• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.489-490
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• 2022

본 논문에서는 주차 공간에 배치된 센서들로부터 차량을 감지하고 이를 서버로 전송함으로써 클라이언트가 실시간적으로 주차 공간 정보 서비스를 받는 시스템을 구현하였다. 또한 이 시스템은 웹이나 앱을 통해 클라이언트가 쉽게 접근 가능하며, 직관적인 사용자 인터페이스(UI)로 쉽고 한눈에 알아볼 수 있도록 한다. 센서는 주차장 환경에 따라 구성과 배치 방법이 달라질 수 있으며, 핵심은 검증된 센서의 값이 서버 전송을 통하여 데이터를 가공하고, 이를 클라이언트에게 제공하는 것에 있다. 제안한 시스템으로 대형 주차장에서의 효율적인 주차 정보 서비스를 통해 주차시간 줄여주는 효과가 있을 것으로 기대된다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.1119-1120
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• 2023

본 논문에서는 LiDAR 만을 이용한 자율주차 시스템을 제안한다. 목표하는 주차공간 양측에 위치한 차량을 감지하여 주차공간의 앞까지 이동한 후 조향장치를 제어하여 주차를 수행하는 알고리즘을 제시하였다. 또한 2023년도 제1회 성균관대학교 자율주행 SW 경진대회를 수행함으로써 해당 알고리즘의 유효성을 검증하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.9-10
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• 2024

본 연구에서는 Renesas RA6M3 Embedded board와 RTOS를 기반으로 하는 교통 표지판 인식 시스템을 구현한다. 초음파 센서 3개를 활용해 상단부, 중심부, 하단부에서 도형을 감지하고, 모터를 제어하여 각각의 초음파 센서로 거리를 판단해 표지판 도형을 인식하게 한다. 이 시스템은 카메라 및 LiDAR와 같은 값비싼 장비보다 상대적으로 저렴한 초음파 센서를 사용하여 차량용 전장 시스템의 원가를 낮추는 데 기여한다. 실제 자동차에서 해당 기술을 쓰기 위해서는 추가적인 보완이 요구될 수 있으나, 본 연구는 새로운 아이디어의 발상 및 하드웨어의 구체적인 구현 방안을 제시함으로써 차후 연구의 방향성을 제시하고자 한다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.3
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• pp.30-39
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• 2012

In this paper, a safe driving assistance system is proposed by detecting the status of driver's doze based on face and eye detection. By the level of the fatigue, safe driving system alarms or set the seatbelt on vibration. To reduce the effect of backward light and too strong solar light which cause a decrease of face and eye detection rate and false fatigue detection, post processing techniques like image equalization are used. Haar transform and PCA are used for face detection. By using the statistic of the face and eye structural ratio of normal Koreans, we can reduce the eye candidate area in the face, which results in reduction of the computational load. We also propose a new eye status detection algorithm based on Hough transform and eye width-height ratio, which are used to detect eye's blinking status which decides doze level by measuring the blinking period. The system alarms and operates seatbelt on vibration through controller area network(CAN) when the driver's doze level is detected. In this paper, four algorithms are implemented and proposed algorithm is made based on the probability model and we achieves 84.88% of correct detection rate through indoor and in-car environment experiments. And also we achieves 69.81% of detection rate which is better result than that of other algorithms using IR camera.

• Journal of the Korean Institute of Gas
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• v.3 no.2 s.7
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• pp.17-23
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• 1999

The wire and/or wireless data communication system for anti-disaster system of natural gas governor station was developed. In oder to prevent accidents of governor station, the operator was replaced by RTU(Remote Terminal Unit) which gather and transmit safety situation of governor station. The database and MMI(Man Machine Interface) were also developed to analyze the situation of governor station. The data communication between server and RTU was designed to switch automatically from wire to wireless communication and vice versa when one of them failed communication. We also have developed the patrol car management system which was applied GPS(Global Position System)/GIS(Geometric Information System), and the earthquake detection/transmission system which was adopted three dimension acceleration sensor. When a earthquake may occur, the earthquake detection/transmission system monitors data such as PGA(Peak Ground Acceleration), Sl(Spectrum Intensity) and orders the emergency shutoff valve close immediately.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.331-345
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• 2021

