• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.729-734
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• 2004

The e-Logistics means the virtual business activity and service architecture among the logistics companies based on the Internet technology. The management of vehicles' location in most conventional vehicle tracking system has some critical defects when it deals with data which are continuously changed. It means the conventional vehicle tracking system based on the conventional database is unable eventually to cope with the environment that should manage the frequently changed location of vehicles. The important things in the evaluation of the vehicle tracking system is to determine the threshold of cost of database ,update period and communication period between vehicles and the system. In other words, the difference between the reallocation of vehicle and the data in database can evaluate the overall performance of vehicle tracking systems. Most of the previous works considers only the information that is valid at the current time, and is hard to manage efficiently the past and future information. To overcome this problem, the efforts on moving objects management system(MOMS) and uncertainty processing have been started from a few years ago. In this paper, we propose an uncertainty processing model and system implementation of moving object that tracks the location of the vehicles. We adopted both linear-interpolation method and trigonometric function to chase up the location of vehicles for the past time as well as future time, respectively. We also explain the comprehensive examples of MOMS and uncertainty processing in parcel application that is one of major application of e-Logistics domain.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.1
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• pp.31-39
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• 2011

This paper presents design and control of a quarter-vehicle magneto-rheological (MR) suspension system for ECS (electronic control suspension). In order to achieve this goal, MR shock absorber is designed and manufactured based on the optimized damping force levels and mechanical dimensions required for a commercial mid-sized passenger vehicle. After experimentally evaluating dynamic characteristics of the manufactured MR shock absorber, the quarter-vehicle MR suspension system consisting of sprung mass, spring, tire and the MR shock absorber is constructed in order to investigate the ride comfort and driving stability. After deriving the equations of the motion for the proposed quarter-vehicle MR suspension system, the skyhook controller is then implemented for the realization of quarter-vehicle MR suspension system. In order to present control performance of MR shock absorber for ECS, ride comfort and driving stability characteristics such as vertical acceleration of sprung mass and tire deflection are experimentally evaluated under various road conditions and presented in both time and frequency domain.

• Journal of the Korea Convergence Society
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• v.9 no.1
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• pp.253-259
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• 2018

The Korea Convergence Society. Recently, as the 4th industrial revolution is rising, there are many changes in various field of industries. Among these industries, autonomous vehicles based on artificial intelligence, big data and internet of things is one of the most promising industry. Autonomous vehicle stray from classical car domain of manufacturers and suppliers, IT/Electronics suppliers and communication companies are widen their business area to autonomous vehicle technology. In this paper, we analysis the state of art of autonomous vehicle technology and development direction of industries/research institute. Finally, we discuss the social/economic effects of autonomous vehicle.

• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.1
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• pp.130-136
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• 2009

A lumped parameter model of Li-ion battery in hybrid electric vehicle(HEV) is constructed and system parameters are identified by using recursive least square estimation for different C-rates, SOCs and temperatures. The system characteristics of pole and zero in frequency domain are analyzed with the parameters obtained from different conditions. The parameterized model of Li-ion battery indicates highly dependant of temperatures. The system pole and internal resistance changes 6.6 and 18 times at $-20^{\circ}C$, comparing with those at $25^{\circ}C$, respectively. These results will be utilized on constructing model-based state observer or an on-line identification and an adaptation of the model parameters in battery management systems for hybrid electric vehicle applications.

• Journal of the Ergonomics Society of Korea
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• v.32 no.2
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• pp.167-177
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• 2013

Objective: This study aims to compare the usefulness of subjective measures which are comprised of existing methods like NASA-TLX, Bedford-scale and ZEIS and newly developed method like DALI in measuring drivers' mental workload in terms of validity, sensitivity and diagnosticity. Background: Nowadays, with the development of intelligent vehicle and HMI, mental workload of driver has become more and more important. For this reason, the studies on drivers' mental workload about driving situation and the use of information technology equipment such as mobile phones and navigations were conducted intensively. However, the studies on measuring drivers' mental workload were rarely conducted. Moreover, most of studies on comparison of subjective measures were used with performance based measure. However, performance based measures can cause distraction effect with subjective measures. Method: Participants (N=19) were engaged in a driving simulation experiment in 2 driving contexts (downtown driving and highway driving context). The experiment has 2 sessions according to driving contexts. The level of difficulties by driving contexts were adjusted according to existence of intersections, traffic signs and signals, billboards and the number of doublings. Moreover, as criteria of concurrent validity and sensitivity, the EEG data were recorded before and during the sessions. Results: The results indicated that all subjective methods were correlates with EEG in high-way driving. On the contrary to this, in downtown driving, all subjective methods were not correlates with EEG. In terms of sensitivity, multi-dimensional scales (NASA-TLX, DALI) were the only ones to identify differences between high way and downtown driving. Finally, in terms of diagnosticity, DALI was the most suitable method for evaluating drivers' mental workload in driving context. Conclusion: The DALI as newly developed method dedicated to evaluate driver's mental workload was superior in terms of sensitivity and diagnosticity. However, researchers should consider the characteristics of each subjective method synthetically according to research objective by selecting the method in subjective measures. Application: The results of this study could be applied to the intelligent vehicle and next generation of HMI design to decrease mental workload of driver and for the development of new subjective method in vehicle domain.

