• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.5
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• pp.91-101
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• 2014

In this study, we presented a timing verification method for a passenger car diesel engine management system (EMS) using measurement-based worst-case execution time (WCET) analysis. In order to cope with AUTOSAR-compliant software architecture, a development process model is proposed. In the process model, a runnable is regarded as a test unit and its temporal behavior (i.e. maximum observed execution time, MOET) is obtained along with on-target functionality evaluation results during online unit test. Furthermore, a cost-effective framework for online unit test is proposed. Because the runtime environment layer and the standard calibration environment are utilized to implement test interface, additional resource consumption of the target processor is minimized. Using the proposed development process model and unit test framework, the MOETs of 86 runnables for diesel EMS are obtained with 213 unit test cases. Using the obtained MOETs of runnables, the WCETs of tasks are estimated and the schedulability is evaluated. From the schedulability analysis results, the problems of the initially designed schedule table is recognized and it is fixed by redesigning of the runnable mapping and task offset. Through the various test scenarios, the proposed method is validated.

• Journal of the Korean Society for Railway
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• v.20 no.4
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• pp.482-490
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• 2017

This study is a railway accident investigation statistic study with the purpose of prediction and classification of accident severity. Linear regression models have some difficulties in classifying accident severity, but a logistic regression model can be used to overcome the weaknesses of linear regression models. The logistic regression model is applied to escalator (E/S) accidents in all stations on 5~8 lines of the Seoul Metro, using data mining techniques such as logistic regression analysis. The forecasting variables of E/S accidents in urban railway stations are considered, such as passenger age, drinking, overall situation, behavior, and handrail grip. In the overall accuracy analysis, the logistic regression accuracy is explained 76.7%. According to the results of this analysis, it has been confirmed that the accuracy and the level of significance of the logistic regression analysis make it a useful data mining technique to establish an accident severity prediction model for urban railway casualty accidents.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.1177-1190
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• 2010

The high-speed railway track occurs train operating result track irregularity, subsidence of the track, ballast abrasion. This is the unusual condition. High-speed railway track maintenance task is the behavior which repairs unusual section by using the human resource or machine resource. The resource used to maintenance task is restrictive. A resource can be efficiently used if the high-speed railway track maintenance scheduling is used. So the more task can be performed in the fit time. In conclusion, this manages the unusual condition of a track efficiently. So additional expenses is minimized cause by deteriorating unusual condition. And it offers comfortable ride to passenger. However, maintenance scheduling has to reflect well practical situation and environment. That's maintenance scheduling is used. We gather the opinions of the hands-on workers. So in this paper define field situation and condition. And suggest mathematical model about this. And we developed the track maintenance scheduling software engine using ILOG.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.1
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• pp.24-29
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• 2017

There is a need for explosion experiments for explosion-related research. However, there are many restrictions in performing an actual experiment. Therefore, in this paper, an alternative method of overcoming the constraints of an explosion experiment has been conducted using a passenger behavior analysis program called MADYMO to assess and analyze the human body injury due to explosion load. To increase the reliability of the analysis, a drop test has been conducted with the analysis. We provide a new framework for performing the analysis. In future, we will further develop our research with the goal of reducing the opportunity cost for the study of the human body injury.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1712-1723
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• 2008

In the trackbed design using an elastic multi-layer model, the stress-dependent resilient modulus is the key input parameter, which reflects substructure performance under repeated traffic loading. The prediction models of resilient modulus of crushed stone and weathered granite soil were developed from nonlinear dynamic stiffness, which can be combined by in-situ and laboratory seismic measurements. The models accommodate the variation with the deviatoric and/or bulk stresses. To investigate the performance of the prediction models proposed, the elastic response of the test trackbed near PyeongTaek, Korea was evaluated using a 3-D nonlinear elastic computer program (GEOTRACK) and compared with measured elastic vertical displacement caused by the passages of freight and passenger trains. The material types of the test sub-ballasts are crushed stone and weathered granite soil, respectively. The calculated vertical displacements within the sub-ballasts are within the order of 1mm, and agree well with measured values with the reasonable margin. The prediction models are thus concluded to work properly in the preliminary investigation.

