• Journal of the Korean Society for Railway
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• v.16 no.2
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• pp.144-150
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• 2013

This paper presents an analysis of door design for the Ui LRT based on experiments to predict doorway flow-time and their analyses results. A similar railway vehicle (from Gimhae LRT) and operational conditions are utilized to assess the doorway flow-time through repetitive experiments. Design of the experiments consists of four scenarios, and the experiments are repeated 39 times in total. We use the results of the experiments to verify the design of doors of Ui LRT (e.g. the required number of doors and their width). Various statistical analyses are carried out for the flow-time with respect to the number of boarding/alighting passengers. We make three category levels of boarding/alighting passengers, and analyze the mean and variance for each category, and then carry out One-Way ANOVA to analyze how the number of boarding/alighting and onboard passengers impact flow-time. The results of this paper can be used for making decisions about doors of the LRT vehicle.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.527-528
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• 2016

현대인들이 가장 많이 사용하는 대중교통은 버스이다. 이에 DB를 통해 많은 이용횟수를 보이는 출, 퇴근시간대에 급행버스를 배치하여 보다 편리한 생활을 위해 다음과 같은 프로젝트를 진행하게 되었다. 서울시를 중심으로 이용객의 시간별, 일별, 월별 승하차 인원을 조사하고 지역인구와 승하차 인원의 연관관계를 탐색하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.06a
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• pp.23-24
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• 2011

본 논문에서는 승객 수송수요 반영 단계에서는 역별 승하차인원, 시간대별 재차인원 등 수송수요에 반영할 기준을 설정하여 수송력과 승차인원의 기준을 판단하고, 열차운행계획 수립 단계에서는 운행구간, 선로용량, 선로조건 등 제약조건과 적정수송력에 맞는 운행계획을 수립하고, 마지막 단계에서 경제성, 능률성, 합리성 등을 감안한 운용효율 향상을 위한 열차 DIA를 작성하고자 한다. 또한 통계적 분석절차에 따라 재차인원과 운행횟수를 각각의 독립변수와 종속변수로 산정하여 두 변수간의 상관관계를 확인한 후 회귀분석을 통해 얻은 회귀식을 실제열차운행 횟수와 비교하여 최적의 열차운행횟수를 산정하였으며 회귀식의 유효성 검증을 통해 열차운행 환경변화에 신속하게 대응할 수 있는 유연한 시스템을 구축한 후 서울도시철도공사 실용 Dia에 적용하여 유효성을 검토하였다.

• Korean Journal of Construction Engineering and Management
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• v.22 no.1
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• pp.27-35
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• 2021

The study intends to identify the effects of infrastructure property on an apartment house by analyzing the price variation affected by factors constituting the quality of the transit services of each individual station in urban railway system based on hedonic price model. The research findings indicate that the prices depending on the transit users have increased from 7.8% to 12.2% in Seoul and decreased from 6.1% to 12.9% in Gyeonggi, which implies that a lower number of transfer users has a positive effect on housing prices in Seoul unlike Gyeonggi. It also is noteworthy that the distance to the urban railway station had a negative effect on housing prices in Seoul and positive effect in Gyeonggi. Taking these results together, in Seoul, the increase in the number of transit users had a negative effect on neighborhood housing prices. When analyzed by segments, however, an additional negative effect was observed only in the apartments located within the radius of 100 meters. It is also found that the impact of transit users varies according to the regional characteristics, such as the density of commercial facilities and the population density, and the spatial extent of negative effect also showed regional differences. These results provide implications for the planning of new stations, new cities, and land use of existing areas around stations.

• Journal of Korean Society of Transportation
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• v.28 no.6
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• pp.85-97
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• 2010

The present study aims at estimating the model of bus bunching duration along with its influential determinants in an attempt to understand the status of bus bunching being created by buses from various routes converging into one bus stop. To do so, the duration analysis, a well-known survival analysis, was adopted in order to capture the distribution of duration time as for 8 base lines, accordingly developing the model best fit for weibull distribution. Key attention to draw out the duration time model for bus bunching phenomena was laid, by analyzing 18 impact factors, on such criterion variables as number of berth, number of bus line in each berth and maximum capacity of on-and-off passengers in each line. Comparison in two typical types of bus lane was made between bus-only center lane(Dobong Mia-ro) and normal street-side lane(Tongil Euiju-ro). In this regard, the study, based on the model as above, suggested appropriate alternatives to improve the bus operation by effectively controlling bus bunching.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.261-273
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• 2022

This study aims to analyze whether facilities linked to the inside and outside of the station affect the revitalization of commercial spaces inside the station where individual rental stores are clustered. Rent, which can replace sales, was set as the determining factor for revitalization. In addition to the variables related to sales, culture, office work/residential, public institutions, and transportation facilities, the independent variables were the number of daily passengers, which is a location factor of the station, and the product sales business, which accounts for the largest number of industries in the commercial space inside the station. As a result of regression analysis, it was proved that rent has an effect on product sales business, linked sales facilities, transportation facilities, and the number of passengers on board. These results indicate that the formation of sales products that can increase purchasing power and the direction of facility linkage that can increase the inflow population into the station are needed to revitalize commercial spaces in the station. In this study, the establishment of a living-friendly SOC for residents' convenience daily life was suggested as a policy management plan for stations with a high vacancy rate due to reduced vitalization.

