• The Journal of Korea Robotics Society
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• v.18 no.1
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• pp.53-58
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• 2023

In general, in order to operate an autonomous underwater vehicle (AUV) in an underwater environment, a navigation system such as a Doppler Log (DVL) using a Doppler phenomenon of ultrasonic waves is used for speed and direction estimation. However, most of the ultrasonic sensors in underwater is large for long-distance sensing and the cost is very high. In this study, not only canal neuromast on the fish's lateral lines but also superficial neuromast are studied on the simulation to obtain pressure values for each pressure sensor, and the obtained pressure data is supervised using spherical CNN. To this end, through supervised learning using pressure data obtained from a pressure sensor attached to an underwater vehicle, we can estimate the speed and angle of the underwater vehicle in a quasi-static underwater environment and propose a method for a non-ultrasonic based navigation system.

• Structural Engineering and Mechanics
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• v.56 no.5
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• pp.871-897
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• 2015

This paper presents a novel method based on sensitivity of structural response for identifying both the system parameters and input excitation force of a bridge. This method, referred to as "Adjoint Variable Method", is a sensitivity-based finite element model updating method. The computational cost of sensitivity analyses is the main concern associated with damage detection by these methods. The main advantage of proposed method is inclusion of an analytical method to augment the accuracy and speed of the solution. The reliable performance of the method to precisely indentify the location and intensity of all types of predetermined single, multiple and random damages over the whole domain of moving vehicle speed is shown. A comparison study is also carried out to demonstrate the relative effectiveness and upgraded performance of the proposed method in comparison to the similar ordinary sensitivity analysis methods. Moreover, various sources of error including the effects of noise and primary errors on the numerical stability of the proposed method are discussed.

• Interaction and multiscale mechanics
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• v.3 no.1
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• pp.95-110
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• 2010

In recent years, study of the static response of pavements to moving vehicle and aircraft loads has received significant attention because of its relevance to the design of pavements and airport runways. The static response of beams resting on an elastic foundation and subjected to moving loads was studied by several researchers in the past. However, most of these studies were limited to steady-state analytical solutions for infinitely long beams resting on Winkler-type elastic foundations. Although the modelling of subgrade as a continuum is more accurate, such an approach can hardly be incorporated in analysis due to its complexity. In contrast, the two-parameter foundation model provides a better way for simulating the underlying soil medium and is conceptually more appealing than the one-parameter (Winkler) foundation model. The finite element method is one of the most suitable mathematical tools for analysing rigid pavements under moving loads. This paper presents an improved solution algorithm based on the finite element method for the static analysis of rigid pavements under moving vehicular or aircraft loads. The concrete pavement is discretized by finite and infinite beam elements, with the latter for modelling the infinity boundary conditions. The underlying soil medium is modelled by the Pasternak model allowing the shear interaction to exist between the spring elements. This can be accomplished by connecting the spring elements to a layer of incompressible vertical elements that can deform in transverse shear only. The deformations and forces maintaining equilibrium in the shear layer are considered by assuming the shear layer to be isotropic. A parametric study is conducted to investigate the effect of the position of moving loads on the response of pavement.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.447-451
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• 2011

Recently, various in-vehicle networks have been developed respectively in order to accomplish their own purposes such as CAN and MOST. Especially, the MOST network is usually adapted to provide entertainment service. The car navigation system is also widely used for guiding driving paths to driver. The position for the navigation system is usually acquired by GPS technology. However, the GPS technique has two serious problems. The first is unavailability in urban canyons. The second is inherent positional error rate. The problems have been studied in many literatures. However, the second still leads to incorrect locational information in some area, especially parallel roads. This paper proposes a performance tuning method of image matching algorithm for the car navigation system. The method utilizes images obtained from in-vehicle MOST network and a real-time image matching algorithm which determines the direction of moving vehicle in parallel section of road. In order to accuracy improvement of image matching algorithm, three conditions are applied. The experimental tests show that the proposed system increases the accuracy.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.258-272
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• 2022