• Journal of the Korean Society for Railway
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• v.12 no.2
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• pp.302-308
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• 2009

This paper presents a comprehensive analysis of intercity rail passengers' and travel patterns based on the 2001 Seoul-Busan rail passengers' Travel Survey. Results representing personal characteristics such as age and income seem to affect on destination the income was not seen to be a critical effect on destination choice. The variables such as travel time, transfer status, and date for travel seem to be and recreation activity. However, the destination choice would be relationship between Seoul and all four destination cities. The insights gained of an activity-based rail travel demand model.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.1
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• pp.41-48
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• 2022

Vehicle vibration was introduced in the time and frequency domains using fast Fourier transform (FFT) analysis. In particular, a vibration mode analysis and characteristics of the frequency response function (FRF) in a sport utility vehicle (SUV) passing over a bump barrier at different speeds was performed systematically. The response behavior of the theoretical acceleration was obtained using a numerical method applied to the forced vibration model. The amplitude and frequency of the external force on the vehicle cause various power spectra with individual intrinsic system frequencies. In this regard, several modes of power spectra were acquired from the spectra and are discussed in this paper. The proposed technique can be used for monitoring the acceleration in a vehicle passing over a bump barrier. To acquire acceleration signals, various experimental runs were performed using the SUV. These acceleration signals were then used to acquire the FRF and to conduct mode analysis. The vehicle characteristics according to the vehicle condition were analyzed using FRF. In addition, the vehicle structural system and bump passing frequencies were discriminated based on their power spectra and other FRF spectra.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.1
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• pp.55-70
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• 2018

Recently, as shared transportation services has expanded, integrated mobility services that link personal transportation and public transportation are paid attention. To do this, it is necessary to analyze trip mode chaining behavior. This study analyzed the characteristics of the trip mode chaining behavior using the 2010 travel diary survey in Seoul, and analyzed factors to affect mode choice of trip chaining through the multinomial logit model. The transportation means were classified into passenger cars, city buses, intercity buses, railways, taxis, and others, and 25 trip mode chaining types were identified. Among them, the trip share connected between city bus and railways was the highest. It was also found that the trip mode chaining occurred mainly at commuting and in the morning and afternoon peak. According to the model results, the mode choice of trip chaining is significantly influenced by individual attributes (sex and age), household attributes (car ownership and income), trip attributes (trip purpose, trip time and trip length), and arrival area attributes (number of subway lines and bus lines, ratio of commercial area, land use mix and central region).

• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.89-100
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• 2011

The MAGLEV (Magnetically Levitated Vehicle) system, which is under commercialization as a new transportation system in Korea, is operated by means of unmanned automatic control system. Therefore the plan of train operation should be carefully established and validated in advance. In general, when making the train operation plan, the statistically predicted traffic data is used. However, traffic wave can occur when real train service is operated, and the demand-driven simulation technology is required to review train operation plans and service qualities considering traffic wave. This paper presents a method and model to simulate the MAGLEV's operation considering continuous demand changes. For this purpose, we employed the discrete event model which is suitable for modeling the behavior of railway passenger transportation, and modeled the system hierarchically using DEVS (Discrete Event System Specification) formalism. In addition, through the implementation and experiment using DEVSim++ simulation environment, we tested the feasibility of the proposed model and it is also verified that our demand-driven simulation technology could be used for the prior review of the train operation plans and strategies.

• Journal of Korean Society of Transportation
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• v.27 no.1
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• pp.73-81
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• 2009

While various factors in passenger and freight demand analysis affect on destination choice, a key factor, in general. is an attractiveness measure by size variable (e.g., population. employment etc) in destination zone. In order to measure the attractiveness, some empirical studies suggested that disaggregate gravity model are more suitable than aggregate gravity model. This study proposes that truck travelers trip diary data among Korean commodity flow data could be used to estimate the behaviors of incorporating trip departure time, activity duration and attractiveness in destination. As a result, the main findings of size and distance variables coincide with the conventional gravity model having a positive effect of population variable and a negative effect of distance variable. Due to disaggregate gravity modeling, the unique findings of this study reports that small trucks are more likely to choose short distance and early morning, morning peak and afternoon peak departure time choice. On the other hand, large trucks are more likely to choose long distance and night time departure time choice.