• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.7
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• pp.16-22
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• 2014

Automotive NVH on brake operation is mainly caused by a coupling action of vehicle speed and inter parts friction and its frequency occurs over a broad band of 0.1 kHz~10 kHz. Especially, squeal noise, being a self-excited vibration generated by friction force between drum and lining, occurs over 1 kHz and consequently dynamic instability is induced when friction energy is applied to a brake vibration system. The squeal strongly depends on nonlinear properties influenced by the material of lining, velocity of vehicle, and the dynamic properties of a brake system. The dynamic properties are considered as a main influential design factor to squeal noise, however the analysis of the properties are rarely facilitated due to arbitrariness of shape by wearing down. In this paper, we research generating tendency of squeal noise through complex eigenvalue analysis, tracking drum brake's unstable modes in accordance with the wear shape of drum and lining such as tapered and bellmouth shape, and analyze computed unstable modes by variable shapes.

• Proceedings of the KIPE Conference
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• 2014.07a
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• pp.325-326
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• 2014

This paper is research about the Maximum Power Point Tracking following algorism of solar power system attached small electric car. In this paper, we investigate P&O MPPT and Incremental Conduction MPPT among existing MPPT following algorism. And by changing them, the better algorism is proposed being able to follow Maximum Power Point rapidly as amount of solar radiation changes applied to the Solar Energy Generation System.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.51-59
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• 2024

In this paper, we propose a novel traffic safety system designed to reduce pedestrian traffic accidents and enhance safety on university campuses. The system involves real-time detection of vehicle speeds in designated areas and the interaction between vehicles and pedestrians at crosswalks. Utilizing the YOLOv5s model and Deep SORT method, the system performs speed measurement and object tracking within specified zones. Second, a condition-based output system is developed for crosswalk areas using the YOLOv5s object detection model to differentiate between pedestrians and vehicles. The functionality of the system was validated in real-time operation. Our system is cost-effective, allowing installation using ordinary smartphones or surveillance cameras. It is anticipated that the system, applicable not only on university campuses but also in similar problem areas, will serve as a solution to enhance safety for both vehicles and pedestrians.

• Journal of the Korean Society for Railway
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• v.17 no.5
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• pp.336-341
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• 2014

The articulated structures seen in train or tram applications are being applied in road transportation systems, for use in mass passenger transit. When articulated vehicles are driven on public roads, they no longer follow a guided track. Therefore, there are a lot of control elements that need to be considered, such as turning radius, swept path width, off-tracking, and swing-out. Some of the currently available articulated vehicles on roads are equipped with an independent drive system; a system that has one motor at each wheel. Through this drive system, each wheel can be independently controlled, making precise and quick dynamic stability control possible. In this paper, we propose a torque distribution algorithm that can reduce the overall turning radius of the articulated vehicle, which has been verified through dynamic simulation.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.6
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• pp.619-623
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• 2008

A lane detection system is one of the major components of intelligent vehicle systems. Difficulties in lane detection mainly come from not only various weather conditions but also a variety of special environment. This paper describes a simple and stable method for the broken lane tracking in various environments. Probabilistic Hough Transform (PHT) and the Least-square method (LSM) are used to track and correct the lane orientation. For the efficiency of the proposed method, two regions of interest (ROIs) are placed in the lower part of each image, where lane marking areas usually appear with less intervention in our system view. By testing in both a set of static images and video sequences, the experiments showed that the proposed approach yielded robust and reliable results.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.117-125
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• 2008

The Object tracking by real-time image analysis is one of the major concerns in computer vision and its application fields. The Object detection process of real-time images must be preceded before the object tracking process. To achieve the stable object detection performance in the exterior environment, adaptive background model generation methods are needed. The adaptive background model can accept the nature's phenomena changes and adapt the system to the changes such as light or shadow movements that are caused by changes of meridian altitudes of the sun. In this paper, we propose a robust background model generation method effective in an illegal parking auto-detection application area. We also provide a evaluation method that judges whether a moving vehicle stops or not. As the first step, an initial background model is generated. Then the differences between the initial model and the input image frame is used to trace the movement of object. The moving vehicle can be easily recognized from the object tracking process. After that, the model is updated by the background information except the moving object. These steps are repeated. The experiment results show that our background model is effective and adaptable in the variable exterior environment. The results also show our model can detect objects moving slowly. This paper includes the performance evaluation results of the proposed method on the real roads.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.6
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• pp.121-130
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• 2009

