칼만필터를 활용한 VDS 데이터 수집 알고리즘 개선에 관한 연구
A Study on the Improvement of VDS Data Collection Algorithm Using Kalman Filter
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도로 이용자의 교통정보에 대한 수요 증가와 효율적인 도로 이용을 위해 또한, 지능형 교통체계(ITS, Intelligent Transport Systems)의 기본 기술로 교통정보를 수집하여 제공하는 시스템에 대한 개발과 요구가 지속되고 있다. 고속도로에서 가장 많이 사용하는 교통정보 수집 도구로는 차량검지기(VDS)와 단거리무선통신(DSRC)이 있으며, 신뢰성 있는 교통정보의 생성을 위해서는 질 높은 교통데이터 수집 및 가공 기술과더불어 수집된 자료의 효율적 관리 및 활용이 필요하다. 본 연구에서는 교통정보 수집·제공 기술의 현황을 기술하고, VDS를 통하여 수집되는 교통정보의현황과 문제점에 대하여 분석한다. 이를 바탕으로 VDS 데이터의 차량정보 계측에 칼만 필터를 활용하여개선된 수집 알고리즘을 제시하고자 한다. 본 연구의 알고리즘을 활용하면 계측 시 필연적으로 발생하는노이즈 제거 뿐만 아니라 추정 값의 시간지연(time delay)을 최소로 할 수 있다.
Abstract
The development and demand for the system that provides users with traffic information and efficient road use have continued. also, this system provides the basic technology of the Intelligent Transport System (ITS). The most used traffic information collection tools are Vehicle detectors (VDS) and short-range wireless communication (DSRC) on express way. In order to generate reliable traffic information, it is necessary to efficiently manage and utilize the collected data as well as high-quality traffic data collection and processing technology. In this study, traffic information collection⋅ processing⋅provision systems were investigated, and analyze the current status and problems of traffic information collected through VDS. Based on this, we would like to present an improved collection algorithm that utilizes the Kalman filter for vehicle information measurement of VDS data. By using the algorithm of this study, it is possible to minimize the time delay of the estimated value as well as the noise removal that inevitably occurs during measurement.
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