• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.17 no.1
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• pp.13-20
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• 2007

This study was performed to investigate the concentrations of PM($PM_{10}$, $PM_{2.5}$, $PM_{1}$) and it's affecting factors in the subway from line 1 to line 8 in Seoul metropolitan area, from Sep. 1 to 30, 2005. PM concentrations were measured at the entrances and centers in subway passenger cabins by a light scattering equipment. And the affecting factors to PM were estimated based on the number of passenger, door open and close and running area etc. The geometric means of $PM_{10}$, $PM_{2.5}$ and $PM_{1}$ concentration in Seoul subway passenger cabins were $214{\mu}g/m^3$, $86.6{\mu}g/m^3$ and $27.0{\mu}g/m^3$, respectively. These mean concentrations in subway carriage were higher when it ran on an underground track than on a ground track. And running time(7AM-9AM, 11AM-13PM, 6PM-8PM) significantly influenced to the concentrations of $PM_{10}$, $PM_{2.5}$ and $PM_{1}$. Daily profile of $PM_{10}$ and $PM_{2.5}$, $PM_{1}$ expressed as an 10 minutes average, showed similar variation pattern over day period. In correlation analysis, significant relations among $PM_{10}$, $PM_{2.5}$ and $PM_{1}$ were detected(p〈0.01). In particular, correlation coefficient between $PM_{10}$and $PM_{1}$ was highly significant(r=0.94). Further study is needed to identity the sources of PM in subway cabins and to compare pollutants concentration among subway lines.

• Journal of the Economic Geographical Society of Korea
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• v.11 no.3
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• pp.459-475
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• 2008

This study analyzes the network structure of the Metropolitan Seoul subway system by applying complex network analysis methods. For the purpose, we construct the Metropolitan Seoul subway system as a network graph, and then calculate various indices introduced in complex network analysis. Structural characteristics of Metropolitan Seoul subway network are discussed by these indices. In particular, this study determines the shortest paths between nodes based on the weighted distance (physical and time distance) as well as topological network distance, since urban travel movements are more sensitive for them. We introduce an accessibility measurement based on the shortest distance both in terms of physical distance and network distance, and then compare the spatial structure between two. Accessibility levels of the system have been getting up overall, and thus the accessibility gaps have been getting lessen between center located subway stops and remote ones during the last 10 years. Passenger traffic volumes are explored from real passenger transaction databases by utilizing data mining techniques, and mapped by GIS. Clear differences reveal between the spatial patterns of real passenger flows and accessibility. That is, passenger flows of the Metropolitan Seoul subway system are related with population distribution and land use around subway stops as well as the accessibility supported by the subway network.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.3
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• pp.247-255
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• 2021

Individual passenger transfer information is not included in Seoul metropolitan subway Automatic Fare Collection (AFC) data. Currently, basic data such as travel time and distance are allocated based on the TagIn terminal ID data records of AFC data. As such, knowledge of the actual path taken by passengers is constrained by the fact that transfers are not applied, resulting in overestimation of the transport index. This research proposes a method by which a transit path that connects the TagIn and TagOut terminal IDs in AFC data is determined and applied to the transit index. The method embodies the concept that a passenger's line of travel also accounts for transfers, and can be applied to the transit index. The path selection model for the passenger calculates the line of transit based on travel time minimization, with in-vehicle time, transfer walking time, and vehicle intervals all incorporated into the travel time. Since the proposed method can take into account estimated passenger movement trajectories, transport-related data of each subway organization included in the trajectories can be accurately explained. The research results in a calculation of 1.47 times the values recorded, and this can be evaluated directly in its ability to better represent the transportation policy index.

• Proceedings of the KOR-KST Conference
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• 1998.09a
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• pp.3-16
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• 1998

The goal of the transportation policy of Seoul is to increase the ridership of the subway system by constructing the public transportation network, the subway system. To accomplish this goal, the city of Seoul has been constructing the Metropolitan Subway System. Currently, seven subway lines which connect major areas in Seoul are operating. However, the ridership of subway system was not increased as much as we expected, even though more subway lines have been implemented. It seems that although the length of the subway line was extended, the current way of the subway operation that trains stop at every station cannot satisfy the passenger's need. Thus, we should try to increase the demand by providing quicker services and diversifying the subway operations; changing the point of view is required. This paper introduces the distinctive features of the express subway system and the model for analysing the effects of that system. This paper also presents the results for the feasibility study of the express subway system on the 5th Subway Line and Kyong-Eue Railway Line. Based on the results of the case studies, We can conclude as : First, the express system reduces a total travel time by about $13\%$; in particular, the Kyong-Eue Line is more effective than the subway Line ${\sharp}5$. Second, the shorter headway of express trains increases the time saving effects on subway system although it requests more waiting time to low-speed train passengers. When the service frequency is increased from 5 to 7.5 times/hour, total saved time ratio is about $10\%$ in the Subway Line ${\sharp}5$ and about $18\%$ in the Kyong-Eue Line.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.250-253
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• 2007

The purpose of this research is focussed on the numerical predictions of the heat and smoke propagations for a passenger train fire in an underground subway tunnel for different air supply and extraction flowrates. The analysis is performed for one of the stations on subway line #5 in Seoul under the emergency operation mode for different air supply and extraction flowrates. Five different the air supply and extraction flowrates are considered for the numerical analyses. The numerical results show that the air supply and extraction flowrates affect the smoke control performance significantly by improving the smoke removal performance for the balanced control of air supply and smoke extraction and for the unbalanced control with lager smoke extraction than air supply.

