1. The Potential of Using the Smart Card Data to Define the Use of Public Transit in Seoul Dr. Jin Young Park The Korea Transport Institute Dept. of Metropolitan & Urban Transport Research

2. 1 Introduction Ⅰ Reliability of information from smart card Ⅳ Conclusion Ⅴ Information from smart card use data Ⅲ Smart card for Fare Payment in Korea Ⅱ

3. 2 Smartcard Smartcard for fare payment Smart card is defined as any pocket-sized card with embedded integrated circuits which can process information, particularly for fare payment of public transit. Types By payment method : pre-paid or credit card By communication technique : contact or contactless (RFID: Radio Frequency Identification) Introduction Ⅰ

4. 3 Smart card in Korea Introduction Ⅰ Needs for real-time, reliable data on public transport is increasing Importance of public transport data has increased with bus system reform Distance-based fare system was introduced Spread of smartcard for public transit fare payment Smartcard was introduced for public transit fare payment in Seoul in 1996, as the first time in Korea. And use of it has been continuously increased. more than 80% of passengers now uses smart card in Seoul in 2007 Valuable information such as getting on and off time, location, passenger types, transfer activity is collected and saved, but currently it is used only for fare collection and distribution among operators

5. 4 Smartcard for fare payment in Korea Current use of smart card in Korea RegionStarting date No. of Cards (thousands) terminal Total 35,77130,049 Seoul Bus ‘96.7 Metro ‘98.6 22,8228,303 BusanBus, Metro ‘98.26,4302,759 Taegu bus‘00.11 Metro ‘02.7 1,8702,008 Incheon bus ‘98.9 metro ‘99.12 6301,856 Taegeonbus ‘03.10300964 Gwangju bus ․ metro ‘04.10 250962 Ulsanbus ‘02.9411527 Ⅱ

6. 5 Smartcard for fare payment in Korea Smart card use rate RegionSeoulBusanTaeguIncheonKwangju ModebusmetrobusmetrobusMetroBusMetroBusMetro Ratio of cash : card use (%) 29:7148:5237:6343:5757:4368:3228:7246:5444:5666:34 Region (Bus) Tae jeon Ulsan Kyung gi Kang won chung buk chung nam Jeonb uk Jeonn am Kyung buk Kyung nam Jeju Ratio of cash : card use (%) 58:4247:5354:4685:1586:1485:1582:1881:1980:2070:3075:25 Ⅱ

7. 6 Data set from smart card system in Seoul InformationDescription Card IDCard number for each smart card Boarding timeBoarding time (year/month/day/hour/minutes/second) Type of modeBus (local/main/feeder/Metropolitan/circle bus), Metro Number of transfersNumber of transfers (from 0 to 4) Number of bus routesGiven number for every bus route Name of bus route ID of operatorGiven number of every bus/Metro operator ID of vehicle (bus)Given number of every operated bus Type of userAdult, student, or children ID of boarding locationGiven number of boarding bus/Metro stop Name of bus stopName of boarding bus/Metro stop Alighting timeAlighting time (year/month/day/hour/minutes/second) ID of alighting locationGiven number of alighting bus/Metro stop Name of bus stopName of alighting bus/Metro stop Basic fareStarting (base) fare Additional fareAdditional fare with distance Information from smart card use data Ⅲ

8. 7 Available information from smart card use data CategoryInformationCategoryInformation Trip No. of Passenger at every stop Revenue (Fare) Average fare per passenger No. of passengers at each route and mode Revenue per each mode/bus No. of trips for every passenger Revenue per each route No. of passengers for each mode Average no. passengers per each bus Transfer Average no. of transfer Average travel time per passenger Average time required for transfer Average travel length per passenger Average No. of trip per passenger Average trip time per each mode Average fare required for transfer Congestion level of each modeO/D Matrix O/D matrix for each mode for peak/off-peak time Information from smart card use data Ⅲ

9. 8 Trip and transfer information have been collected, and O/D matrix have been created Revenue data is main data from smart card use, and already fully used by operation company Collected information at this study categoryinformationcategoryinformation Trip No. Passenger per each mode transfer Average no. of transfer No. of trip for every passenger Average travel time per passenger Average time required for transfer Average travel length per passenger Average No. of trip per passenger Average trip time of each mode O/D matrix O/D matrix for each mode for peak/off-peak time Information from smart card use data Ⅲ

10. 9 Data from T-money, which is currently used in Seoul area About 10 million transactions are occurred everyday. passenger trip information is collected by T-money to accommodate distance-based fare system Percentage of card use in the first half of 2005 was 89.7 % for bus, 71.7% for Metro To investigate daily variation and yearly trends, one weekday smart card use data of 2004 and 2005 have been processed. Data processed Information from smart card use data Ⅲ

