관측자료가 없는 교통존 내부통행 발생량 추정 방법

Abstract

교통수요분석 4단계 과정 중 통행배정 단계에서 존내부통행은 배정이 되지 않는다. 통행의 기종점이 교통존으로 표현되며, 교통존의 centroid에서 통행이 시작되고 끝나기 때문에 통행의 기종점이 동일한 교통존으로 이루어진 존내부통행은 그 양에 상관없이 통행배정 시에 적용이 되지 않는다. 정교한 분석이 이루어지려면 교통존을 세분화하여 현실묘사력을 높일 필요가 있다. 교통존을 세분화하여 분석하려면, 우선 대존의 존내부통행량을 근거로 세부존간 통행량을 산정해야 한다. 그러나 수도권 및 광역권과 같이 대도시권역의 지역만 관측자료를 기초로 하여 존내부통행량을 배포하고 있으며 대부분 지역은 대존의 존내부통행량을 제시하지 못하고 있는 실정이다. 그러므로 본 연구에서는 교통존을 세분화하기 위해 필요한 대존의 존내부통행량을 산정하는 것을 목적으로 한다. 본 연구는 대존의 존내부통행량이 존재하는 교통존의 지역적 특성, 사회경제적 특성, 통행패턴 등을 이용하여 유사한 그룹으로 형성하는 군집분석과 대존의 총 통행생성량, 존내부통행량 비율, 직접수요모형 등에 회귀분석을 실시하여 대존의 존내부통행량을 산출한다. 그리고 관측자료가 없는 가운데 존내부통행량 산정 연구방법론을 통계적 이론에 기초하여 확고한 분석체계를 정립하고 순차적으로 진행하여, 산출된 존내부통행량으로 세부존간 통행량을 산정하였다. 마지막으로 관측자료를 통해 얻은 결과와 통계적 검증을 통하여 본 연구결과의 적절성을 검토한 결과 통계적으로 적절한 값이 도출되었음을 알 수 있었다. 본 연구가 향후 교통존 내부통행 발생량 추정연구에 기초자료로 활용될 수 있기를 기대한다.| In the final part of four steps for Transportation demand analysis, traffic assignment, intra-zonal trips are not assigned. Because trips begin and end at the centroid of trip zone, intra-zonal trips which have identical centroids for trip ends are not applied regardless of the flow upon assignment. In order to do more specified analysis, at first we need to raise explanation for reality by classifying trip zones. And on the basis of intra-zonal trips for large zones we need to generate detailed inter-zonal trips which are components of the trips to analyze specified trip zones. But we have been providing intra-zonal trips on the basis of household survey data for only big cities such as Seoul national capital area and metropolitan area. So, most of regions does not have any data for intra-zonal trips. Therefore, this study is to calculate intra-zonal trips for large zones which are needed to specify trip zones. This study forecasts intra-zonal trips for large zone by using regional, socio-economical characteristics, trip patterns of trip zones where exist intra-zonal trips for large zones. And we study by implementing k-means cluster analysis classifying k similar groups and regression analysis for total generated trips of large zone, rates of intra-zonal trips and direct demand model. And even though there is not observation data for intra-zonal trips(e.g. household survey), we made brief analysis system on the basis of statistical theory of research methodology for intra-zonal trips and calculated detailed inter-zonal trips through generated intra-zonal trips. Finally, through the results of observations and statistical validation, this study represents that we gained proper values statistically. In the future, we expect that this study will be used as the basic process for approximation of intra-zonal trips in the situation where does not exist the observation data.; In the final part of four steps for Transportation demand analysis, traffic assignment, intra-zonal trips are not assigned. Because trips begin and end at the centroid of trip zone, intra-zonal trips which have identical centroids for trip ends are not applied regardless of the flow upon assignment. In order to do more specified analysis, at first we need to raise explanation for reality by classifying trip zones. And on the basis of intra-zonal trips for large zones we need to generate detailed inter-zonal trips which are components of the trips to analyze specified trip zones. But we have been providing intra-zonal trips on the basis of household survey data for only big cities such as Seoul national capital area and metropolitan area. So, most of regions does not have any data for intra-zonal trips. Therefore, this study is to calculate intra-zonal trips for large zones which are needed to specify trip zones. This study forecasts intra-zonal trips for large zone by using regional, socio-economical characteristics, trip patterns of trip zones where exist intra-zonal trips for large zones. And we study by implementing k-means cluster analysis classifying k similar groups and regression analysis for total generated trips of large zone, rates of intra-zonal trips and direct demand model. And even though there is not observation data for intra-zonal trips(e.g. household survey), we made brief analysis system on the basis of statistical theory of research methodology for intra-zonal trips and calculated detailed inter-zonal trips through generated intra-zonal trips. Finally, through the results of observations and statistical validation, this study represents that we gained proper values statistically. In the future, we expect that this study will be used as the basic process for approximation of intra-zonal trips in the situation where does not exist the observation data.