Journal of the Korean Society for Railway (한국철도학회논문집)

The Korean Society for Railway (한국철도학회)
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Public Transportation Alighting Estimation Method Using Smart Card Data

교통카드데이터를 활용한 하차정류장 추정 방법론 연구

  • Received : 2017.08.16
  • Accepted : 2017.09.09
  • Published : 2017.10.31
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Abstract

Recently, there has been a growing interest in using smart card data. However, there are restrictions on the utilization of data in many areas outside the Seoul metropolitan area because the data does not contain alighting information. This paper presents a methodology for estimating alighting stops of smart card data. Estimation results were verified by smart card data from Seoul and Gwangju. The estimation rates were 78.2% and 81.6% in Seoul and Gwangju, respectively. The matching accuracy was 54.2% and 33.4%, respectively. However, if up to two stops of error are allowed, the accuracy values were 93.6% and 94.0%, respectively. We also discussed changes in estimation results due to adjusting the allowable walking distance, which is a key parameter of trip chaining methods. As the allowable walking distance increases, the estimation rate increases, while the accuracy decreases, and it is found that the estimation results change by around 500m.

최근 데이터 중심적 교통정책수립 필요성 인식에 따라 교통카드데이터 활용에 관심이 고조되고 있다. 하지만 수도권 외의 많은 지역의 데이터에 하차 정보가 없어 활용에 제약이 있다. 이 논문은 승차 정보만 포함된 교통카드데이터에서 하차 정류장을 추정하는 방법론을 제시하였다. 검증은 서울시와 광주시의 데이터를 활용하였다. 추정 성공률은 서울시, 광주시 각각 78.2%, 81.6%로 나타났다. 정확도는 각각 54.2%, 33.4%로 나타났는데, 2개 정류장 오차까지 허용하는 경우 정확도가 서울시 93.6%, 광주시 94.0%로 크게 높아진다. 또한 광주시와 서울시가 오차 양상이 다름을 밝혔다. 통행사슬 방법의 핵심 매개변수인 허용 도보거리 조정에 따른 추정 성공률 및 정확도의 변화도 다루었다. 허용 도보거리가 증가됨에 따라 추정 성공률은 높아지는 반면 추정 정확도는 낮아지는 것을 확인하였으며, 500m를 전후하여 추정 결과의 변화 양상이 있음을 발견하였다.

Keywords

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