11. 10 Data analysis Use of DBMS (DataBase Management System) : about 1GB data size for every day! SQL (Structured Query Language) Use of ORACLE RDBMS Multi-dimensional analysis technique has been implemented Approach implemented Cube Time Passenger Type Mode Seoul Seocho-GuJung-Gu Jongro-Gu BangbaedongSeochodongNonhyundong Seocho Sta.Supreme CourtSadang sta. … … … Information from smart card use data Ⅲ

12. 11 Daily total trip of public transit has increased 7.58% from 2004. Passengers for bus has increased 10.93%, metro has increased 3.95% No. of passengers per each mode mode20042005Change(%) Local bus928,9741,037,52211.68 Urban main route bus1,641,2082,095,12127.66 Urban feeder route bus2,510,7512,547,9861.48 Metropolitan express bus148,351122,943-17.13 Circle route bus15,43414,615-5.31 Bus total5,244,7185,818,18710.93 Metro4,843,4385,034,5313.95 Total10,088,15610,852,7187.58 Information from smart card use data Ⅲ

13. 12 Transfer trip has increased by 18.86% Time required for transfer has been reduced by 4.28% No. of transfer20042005Change (%) 11,861,6502,167,88716.45 2213,533288,20434.97 331,73345,96844.86 47,41411,01148.52 total2,114,3302,513,07018.86 20042005change(%) 414sec.(6.9 min.)397sec.(6.6 min.)-4.28 Transfer information Information from smart card use data Ⅲ

14. 13 Hourly distribution of trips Information from smart card use data Ⅲ

15. 14 Trip distribution of different modes Information from smart card use data Ⅲ

16. 15 Cumulative travel time Information from smart card use data Ⅲ

17. 16 Set up O/D matrix for TAZ (Traffic Analysis Zone) for public transit mode Hourly O/D matrix including morning peak and evening peak has been produced By matching bus/metro stop’s coordinate with TAZ data, passengers at every stops have been aggregated by TAZ. D O GangnamGangdongGangbukGangseoGwanakGwangjinGuro… Gangnam82,19488074105586930… Gangdong1,1726,648230001,2300… Gangbuk76216230,14210821233188… Gangseo0013816,7233740524… Gwanak78102140718,4770582… Gwangjin5221,085261004,1610… Guro00169615349012,566… ……………………… O/D Matrix Information from smart card use data Ⅲ

18. 17 Cash users? Most of smart card systems are required to be contacted only when you are getting- on ! (what about getting-off information?) For distance-based fare system, smart card data only has 10% loss of getting-off information, but this is most important issue for use of smartcard data for research. Missing data mode Ratio of getting-off information loss (%) 20042005 urban main route bus10.1710.96 Metropolitan express bus64.3680.01 Metro0.500.33 total6.086.29 Reliability of smart card data Ⅳ

19. 18 Ratio of Metro users from smart card data to SMC data to investigate the reliability of smart card data, number of users from every station in metro line 1 to 8 obtained from smart card data is compared with passenger data published from Seoul Metro Company. Total users of each Metro station (smart card users + cash users) on one day = number of smart card users ÷ 0.705 (proportion of smart card users per total Metro users) (1) Number of total users per day considering daily variation = total users of the day ÷ 1.098 (Wednesday variation) (2) Reliability of information from smart card Ⅳ

20. 19 Ratio of Metro users from smart card data to SMC data Reliability of information from smart card Ⅳ

21. 20 Difference between smart card data and SMC data (average applied) Reliability of information from smart card Ⅳ

22. 21 Why line 1 and 2 show bigger differences? Line 1has 2 major inter-regional railway station - People from other region pay their fares by cash - In other words, smart card ratio at three railway station is less than other Metro station. Line 2 has major sport complex and business district - At the day, there was big sport match at the stadium. - In other words, smart card ratio at the station is more than other Metro station. Reliability of information from smart card Ⅳ

23. 22 Difference between smart card and SMC (line specific data applied) Reliability of information from smart card Ⅳ

24. 23 Advantage of use of smartcard data AccuracyIncrease of accuracy and reliability Less costLess cost for collecting data SensitivenessData from every hour and region Less time Real time data and less time required for collecting data Potential as database Historic data for future plan Conclusion Ⅴ

25. 24 Missing data - cash users - complement of alighting information Limitation & Further studies Building historic DB (database) - required to identify daily variation and historic trends - linked with GIS Finding trip purpose - for planning study, purpose based O/D matrix is required Conclusion Ⅴ

26. Thank you