Journal of the Korea Convergence Society (한국융합학회논문지)

Korea Convergence Society (한국융합학회)
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Analysis of Passenger Movement Patterns Using Subway OD Data

도시철도 출·도착데이터를 이용한 승객이동 패턴 분석

  • Baik, Euiyoung (Spatio-temporal Data Analysis Lab, Kwangwoon University) ;
  • Cho, Jae Hee (Information Convergence College, Kwangwoon University) ;
  • Kim, Dong-Geon (Information Science College, Dongduk Women's University)
  • 백의영 (광운대학교 시공간분석연구실) ;
  • 조재희 (광운대학교 정보융합학부) ;
  • 김동건 (동덕여자대학교 정보통계학과)
  • Received : 2019.10.31
  • Accepted : 2019.12.20
  • Published : 2019.12.28
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Abstract

The purpose of this study is to design and construct a data mart that anyone can easily analyze subway OD movement patterns. Subway OD data of the year 2017 was downloaded from the Seoul Open Data Plaza and used as the source data. A multidimensional model was designed, and Gaussian mixed cluster analysis and visualization analysis using Tableau were performed. Interestingly, movement between suburban and Seoul accounts for 23% of the total traffic. The passengers of Suwon Station move to the suburbs much more than Seoul, while Pangyo Station mostly moves to Seoul. As a result of Gaussian mixed cluster, eight clusters of OD segments were found, and the characteristics of each cluster were characterized by segment distance and passenger size.

본 연구의 목적은 누구나 쉽게 지하철 OD 이동패턴 정보를 분석할 수 있는 데이터마트를 설계하고 구축하는 것이다. 서울 열린데이터광장에서 받은 2017년도 데이터를 원천 데이터로 이용하였다. 다차원모델을 설계하였고, 가우시안 혼합 군집분석과 Tableau를 이용한 다차원 분석을 실시하였다. 흥미로운 사실은 교외지역과 서울 간 이동은 전체 이동량의 23%에 해당하며, 수원역의 이용객은 서울보다 교외로의 이동이 매우 크며, 반면 판교역은 이동량의 대부분이 서울로의 이동이다. 가우시안 혼합 군집결과 8개의 OD구간 군집을 발견하였고, 구간 거리와 승객 수에 의해 각 군집의 특징을 네이밍하였다.

Keywords

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