In this paper, Gaussian probability distribution model based multi-sensor data fusion algorithm is proposed for a vehicular location awareness system. Conventional vehicular location awareness systems are operated by GPS (Global Positioning System). However, the conventional system is not working in the indoor of building or urban area where the receiver is difficult to receive the signal from satellites. A method which is combined GPS and UWB (Ultra Wide-Band) has developed to improve this problem. However, vehicular is difficult to receive seamless location information since the measurement systems by both GPS and UWB convert the vehicle's movement information separately at each sensor. In this paper, normalized probability distribution model based Hybrid UWB/GPS is proposed by utilizing GPS location data and UWB sensor data. Therefore the proposed system provides information with seamless and location flexible properties. The proposed system tested by Ubisense and Asen GPS in the $12m{\times}8m$ outdoor environments. As a result, the proposed system has improved performance for accurateness and connection ability between devices to support various CNS (Car Navigation System).

• Journal of Astronomy and Space Sciences
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• v.18 no.1
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• pp.63-70
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• 2001

IDGPS(Inverted Differential Global Positioning System) is one of technique improving the accuracy of GPS positioning and is mostly used for tracking an automatic vehicle. In the IDGPS, the user send it’s GPS position and related satellite information to dispatcher, and the corrections are made at the dispatcher to get corrected user position. IDGPS suffered correction degradation as the baseline become large. This problem is resolved using NIDGPS(Network IDGPS). As the experimental results are demonstrated, the improvement of position accuracy using IDGPS and NIDGPS is verified.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.11a
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• pp.147-153
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• 2005

폐기물의 처리과정을 발생부터 최종 처리까지 처리경로를 확인하여 적정하고 투명한 처리를 도모하기 위해 폐기물의 배출에서부터 최종처리까지의 과정을 실시간 확인할 수 있는 Web 기반의 폐기물 적법처리 입증정보시스템을 구축하였다. 그러나 위치적으로 고정적인 폐기물 배출자 및 처리자와는 달리 양자간에 움직이며 폐기물을 실질적으로 이동하는 폐기물 운반차량의 관리에 대한 한계가 제기되고 있다. 이러한 폐기물 운반차량의 부실관리는 운반차량의 불법적인 투기 및 부실운반 사례로 이어져, 폐기물의 방치로 인한 환경오염을 초래하게 된다. 이러한 문제점을 해결하고자 국내의 실정에 맞는 GPS를 이용한 위치추적시스템을 구축하여 폐기물운반차량관리를 할 수 있는 시스템구축의 필요성이 제기되고 있다. 본 연구에서는 국내 도로데이터 구축현황, 시스템 구축방법 등 국내 실정에 맞는 폐기물 운반차량 위치추적시스템 구축에 대한 방법에 대한 연구를 수행하였다.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1871-1876
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• 2005

In this paper, We present a new nonlinear adaptive control law using a disturbance accommodating control (DAC) observer for a Japanese automatic landing flight experiment vehicle called ALFLEX. A future spaceplane must have ability to deal with greater fluctuations in the stability and control derivatives of flight dynamics, because its flight region is much wider than that of conventional aircraft. In our previous studies, digital adaptive flight control systems have been developed based on a linear-parameter-varying (LPV) model depending on dynamic pressure, and obtained good simulation results. However, under previous control laws, it is difficult to accommodate uncertainties represented by disturbance and nonlinearity, and to design a stable flight control system. Therefore, in this study, we attempted to design a nonlinear adaptive control law using the DAC Observer and inverse dynamic methods. A good tracking property of the obtained system was confirmed in numerical simulation.