• Journal of Convergence for Information Technology
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• v.8 no.5
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• pp.115-120
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• 2018

As the number ofconnected cars grows, the security of the connected cars is becoming more important. There are also increasing warnings about the threat of attacks via the CAN bus used for in-vehicle networks. An attack can attack through a vulnerability in the CAN bus because the attacker can access the CAN bus remotely, or directly to the vehicle, without a security certificate on the vehicle, and send a malicious error message to the devices connected to the CAN bus. A large number of error messages put the devices into a 'Bus-Off' state, causing the device to stop functioning. There is a way to detect the error frame, or to manage the power of the devices related to the bus, but eventually the new standard for the CAN bus will be the fundamental solution to the problem. If new standards are adopted in the future, they will need to be studied.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.5
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• pp.173-187
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• 2018

This paper proposes a computer vision and deep learning-based technique for surveillance camera system for vehicle counting as one part of parking lot management system. We applied the You Only Look Once version 2 (YOLOv2) detector and come up with a deep convolutional neural network (CNN) based on YOLOv2 with a different architecture and two models. The effectiveness of the proposed architecture is illustrated using a publicly available Udacity's self-driving-car datasets. After training and testing, our proposed architecture with new models is able to obtain 64.30% mean average precision which is a better performance compare to the original architecture (YOLOv2) that achieved only 47.89% mean average precision on the detection of car, truck, and pedestrian.

• International Journal of Highway Engineering
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• v.10 no.4
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• pp.127-138
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• 2008

Vehicles have recently become one of the main factors affecting our quality of life, and the needs of vehicles are still increasing. As a result, the growth of vehicles generate more crashes every year. One main factor for vehicle crashes is uncareful driving behaviors. Especially, drowsy or fatigue driving behaviors explain about 10-20% of the crashes, and they cause serious results because of the delay of response time and the decrease of object-recognition. Therefore, this research conducted real time image processing tests in order to study how cellular phone usages and drowy(or fatigue) drives affect driving behaviors. A vehicle simulator was used for this research, and the faceLAB 4.5 of Seeing Machines for eye image tracking tests using a small camera was installed in the front of the simulator, and normal and drowsy(or fatigue) driving patterns were analyzed.

• Journal of IKEEE
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• v.21 no.4
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• pp.358-367
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• 2017

Advanced Driver Assistance Systems(ADAS), such as Front Collision Warning System (FCWS) are currently being developed. FCWS require high processing speed because it must operate in real time while driving. In addition, a low-power system is required to operate in an automobile embedded system. In this paper, FCWS is implemented in CPU-FPGA architecture in embedded system to enable real-time processing. The lane detection enabled the use of the Inverse Transform Perspective (IPM) and sliding window methods to operate at fast speed. To detect the vehicle, a Convolutional Neural Network (CNN) with high recognition rate and accelerated by parallel processing in FPGA is used. The proposed architecture was verified using Intel FPGA Cyclone V SoC(System on Chip) with ARM-Core A9 which operates in low power and on-board FPGA. The performance of FCWS in HD resolution is 44FPS, which is real time, and energy efficiency is about 3.33 times higher than that of high performance PC enviroment.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.93-101
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• 2023

In this paper, we propose a method of creating a 3D bounding box for an object using a vanishing point to increase the accuracy of object recognition in an image when recognizing an traffic object using a video camera. Recently, when vehicles captured by a traffic video camera is to be detected using artificial intelligence, this 3D bounding box generation algorithm is applied. The vertical vanishing point (VP1) and horizontal vanishing point (VP2) are derived by analyzing the camera installation angle and the direction of the image captured by the camera, and based on this, the moving object in the video subject to analysis is specified. If this algorithm is applied, it is easy to detect object information such as the location, type, and size of the detected object, and when applied to a moving type such as a car, it is tracked to determine the location, coordinates, movement speed, and direction of each object by tracking it. Able to know. As a result of application to actual roads, tracking improved by 10%, in particular, the recognition rate and tracking of shaded areas (extremely small vehicle parts hidden by large cars) improved by 100%, and traffic data analysis accuracy was improved.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.465-468
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• 2022

