도시부 경로자료를 이용한 통행의 공간적 규칙성 분석
Analysis of Spatial Trip Regularity using Trajectory Data in Urban Areas
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참고문헌
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초록
최근 정보통신기술의 발달로 다양한 통행 정보 수집이 용이해지면서, 신규 교통정보 생성에대한 연구가 주목받고 있다. 그 중 수요 및 교통량에 대한 추정 및 예측은 교통 운영에 필수적인 주요 지표 중 하나로, 특정 지점 혹은 구간의 통행 패턴이 반복됨을 전제로 한다. 기존에는이러한 통행 규칙성을 증명하기 위해 설문 방식을 사용하였으나, 해당 방식은 높은 비용과 응답자 기억에 의존하는 응답으로 높은 정확도를 확보하기에는 한계가 있었다. 최근 ETC시스템, 스마트카드 등의 방법으로 통행데이터 수집이 용이해지면서, 다양한 시각에서 통행 규칙성을규명하고자 하는 연구가 진행되고 있다. 본 연구에서는 대구광역시의 대규모 경로형 데이터를분석하여 개별통행자가 여러 날에 걸쳐 공간적으로 유사한 통행사슬을 형성하는 것을 확인하였다. 이를 위하여 공간적 통행 유사성을 새롭게 정의하며, 서열정렬 알고리즘인 Dynamic Time Warping을 이용하여 일별 통행사슬 간 공간적 차이를 산정한다. 또한 산출된 공간적 통행규칙성을 통해 고정적 교통수요 추정의 지표 및 교통서비스로의 활용방안을 논 하고자 한다.
Abstract
As the development of ICT has made it easier to collect various traffic information, research on creating new traffic attributes is drawing attention. Estimation and forecasts of demand and traffic volume are one of the main indicators that are essential to traffic operation, assuming that the traffic pattern at a particular node or link is repeated. Traditionally, a survey method was used to demonstrate this similarity on trip behavior. However, the method was limited to achieving high accuracy with high costs and responses that relied on the respondents’ memory. Recently, as traffic data has become easier to gather through ETC system, smart card, studies are performed to identify the regularity of trip in various ways. In, this study, route-level trip data collected in Daegu metropolitan city were analyzed to confirm that individual traveler forms a spatially similar trip chain over several days. For this purpose, we newly define the concept of spatial trip regularity and assess the spatial difference between daily trip chains using the sequence alignment algorithm, Dynamic Time Warping. In addition, we will discuss the applications as the indicators of fixed traffic demand and transportation services.
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