accuracy. To verify the performance of proposed method, we designed MGV for the experiment. As the results, we can confirm the performance of propoesed method to recognize the pattern and to control the backward movement. With respect to localization, proposed method has the less RMSE about 5.6904 mm than previous method.