• Title/Summary/Keyword: Transport card data

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A Study on the GIS Analysis Techniques for Finding an Catchment Area by Public Transport at Railway Stations Using Transport Cards Big Data (교통카드 빅 데이터를 활용한 철도역의 대중교통 연계영향권 설정을 위한 GIS 분석 기법 연구)

  • Jin, Sang Kyu;Kim, Hawng Bae
    • 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.

An Investigation of Rider Behavior to Transfer Seoul Metropolitan Transit Using Public Transport Card Data (교통카드 데이터를 이용한 수도권 광역급행철도 환승행태에 관한 연구)

  • Gun ki Jung;Dong min Lee;Sun hoon Kim
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.6
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    • pp.146-164
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    • 2022
  • Recently, the Korean government promoted the construction of metropolitan express subway to connect major transportation hub in the metropolitan area within 30 minutes. Most stations of the metropolitan express subway are connected to existing subway stations, so the importance of transfer increased. Although many studies have been conducted on the effect of transfer penalty on route choice, there are few studies on the transfer behavior of the metropolitan express subway. Therefore, in this study, a transfer behavior analysis was conducted on the Shinbundang Line, a representative metropolitan express subway. To analyze the transfer behavior according to the degree of traffic congestion and the presence of fare payment, route choice models were made using transport card data divided according to week, time, and user characteristics. As a result of the analysis, users of the metropolitan express subway had greater disutility to the transfer waiting time compared to the transfer moving time. Furthermore, especially during the peak time, EIVM(Equivalent in-vehicle minutes) of the transfer waiting time was 3.51. In this study, EIVM for metropolitan express subway users were analyzed to be 2.6 minutes, which is significantly lower than the results of previous studies on subways. This suggests that there is a difference in the transfer penalty between subways and metropolitan express subway, and that it is necessary to apply the transfer penalty between subways and express subway differently when forecasting subway traffic demand.

Developing the Test Module of PSAM for $Hipass^{PLUS}$ Card System (하이패스플러스카드 시스템을 위한 PSAM 시험 모듈 개발)

  • Lee Ki-Han;Suh Hyun Kyo;Yoo Chang Hee;Lee Seung-Hwan
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.2 no.2 s.3
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    • pp.73-84
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    • 2003
  • Due to the problems of existing prepaid plastic card issued by Korea Highway Company, the prepaid electronic payment system using a smart card, called HipassPLUS Card, was developed to overcome the Problems. PSAM is one of the main component of the systea which can retrieve the value from HipassPLUS card, transmit the transaction data to CSAM, and store the accumulated account lists. For the safety of the elecoonic payment system, the functions of PSAM should be faultless. This paper developed a test module including the test method, the test checklist, and the test procedure. The test module examines the functionality and security of the payment mechanism to insure that the value stored in HipassPLUS card can be raid to PSAM by the merchants and the standardized SAM. The test module also inspects the transmission mechanism to send and store the transaction data kom PShM to CSAM correctly and safely. Ihe module is designed to test the standard items using the test checklists for PSAM. The test items and the test checklists of PShM was selected under the provision of the specification of Korea Highway Company and ISO standard. Ihe evaluation on PSAM using the test module indicates that PSAM satisfies the evaluation criteria on the quality characteristics of the functionality, security, and compatibility.

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Analysis of Public Transport Travel Behavior by using Transport Card Data (대중교통 card data를 이용한 통행행태 분석(지하철역 하차후 환승 버스 이용자 중심으로))

  • Kim, Dae-Seong;Eom, Jin-Ki;Moon, Dae-Seop;Choi, Myoung-Hun;Song, Ji-Young
    • Proceedings of the KSR Conference
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    • 2011.10a
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    • pp.443-452
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    • 2011
  • This study analyzed passenger travel patterns especially for the transfer from metro to bus by using transit smart card data. We classified three types of land use such as residential, business, and shopping area where metro stations are located. The results show that more number of transfers was observed at residential area compared to that of shopping and business area. Also, more number of transfers from metro to arterial bus was observed than that of transfers to local bus. Further, the high number of transfers to arterial bus was observed at business and shopping area. This means that the transfer to bus at metro stations varies by land use. The egress walk distance from metro station was found to be approximately 400 meters and the average walk distance of young people was found to be shorter than that of the old.