The incidence of traffic accidents is increasing every year, and Korea is among the top OECD countries. In order to improve this, various road traffic laws are being implemented, and various traffic control methods using equipment such as unmanned speed cameras and traffic control cameras are being applied. However, as drivers avoid crackdowns by detecting the location of traffic control cameras in advance through navigation, a mobile crackdown system that can be cracked down is needed, and research is needed to increase the recognition rate of vehicle license plates on the side of the road for accurate crackdown. This paper proposes a method to improve the vehicle number recognition rate on the road side by applying a gradient correction algorithm using image processing. In addition, custom data learning was conducted using a CNN-based YOLO algorithm to improve character recognition accuracy. It is expected that the algorithm can be used for mobile traffic control cameras without restrictions on the installation location.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.430-436
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• 2018

Special railway vehicles for track maintenance are equipped with a tamping device that adjusts various track trajectories to reduce the vibration of rolling stock and improve ride quality during trains passing over a track. The development of a simulator that can confirm the error of the actual tamping work is important for reducing human error in the linearization of the track misalignment. In this study, to improve the reality and training effect of conventional 2D simulator, 3D simulator modeling was implemented for tamping work of special railway vehicles in virtual space. The problem of buffering during high screen quality of tamping work was solved using the Unwrap UVW mapping technique of a low polygon extracted from high quality polygon modeling. The human error in the training of the tamping work was detected by the principle of circle and square collision when the tamping tyne and the sleeper collided. In addition, vibration of the driving chair was generated at the same time as the collision, and the number of the sleeper strikes is displayed on the simulator exercise screen. Owing to the scattering of railway ballast protruding from the sleepers, which had a serious effect on the safety of the vehicle, the gravel bouncing effect of the tamping unit was applied.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.2
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• pp.175-181
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• 2004

Analysis of brake characteristics has progressed rapidly in recent years, as computer techniques have developed. However, there are many problems in predicting braking characteristics, due to the numerous design variables of the brake system. Therefore, a synthetic braking performance analysis is required for all brake system parts such as master cylinder, booster, control valve and split system. In this paper, a program which can analyze braking performance such as force distribution, braking efficiency, pedal force and pedal travel, is presented. The preprocessor of the program helps users prepare input files through a dialog box. An additional postprocessor makes the graph presentation of solved results. Also, a simple example problem is applied to show the usefulness of the presented program.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.1
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• pp.51-57
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• 2011

Information of the lateral velocity and the sideslip angle in a vehicle is very useful in many active vehicle safety applications such as yaw stability control and rollover prevention. Because cost-effective sensors to measure the lateral velocity and the sideslip angle are not available, reliable algorithms to estimation them are necessary. In this paper, a sliding mode observer is designed to estimate the lateral velocity. The side slip angle is estimated using the recursive least square with the disturbance observer and the pseudo integral. The estimated parameters from the combined estimation method are updated recursively to minimize the discrepancy between the model and the physical plant, and any possible effects caused by disturbances. The performance of the proposed monitoring system is evaluated through simulations and experiments.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.09a
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• pp.326-329
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• 2010

현재 시행 중인 승용차 RFID 요일제는 제한적인 설치장소와 RFID 설치시 많은 비용이 소비된다. 따라서 본 연구에서는 기존의 RFID 승용차 요일제 방식과 달리 효율성을 높이고 비용을 절감할수 있는 BMS(BUS Management System)를 활용한 버스 RFID system에 관한 방안을 제안한다. 제안하는 방안은 버스 RFID system은 대구시의 시내 버스 뒤편에 양쪽 상단에 RFID 안테나를 설치하여 대구시의 주요 도로를 운행 하며 승용차 요일제를 미준수 여부를 파악하는 것이다. 기존의 고정형 RFID는 설치 위치를 우회 할수 있지만 버스 RFID는 항상 이동하며 감지 하기때문에 차량의 우회에 따른 미확인 경우를 줄일 수 있다. 또한, BMS 활용으로 설치비용을 절감하여 비용대비 효율성을 제고할 수 있을 것으로 예상된다. 구체적인 방안 마련을 위하여 주요도로 버스노선도 파악, 중첩지점 그리고 기존의 승용차 요일제 시스템과 비교 분석을 하여 성능 평가들 실시하는 것에 주안점을 두고 연구를 수행하였다.