• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.6
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• pp.1069-1073
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• 2016

The current free-riding subway system for the elderly over 65 years old has been implemented since in 1980. As the aging population increases, the number of free riders also increases. It results eventually in the increase of subsidy from government. In addition, a transfer between subway and bus is not good enough since the free ride system is applied to only subway not to bus. The aim of this study is to analyze the transport card data to understand the impact of free-riding in the viewpoint of economic issues. It aims also to analyze the transfer patterns between public transport. At the end it compares Korea case with international cases and finds out some issues on free-ride systems. Finally, counter-measures aimed at improving the current free-rider system is suggested.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1811-1825
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• 2011

This study analyzed the transit services with respect to transit service measures such as the load factor representing number of passengers between stops, dwelling time, and operational speed based on transit smart card data recorded in 2009. A case study on the local bus line 7024 connecting Seoul railway station to evaluate bus services at passenger perspectives was accomplished. From the results, we found that the dwelling time was not affected by the number of passengers which is because the tagging patterns are different among passengers. The operational speed was analyzed by calculating the average speed of the bus route and the speed of each bus stops based on dwelling time. Interestingly, calculating operation speed based on the transit smart card data is the first time effort ever made and this means that it is not necessary to observe travel speed of bus and railway at a field level any more. we hope that this study will be a basis of evaluation of transit services purely based on the transit smart card data and help to make better transit services for passengers and operators as well.

• Journal of Korean Society of Transportation
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• v.34 no.5
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• pp.437-448
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• 2016

Some previous researches suggested a transit trip destination inference method by constructing trip chains with incomplete(missing destination) smart card dataset obtained on the entry fare control systems. To explore the feasibility of the transit trip destination inference method, the transit trip chains are constructed from the pre-paid smart card tagging data collected in Busan on October 2014 weekdays by tracing the card IDs, tagging times(boarding, alighting, transfer), and the trip linking distances between two consecutive transit trips in a daily sequences. Assuming that most trips in the transit trip chains are linked successively, the individual transit trip destination zones are inferred as the consecutive linking trip's origin zones. Applying the model to the complete trips with observed OD reveals that about 82% of the inferred trip destinations are the same as those of the observed trip destinations and the inference error defined as the difference in distance between the inferred and observed alighting stops is minimized when the trip linking distance is less than or equal to 0.5km. When applying the model to the incomplete trips with missing destinations, the overall destination missing rate decreases from 71.40% to 21.74% and approximately 77% of the destination missing trips are the single transit trips for which the destinations can not be inferable. In addition, the model remarkably reduces the destination missing rate of the multiple incomplete transit trips from 69.56% to 6.27%. Spearman's rank correlation and Chi-squared goodness-of-fit tests showed that the ranks for transit trips of each zone are not significantly affected by the inferred trips, but the transit trip distributions only using small complete trips are significantly different from those using complete and inferred trips. Therefore, it is concluded that the model should be applicable to derive a realistic transit trip patterns in cities with the incomplete smart card data.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.233-243
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• 2008

Recognition for the importance and roles of public transportation is increasing because of traffic problems in many cities. In spite of this paradigm change, previous researches related with public transportation trip assignment have limits in some aspects. Especially, in case of multimodal public transportation networks, many characters should be considered such as transfers. operational time schedules, waiting time and travel cost. After metropolitan integrated transfer discount system was carried out, transfer trips are increasing among traffic modes and this takes the variation of users' route choices. Moreover, the advent of high-technology public transportation card called smart card, public transportation users' travel information can be recorded automatically and this gives many researchers new analytical methodology for multimodal public transportation networks. In this paper, it is suggested that the methodology for establishment of brand new multimodal public transportation networks based on computer programming methods using transportation card data. First, we propose the building method of integrated transportation networks based on bus and urban railroad stations in order to make full use of travel information from transportation card data. Second, it is offered how to connect the broken transfer links by computer-based programming techniques. This is very helpful to solve the transfer problems that existing transportation networks have. Lastly, we give the methodology for users' paths finding and network establishment among multi-modes in multimodal public transportation networks. By using proposed methodology in this research, it becomes easy to build multimodal public transportation networks with existing bus and urban railroad station coordinates. Also, without extra works including transfer links connection, it is possible to make large-scaled multimodal public transportation networks. In the end, this study can contribute to solve users' paths finding problem among multi-modes which is regarded as an unsolved issue in existing transportation networks.