Virtual testing is considered a major requirement for the safety verification of autonomous driving functions. For virtual testing, both the autonomous vehicle and the driving environment should be modeled appropriately. In particular, a realistic modeling of the perception sensor system such as the one having a camera and radar is important. However, research on modeling to consistently generate realistic perception results is lacking. Therefore, this paper presents a sensor modeling method to provide realistic object detection results in a MILS (Model in the Loop Simulation) environment. First, the key parameters for modeling are defined, and the object detection characteristics of actual cameras and radar sensors are analyzed. Then, the detection characteristics of a sensor modeled in a simulation environment, based on the analysis results, are validated through a correlation coefficient analysis that considers an actual sensor.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.3
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• pp.339-349
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• 2017

This paper proposes a four-stage algorithm for detecting lanes on a driving car. In the first stage, it extracts region of interests in an image. In the second stage, it employs a median filter to remove noise. In the third stage, a binary algorithm is used to classify two classes of backgrond and foreground of an input image. Finally, an image erosion algorithm is utilized to obtain clear lanes by removing noises and edges remained after the binary process. However, the proposed lane detection algorithm requires high computational time. To address this issue, this paper presents a parallel implementation of a real-time line detection algorithm on a multi-core architecture. In addition, we implement and simulate 8 different processing element (PE) architectures to select an optimal PE architecture for the target application. Experimental results indicate that 40×40 PE architecture show the best performance, energy efficiency and area efficiency.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.6
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• pp.47-55
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• 2003

In this paper, we propose a new approach to detect peculiar features of license plates using intensity vector and composite color component in order to extract license plates from parking regulation images, which is captured in various locations around the front or the rear of cars at various times and places, and in which complex background is included. We fundamentally use both features that intensity value repeats frequently increasing and decreasing because intensity is obviously different at numerics and background, and that color is uniform in the area of license plates. First, we search each row at regular intervals starting from the bottom of a license-plate image, and we set up a rough region for a certain zone in which tile sign of intensity vector changes frequently enough and color of license plate is detected enough, assuming it as a candidate location of a license plate. And then, we extract an elaborate area of a license plate by projecting vertical edges horizontally and vertically. Here, type of cars, such as the urinate and the public, is easily classified according to the color of extracted plates. We used 200 actual regulation images, which are captured at various times and places, to evaluate the performance of the proposed method. As a result, the proposed method showed extraction rate of 96%, which is 9% higher than the previous method using only intensity vector.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.468-474
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• 2019

Korea had the highest accident rate among OECD countries in 2018, with 8.4 per 100,000 population, ranking 4th among 35 countries. In addition, the accident rate of traffic with children and the elderly was also high. This study reviewed the relevant literature and analyzed the traffic-accident analysis system. Customized traffic safety facilities were developed. In addition, by measuring the visibility of the traffic safety facilities by installing a test bed, this study measured the forward driving frequency and vehicle driving speed while driving. As a result of applying the "pedestrian pedestrian model" collision test model, the possibility of serious injury after installing the facility was reduced greatly to 4.6%. In this study, the visibility of traffic safety facilities and the effect of reducing the traffic speed were verified through test beds. Recognizing traffic safety facilities will reduce traffic accidents.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.2
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• pp.227-235
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• 2018

In this study, we developed a relational formula for observing high - resolution rainfall using vehicle rain sensor. The vehicle rain sensor consists of eight channels. Each channel generates a sensor signal by detecting the amount of rainfall on the windshield of the vehicle when rainfall occurs. The higher the rainfall, the lower the sensor signal is. Using these characteristics of the sensor signal generated by the rain sensor, we developed a relational expression. In order to generate specific rainfall, an artificial rainfall generator was constructed and the change of the sensor signal according to the variation of the rainfall amount in the artificial rainfall generator was analyzed. Among them, the optimal sensor channel which reflects various rainfall amounts through the sensitivity analysis was selected. The sensor signal was generated in 5 minutes using the selected channel and the representative values of the generated 5 - minute sensor signals were set as the average, 25th, 50th, and 75th quartiles. The calculated rainfall values were applied to the actual rainfall data using the constructed relational equation and the calculated rainfall amount was compared with the rainfall values observed at the rainfall station. Although the reliability of the relational expression was somewhat lower than that of the data of the verification result data, it was judged that the experimental data of the residual range was insufficient. The rainfall value was calculated by applying the developed relation to the actual rainfall, and compared with the rainfall value generated by the ground rainfall observation instrument observed at the same time to verify the reliability. As a result, the rain sensor showed a fine rainfall of less than 0.5 mm And the average observation error was 0.36mm.