• Proceedings of the KSR Conference
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• 2005.05a
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• pp.42-47
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• 2005

When the train travels quickly, in the center of city subway tunnel the strong wind blows caused by its piston effect, and the train wind blows while train enter the subway station with this effect. The train wind brings unpleasantness which passenger's hair wavering and the skirts of passengers flapping severely, and critical situations to the old and the weak people. It considers seriously like this, the research is meant to find extent of subway train wind influence on the passengers from the part Seoul subway stations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.14-24
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• 2018

Pedestrian movement of passengers using smart card within stations can be divided into three types of activities - straight ride and alight, line transfer, and station transfer. Straight ride and alight is transfer activity for which the card terminal and embarking line are identical. In this case, straight ride occurs at the origin station and straight alight occurs at the destination station. Line transfer refers to activity in which the subway line embarked on by the passenger is different from that which is disembarked. Succinctly, line transfer is transfer at a middle station, rather than at origin or destination stations. Station transfer occurs when the card terminal line and embarking line are different. It appears when station transfer happens at the origin station as starting transfer, and at the destination station as destination transfer. In the case of Metropolitan smart card data, origin and destination station card terminal line number data is recorded, but subway line data does not exist. Consequently, transportation card data, as it exists, cannot adequately be used to analyze pedestrian movement as a whole in subway stations. This research uses the smart card data, with its constraints, to propose an analysis model for passenger pedestrian movement within subway stations. To achieve this, a path selection model is constructed, which links origin and destination stations, and then applied for analysis. Finally, a case study of the metropolitan subway is undertaken and pedestrian volume analyzed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.49-63
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• 2019

Crowdedness management at subway platforms is essential to improve services, including the prevention of train delays and ensuring passenger safety. Establishing effective crowdedness mitigation measures for platforms requires accurate estimation of the congestion level. There are temporal and spatial constraints since crowdedness on subway platforms is assessed at certain locations every 1-2 years by hand counting. However, smart cards generate real-time big data 24 hours a day and could be used in estimating congestion. This study proposes a model based on data from transit cards to estimate crowdedness dynamically. Crowdedness was defined as demand, which can be translated into passengers dynamically moving along a subway network. The trajectory of an individual passenger can be identified through this model. Passenger flow that concentrates or disperses at a platform is also calculated every minute. Lastly, the platform congestion level is estimated based on effective waiting areas for each platform structure.

• Journal of the Korean Society for Railway
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• v.20 no.3
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• pp.413-422
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• 2017

In this study we investigate the importance of the subway station using network centrality measures. For centrality measures, we have used betweenness centrality, closeness centrality, and degree centrality. A new measure called weighted betweenness centrality is proposed, that combines both traditional betweenness centrality and passenger flow between stations. Through correlation analysis and power-law analysis of passenger flow on the Seoul metropolitan subway network, we have shown that weighted betweenness centrality is a meaningful and practical measure. We have also shown that passenger flow between any two stations follows a highly skewed power-law distribution.

• Journal of Environmental Health Sciences
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• v.35 no.6
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• pp.454-460
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• 2009

The subway is the major public transportation system in Seoul with 2.2 million people using it everyday. Indoor air pollution in the subway can be a significant part of population exposure because of the number of people using the subway, time spent in transit and potentially high exposure for certain pollutants. The Korea Ministry of Environment has established the level 2 of recommended standards of $PM_{10}$ and $CO_2$ in subway trains. The aims of this study were to determine the airborne levels of $PM_{10}$, $CO_2$ and any correlation between pollutant levels and number of passenger in a subway train. The airborne $PM_{10}$ and $CO_2$ were measured on the inside of trains on line #4 for 4 different days from October to November in 2008. Average $PM_{10}$ and $CO_2$ levels were $113{\pm}25{\mu}g/m^3$ and $1402{\pm}442$ ppm, respectively. These levels did not exceed the level 2 of recommended standards of $250{\mu}g/m^3$ for $PM_{10}$ and 3500 ppm for $CO_2$. $PM_{10}$ level was not correlated with the number of passengers, while $CO_2$ levels were positively correlated with the number of passengers. The findings suggested that $PM_{10}$ in subway trains may have sources other than those directly associated with the number of passengers.