• Journal of Trauma and Injury
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• v.29 no.4
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• pp.155-160
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• 2016

Purpose: Two years have passed since a level I trauma center was officially opened in the Gacheon Gil Hospital, South Korea. We analyzed 2014 and 2015 registered patient data from the Korean Trauma Data Base (KTDB) to identify trends in trauma patient care and factors that influence the quality of trauma care at the Gacheon Gil trauma center. Methods: Data was extracted from the KTDB included patient age, sex, systolic blood pressure at emergency room arrival, revised trauma score, injury severity score, trauma injury severity score, transfusion amount, and the cause of death was analyzed. Results: A total of 3269 trauma patients were admitted to our trauma center in 2014 and 3225 in 2015. Demographics and mechanism of injury were not significantly different between years. The severity of trauma injury was decreased in 2015 although the mortality rate was slightly increased. This requires further analysis. Conclusion: The aim of this study was to determine the general status and trends in trauma incidence and management outcomes for the Incheon area. We noted no significant changes in trauma status from 2014 to 2015. We need to collect and review trauma patient data over a long period in order to elucidate trauma incidence and management trends in the trauma field. Finally, studies using trauma patient data will indicate appropriate quality control factors for trauma care and help to improve the quality of trauma management.

• Journal of Korean Society of Transportation
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• v.29 no.1
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• pp.17-27
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• 2011

This paper investigates some critical errors influencing travel demand estimation in Korea Transportation Data Base (KTDB), and through this investigation reasonable traffic analysis zone (TAZ) size and internal trips ratio are analyzed. With varying zone size, the accuracy of travel demand estimation is studied and appropriate level of zone size in KTDB is also presented. For this purpose zonal structure consisting of location of zone centroid, number of centroid connecters has been constructed by social economic index, and then some descriptive statistical analyses such as F-test, coefficient of correlation are performed. From the results, this paper shows that the optimum levels of zone system were various according to the order and capacity of roads, and also shows that the smaller TAZ, the less error in this research. In conclusion, in order to improve accuracy of traffic demand estimation it is necessary to make zone size smaller.

• Journal of Korean Society of Transportation
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• v.31 no.2
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• pp.45-59
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• 2013

This study deals with the comparative analysis between two freight demand estimation methods : Unimodal O/D based method and P/C based method. The data of access/egress truck trips has been omitted from the Korean freight unimodal O/D of KTDB. This is because KTDB's unimodal O/D has not marked the series of unlinked trips down as the whole freight intermodal transport and surveyed only the main-haul trips of them. For these reasons, freight intermodal transport mechanism has not been analysed perfectly with Korean unimodal O/D data. This study tries to estimate P/C table of Korean Import/Export container freight and develop the MCC(Multimodal Channel Choice) model. Then, comparing unimodal O/D based method and P/C based method in terms of the switch commodities between production point(the initial point of freight transport) and consumption point(the terminal point of freight transport), unimodal commodities, and commodities on links is conducted. The results show that the P/C based method is able to simulate the freight intermodal transport.

• Journal of Korean Society of Transportation
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• v.35 no.6
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• pp.469-480
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• 2017

On April 1, 2004, KTX (Korea Train eXpress), the first HSR (High-Speed Rail) in Korea, was introduced to Gyeongbu Line. The introduction of the KTX service led to a change in the number of passengers for Gyeongbu Line. Previous studies have analyzed the pre and post-event changes of the intervening events by either simple statistics or intervention ARIMA analysis. However, the intervention ARIMA model has a limitation that several assumptions such as the occurrence time and the type of intervention events are necessary. To this end, this study analyzed the effects of intervention event on the number of passengers using the Gyeongbu line based on a time series outlier detection technique which can overcome limitations in the previous studies. The time series outlier detection technique can analyze the time, effect type and size of an intervention event without the assumption of the time and effect type of the intervention event. The data were collected from the Korea Transport Database (KTDB) for twelve years from 2003 to 2014 (144 months). The analysis results showed that the size of the influence type in the same intervention events was different across the major city routes, and the intervention event which could not be found by previous study methods was also found.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.1
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• pp.1-13
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• 2019

With commercial apps popular in EU, MaaS has been emerging around the globe as a new approach to worsening urban traffic problems. In contrast, it is still mainstay in Korea simply discussing the concept and necessities of MaaS, rather than seeking for real-world solutions for the commercialization. The purpose of this research is to analyze the demand-side i1mpacts of travel time and cost changes according to MaaS adoption, and to see its commercial feasibility in Korea. The 2010 KTDB traveler's nationwide OD data is used to estimate the level of fare discount for balancing the mode shift and fare revenue changes followed by MaaS implementation. The analysis results show that MaaS leads to the increase of public transport ridership as a result of the diminishing travel cost and time, and that the time saving works more positively for ridership increase. Also, the optimum level of fare discount is estimated 2.56% without damaging the revenue. This finding reveals that MaaS impact is superior to the other single-sided public transport inventive measures since it can affect both travel cost and time reduction at the same time.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.32-48
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• 2023

