• Proceedings of the Korean Society of Computer Information Conference
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• 2012.07a
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• pp.335-338
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• 2012

교통카드는 1996년 충전방식의 선불카드가 처음 사용되었고, 후불방식의 교통카드는 1998년 6월부터 도입되어 함께 사용되었다. 교통카드 사용할 수 있기 위해서는 사용자의 사용여부 및 각종 신상정보의 변경에 따라 결제방식이 변경되는 것에 대해 카드거래 승인시스템에 적절한 반영이 필요하다. 이를 위해 기존 서울교통시스템에서는 메모리 주소를 이용한 카드거래승인시스템을 이용하고 있으며 본 연구에서는 임베디드 교통카드단말기에서 사용 가능한 오프라인 카드거래 승인 알고리즘을 개발하는 것을 목표로 한다. 본 논문에서는 카드 사용정보를 압축 저장하는 방식을 제안하고 있으며, 사용자 할인정보는 한 카드당 2bit의 공간을 차지하도록 설계 했다. 또한 검색알고리즘으로 이진탐색을 사용하여 기존에 비해 검색 속도가 향상 되었다.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.3
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• pp.68-76
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• 2016

The pre-paid nation-wide interoperable transportation card, which an pay fee of bus, subway, train, and highway with just one card, released in June. 2014. It has started and operated from Seoul, Gyeonggi, and major local metropolitan area. In this paper, after starting of service, we evaluate conformance and interoperability of nation-wide interoperable transportation card system in real situation. Through this, we check the status of its technical operation. For this, we choose 6 region included Seoul, Gyeonggi which are serviced by different transport vendors and check recognition and billing result from field of transportation card terminal. As a result, we can reach that the major nation-wide interoperable transportation card operate normally and deliver CONFIG DF query command. It means nation-wide interoperable transportation card system which use only one card stably adapt the public transport system and it can make user's public transport use convenience higher through the extension of service area.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.131-146
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• 2023

Smart card data is widely used in the public transportation field. Despite the inevitability of various errors occur during the data collection and storage; however, smart card data errors have not been extensively studied. This paper investigates inherent errors in boarding and alighting station information in smart card data. A comparison smart card data and bus boarding and alighting survey data for the same time frame shows that boarding station names differ by 6.2% between the two data sets. This indicates that the error rate of smart card data is 6.2% in terms of boarding station information, given that bus boarding and alighting survey data can be considered as ground truth. This paper propose 6-step algorithm for correcting errors in smart card boarding station information, linking them to corresponding information in Bus Information System(BIS) Data. Comparing BIS data and bus boarding and alighting survey data for the same time frame reveals that boarding station names correspond by 98.3% between the two data sets, indicating that BIS data can be used as reliable reference for ground truth. To evaluate its performance, applying the 6-step algorithm proposed in this paper to smart card data set shows that the error rate of boarding station information is reduced from 6.2% to 1.0%, resulting in a 5.2%p improvement in the accuracy of smart card data. It is expected that the proposed algorithm will enhance the process of adjusting bus routes and making decisions related to public transportation infrastructure investments.

• 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.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06d
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• pp.187-189
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• 2006

최근 지하철이나 버스 등의 교통수단을 이용하기 위해 지불방식의 편리, 지연시간의 단축 등 효율성이 높은 비접촉식 카드를 많이 사용하고 있다. 이러한 비접촉식 스마트 카드를 인증하기 위해서는 스마트카드ID가 스마트카드 단말기 내부에 저장하고 있어야 하며, 스마트카드ID가 변경될 때마다 서버으로부터 전송받아 최신의 정보로 갱신되어야 한다. 교통시스템에서 사용되는 통신매체는 RS-485를 사용하여 38.5Kbps로 통신하고 있고, 그로인해 스마트카드ID를 전송할 때 시간이 많이 소모되고, 스마트카드ID를 전승하는 동안에는 스마트카드 단말기의 사용이 제한되고 있어 단말기가 사용되지 않는 시간에 전송하고 있다. 이러한 교통시스템의 환경에서 점점 더 많아지고 있는 대량의 데이터를 스마트카드 단말기에 빠르게 전송하기 위해 스마트카드ID의 특성을 이용한 인코딩 기법을 적용하여 스마트카드ID의 크기를 줄여 전송함으로써 전송시간을 줄이는 방법을 제안하였다.

• 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 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.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1835-1847
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• 2011

After conducting demonstration of transportation card for bus from Godeok-dong to Sangil-dong in 1996, due to continuously support for public transportation, the transportation card utilization of metropolitan public transportation passengers is currently going beyond 90%. In the current situation, transportation information system is mainly focused on road operation and control, offer of real time information and research of transportation information system using transportation card data which is differentiated by previous transportation information system is needed to study. This paper compare and analyze transportation information system, which is being used to each country, based on foreign examples of activating use of transportation card then introduce figure of advanced transportation information system which provide decision making feature for improving policy and institution of public transportation based on transportation card data, scientific analysis of passenger information, information of demand forecasting, variation and so on for constructing new route.

• 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.