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Analysis of the Transit Ridership Pattern using Transportation Card Data : focusing on Ganghwa (교통카드 데이터를 이용한 대중교통 통행패턴 분석 : 강화군을 중심으로)

  • Lee, Minwoo;Han, Jonghak;Lee, Hyangsook
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.17 no.2
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    • pp.58-72
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    • 2018
  • Ganghwa has met a new development period in land use and infrastructure based on the 4th National Development Planning, however the public transportation system is not systematically operated yet. This paper analyzes the bus trip pattern in Ganghwa using transportation card data during a week. The result indicates that average 7,100 people use buses a day and the most frequent use occurred in Friday. Clear peak-hours between 7 and 8 A.M. and between 4 and 5 P.M. were appeared due to commuting and school trips. According the result of regression analysis, population and the number of hospitals and schools area showed positive relationships with but trips reflecting regional characteristics. The research contributes to providing basic data for constructing an efficient public transportation system in the future.

Exploring the Relationship between Transfer Trips and Land Use (환승통행과 토지이용의 연관성 분석)

  • Lim, Su-yeon;Lee, Hyangsook;Choo, Sangho
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.15 no.2
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    • pp.1-12
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    • 2016
  • This paper is to analyze characteristics of transfer trips and to identify impacts of land use on them. Using the smart transport card data of Seoul on a weekday in April 2013, we explored general characteristics of the transfer trips such as spatial and temporal distributions, transfer types, and geographical patterns of transfer trips. Then, the multiple regression model for the transfer trips was developed, considering land use as well as socio-economic variables as explanatory ones. For the characteristics of the transfer trips, their ratio to the total trips accounts for 26.7%. Nearly 87% of the trips are one-time transferred, and 64.7% are bus-subway transfer trips. In addition, the transfer trips are more likely to appear nearby subway stations and business facilities. The regression model indicates that land use variables such as the floor areas of business facilities and department stores and mixed land use index significantly positively affect the transfer trips. Our results can be used as basic data for choosing feasible locations of multi-modal transfer centers in urban areas.

Trip Assignment for Transport Card Based Seoul Metropolitan Subway Using Monte Carlo Method (Monte Carlo 기법을 이용한 교통카드기반 수도권 지하철 통행배정)

  • Meeyoung Lee;Doohee Nam
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.2
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    • pp.64-79
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    • 2023
  • This study reviewed the process of applying the Monte Carlo simulation technique to the traffic allocation problem of metropolitan subways. The analysis applied the assumption of a normal distribution in which the travel time information of the inter-station sample is the basis of the probit model. From this, the average and standard deviation are calculated by separating the traffic between stations. A plan was proposed to apply the simulation with the weights of the in-vehicle time of individual links and the walking and dispatch interval of transfer. Long-distance traffic with a low number of samples of 50 or fewer was evaluated as a way to analyze the characteristics of similar traffic. The research results were reviewed in two directions by applying them to the Seoul Metropolitan Subway Network. The travel time between single stations on the Seolleung-Seongsu route was verified by applying random sampling to the in-vehicle time and transfer time. The assumption of a normal distribution was accepted for sample sizes of more than 50 stations according to the inter-station traffic sample of the entire Seoul Metropolitan Subway. For long-distance traffic with samples numbering less than 50, the minimum distance between stations was 122Km. Therefore, it was judged that the sample deviation equality was achieved and the inter-station mean and standard deviation of the transport card data for stations at this distance could be applied.

A Study of Estimating the Alighting Stop on the Decision Tree Learning Model Using Smart Card Data (의사결정 학습 모델 기반 교통카드 데이터 하차 정류장 추정 모델 연구)

  • Yoo, Bongseok;Choo, Sangho
    • 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.

Analysis of Public Transport Ridership during a Heavy Snowfall in Seoul (기상상황에 따른 서울시 대중교통 이용 변화 분석: 폭설을 중심으로)

  • Won, Minsu;Cheon, Seunghoon;Shin, Seongil;Lee, Seonyeong
    • 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.