• International Journal of Highway Engineering
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• v.13 no.4
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• pp.211-220
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• 2011

TOD(Transit Oriented Development) has recently been active, which presents that TOD planning elements should be comprehensively taken into consideration in order to enhance domestic transit ridership by changing environments in rail station areas and an empirical analysis on the type of rail station areas and transportation demand should be a prerequisite for usage of future development planning. This study aims to grasp a variety of TOD of influence factors in Seoul rail station area and to perform analysis to identify relationship between public transportation demand and these TOD design factors. To make it come true, we gathered data with respect to Density, Diversity, and Accessibility as representative TOD planning elements and carried out factorial and regression analysis. Consequently, we drew 7 influence factors base on factorial analysis: Factor 1(Diversity/ -Use Mix(LUM)), Factor 2(Density/development density), Factor 3(Accessibility/public transportation facility supply), Factor 4(Design/street design), Factor 5(Green/access mode (pedestrian, bike), Factor 6(Design/subway size), Factor 7(Accessibility/Public transit operation) As the result of model development by using factorial and regression analysis, positive influence factors on passenger flow in rail station area are Factor 1(Diversity : Land-Use Mix), Factor 3(Accessibility : public transportation facility supply), Factor 2(Density : development density), Factor 5(Design/ access mode) and Factor 6(subway size) Next, negative influence factor on passenger flow in rail station area shows Factor 7(Accessibility/Public transit operation) as the most influential factor. This is because the growth of service interval of linked subway and bus leads to reduced demand.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1612-1627
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• 2008

Dwelling time is one of the factors that influence in rail. Current research in dwelling time has been focusing on railways, the state of the research in high-speed rail's dwelling time is not complete. Dwelling time is consisted of time to open door, time to get into and out of vehicle and time of the departure it takes after the passenger's door was closed, it was affected by various factors such as congestion's degree in vehicle, the number of persons that get into and out of vehicle, congestion's degree in station. In order to analyze theses, we need data analysis such as the number of persons that get into and out of vehicle, congestion's degree in station, congestion's degree in vehicle, but the congestion's degree and passenger's distribution chart in vehicle is excluded in this research due to difficulty of gathering data, and thus we will develop forecasting models through high-speed rail's demand most affected by the dwelling time.

• Journal of the Semiconductor & Display Technology
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• v.22 no.4
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• pp.13-18
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• 2023

A subway station is a prominent multi-purpose facility where the quantitative management of fine dust, generated by various factors, is conducted. Recently, eco-friendly air purification methods using air-purifying plants are being discussed, with the focus on biofiltration through vegetation. Previous research in this field has confirmed the reduction effects of transition metals such as Fe, which have been identified as harmful to human health. This study aimed to identify the sources of fine dust dispersion within subway stations and derive an efficient operational strategy for air-purifying plants that takes into account the behavior characteristics of fine dust within multi-purpose facilities. The experiment monitored regional fine dust levels through IAQ stations established based on prior research. Also, the data was analyzed through time-series and correlation analyses by linking it with passenger counts at subway stations and the frequency of train stops. Furthermore, to consider energy efficiency, we conducted component-specific power consumption monitoring. Through this study, we were able to derive the optimal operational strategy for air-purifying plants based on time-series comprehensive analysis data and confirm significant energy efficiency.

• Journal of Korean Society of Transportation
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• v.32 no.2
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• pp.139-151
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• 2014

This paper analyzes factors affecting rail transit ridership at urban rail stations of the Daegu Metropolitan City in 2011. Rail transit ridership is analyzed by dividing weekdays and weekends in order that their differences may be observed. The data used in this study includes various explanatory variables, such as floor area which was collected from building ledger and GIS cadastral map, number of bus routes(line) possible to transfer from urban rail transit, number of students enrolled in middle and high schools, and universities located in access areas of rail transit. For this study, multiple regression models are estimated including various explanatory variables affecting rail transit ridership of weekdays and weekends. From the study, the number of statistically significant explanatory variables and the relative effect of each variable are shown to be different between weekdays and weekends.