The technology implementation method was diversified into an 'autonomous cooperative driving' method to overcome the limitations of a stand-alone autonomous vehicle with vehicle sensor-based autonomous driving. The autonomous cooperative driving method involves exchanging information between roadside infrastructure and autonomous vehicles. In this process, the concept of dynamic information (LDM), a target of cooperation, was established. But, evaluation methods and standards for dynamic information have not been established. Therefore, this study, a dynamic information evaluation method based on information on pedestrians within the moving objects. In addition, autonomous cooperative driving was demonstrated, and dynamic information was also verified through the evaluation method. The significance of this study is that it established the dynamic information evaluation methodology for autonomous cooperative driving for the first time. Based on this, this study is expected to contribute to the application of safe autonomous cooperative driving technology to the field.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3672-3679
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• 2012

Vehicle Ad hoc Network (VANET) is next-generation network technology to provide various services using V2V (Vehicle-to-Vehicle) and V2I (Vehicle-to-Infrastructure). In VANET, many researchers proposed various studies for the safety of drivers. In particular, using the emergency message to increase the efficiency of traffic safety have been actively studied. In order to efficiently transmit to moving vehicle, to send a quick message to as many nodes is very important via broadcasting belong to communication range of vehicle nodes. However, existing studies have suggested a message for transmission to the communication node through indiscriminate broadcasting and broadcast storm problems, thereby decreasing the overall performance has caused the problem. In addition, theses problems has decreasing performance of overall network in various form of road and high density of vehicle node as urban area. Therefore, this paper proposed Clustering based Routing Algorithm (CBRA) to efficiently transmit emergency message in high density of vehicle as urban area. The CBRA managed moving vehicle via clustering when vehicle transmit emergency messages. In addition, we resolve linkage problem between vehicles according to various form of road. The CBRA resolve link brokage problem according to various form of road as urban using clustering. In addition, we resolve broadcasting storm problem and improving efficacy using selection flooding method. simulation results using ns-2 revealed that the proposed CBRA performs much better than the existing routing protocols.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.184-189
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• 2008

In this study, an artificial wheel load generation method is proposed to assist practical engineers performing dynamic analysis with simple procedure. To generate an artificial wheel loads from running vehicle, PSD(Power Spectrum Density) profiles of actual wheel load were sampled in terms of various road roughnesses. A detailed truck and bridge models were used for sampling actual wheel load to represent the real motion of moving vehicle. These wheel load profiles were simplified for the artificial wheel load. The simplification of actual wheel load profiles was performed by regression analysis. The result showed that the artificial wheel load well represents the real profiles of wheel load.

• Structural Engineering and Mechanics
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• v.10 no.3
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• pp.197-209
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• 2000

The effects of weight and axial inertia of a beam are taken into account for studying the nonlinear vibration of the Timoshenko beam due to external loads. The combination of Galerkins method and Runge-Kutta method are employed to obtain the dynamic responses of the beam. A concentrated force and a two-axle vehicle traversing on the beam are taken as two examples to investigate the response characteristics of the beam. Results show that the effect of axial inertia of the beam increases the fundamental period of the beam. Further, both the dynamic deflection and the dynamic moment of the beam obtained with including the effect of axial inertia of the beam are greater than those of the beam without including that effect of the beam.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.1
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• pp.11-20
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• 2000

This paper presents the method of extracting the contour and shape parameters for moving object tracking in traffic scenes. The contour is extracted by applying difference image method in reduction image and the features are extracted from original image to grow the accuracy of tracking. We used features such as circle distribution, center moment, and maximum and minimum ratio. Data association problem is solved by these features. Kalman filters are used for moving object tracking on real time. The simulation results indicate that the proposed algorithm appears to generate feature vectors good enough for multiple vehicle tracking.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.677-680
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• 2015

In this paper, we propsed scheme to mitigate conflict and loss of message in vehicle communication. And vehicles that exist in the moving direction, were grouping to the cluster form. Through, to select best relay vehicle, transmit a message to the destination. In addition, we applied the double rayleigh fading environment so that can applied in real-environments. Therefore, vehicle communication network applied proposed scheme, can be problem of mitigate conflict and loss of message. Thus, Increase the reliability of the received signal.