건축물 연면적에 따른 노상·노외 주차수요 산정 모형 구축 Establishment of a Estimation Model of On-Road and Off-Road Parking Demand Based on the Total Floor Area of Buildings원문보기
최근 충분한 주차공간 확보의 어려움으로 심각한 주차문제가 발생하고 있으며 또 다른 교통문제나 사회문제로 이어지기도 한다. 일정 범위 이상의 지역·지구에서 발생하는 주차문제를 해결하기 위해서는 지역특성을 반영한 노상 및 노외주차장에 대한 연구가 필요하며 본 연구에서는 지역·지구의 특성을 고려한 노상 및 노외주차 공급 정책을 수립하는데 기초 연구로 활용하기 위한 주차수요 산정모형을 구축하였다. 연구수행을 위해 대구광역시 동구를 행정동으로 구분하여 주차시설, 주차수요를 조사하였다. 조사시간은 평일에 주간과 야간으로 구분하였으며 차종은 승용차 소형트럭·버스, 대형트럭·버스 3종으로 구분하였다. 주차수요 산정을 위한 설명변수로 단독주택, 공동주택, 근린생활시설, 문화·집회시설, 업무시설, 판매시설 등 6가지의 용도별 건축물 연면적을 사용하였다. 상관분석 결과 6가지 설명변수 중 근린생활시설의 연면적이 노상 및 노외 주차수요와 유의미한 상관관계를 나타내었다. 근린생활시설의 연면적을 설명변수로 하여 회귀분석 모형을 구축하였고 통계적으로 유의미한 결과를 얻었다.
최근 충분한 주차공간 확보의 어려움으로 심각한 주차문제가 발생하고 있으며 또 다른 교통문제나 사회문제로 이어지기도 한다. 일정 범위 이상의 지역·지구에서 발생하는 주차문제를 해결하기 위해서는 지역특성을 반영한 노상 및 노외주차장에 대한 연구가 필요하며 본 연구에서는 지역·지구의 특성을 고려한 노상 및 노외주차 공급 정책을 수립하는데 기초 연구로 활용하기 위한 주차수요 산정모형을 구축하였다. 연구수행을 위해 대구광역시 동구를 행정동으로 구분하여 주차시설, 주차수요를 조사하였다. 조사시간은 평일에 주간과 야간으로 구분하였으며 차종은 승용차 소형트럭·버스, 대형트럭·버스 3종으로 구분하였다. 주차수요 산정을 위한 설명변수로 단독주택, 공동주택, 근린생활시설, 문화·집회시설, 업무시설, 판매시설 등 6가지의 용도별 건축물 연면적을 사용하였다. 상관분석 결과 6가지 설명변수 중 근린생활시설의 연면적이 노상 및 노외 주차수요와 유의미한 상관관계를 나타내었다. 근린생활시설의 연면적을 설명변수로 하여 회귀분석 모형을 구축하였고 통계적으로 유의미한 결과를 얻었다.
Recently, serious parking problems are occurring due to the difficulty of securing sufficient parking space, and it may lead to other traffic or social problems. In order to solve the parking problem in areas and districts beyond a certain range, a study on-roads and off-street parking lots reflecti...
Recently, serious parking problems are occurring due to the difficulty of securing sufficient parking space, and it may lead to other traffic or social problems. In order to solve the parking problem in areas and districts beyond a certain range, a study on-roads and off-street parking lots reflecting regional characteristics is necessary. Therefore, this study establishing a parking demand calculation model for use as a basic study in establishing on-road and off-road characteristics. In order to conduct the study, Dong-fu, Daegu Metropolitan City was divided into dongs, and parking facilities and parking demand were investigated. The survey time was divided into daytime and nighttime on weekdays, and the types of vehicles were divided into three types: passenger car, small trucks and buses, large trucks and buses. As explanatory variables for calculating parking demand, the total floor area of buildings for each of six purposes was used, including detached houses, apartment houses, neighborhood living facilities, cultural and assembly facilities, business facilities, and sales facilities. As a result of the correlation analysis, among the six explanatory variables, the total area of neighborhood living facilities showed a significant correlation with on- and off-street parking demand. A regression analysis model was constructed using the total area of neighborhood living facilities as an explanatory variable, and statistically significant results were obtained.
Recently, serious parking problems are occurring due to the difficulty of securing sufficient parking space, and it may lead to other traffic or social problems. In order to solve the parking problem in areas and districts beyond a certain range, a study on-roads and off-street parking lots reflecting regional characteristics is necessary. Therefore, this study establishing a parking demand calculation model for use as a basic study in establishing on-road and off-road characteristics. In order to conduct the study, Dong-fu, Daegu Metropolitan City was divided into dongs, and parking facilities and parking demand were investigated. The survey time was divided into daytime and nighttime on weekdays, and the types of vehicles were divided into three types: passenger car, small trucks and buses, large trucks and buses. As explanatory variables for calculating parking demand, the total floor area of buildings for each of six purposes was used, including detached houses, apartment houses, neighborhood living facilities, cultural and assembly facilities, business facilities, and sales facilities. As a result of the correlation analysis, among the six explanatory variables, the total area of neighborhood living facilities showed a significant correlation with on- and off-street parking demand. A regression analysis model was constructed using the total area of neighborhood living facilities as an explanatory variable, and statistically significant results were obtained.
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