• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.19-27
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• 2019

This paper proposes a new method using multi-layer overlapped windows to improve the performance of YOLO network which is vulnerable to detect small dense objects. In particular, the proposed method uses the YOLO Network based on the multi-layer overlapped windows to track small dense vehicles that approach from long distances. The method improves the detection performance for location and size of small vehicles. It allows crossing area of two multi-layer overlapped windows to track moving vehicles from a long distance to a short distance. And the YOLO network is optimized so that GPU computation time due to multi-layer overlapped windows should be reduced. The superiority of the proposed algorithm has been proved through various experiments using captured images from road surveillance cameras.

• The KIPS Transactions:PartB
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• v.14B no.3 s.113
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• pp.163-170
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• 2007

In autonomous navigation of a mobile vehicle or a mobile robot, localization calculated from recognizing its environment is most important factor. Generally, we can determine position and pose of a camera equipped mobile vehicle or mobile robot using INS and GPS but, in this case, we must use enough known ground landmark for accurate localization. hi contrast with homography method to calculate position and pose of a camera by only using the relation of two dimensional feature point between two frames, in this paper, we propose a method to calculate the position and the pose of a camera using relation between the location to predict through perspective transform of 3D feature points obtained by overlaying 3D model with previous frame using GPS and INS input and the location of corresponding feature point calculated using KLT tracking method in current frame. For the purpose of the performance evaluation, we use wireless-controlled vehicle mounted CCD camera, GPS and INS, and performed the test to calculate the location and the rotation angle of the camera with the video sequence stream obtained at 15Hz frame rate.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.1
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• pp.29-37
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• 2015

In this study, the estimation of axial load and total axial load was conducted using Bridge Weigh-in-Motion(BWIM) technique which generally consists of devices for measuring the strain induced in the bridge by the vehicles. axle detectors for collecting information on vehicle velocity and axle spacing. and data acquisition equipment. Vehicle driving test for the development of the BWIM system is necessary but it needs much cost and time. In addition, it demands various driving conditions for the test. Thus, we need a numerical-simulation method for resolving the cost and time problems of vehicle driving tests, and a way of measuring bridge response according to various driving conditions. Using a bridge model reflecting the dynamic characteristic contributes to increased accuracy in numerical simulation. In this paper, we conduct a numerical simulation which reflects the dynamic characteristic of a bridge using the Bridge Weigh-in-Motion technique, and suggest overload vehicle enforcement technology.

• Journal of Korean Society of Steel Construction
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• v.10 no.4 s.37
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• pp.577-587
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• 1998

The influences of high speed train on the dynamic responses of steel composite railway bridges are investigated. The bridge system which has two I-girder and several cross beams is modeled with plate and frame elements. With assumption of concrete slabs are fully connected with steel girders, the offset between slabs and girders is modeled using constraint equation. The track system is modeled using beams on elastic foundation theory. And, the TGV train model is developed in 2-dimension considering bouncing and pitching motion. And braking action of vehicle is considered using speed dependent braking function. To investigate the behavior of bridges due to moving trains, parametric studies on the variation of natural frequency of bridge, speed parameter, vehicle modeling method, braking action of train, etc are performed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.155-162
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• 2014

In this paper, we propose an efficient shaking correction techniques for a moving vehicle image stabilization. The proposed shaking correction techniques was calculated cumulative histogram for the conversion and the separating information via color separation of video image frame of the input received. And it were to matching the histogram for match the color information as compensation result of the shaking vehicle video imaging. In this paper, the proposed the shaking correction techniques was obtained to the restoration result when compared to the existing shaking correction techniques that the smallest noise and better the naturalness of image through stabilization of luminance level and color level. Also, the imaging stabilization method was demonstrated the efficiency compared to other methods through to the real-time processing without the use of the memory.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.6
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• pp.1655-1665
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• 2014

