• Proceedings of the KSR Conference
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• 2005.05a
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• pp.1073-1083
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• 2005

Since the operation of subway line 1 between Seoul and Cheongryangri stations in 1974, the rail length and riderships have been increased during the three decades. Furthermore, it was a remarkable increase of line length between 1995 and 2004 by the operation of Lines 5, 6, 7, and 8 within Seoul metropolitan area. This study reports the variations of riderships by the changing urban spatial structure. According to analysis results by station-to-station origin-destination trip tables, there were increasing ridership changes in new stations within new subcenters, while there were little ridership changes in old stations within Seoul and existing subcenters. The levels of competition between the existing and new lines brought about the difference of ridership changes.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.135-147
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• 2008

One of the efforts both to prevent urban sprawling development patterns and to promote use of public transportation is known as Transit-Oriented Development (TOD), including such planning elements as the density and diversity of land use and pedestrian-friendly urban design around a transit center. The aim of this study is thus to conduct impact analyses of TOD planning elements on transit ridership in the Seoul rail station areas. First, the authors investigate and draw out various actual elements of TOD planning by using GIS-based data and Smart Card data. Then the authors analyze impacts of TOD planning elements on transit ridership for the Seoul rail station areas. After condensing 34 variables presumably influencing transit ridership into seven factors by using factor analyses, the study utilizes multiple regression modeling methods to identify their impacts on transit ridership. The analysis results demonstrate that transit ridership tends to increase more in rail station areas where there is a non-residential high density, mixed use of land and narrow and small-size road network patterns. The implementation of TODs should be a useful method in inducing a Transit-Oriented City through redevelopment and new development.

• Journal of the Korean Society for Railway
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• v.18 no.2
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• pp.166-174
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• 2015

A direct demand model requires relatively little analysis time and incurs a low cost. It is also known to be useful for the preliminary screening of promising configurations or concepts. This study reviews direct demand models of 12 existing urban railways using demographic data based on a block group level which is approximately 1/24 of a traditional zone area. However, direct demand models are limited. Therefore, a new approach is suggested. The proposed method is based on a field study and an empirical analysis. The study finds factors that affect ridership at the station level. As a case study, the proposed approach is tested using 54 light railway transit stations. The results of this empirical study demonstrate its applicability to improve the error rates of the predicted ridership at the station level.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.3
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• pp.147-159
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• 2014

Public transportation ridership and walkability of urban district can be enhanced through high quality of TOD(Transit Oriented Development) elements. Generally, TOD have been evaluated several physical components such as the diversity of land use pattern, accessibility of public transportation and aspects of urban design around the station area. Especially, Spatial characteristics of TOD planning elements have many potential dependent when considering the characteristics of Rail Station-Influenced Area Development which is performing around subway station. Therefore, researchers should be considering the variation of spatial properties for planning elements according the set of spatial area and their socioeconomic factors. However, existing many cases related TOD does not consider about this point. In this paper, the changes of TOD characteristics were analyzed by different spatial units surrounding subway station in Busan Metropolitan City. Multiple Regression Analysis was performed for an investigation of effective spatial unit of TOD planning elements in this area using subway ridership data. In addition, the application validity of socioeconomic variables was examined through a comparative analysis of regression results with the multiple regression that implied only physical TOD elements. As the result, the variation of spatial properties for TOD planning elements according to the set of spatial unit was found. Furthermore, the specific spatial unit to applicable TOD elements in this area was derived. And the multiple regression model which added socioeconomic variables was derived more improved estimate results than the multiple regression model that implied only physical TOD elements.

• Journal of Korean Society of Transportation
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• v.25 no.5
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• pp.111-122
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• 2007

This paper investigates the rail service patterns by train class. The emphasis in intercity rail planning is to more efficiently use of existing station facilities. Rail transit operations are affected by the system layout and ridership patterns and by work rules. Operations are also influenced by past practices and the institutional setting. Main factors to decide train service patterns are the location, socioeconomic characteristics, land use and travel demand of the station. In this context, the travel demand of intercity rail station is of crucial significance. Tests on a KTX case shows that train service frequency can be efficiently decreased in weekday to transport the same passenger demand. The work has shown many subjects that need further research including various factors influencing on train frequency. This study serves the railroad authorities in planning and determining business strategy in the increasingly competitive environment of regional rail transport.

