• Journal of Korean Society of Transportation
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• v.17 no.5
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• pp.123-135
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• 1999

The rapid increase of Passenger cars which is caused by the discomfort of Public transit and the Preference of automobiles is the major factor of increasing traffic congestions in Seoul With the point that leading the automobilists to the Public transit can be the most important Policy to ease these traffic congestions, this study focuses on the behavioral aspects of company employees and university students and investigates factors influencing bus ridership. To be brief, by estimating bus ridership through count models, this study investigates factors which influence bus ridership and elicits Political suggestions which lead automobilists to Public transit. The Purpose in this study is the application of appropriate count data model. The count data models have been widely applied to the economic area from the middle of the 1980s and to transportation aspect mainly in the foreign countries from the latter half of the 1980s. Even though a few studies in this country employed count data model to count data. all of them were Poisson regression models without suitable tests for the importance of the model specification. In the end, as the result of statistical test, negative binomial regression model which is suitable for overdispersed data was found to be appropriate for the data of weekly bus ridership. To emphasize the importance of model specification, both of poisson regression model and negative binomial regression model were estimated and the results were compared.

• Journal of Korean Society of Transportation
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• v.32 no.2
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• pp.83-92
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• 2014

Weather condition is one of the crucial factors affecting travelers' mode choice. Nevertheless, there are numerous indefinite traffic phenomena under various weather conditions. This study was conducted to verify the hypothesis that transit riderships decrease as precipitation increases. To clarify the relationship between precipitation and transit ridership, a seemingly unrelated regression model was employed with data such as daily precipitation and daily transit riderships of 3 transit modes (bus, metro, and shuttle bus) collected in Busan for recent 24 months. The estimation results show that transit riderships decreased as the daily precipitation increased when the daily precipitation is greater or equal to 10mm/day (0.169%, 0.101%, and 0.172% reduction in bus, metro, and shuttle bus riderships, respectively, when the daily precipitation increased by 1mm). When comparing the impact of precipitation on transit riderships by modes using a cross-equation parameter restriction test, the decrease in metro ridership is relatively insensitive to the change in precipitation. However, the negative coefficient of precipitation in the metro ridership estimation model indicates that the transit users in Busan may alter their mode to taxi or automobile and/or may give up the trip itself in bad weather condition.

• Proceedings of the KOR-KST Conference
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• 1998.09a
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• pp.108-120
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• 1998

• Proceedings of the KSR Conference
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• 2005.05a
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• pp.1097-1100
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• 2005

This study explored the ridership pattern between Seoul and Busan after the introduction of KTX in 2004. Since the KTX opening, average daily passengers on the Kyungbu lines have increased. These figures clearly indicate that the transportation network is becoming railroad-centric. However, the operation. of the KTX will leave many existing Saemaul and Mugunghwa train sets idle, which will be put into operation for areas, not covered by the KTX. Statistics show that the railroad ridership is clarified the distinction between train service levels. So, our paper studied the change of market share by service levels between Seoul-Busan line which is a long distance route.

• KDI Journal of Economic Policy
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• v.42 no.4
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• pp.117-138
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• 2020

Few studies have specifically focused on the uncertainty of demand forecasting despite the fact that uncertainty is the one of greatest risks for governments and private partners in PPP projects. This study presents a methodology for finding robust contract conditions considering uncertainty in travel demand forecasting in a PPP project. Through a case study of an urban railway PPP project in Korea, this study uncovered the risk of excessive government payments to private partners due to the uncertainty in contracted forecast ridership levels. The results allow the suggestion that robust contract conditions could reduce the expected total level of government payments and lower user fees while maintaining profitability of the project. This study offers a framework that assists contract negotiators and gives them more information regarding financial risks and vulnerabilities and helps them to quantify the likelihood of these vulnerabilities coming into play during PPP projects.

• 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.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.859-867
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• 2019

Severe weather conditions, such as heavy snowfall, rain, heatwave, etc., may affect travel behaviors of people and finally change traffic patterns in transportation networks. To deal with those changes and prevent any negative impacts on the transportation system, understanding those impacts of severe weather conditions on the travel patterns is one of the critical issues in the transportation fields. Hence, this study has focused on the impacts of a weather condition on travel patterns of public transportations, especially when a heavy snowfall which is one of the most critical weather conditions. First, this study has figured out the most significant weather condition affecting changes of public transport ridership using weather information, card data for public transportation, mobile phone data; and then, developed a decision-tree model to determine complex inter-relations between various factors such as socio-economic indicators, transportation-related information, etc. As a result, the trip generation of public transportations in Seoul during a heavy snowfall is mostly related to average access times to subway stations by walk and the number of available parking lots and spaces. Meanwhile, the trip attraction is more related to business and employment densities in that destination.

• 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.

• 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.