Dynamic displacements of structures shows general behavior of structures. Generally, It is used to estimate structure condition and trustworthy physical quantity directly. Especially, measuring vertical displacement which is affected by moving load is very important part to find or identify a problem of bridge in advance. However directly measuring vertical displacement of the bridge is difficult because of test conditions and restriction of measuring equipment. In this study, Artificial Neural Network (ANN) is used to suggest estimation method of bridge displacement to overcome constrain conditions, restriction and so on. Horizontal strain and vertical displacement which are measured by appling random moving load on the bridge are applied for learning and verification of ANN. Measured horizontal strain is used to learn ANN to estimate vertical displacement of the bridge. Numerical analysis is used to acquire learning data for axis strain and vertical displacement for applying ANN. Moving load scenario which is made by vehicle type and vehicle distance time using Pearson Type III distribution is applied to analysis modeling to reflect real traffic situation. Estimated vertical displacement in respect of horizontal strain according to learning result using ANN is compared with vertical displacement of experiment and it presents vertical displacement of experiment well.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.6
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• pp.549-559
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• 2015

In this paper, an efficient dynamic reactive motion planning method for an autonomous vehicle in a dynamic environment is proposed. The purpose of the proposed method is to improve the robustness of autonomous robot motion planning capabilities within dynamic, uncertain environments by integrating a virtual plane-based reactive motion planning technique with a sensor fusion-based obstacle detection approach. The dynamic reactive motion planning method assumes a local observer in the virtual plane, which allows the effective transformation of complex dynamic planning problems into simple stationary ones proving the speed and orientation information between the robot and obstacles. In addition, the sensor fusion-based obstacle detection technique allows the pose estimation of moving obstacles using a Kinect sensor and sonar sensors, thus improving the accuracy and robustness of the reactive motion planning approach. The performance of the proposed method was demonstrated through not only simulation studies but also field experiments using multiple moving obstacles in hostile dynamic environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.10
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• pp.850-857
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• 2012

A moving network is the usage model that provides the mobile stations to the communication service via the mobile relay deployed in the high-speed vehicle. The mobile relay periodically performs the signal strength measurement of the neighbor base stations to select the target base station during the handover procedure. The mobile stations experience the service disruption during the measurement of the mobile relay. In this paper, we propose the estimation based scanning method to overcome the service disruption of the mobile stations connected via the mobile relay. In the proposed method, mobile stations subordinated in the mobile relay periodically measure the signal strength of neighbor base stations in order to perform handover. The measured signal strength is used to estimate the signal strength between the mobile relay and the neighbor base station. We performed simulations in order to evaluate the performance of the proposed method in terms of the estimation accuracy and the overhead due to the exchange of channel information. By the simulation result, The estimation error is less than 4dBm when more than 6 mobile stations are used for the estimation. The overhead caused by the proposed method is less than that caused by the direct measurement of the mobile relay when the data rate is more than 8Mbps.

• Structural Monitoring and Maintenance
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• v.7 no.2
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• pp.149-166
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• 2020

This paper presents the results of an experimental investigation on a vibration-based damage identification framework for a steel girder type and a truss bridge based on acceleration responses to operational loading. The method relies on sensor clustering-based time-series analysis of the operational acceleration response of the bridge to the passage of a moving vehicle. The results are presented in terms of Damage Features from each sensor, which are obtained by comparing the actual acceleration response from the sensors to the predicted response from the time-series model. The damage in the bridge is detected by observing the change in damage features of the bridge as structural changes occur in the bridge. The relative severity of the damage can also be quantitatively assessed by observing the magnitude of the changes in the damage features. The experimental results show the potential usefulness of the proposed method for future applications on condition assessment of real-life bridge infrastructures.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2442-2447
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• 2015

Because an electric railway vehicle is a large scale moving load, it can cause various kinds of power quality problems in the railroad power system. The power quality impacts are considered as the strong instantaneous stresses to the related power systems and can cause an accelerating aging and a malfunction of the power supplying components. Therefore, it is necessary to detect the small and intermittent symptoms mixed in the voltage waveform. However, they cannot be detected by the triggering functions of the existing power analyzers installed in the railway systems. This paper will examine the drawback of some fast detection tools and propose an advanced detecting and analyzing method based on a combined TEO and STFT algorithm.