• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.3
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• pp.1-11
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• 2023

COVID-19 has caused the dramatic reduction of public transportation demand in Busan Metropolitan City, that is, daily public transportation trips in 2020 dropped by approximately 920,000 trips from 2019 based on the public transportation card data. This study investigated the underlying factors affecting the public transportation demand discrepancy between before and after COVID-19 at the primary administration unit(i.e., Eup, Myeon, Dong) level with Ordered Logistic Regression model. Finding of this study is as follows. The primary administration units characterized with high ratio of welfare recipients, industrial area, and day boarders were heavily dependent on public transit, indicating little change in public transportation demand. On the other hands, the primary administration units which have high ratio of urban rail transit uses experienced significant reduction of public transportation demand. In conclusion, transportation policies taken under emergent situation such as COVID-19 need to take into account the region-based characteristics rather than unilateral ones.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.6
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• pp.1083-1091
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• 2016

This research uses public transportation card data to analyze the inter-regional transfer times, transfer frequencies, and transfer resistance that passengers experience during transit amongst the metropolitan public transportation modes. Currently, mode transfers between bus and rail are recorded up to five times during one transit movement by Trip Chain, facilitating greater comprehension of intermodal movements. However, lack of information on what arises during these transfers poses a problem in that it leads to an underestimation of transfer resistances on the Trip Chain. As such, a path choice model that reflects passenger movements during transit activities is created, which attains explanatory power on transfer resistance through its inclusion of transfer times and frequencies. The methodology adopted in this research is to first conceptualize the idea of metropolitan public transportation transfer, and in the case that mode transfers include the city-rail, to newly conceptualize the idea of transfer resistance using transportation card data. Also, the city-rail path choice model within the Trip Chain is constructed, with transfer time and frequency used to reevaluate transfer resistance. Further, in order to align bus and city-rail station administrative level small-zone coordinates to state and regional level mid-zone coordinates, the big node methdod is utilized. Finally, case studies on trip chains using at least one transfer onto the city-rail is used to determine the validity of the results obtained.

• Journal of the Korean Society for Railway
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• v.18 no.3
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• pp.270-277
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• 2015

In some sections of the Seoul Metropolitan Subway, severe congestion can be observed during rush hours and on specific days. The subway operators have been conducting regular surveys to measure the level of congestion on trains: the results are then used to make plans for congestion reduction. However, the survey has so far focused just on train' congestion and has been unable to determine non-recurring congestion due to special events. This study develops an algorithm to estimate the platform congestion rate by time using individual public transportation card data. The algorithm is evaluated by comparison of the estimated congestion rate and the ground truth data that are actually observed at non-transfer subway stations on Seoul subway line 2. The error rates are within ${pm}2%$ and the performance of the algorithm is fairly good. However, varying walking times from gates to platforms, which are applied to both non-peak periods and peak time periods, are needed to improve the algorithm.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.1
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• pp.101-116
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• 2017

This Study estimates the actual night traffic using the smart card data used by most of the public transportation users, and compares it with the current night bus routes by KT Telecom based on the night time call volume. In order to compare the current night bus and night trips evaluated by smart card data, we presented indicators related to the degree of matching, and estimated the volume of service currently provided. The unique approach of the study is that we chose subway station instead of bus stop for the unit of the study. Bus stops has their complexity in a way that stops with same name could belong to different administrative area depending on its direction. For this reason, we decided to use subway station and defined its adjacent administrative district as the scope of influence. Since night bus is the primary means of transportation during the late night, it is anticipated that they will be able to provide better service by calculating the actual traffic and selecting the routes.

• Journal of the Korean Society for Railway
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• v.20 no.5
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• pp.692-702
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• 2017

Recently, there has been a growing interest in using smart card data. However, there are restrictions on the utilization of data in many areas outside the Seoul metropolitan area because the data does not contain alighting information. This paper presents a methodology for estimating alighting stops of smart card data. Estimation results were verified by smart card data from Seoul and Gwangju. The estimation rates were 78.2% and 81.6% in Seoul and Gwangju, respectively. The matching accuracy was 54.2% and 33.4%, respectively. However, if up to two stops of error are allowed, the accuracy values were 93.6% and 94.0%, respectively. We also discussed changes in estimation results due to adjusting the allowable walking distance, which is a key parameter of trip chaining methods. As the allowable walking distance increases, the estimation rate increases, while the accuracy decreases, and it is found that the estimation results change by around 500m.

• 한국ITS학회:학술대회논문집
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• v.2007 no.10
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• pp.42-50
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• 2007

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.183-196
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• 2022

Public transportation accessibility has been evaluated through minimum level of service for public transportation. However it is evaluated based operators rather than users. This study analyzed the users' accessibility(first-mile, last-mile) to public transportation using altteul transport card data. As a result of user's accessibility of public transportation, rural areas was lower than that in the urban areas. This study calssified type 1 and 2 based average approach time, and average approach time of Type 1 and 2 were more than average approach time of total area. We propsed an efficient introduction of autonomous public transportation on-demand service using delphi survey. As a result of delphi survey, experts agreed on 9 items regarding function, service item, route operation, approach distance, route mileage, punctuality.

• Journal of the Economic Geographical Society of Korea
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• v.21 no.4
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• pp.335-349
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• 2018

This study analyzes the effect of the changes in traffic environments such as transportation speeds on the time-distance accessibility for the public transportation passengers. To do this, we use passenger transaction databases of the Seoul metropolitan public transportation system: one week for each of the three years (2011, 2013, and 2015). These big data contain the information about time and space on the traffic trajectories of every passenger. In this study, the time-distances of links between subway stations and bus stops of the public transportation system at each time are calculated based on the actual travel time extracted from the traffic-card transaction database. The changes in the time-distance accessibility of the integrated transportation network from the experimental results can be summarized in two aspects. First, the accessibility tends to decline as the year goes by. This is because the transportation network becomes more complicated and then the average moving speed of the vehicles is lowered. Second, the accessibility tends to increase on the weekend in the analysis of accessibility changes by day. This tendency is because the bus speeds on bus routes on the weekend are faster than other days. In order to analyze the accessibility changes, we illustrate graphs of the vehicle speeds and the numbers of passengers by year and day.

• Journal of Korean Society of Transportation
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• v.35 no.5
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• pp.409-422
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• 2017

TOD (Transit-Oriented Development) is one of the urban structure concentrated on the multifunctional space/district with public transportation system, which is introduced for maintaining sustainable future cities. With such trends, the project of building complex transferring centers located at a urban railway station has widely been spreaded and a comprehensive and systematic analytical framework is required to clarify and readily understand the complicated procedure of estimation with the large scale of the project. By doing so, this study is to develop a comprehensive analytical framework for estimating a pedestrian OD matrix using a spatial information and an integrated smart card data, which is so called a data depository and it has been applied to the Samseong station for the model validation. The proposed analytical framework contributes on providing a chance to possibly extend with digitalized and automated data collection technologies and a BigData mining methods.