DOI QR코드

DOI QR Code

Categorization of Traffic Type According to Seoul-City Administrative District Using Cluster Analysis

군집분석을 이용한 서울시 행정구역별 교통유형 분류

  • 한만섭 (경기대학교 공과대학 도시.교통공학과) ;
  • 오흥운 (경기대학교 공과대학 도시.교통공학과)
  • Received : 2012.05.24
  • Accepted : 2012.07.23
  • Published : 2012.08.15

Abstract

PURPOSES : Traffic situation of Seoul City is different each administrative district. because each administrative district population, average travel speed, etc are different. thus, regionally differentiated policy is necessary. METHODS : In this study, first, it is to implement the cluster analysis using the traffic factor of twenty-five administrative districts in Seoul, categorize it into the cluster and understand the properties. second, related factors of speed were derived. and method to increase the speed was investigated. we choose the eleven traffic factors such as the number of traffic accident cases, total length, speed, the number of cross section, the number of cross section per km, the rate of roads, registered cars, population attending office and school, population density, area. RESULTS : In the results, first, we could categorize the Seoul-City administrative district into three clusters. in order to find Factors associated with speed a simple regression analysis was performed. and the number of intersections per km is closely related to the speed. CONCLUSIONS : Through this study, transportation policies reflecting local traffic-related characteristics are required.

Keywords

References

  1. Choi, Keechoo et. al, 2007, Classification of Freeways based on the Characteristics of Hourly Traffic Variation for Efficient Network Planning, Journal of Korea Society of Civil Engineers, vol. 6. 713-739 (최기주 외 2명, 2007 효율적 고속도로 계획을 위한 고속도로 시간교통량 변동특성 고찰 및 고속도로 유형분류, 대한토목학회논문집, Vol. 6, 713-739)
  2. Jang, Hyunmin, 2010, A study on the cluster analysis of the administrative districts of Seoul using demographics, Graduate School of HANYANG University (장현민, 2010, 인구통계를 이용한 서울시 행정구역의 군집분석 연구, 한양대학교일반대학원)
  3. Kim, Youngsin, 2008, Classification of Function of Urban Arterial Using Cluster Analysis, Graduate School of HANYANG University (김용신, 2008, 군집분석을 이용한 도시간선도로의 도로기능분류, 한양대학교일반대학원)
  4. Kwon, Minjung, 2008, Development of Traffic Accident Precidtion Model using cluster analysis method based on the type of city, Graduate School of AJOU University (권민정, 2008, 군집분석을 통한 도시유형별 교통사고예측 모형개발에 관한 연구, 아주대학교일반대학원)
  5. Lee, haksik et. al, 2004, SPSS 12.0 manual, Bobmunsa (이학식 외 1명, 2004, SPSS 12.0 매뉴얼 통계분석방법 및 해설)
  6. Lee, Keecheol, 2009 Classification of Recreation Forests through Cluster Analysis, Journal of the Korean Institute of Landscape Architecture, vol. 37. 9-17 (이기철, 2009, 군집분석을 통한 전국 자연휴양림 유형분류, 한국조경학회지, Vol. 37. 9-17)
  7. Seoul city, 2010, 2009 Seoul city vehicle travel speed. Regular speed survey report, Seoul city (서울시, 2010, 2009년도 서울시 차량통행속도 보고서, 서울시)
  8. Song, Minkyung et. al, 2010, Charaterization of Cities in Seoul Metropolitan Area by Cluster Analysis, Journal of The Korean Society for GeoSpatial Information System, vol. 1. 83-88 (송민경 외 1명, 2010, 군집분석을 이용한 수도권 도시의 유형화에 관한 연구, 한국지형공간정보학회지, Vol. 1, 83-88)
  9. Yoon, Hyojin, 2004, A Study of Forming Areas of Uniform Characteristics within Metropolis: Analyzing socio-economic Indexes, Journal of Korea Society of Civil Engineers, vol. 4. 631-639 (윤효진, 2004, 사회경제 지표 설정에 의한 도시공간 동질지역 설정 연구, 대한토목학회논문집, Vol. 4, 631-639 )
  10. Yoo, Jisung et. al, 2004, Modern Statistics, Pakyoungsa (유지성 외 1명, 2004, 현대통계학, 박영사)