Autonomous driving technology is shaping the future of personalized travel, encouraging personalized travel, and traffic impact could be influenced by individualized travel behavior during the transition of driving entity from human to machine. In order to evaluate traffic impact, it is necessary to estimate the total number of trips based on an understanding of individual travel characteristics. The Activity-based model(ABM), which allows for the reflection of individual travel characteristics, deals with all travel sequences of an individual. Understanding the relationship between travel and travel must be important for assessing traffic impact using ABM. However, the ABM has a limitation in the data hunger model. It is difficult to adjust in the actual demand forecasting. Therefore, we utilized a Tour-based model that can explain the relationship between travels based on household travel survey data instead. After that, vehicle registration and population data were used for correction. The result showed that, compared to the KTDB one, the traffic generation exhibited a 13% increase in total trips and approximately 9% reduction in working trips, valid within an acceptable margin of error. As a result, it can be used as a generation correction method based on Tour, which can reflect individual travel characteristics, prior to building an activity-based model to predict demand due to the introduction of autonomous vehicles in terms of road operation, which is the ultimate goal of this study.

• Journal of Korean Society of Rural Planning
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• v.23 no.2
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• pp.43-54
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• 2017

When an age of low growth and population decline, population migration plays an important role in spatial structure of region. There have been many researches on migration and regional spatial structure. The purpose of this study is to examine the changes of Gwangju and Jeonnam region's spatial structure and central area using social network analysis methods. For analysis it was used that population and migration data and passenger OD(Origin and Destination) travel data released by Statistics Korea and Korea Transport Database(KTDB). Using Gephi 0.8.2, migration and passenger OD networks were visualized, and this describe network flow and density. The results of the network centrality analysis show that the most populated village is not always network center though population mass is an important factor of central places. The average eigenvector centrality of 2010 migration is the lowest during 2005-2015, and it means few regions have high centralities. When comparing migration and travel networks, travel data is more effective than migration data in determining the central location considering spatial functions.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.4
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• pp.253-259
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• 2013

Investment scenarios in the transportation network design problem usually contain installation or expansion of multi-mode transportation links. When one applies the mode choice analysis and traffic assignment sequentially for each investment scenario, it is possible that the travel impedance used in the mode choice analysis is different from the user equilibrium cost of the traffic assignment step. Therefore, to estimate the travel impedance and mode choice accurately, one needs to develop a combined model for the mode choice and traffic assignment. In this paper, we derive the inverse demand and the excess demand functions for the multi-mode multinomial logit mode choice function and develop a combined model for the multi-mode variable demand traffic assignment problem. Using data from the regional O/D and network data provided by the KTDB, we compared the performance of the partial linearization algorithm with the Frank-Wolfe algorithm applied to the excess demand model and with the sequential heuristic procedures.

• Journal of Korean Society of Transportation
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• v.30 no.6
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• pp.47-57
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• 2012

The purpose of this study is to propose a supplement to current freight demand model by analyzing factors that influence the generation of empty truck movements in regional and urban realms. To achieve this, we examined the relation between the number of empty truck trips and various generators such as truck attributes, origin type and attributes, destination type and attributes, and commodity type. We structured the ordered logit model using 2011 Korea Transport Database (KTDB) data to analyze the generator characteristic of empty truck movements in regional and urban settings. According to the results, the characteristics of regional and urban empty truck movements differed depending on truck attributes, origin type and attributes, destination type and attributes, and commodity type.

• Journal of Information Technology Applications and Management
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• v.26 no.1
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• pp.95-102
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• 2019

Public transportation systems play key roles in supporting dynamic activities and interaction between urban places. Especially, high efficient public transportation systems are required in order to support large traffic demands in urban areas. In this paper, we define a new metric, structural activation level (SAL), to replace the conventional transportation share ratio (TSR) measuring efficiency of public transportation systems. First of all, we access the Korea Transport Database (KTDB) and download origin-destination data by transport types to construct traffic networks with respect to transport types for each city. Then, we calculate the QAP (Quadratic Assignment Procedure) correlation between each traffic network and the total traffic network for each city to investigate SAL by comparing cities one another. The results of our investigation reveal inconsistency between TSR and SAL. In Daegu, TSR of public transportation systems is relatively low while SAL is high. In Deajeon, however, SAL is low while TSR is high. Therefore, we suggest to take into consideration SAL as well as TSR in order to investigate the degree of activation of public transportation.