• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.896-897
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• 2014

Multi-lane detection is useful for the smart navigation system. In this paper, a novel multi-lane detection method is presented. The proposed three point Laplacian filter (TPLF) can complement the weak points of the previous box filter and step filter. The experimental results validate the feasibility of the proposed multi-lane detection method.

• Review of KIISC
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• v.19 no.4
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• pp.11-20
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• 2009

차량네트워크(VANET)는 이동형 에드 혹 네트워크의 가장 유망한 응용환경으로 인식되어 지고 있다. 특히, 차량간의 안전주행 통신인 V2V의 경우 운전자의 안전을 위한 통신기술로 주목받고 있다. 안전주행을 위해서 V2V에서 송수신되는 메시지는 다양한 네트워크 공격을 막기 위해서 반드시 인증이 되어야 하는 반면 운전자의 위치 프라이버시를 보호하기 위해서는 익명성이 보장되어야 한다. 이러한 보안 속성은 V2V 통신만의 고유한 성질로써, 현재 인증과 프라이버시를 동시에 보장하기 위한 인증기술에 대한 연구가 활발히 진행되고 있다. 본 고에서는 프라이버시를 보장하는 V2V 인증 프로트콜들을 분석하고 보안 및 효율성 관점에서 각 프로트콜을 비교분석한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.433-434
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• 2023

본 논문에서는 미디어파이프와 아이트래킹의 손동작 및 눈 위치 인식을 이용하여 차량 내 조작할 수 있는 다양한 기능을 감압식 버튼이 아닌 카메라를 이용한 동작 기능을 제공해주는 차량 인포테인먼트시스템을 제안한다. 인공지능 모델은 Open-CV 구조를 활용하여 학습을 진행하였고, 라즈베리파이를 이용하여 구현하였다. 제안된 시스템은 운전자를 위해 설계된 다양한 동작들을 시각 정보로 전달해 운전 중 불편함을 대체할 수 있을 뿐만 아니라, 설치 및 사용방법이 간편하여 활용도가 높을 것으로 기대된다.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.1
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• pp.93-103
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• 1999

To detect obstacles and lane-markers for driving vehicles, a new moving window scheme where moving windows are assigned to an image frame captured by a camera is addressed. For the detection of obstacles, it is important to estimate lane-markers precisely and rapidly. For this purpose, selecting some partes of an image frame at the expected lane locations, i.e., selecting window are generally adopted for extracting lane-markers efficiently. In this paper, a new scheme that extracts lane-markers precisely by assigning variable size windows at the expected locations of lane-markers considering the road curvature and finally detects obstacles within a driving lane is proposed. The accuracy improvement using this moving window scheme is showed by comparing to the conventional fixed window method and to using radar to laser sensors.

• Journal of the Korean Society for Railway
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• v.11 no.3
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• pp.286-293
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• 2008

In this paper, u-FOS system is applied to field test in order to design the code structure based on standards and both 900MHz passive and 2.45GHz active RFID devices were used to test identification capacity in the field tests. For the stable RFID data obtainments, optimum speed of trucks and rail cars and most suitable tagging locations on them were resulted from field tests. The data obtained from ground logistics base and identified through the system is sent to u-FOS. Because the code structure is designed in the form of KKR code structure, this system can be implemented on RFID ODS network without difficulty. Therefore, we suggested the result as a guideline for corporations and government agencies to easily adopt the system.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.8
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• pp.872-879
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• 2010

This paper describes the design for radiation pattern directivity of vehicle license plate RFID tag antenna to improve the readable range. Directivity pattern of the proposed passive antenna is decided by the meander line position and the bumper size attached to the tag antenna. In order to prove the verification of the calculated directivity pattern and readable range of the proposed antenna, the tag antenna has been fabricated and measured at the anechoic chamber. It is shown that the maximum directivity gain of the measured radiation pattern of active and passive tag antenna were observed 2.32 dBi and 3.1 dBi, respectively. The maximum readable range of passive tag antenna was measured about 8.5 m at ${\pm}45^{\circ}$ beam direction on the basis of the driving car direction($0^{\circ}$ of azimuth angle).

• 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 Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.55-69
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• 2017

Recently, the IoT (Internet of Things) environment is being developed rapidly through network which is linked to intellectual objects. Through the IoT, it is possible for human to intercommunicate with objects and objects to objects. Also, the IoT provides artificial intelligent service mixed with knowledge of situational awareness. One of the industries based on the IoT is a car industry. Nowadays, a self-driving vehicle which is not only fuel-efficient, smooth for traffic, but also puts top priority on eventual safety for humans became the most important conversation topic. Since several years ago, a research on the recognition of the surrounding environment for self-driving vehicles using sensors, lidar, camera, and radar techniques has been progressed actively. Currently, based on the WAVE (Wireless Access in Vehicular Environment), the research is being boosted by forming networking between vehicles, vehicle and infrastructures. In this paper, a research on the recognition of a traffic signs on highway was processed as a part of the awareness of the surrounding environment for self-driving vehicles. Through the traffic signs which have features of fixed standard and installation location, we provided a learning theory and a corresponding results of experiment about the way that a vehicle is aware of traffic signs and additional informations on it.

• Journal of Advanced Navigation Technology
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• v.11 no.4
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• pp.359-370
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• 2007

Lane tracking and obstacle avoidance are considered two of the key technologies on an unmanned ground vehicle system. In this paper, we propose a method of lane tracking and obstacle avoidance, which can be expressed as vehicle control, modeling, and sensor experiments. First, obstacle avoidance consists of two parts: a longitudinal control system for acceleration and deceleration and a lateral control system for steering control. Each system is used for unmanned ground vehicle control, which notes the vehicle's location, recognizes obstacles surrounding it, and makes a decision how fast to proceed according to circumstances. During the operation, the control strategy of the vehicle can detect obstacle and perform obstacle avoidance on the road, which involves vehicle velocity. Second, we explain a method of lane tracking by means of a vision system, which consists of two parts: First, vehicle control is included in the road model through lateral and longitudinal control. Second, the image processing method deals with the lane tracking method, the image processing algorithm, and the filtering method. Finally, in this paper, we propose a method for vehicle control, modeling, lane tracking, and obstacle avoidance, which are confirmed through vehicles tests.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.6
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• pp.149-161
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• 2009

Electronic control systems of vehicle are rapidly developed to keep balance of a driver`s safety and the legal, social needs. The driver assistance systems are putted into practical use according to the cost drop in hardware and highly efficient sensor, etc. This study has developed a lane and vehicle detection program using CCD camera. The Risky Driving Analysis Program based on vision systems is developed by combining a risky driving detection algorithm formed in previous study with lane and vehicle detection program suggested in this study. Risky driving detection programs developed in this study with information coming from the vehicle moving data and lane data are useful in efficiently analyzing the cause and effect of risky driving behavior.