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공간 상관성을 고려한 서울시 택시통행의 영향요인 분석

Identifying Key Factors to Affect Taxi Travel Considering Spatial Dependence: A Case Study for Seoul

  • 이향숙 (인천대학교 동북아물류대학원) ;
  • 김지윤 (홍익대학교 도시계획과) ;
  • 추상호 (홍익대학교 건설도시공학부) ;
  • 장진영 (홍익대학교 도시계획과) ;
  • 최성택 (조지아공과대학교 토목.환경공학과)
  • Lee, Hyangsook (Graduate School of Logistics, Incheon National University) ;
  • Kim, Ji yoon (Dept. of Urban Planning, Hongik University) ;
  • Choo, Sangho (Dept. of Urban Design & Planning, Hongik University) ;
  • Jang, Jin young (Dept. of Urban Planning, Hongik University) ;
  • Choi, Sung taek (School of Civil and Environmental Eng.. Georgia Institute of Technology)
  • 투고 : 2019.09.06
  • 심사 : 2019.10.10
  • 발행 : 2019.10.31

초록

본 논문은 공간 상관성을 고려하여 서울의 택시통행에 영향을 미치는 요인을 분석한 것으로 택시의 GPS 자료를 이용하였다. 먼저 이들 자료를 이용하여 택시통행의 평균 통행시간, 평균 통행거리, 시공간적 분포 등의 통행특성을 분석하였다. 분석결과, 상당수의 택시통행이 평일 오전 첨두(8-9시)와 심야(0-1시) 시간대에 집중하는 것으로 나타났으며, 평균 통행거리와 통행시간은 각각 5.9km와 13분으로 나타났다. 이는 택시가 주로 단거리 통행수단이나 심야에 대중교통의 대체수단으로 활용되고 있음을 보여주고 있다. 다음으로 Moran's I 검정을 통해 교통존 기반의 택시통행들이 공간적으로 상관성이 있음을 규명하였다. 따라서 이를 고려한 택시통행에 대한 공간회귀모형(공간시차모형과 공간오차모형)을 추정하였으며, 인구사회 변수(가구수, 고령자수, 여성인구비, 자동차대수 등), 교통서비스 변수(지하철역수, 버스 정류장수 등), 토지이용 변수(인구밀도, 고용밀도, 주거면적 등) 등을 독립변수로 고려하였다. 모형분석 결과 이들 변수들이 통계적으로 유의하게 택시통행에 영향을 미치는 것으로 나타났다.

This paper explores key factors affecting taxi travel using global positioning system(GPS) data in Seoul, Korea, considering spatial dependence. We first analyzed the travel characteristics of taxis such as average travel time, average travel distance, and spatial distribution of taxi trips according to the time of the day and the day of the week. As a result, it is found that the most taxi trips were generated during the morning peak time (8 a.m. to 9 a.m.) and after the midnight (until 1 a.m.) on weekdays. The average travel distance and travel time for taxi trips were 5.9 km and 13 minutes, respectively. This implies that taxis are mainly used for short-distance travel and as an alternative to public transit after midnight in a large city. In addition, we identified that taxi trips were spatially correlated at the traffic analysis zone(TAZ) level through the Moran's I test. Thus, spatial regression models (spatial-lagged and spatial-error models) for taxi trips were developed, accounting for socio-demographics (such as the number of households, the number of elderly people, female ratio to the total population, and the number of vehicles), transportation services (such as the number of subway stations and bus stops), and land-use characteristics (such as population density, employment density, and residential areas) as explanatory variables. The model results indicate that these variables are significantly associated with taxi trips.

키워드

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피인용 문헌

  1. 동적·정적 자료 기반 도로위험도 산정 알고리즘 개발 vol.19, pp.4, 2020, https://doi.org/10.12815/kits.2020.19.4.55