• Journal of the Korean Geographical Society
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• v.45 no.5
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• pp.592-608
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• 2010

This study investigates the diurnal pattern of transit ridership in the Metropolitan Seoul area. For the purpose, we use a weekday Smart Card passenger transaction data in 2005. Eleven passenger trip patterns are found from 2.74 million passengers moving on the Metropolitan Seoul Metro system. Among them, we analyze 2.4 million passengers blonging to five trip types having only one or two transaction record during a day. A total of 357 metro stations are classified to four types according to their diurnal pattern of passenger riderships. We analyze the relationships between passenger's trip chain patterns and subway station's diurnal transit ridership patterns. The result shows that the ratio of the number of passengers of particular time of the day is hierarchically related with trip chain patterns.

• Journal of Information Technology Services
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• v.17 no.4
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• pp.139-150
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• 2018

This paper investigated the human distribution in subway station areas in Seoul, using geotweets and subway ridership data. Eight stations were selected from the districts of Gangnam and Gangbuk. Geotweets located within a 600-meter radius of the central coordinates of each station were extracted, and distances between the center of station and each tweet location were calculated. Donut-shaped dimension and pie-shaped dimension were generated, using the Haversine distance formula and the Azimuth angle formula respectively. By combining the two dimensions, Dartboard-shaped space division is created. Popular places within the subway station areas identified from this research are almost the same as the current well-known popular places, and this is an important case showing that people send tweets from various places where they engage in daily activities. We expect this study can be a methodological guideline for social scientists who use spatio-temporal or GPS data for their research.

• Journal of the Economic Geographical Society of Korea
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• v.15 no.1
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• pp.26-41
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• 2012

This study investigates the time-space characteristics of intra-urban passenger flows in the Metropolitan Seoul area. In particular, we analyze the relationships between transit ridership and land use through the use of the subway passenger flow data obtained from the transit transaction databases. For this purpose, the strength of each subway station, i.e., the number of total in-coming and out-going passengers at each station, in the morning, afternoon, and evening, is calculated and visualized, which reflects urban land use patterns. Then the subway stations are classified into four groups via a hierarchical analysis of the in-coming and out-going passenger flows at 353 stations. Each group appears to have characteristic properties according to the region, e.g., residential areas and central business districts. This has been confirmed by the analysis which probes explicitly the relationship between the local socio-economic variables and station groups. This analysis, disclosing the inter-relationship between the subway network and urban land use, may be useful at various stages in urban as well as transportation planning, and provides analytical tools for a wide spectrum of applications ranging from impact evaluation to decision-making and planning support.

• Spatial Information Research
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• v.22 no.5
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• pp.65-75
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• 2014

Bus headway plays an important role not only in determining the passenger waiting time and bus service quality, but also in influencing the bus operation cost and passenger demand. Previous research on headway control has considered only an hourly difference in the distribution of ridership between peak and non-peak hours. However, this approach is too simple to help manage ridership demand fluctuations in a short time scale; thus passengers' waiting cost will be generated when ridership demand exceeds the supply of bus services. Moreover, bus ridership demand varies by station location and traffic situation. To address this concern, we propose a headway control algorithm for minimizing the waiting time cost by using Smart Card data. We also provide proof of the convergence of the algorithm to the desired headway allocation using a set of preconditions of political waiting time guarantees and available fleet constraints. For model verification, the data from the No. 143 bus line in Seoul were used. The results show that the total savings in cost totaled approximately 600,000 won per day when we apply the time-value cost of waiting time. Thus, we can expect that cost savings will be more pronounced when the algorithm is applied to larger systems.

• 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.