• Structural Engineering and Mechanics
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• v.29 no.2
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• pp.135-154
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• 2008

The moving vehicle loads on a bridge deck is one of the most important live loads of bridges. They should be understood, monitored and controlled before the bridge design as well as when the bridge is open for traffic. A MOM-based algorithm (MOMA) is proposed for identifying the timevarying moving vehicle loads from the responses of bridge deck in this paper. It aims at an acceptable solution to the ill-conditioning problem that often exists in the inverse problem of moving force identification. The moving vehicle loads are described as a combination of whole basis functions, such as orthogonal Legendre polynomials or Fourier series, and further estimated by solving the new system equations developed with the basis functions. A number of responses have been combined, some numerical simulations on single axle, two axle and multiple-axle loads, being either constant or timevarying, have been carried out and compared with the existing time domain method (TDM) in this paper. The illustrated results show that the MOMA has higher identification accuracy and robust noise immunity as well as producing an acceptable solution to ill-conditioning cases to some extent when it is used to identify the moving force from bridge responses.

• The Journal of the Acoustical Society of Korea
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• v.28 no.7
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• pp.646-652
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• 2009

In this paper, welding pitch optimization technique of vehicle subframe is presented considering the fatigue life of spot welding nuggets. Fatigue life of spot welding nuggets is estimated by using the frequency-domain fatigue analysis technique. The input data, which are used in the fatigue analysis, are obtained by performing the dynamic analysis of vehicle model passing through the Belgian road profile and also the modal frequency response analysis of finite element model of vehicle subframe. According to the fatigue life result obtained from the frequency-domain fatigue analysis, the design points to optimize the weld pitch distance are determined. For obtaining the welding pitch combination to maximize the fatigue life of the spot welding nuggets, 4-factor, 3-level orthogonal array experimental design is used. This study shows that the optimized subframe improves the fatigue life of welding nugget with minimum fatigue life about 65.8 % as compared with the baseline design.

• Wind and Structures
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• v.25 no.1
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• pp.63-77
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• 2017

When railway vehicles run by towers of long span bridges, the railway vehicles might experience a sudden load-off and load-on phenomenon in crosswind conditions. To ensure the running safety of the railway vehicles and the running comfort of the passengers, some studies were carried out to investigate the impacts of sudden changes of aerodynamic loads on moving railway vehicles. In the present study, the aerodynamic coefficients which were measured in wind tunnel tests using a moving train model are converted into the aerodynamic coefficients in the actual scale. The three-component aerodynamic loads are calculated based on the aerodynamic coefficients with consideration of the vehicle movement. A three-dimensional railway vehicle model is set up using the multibody dynamic theory, and the aerodynamic loads are treated as the inputs of excitation varied with time for kinetic simulations of the railway vehicle. Thus the dynamic responses of the railway vehicle passing by the bridge tower can be obtained from the kinetic simulations in the time domain. The effects of the mean wind speeds and the rail track positions on the running performance of the railway vehicle are discussed. The three-component aerodynamic loads on the railway vehicle are found to experience significant sudden changes when the vehicle passes by the bridge tower. Correspondingly, such sudden changes of aerodynamic loads have a large impact on the dynamic performance of the running railway vehicle. The dynamic responses of the railway vehicle have great fluctuations and significant sudden changes, which is adverse to the running safety and comfort of the railway vehicle passing by the bridge tower in crosswind conditions.

• Journal of the Korean Society for Railway
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• v.9 no.2 s.33
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• pp.187-192
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• 2006

The regularity of railway track alignment is a crucial component fur maintaining travel safety and the smoothness of passenger ride. The conventional spectral analysis has been considered to estimate the severity of the track irregularity from measured data. The time domain data used to be changed into the frequency domain by Fourier transform. Because the measuring points can be regarded as the time points, the spatial-frequency can be introduced instead of the time-frequency. Although FFT(Fast Fourier Transform) and/or PSD(Power Spectral Density) function could provide fairly localized information within frequency domain, but chronical configurations of data could be missed. In this study, we attempt to apply the Morlet wavelet transform for the purpose of a frequency-time-domain analysis rather than a frequency-domain analysis. The applicability of wavelet transform is examined for the estimation of the track irregularity with real measured track data on the section of Kyoung-bu line by EM-120 measuring vehicle. It is shown that the wavelet transform can be an effective tool to manage the track irregularity.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1309-1314
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• 2003

If an agent has a learning ability using previous knowledge, then it is expected that the agent can speed up learning by interacting with environment. In this paper, we present an improved reinforcement learning algorithm using domain knowledge which can be represented by problem-independent features and their classifiers. Here, neural networks are employed as knowledge classifiers. To show the validity of our proposed algorithm, computer simulations are illustrated, where navigation problem of a mobile robot and a micro aerial vehicle(MAV) are considered.