• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.3
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• pp.117-123
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• 2011

In this paper, we design the hardware platform and implement the embedded software based on the FPGA and the DSP for the automotive 77GHz FMCW radar system. This embedded software is built into the DSP as the multi-tasking architecture to support the basic target detection algorithm and the Ethernet link. The designed GUI(Graphic User Interface) provides ability to adjust parameters associated with the radar performance, to monitor signal processing results, and to download the raw received signal. The designed platform can be used to develop the optimal detection algorithms for the various applications.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1972-1974
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• 2011

차량에 장착되는 전장품 사이의 정보 교환용 통신방식으로 주로 사용되는 CAN 통신 프로토콜의 이상상태를 분석하고 차량제어기에 적용해야할 CAN 이상상태 검출 및 처리 기능에 대해 연구하였다. 이 연구결과는 CAN 통신 문제의 탐지와 대응 방법을 제시하여 차량운행 시 시스템의 안정성을 높이는데 기여할 것으로 예상된다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.1
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• pp.69-74
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• 2010

Now the CAN(controller Area Network) is using electronic modules as a serial communication which is very robust to noise. Especially the CAN is using for automotive part that very popular in which automotive electronic control module, engine controller unit, sensor modules, etc. but the CAN has the order of priority to linking node and also has fault confinement so using in these features that is applied to in factory automation product line. The CAN communication is basically very robust to electric noise so varied applying to others part. In this paper, we suggest to CAN interface for embedded system that is possible for error detection using two CAN nodes on Hi-speed, full-CAN.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1819-1823
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• 2005

Incorrect information on public sites can cause serious problem. One of relevant countermeasures against this problem is to detect of buried underground utilities in real time. Although there have been several method to detect of buried underground utilities, such as investigating of gravity and elastic wave and electric field, they have not been so efficient tools. Because it is too expensive and difficult to use. In this paper, magnetic sensors which could provide an easier and more efficient method are used to detect of buried underground utilities. Also fluxgate method of self detection are used. Input signal is used $1\~10kHz$ frequency. Filtering and signal processing of output signal are used labview software. After experiment, detection system of buried underground utilities which used magnetic shows possibility of precise detecting of laying object based on theorectical analysis for electromagnetic field.

• The KSFM Journal of Fluid Machinery
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• v.19 no.4
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• pp.39-42
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• 2016

A PFA lined ball valve, which is machined with fluorinated resin PFA to its inner part for improving corrosion resistance, non-stickness, heat-resistance, has been widely used to the chemical/pharmaceutical industries, the semiconductor/LCD manufacturing processes, etc. with the high purity chemicals as working fluid. EPA stated that 60% of all fugitive emissions come from the valve stem packing in a typical petroleum or chemical processing plant. They monitor regulated components for leaks and maintain seal performance at acceptable levels. Korean industrial standards only deals with the bubble test for in-line leakage of valves, which has the detectable leak rate of $10^{-4}$ [$mbar{\cdot}L{\cdot}s^{-1}$], therefore, it is not sufficient to check fugitive emissions. In this study, we conducted Helium leak detection from a PFA lined ball valve and evaluated fugitive emissions according to ISO 15848-1, which has the detectable leak rate of $10^{-9}$ [$mbar{\cdot}L{\cdot}s^{-1}$], for manufacturing the high-reliable PFA lined ball valves against fugitive emissions.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.4
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• pp.97-104
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• 2005

Vision-based lane sensing systems require accurate and robust sensing performance in lane detection. Besides, there exists trade-off between the computational burden and processor cost, which should be considered for implementing the systems in passenger cars. In this paper, a stereo vision-based lane detection system is developed with considering sensor configuration aspects. An inverse perspective mapping method is formulated based on the relative correspondence between the left and right cameras so that the 3-dimensional road geometry can be reconstructed in a robust manner. A new monitoring model for estimating the road geometry parameters is constructed to reduce the number of the measured signals. The selection of the sensor configuration and specifications is investigated by utilizing the characteristics of standard highways. Based on the sensor configurations, it is shown that appropriate sensing region on the camera image coordinate can be determined. The proposed system is implemented on a passenger car and verified experimentally.

• International Journal of Automotive Technology
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• v.7 no.1
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• pp.83-90
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• 2006

The purpose of this paper is to describe the design and implementation of an unmanned ground vehicle, called the TailGator at CIMAR (Center for Intelligent Machines and Robotics) of the University of Florida. The TailGator is a gas powered, four-wheeled vehicle that was designed for the AUVSI Intelligent Ground Vehicle Competition and has been tested in the contest for 2 years. The vehicle control model and design of the sensory systems are described. The competition is comprised of two events called the Autonomous Challenge and the Navigation Challenge: For the autonomous challenge, line following, obstacle avoidance, and detection are required. Line following is accomplished with a camera system. Obstacle avoidance and detection are accomplished with a laser scanner. For the navigation challenge, waypoint following and obstacle detection are required. The waypoint navigation is implemented with a global positioning system. The TailGator has provided an educational test bed for not only the contest requirements but also other studies in developing artificial intelligence algorithms such as adaptive control, creative control, automatic calibration, and internet-base control. The significance of this effort is in helping engineering and technology students understand the transition from theory to practice.

• Journal of IKEEE
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• v.28 no.1
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• pp.6-13
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• 2024

This paper proposes an approach to detect abnormal data in automotive controller area network (CAN) using an unsupervised learning model, i.e. autoencoder and Gaussian kernel density estimation function. The proposed autoencoder model is trained with only message ID of CAN data frames. Afterwards, by employing the Gaussian kernel density estimation function, it effectively detects abnormal data based on the trained model characterized by the optimally determined number of frames and a loss threshold. It was verified and evaluated using four types of attack data, i.e. DoS attacks, gear spoofing attacks, RPM spoofing attacks, and fuzzy attacks. Compared with conventional unsupervised learning-based models, it has achieved over 99% detection performance across all evaluation metrics.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.6
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• pp.565-574
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• 2015

Recently, a medium-level representation named "Stixel" has been extensively researched in stereo vision-based environmental perception. Obstacle detection using Stixel representation consists of three steps: static Stixel generation, dynamic Stixel generation, and Stixel segmentation. This paper focuses on the Stixel segmentation step and has two contributions. One is that it shows that Stixel segmentation performance can be enhanced by utilizing both image domain and real world domain features. The other is that it suggests that parameters used for Stixel segmentation can be effectively tuned based on genetic algorithm. The proposed method was quantitatively evaluated and the result showed that the proposed method increased Stixel segmentation accuracy compared with the previous method.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.1
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• pp.1-8
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• 2023

In this paper, we developed a mid-range automotive radar systems based on the performance requirements and test procedures of the intelligent transport systems, that is lane change decision aid systems (LCDAS). The mid-range automotive radar has the maximum detection range up to 80m and an update time within 50ms. The computational loads of a signal processing were reduced by using ROI preprocessing technique. Considering actual driving environments, radar performance evaluations were conducted in two driving scenarios at an automotive proving ground.