[논문]수도권 지하철 7호선 주요역 통근통행특성 분석 연구

한상천; 이경철; 김환용; 최영우

doi:10.13161/kibim.2019.9.4.075

수도권 지하철 7호선 주요역 통근통행특성 분석 연구
Travel Behavior Analysis using Origin-Destination Data for the Subway Line No.7 원문보기

Journal of KIBIM = 한국BIM학회논문집, v.9 no.4, 2019년, pp.75 - 83

한상천 (인천대학교 도시건축학부) , 이경철 (한국철도기술연구원, 철도정책연구팀) , 김환용 (인천대학교 도시건축학부) , 최영우 (인천대학교 도시건축학부)

Abstract ▼ AI-Helper

Recent data development has made it possible to analyze each individual's daily commuting by using transportation card transaction. This research utilizes about 1 million observations from the subway line no.7 of Seoul metropolitan transportation data. By using such a massive dataset, the authors try to identify daily travel behavior of morning commute and its possible relationship between subway usage and socio-economic factors. There are 4 main types of users and their travel behavior, and top 15 stations with the most users for arrival and departure are selected. Accordingly, 15 stations have distinctive characteristics including population density and the number of businesses around stations. To identify this fact, the 4 most populated stations are selected and their socio-economic factors are examined. According to the analysis, the most departure stations are generally surrounded by hihgly populated residential areas, whereas the most arrival stations are stood within the job concentrated districts.

주제어

표/그림 (13)

표 Table 1. Research methods and process
표 Table 2. Study on the Transportation Card Data Utilization
표 Table 3. Set Criteria By Type
그림 Figure 1. Location by line 7(Bas Map Source: 2019. Kakao Map)
표 Table 4. The Number of Passenger Types and Ratio by Main Stations of Line 7
그림 Figure 2. Status of bus stops by users at 15 departure stations
표 Table 5. Commute Time at 15 Departure Stations
표 Table 6. The Number of Users within 3km Radius of 15 Departure Stations
그림 Figure 3. Status of bus stops by users at 15 arrival stations
표 Table 7. Commute Time at 15 Arrival Stations
표 Table 8. The Number of Users within 3km Radius of 15 Arrival Stations
표 Table 9. Conditions of Population Density of 3km around Bupyeong-gu Office Station and Maddle Station
표 Table 10. Conditions of Business of 3km around Gasan Digital Complex Station and Cheongdam Station

참고문헌 (12)

Beak, J. W., Lee, B. J., Yoo, H. S. (2018). An Economic Efficiency Analysis for Hyperloop, The Korean Society For Railway. pp. 178-179.
Jo, M. S. (2013). Study on Relationship Between Mixed Land-Use Characteristics and Time-Based Patterns of Users in The Surrounding Areas of Seoul Subway Stations, Hanyang University.
Kim, J. Y., Lim, S. Y., Choo, S. H., Park, I. K. (2015). Analysis of Transit Ridership Patterns and Influencing Factors in Seoul, The Korea Transport Institute, 87, pp. 49-65.
Kim, K. H., Oh, K. H., Lee, Y. K., Jung, J. Y. (2013). Discovery of Travel Patterns in Seoul Metropolitan Subway Using Big Data of Smart Card Transaction Systems, The Journal of Society for e-Business Studies, 18(3), pp. 211-222.

원문보기 상세보기
Lee, M. Y., Kim, J. H. (2016). Analysis of Transit Passenger Movements within Seoul-Gyeonggi-Incheon Area using Transportation Card, J. Korea Inst. Intell. Transport. Syst, 15(5), pp. 12-19.

원문보기 상세보기
Lee, M. Y., Shin, S. I., Kim, B. W. (2018). An Analysis Model on Passenger Pedestrian Flow within Subway Stations - Using Smart Card Data -, J. Korea Inst. Intell. Transport. Syst, 17(6), pp. 14-24.
Lim, Y. T., Park, C., Kim, D. S., Eom, J. K., Lee, J. (2012). Estimating Trip Distribution Model by Using Transit Card Data, The Korea Transport Institute, 19(2), pp. 1-11.
Park, J. S., Kim, H. S., Lee, K. S. (2010). Classification of Subway Trip Patterns from Smart Card Transaction Databases, The Korea Contents Society, 10(12), pp. 91-100.

원문보기 상세보기
Park, J. S., Lee, K. S., (2015). Time-distance Accessibility Computation of Seoul Bus System based on the T-card Transaction Big Databases, Journal of the Association of Korean Geographers, 18(4), pp. 539-555.
Park, S. J., Koo, D. H. (2016). Spatial Travel Patterns of Subway Passengers in Busan, Korea, The Geographical Journal of Korea, 50(3), pp. 336-348.
Shin, I. H. (2012). An Analysis of Activity Centers by age groups based on commuting patterns in seoul Metropolitan Subway, Hanyang University.
Song, J. Y., Eom, J. K., Park, J. H., Kim, D. S., Choi, M. H. (2011). Analysis of Passenger Transfer Patterns Based on Transit Smart Card Data in Seoul, The Korean Society For Railway, pp. 563-573.

내보내기 구분	파일저장 인쇄 메일전송
구성항목	기본정보 상세정보 관리번호, 논문명, 저널/프로시딩명, 저자 , 발행년, 권, 호, 시작페이지, 끝페이지, 발행기관 관리번호, 논문명, 대등논문명, 저자 , 저널/프로시딩명, 발행기관, 발행년, 발행언어, 권, 호, 시작페이지, 끝페이지, ISBN, ISSN, 주제분야, 키워드, 초록(한글), 초록(영문), 저자(소속기관)
저장형식	Text(ASCII format) Excel format RefWorks Direct Export RIS format (for Reference Manager, ProCite, EndNote), Scholar's Aids, Mendeley
메일정보	받는사람 (필수) @ 보내는사람 (선택) @ 제목 내용 KISTI 검색결과 이메일 서비스
안내	총 건의 자료가 검색되었습니다. 다운받으실 자료의 인덱스를 입력하세요. (1-10,000) 검색결과의 순서대로 최대 10,000건 까지 다운로드가 가능합니다. 데이타가 많을 경우 속도가 느려질 수 있습니다.(최대 2~3분 소요) 다운로드 파일은 UTF-8 형태로 저장됩니다. 파일의 내용이 제대로 보이지 않을실 때는 웹브라우저 상단의 보기 -> 인코딩 -> 자동선택 여부를 확인하십시오. ~ Text(ASCII format) Excel format

연합인증