한국ITS학회 논문지 (The Journal of The Korea Institute of Intelligent Transport Systems)

  • 제23권3호
  • /
  • Pages.29-47
  • /
  • 2024
  • /
  • 1738-0774(pISSN)
  • /
  • 2384-1729(eISSN)
한국ITS학회 (The Korea Institute of Intelligent Transport Systems)
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공유 전동킥보드 이용 예측력에 대한 모형 및 영향요인에 관한 연구

A Study on the Inter-Model Comparison and Influencing Factors on the Use Predictive Power of Shared E-scooter

  • 김대원 (서울시립대학교 스마트시티학과) ;
  • 이동민 (서울시립대학교 교통공학과 & 스마트시티학과)
  • Daewon Kim (Dept. of Smart cities., Univ. of Seoul) ;
  • Dongmin Lee (Dept. of Transportation Eng & Smart cities., Univ. of Seoul)
  • 투고 : 2023.06.13
  • 심사 : 2024.06.18
  • 발행 : 2024.06.30
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초록

공유 전동킥보드 실적자료를 기반으로 공유 전동킥보드 이용에 유의미한 영향을 미치는 요인을 도출한 연구는 국내외 다수 존재하나, 이용 예측력을 활용하여 모형을 비교 분석하고 타지역에 대한 적용을 통해 최적의 예측모형을 구축한 연구는 아직 많이 이루어지지 않았다. 따라서 본 연구에서는 국내의 공유 전동킥보드 실적자료를 활용하여 광진구 및 강남구 지역에 대한 세부적인 공유 전동킥보드 이용 영향요인 및 영향권을 명확히 정립함으로써 이용 예측력을 높이고, 공간적 자기상관성 검증을 통해 지역적 특성을 반영한 최적의 모형으로 지리가중 회귀모형을 도출하였다. 본 결과를 바탕으로 지역적 차이에 따라 발생하는 구축 모형의 방향성을 제시하고, 실제 이용량과 모형 예측량의 차이에 따른 이용자 관점에서의 주요 시사점을 도출하였다.

Many domestic and foreign studies derive factors that significantly affect the use of shared E-scooters based on performance data, but few studies have been conducted with comparative analysis models using predictive power, applying them to other regions. Therefore, by clearly establishing detailed influencing factors and scope in Gwangjin-gu and Gangnam-gu by using domestic shared E-scooter performance data, this study enhances predictive power, and the Geographically Weighted Regression model is derived through spatial autocorrelation verification. Based on the results, the direction of a construction model created from regional differences was presented, and major implications from the user's perspective are derived based on the difference between actual use and the model's prediction.

키워드

과제정보

본 연구는 산업통상자원부/한국산업기술진흥원 및 국토교통부 스마트시티 혁신인재육성사업('19-'23) 지원으로 수행되었습니다(과제번호 P0013601).

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