• Proceedings of the Korean Information Science Society Conference
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• 2010.06a
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• pp.38-39
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• 2010

수도권 대중교통 이용자는 2004년 서울시의 대중교통 체계 개편에 따라 교통 카드를 사용하여 버스와 지하철을 이용하게 되었다. 교통 카드를 사용하는 각 승객의 승차와 하차에 관한 데이터가 하나의 트랜잭션으로 구성되고, 하루 천만 건 이상의 트랜잭션들로 구성된 대용량 교통카드 트랜잭션 데이터베이스가 만들어지고 있다. 대중교통을 이용하는 승객들의 승차와 하차에 관한 여러 정보를 담고 있는 교통카드 트랜잭션 데이터베이스에서 유용한 패턴이나 정보를 탐사해내는 연구가 계속 진행되고 있다. 이런 연구 결과는 수도권 대중교통 정책을 입안하는데 중요한 기초 자료가 되고 수도권 승객들에게 대중교통을 보다 잘 이용할 수 있는 정보로 제공된다. 교통카드 이용률은 2006년 79.5%, 2007년 80.3%, 2008년 81.6%로 점차적으로 증가하고 있다. 대용량의 교통카드 트랜잭션 데이터베이스에 대한 연구를 살펴보면 하루 동안의 교통카드 트랜잭션 데이터베이스에서 순차 패턴을 탐사하는 알고리즘을 연구하였고[1], 승객들의 통행 패턴에 대한 분석연구를 확장하여 일 년에 하루씩 2004년에서 2006년까지 3일간의 교통카드 트랜잭션 데이터베이스로부터 승객 시퀀스의 평균 정류장 개수와 환승 횟수 등을 연도별로 비교하였다[2]. 수도권 지하철 시스템의 특성에 관한 연구로는 네트워크 구조 분석이 있었고[3], 승객의 기종점 통행 행렬(Origin-Destination trip matrix)에 의한 승객 흐름의 분포가 멱함수 법칙(power law)임을 보여주는 연구가 있었고[4], 지하철 교통망에서 모든 링크상의 승객들의 흐름을 찾아내는 연구가 있었다[5]. 본 논문에서는 교통카드 트랜잭션 데이터베이스에서 지하철 승객들의 통근 패턴을 탐사해내는 방법을 연구하였다. 수도권 지하철 네트워크에 대한 정보를 입력하고 하루치의 교통카드 트랜잭션 데이터베이스에 연구된 방법을 적용하여 8가지 통근 패턴들을 탐사해내고 분석하였다. 탐사된 패턴들 중에서 많은 승객들이 지지하는 출퇴근 패턴에 대해서는 시간대별로 승객수를 그래프로 보여주었다.

• Journal of Korean Society of Transportation
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• v.26 no.2
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• pp.109-119
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• 2008

The number of card users has grown steadily after the adaption of smart card. Considering the diverse information from smart card data, the increase of card usage rate leads to various useful implications meaning in travel pattern analysis and transportation policy. One of the most important implications is the possibility that the data enables us to generate transit O/D tables easily. In the case of generating transit O/D tables from smart card data, it is necessary to filter data error and/or data missing. Also, the correction of data missing is an important procedure. In this study, it is examined to compute the level of data error and data missing, and to correct data missing for transit O/D generation.

• Journal of the Korean Regional Science Association
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• v.33 no.3
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• pp.101-113
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• 2017

This study examines the mobility of the disadvantaged population groups in terms of public transportation using the 2014 smart card data in Seoul, Korea. Particularly, we focus on the disadvantaged population such as senior group, junior group, and low-income population group. Based on the spatial distributions of public transportation mobility levels and the disadvantaged population groups, we identify specific areas where public transportation service should be improved for the disadvantaged population. As a result, we identify 15 administrative-dongs where the ratio of the disadvantaged population is high while the mobility index of public transit is low. The main contributions of this study are as follows. First, we use the smart card data which contains the information of actual trip made by individuals and develop the evaluation process of urban mobility for the disadvantaged population groups. Second, we identify the specific areas where public transportation service should be improved for the different group of the disadvantaged population. Lastly, we discuss policy implications to improve the urban mobility of the disadvantaged population.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.104-115
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• 2023