• Journal of Korean Society of Transportation
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• v.28 no.2
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• pp.7-19
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• 2010

Users of metropolitan railroad is increased continuously because of its various advantage such as comfortableness, convenience and punctuality. Thus, several local government including Seoul considered new installation or extension of railroads and four railroad operators maintain seventeen lines at present. After public transportation reforms in 2004 and integrated discount fare system in 2007, public transportation become more convenient in many aspects. However, these trials gives much more complex allocating problems of revenues among public transportation operators. In this paper, we deal with revenue allocating problems among public transportation operators after integrated discount fare system in 2007. Specifically, this study focuses on allocating revenues to metropolitan railroad operators by using RF card data. This research roughly proposes the methodology of O/D extraction from RF card data, generalized cost estimation and allocating revenue algorithm. We use RF card data in order to draw out exact individual O/D data and try to compare our results with those of Korea Smart Card Company. In generalized cost estimation, survey study about transfer factors is conducted for accurate estimation of generalized cost function. Lastly, new allocating revenue algorithm using k-path and non-dominated path concept is suggested. It is expected that case study is also performed with real revenues and O/D data in order to check up the application. Preposed methodology in this research can contribute to solve present and future revenue allocating issues according to the introduction of LRT and private railroad.

• The Korean Journal of Applied Statistics
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• v.26 no.4
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• pp.623-634
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• 2013

In this study, we provide empirical evidence of whether a spatial correlation among mode choices at the TAZ(Traffic Analysis Zone) level exists based on transit smart card data observed in Seoul, Korea. The results show that the areas with a higher probability that passengers choose to take a bus are clustered and that those regions have fewer metro stations than bus stations. We also found that the spatial correlation turned out to be statistically meaningful and provided an opportunity for the potential use of the spatial correlation in modeling mode choices. A reliable spatial interaction would constitute valuable information for transportation agencies in terms of their route planning and scheduling based on the transit smart card data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6D
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• pp.539-547
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• 2012

Increasing the mode transfer volume between public transportation modes has known to be necessary for efficiency improvement of public transportation system operation and it is also found to be important to have relevant transfer point selection with reflection of current travel pattern. This study is in regards to providing a selection guideline for the location of transfer point between public transport modes. This case study has been carried out for Daegu Metropolitan City especially for public transportation users behaviour by analysis of daily usage of transportation card to identify the transfer travel pattern. A cluster analysis was applied to categorize the pattern of transfer stop which induces many users and a discriminant analysis also utilized for grouping the stops by number of transfer trip. This research produces the estimation result of transfer volume for urban railway system no.3 in Daegu City which is currently under construction. In addition, the locations of transfer center has also been proposed.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.6
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• pp.1093-1099
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• 2016

Currently, there are 499 metropolitan subway stations in Korea, but there are not many studies on the influence zone of linkage between railway station and public transport. Existing studies have been studied almost in terms of accessibility.. In addition, the existing research on the influence zone of linkage using survey data and statistics, there is a limit to the theoretical basis and analysis techniques. In this paper, we propose a new method to select on the influence zone of linkage, It is a GIS analysis technique using the spatial data of the railway station user as the large data of the traffic card. We applied the GIS analysis technique for select the influence zone of linkage based on the travel time of the network for each public transportation system. As a result, it was confirmed that the influence of the link of 15 minutes on the local bus, 20 minutes on the city bus and 25 minutes on the intercity bus were clearly distinguished according to the difference in network access time.

• 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.