User-centered public transportation services such as DRT, Autonomous Transit etc. have been provied but current minimum level of service for public transportation has been evaluated by the operator because there is no data on user's accessibility to use public transportation. This study was performed GRID analysis using altteul transport card data including user's accessibility to use public transportation. The analysis result showed that user's accessibility to use public transportation was different within a same dong area. We proposed improving minimum level of service for public transportation considered by the user. The result of applying the proposed method showed that many area was changed to unsatisfied area for minimum level of service for public transportation

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.5
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• pp.12-19
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• 2016

An average of 20 million individual transit unit activities per day on the Seoul-Gyeonggi-Incheon public transportation network are provided as transportation card analysis data by the metropolitan district (99.02% by 2014 standard, Humanlive, 2015.4). The metropolitan transportation card data can be employed in a comprehensive analysis of public transportation users' current transit patterns and by means of this, an effective use plan can be explored. In enhancing the existing information on the bus and rail integrated network of the metropolis with public transportation card data, the constraints in the existing methodology of metropolitan transit analysis, which functions on a zone unit origin and destination basis, can be overcome. Framework for metropolitan public transportation card data based integrated public transportation analysis, which consists of bus and rail integrated transport modes, is constructed, and through this, a single passenger's transit behavior transit volume can be approximated. This research proposes that in the use of metropolitan public transportation card data, integrated public transportation usage, as a part of individual passenger spatial movements, can be analyzed. Furthermore, metropolitan public transportation card usage data can provide insights into understanding not only movements of populations taking on transit activities, but also, characteristics of metropolitan local space.

• Journal of the Korea Society of Computer and Information
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• v.15 no.3
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• pp.99-109
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• 2010

Since introduced in 1997, the transportation card system in Korea has been developed up to the world-top-tier technical level and gradually implemented in many other countries. Especially, the public transportations are significantly considered in terms of reducing greenhouse gas emission and environment pollution. In addition, a nation-wide transportation card system will be feasibly completed until 2013. However, for overcoming user's inconvenience, the unmanned sales/charging machines of the cards should be urgently required. In this paper, a new integrated operating system for unmanned sales/charging machines of such cards is designed and implemented by analyzing problems of the existing machines. The proposed system is hierarchically composed of multiple modules; machine initialization, work finishing, sales, charging, A/S handling, and management modules. We established and operated this machine in Seoul and Gyeonggi region. This research demonstrates that spread of the user-friendly integrated operating system improve user's convenience especially with respect to interoperability among transportation means and their areas.

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

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.3
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• pp.1-11
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• 2007

Seoul's transportation system was changed drastically starting the first of June in two thousand. This policy includes integrated distance-based fare system and public transportation card system called smart card. Especially, as public transportation card data contains individual travel, transfer and using modes information it is possible to catch the characteristics of path-based individuals and mass transit. Thus, public transportation card data can contribute to evaluate the mass transit service in integrated public transportation networks. In addition, public transportation card data are able to help to convert previous researches and analyses with link-based trip assignment models to path-based mass transit service analysis. In this study, an algorithm being suitable for path-based trip assignment models is suggested and proposed algorithm can also contribute to make full use of public transportation card data. For this, column generation algorithm hewn to draw the stable solution is adopted. This paper uses the methodology that is to take local approximate equilibrium from partial network and expand local approximate equilibrium to global equilibrium.

• Transportation Technology and Policy
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• v.5 no.1
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• pp.111-127
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• 2008

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.11-30
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• 2019

Smartcards are used as the basic data for utilizing the various transportation policies and evaluations, etc. and provided the transportation basic statistics index. However, the main problem of the smartcard data is that the most of users do not take the alighting tag at the stop, so there is a limit to the scope of use for the total O-D trip data because incomplete O-D traffic data of transportation card users. In this study, a decision tree of learning model is estimated for the alighting stop of smartcard users. The model estimation accuracy in range less than 2 stops interval was 89.7% on average. By eliminating the incompleteness alighting stop of smartcard data through this model, it is expected to be used as the basic data for various transportation analyses and evaluations.