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

The Korea Institute of Intelligent Transport Systems (한국ITS학회)
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Study of Analysis for Autonomous Vehicle Collision Using Text Embedding

텍스트 임베딩을 이용한 자율주행자동차 교통사고 분석에 관한 연구

  • Park, Sangmin (Dept. of Transportation System Engineering, Univ. of Ajou) ;
  • Lee, Hwanpil (Division of Transportation Research, Korea Expressway Corporation Research Institute) ;
  • So, Jaehyun(Jason) (Dept. of Transportation System Engineering, Univ. of Ajou) ;
  • Yun, Ilsoo (Dept. of Transportation System Engineering, Univ. of Ajou)
  • 박상민 (아주대학교 교통시스템공학과) ;
  • 이환필 (한국도로공사 도로교통연구원) ;
  • 소재현 (아주대학교 교통시스템공학과) ;
  • 윤일수 (아주대학교 교통시스템공학과)
  • Received : 2020.11.15
  • Accepted : 2021.02.18
  • Published : 2021.02.28
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Abstract

Recently, research on the development of autonomous vehicles has increased worldwide. Moreover, a means to identify and analyze the characteristics of traffic accidents of autonomous vehicles is needed. Accordingly, traffic accident data of autonomous vehicles are being collected in California, USA. This research examined the characteristics of traffic accidents of autonomous vehicles. Primarily, traffic accident data for autonomous vehicles were analyzed, and the text data used text-embedding techniques to derive major keywords and four topics. The methodology of this study is expected to be used in the analysis of traffic accidents in autonomous vehicles.

최근 전 세계적으로 자율주행자동차 개발을 위한 연구가 증가하고 있으며, 자율주행자동차의 실도로 도입이 증가되고 있는 추세이다. 하지만, 자율주행자동차의 교통사고 발생으로 인해 자율주행자동차 안전성에 대한 관심이 높아지고 있다. 또한, 자율주행자동차 교통사고에 대한 특성 파악 및 분석 방법론 개발의 필요성이 대두되고 있다. 특히 미국 캘리포니아 차량관리국(California Department of Motor Vehicles, DMV)에서는 자율주행자동차의 교통사고 데이터를 수집하여 리포트 형태로 제공하고 있다. 본 연구에서는 DMV에서 제공하는 자율주행자동차 교통사고를 분석하는 방법론을 제시하였다. 또한, 텍스트 임베딩 기법을 이용하여 주요 키워드 및 주요 토픽 도출을 통해 개발된 방법론의 활용도를 검토하였다. 본 연구에서 개발된 방법론은 향후 자율주행자동차 교통사고 데이터가 충분히 수집된다면 자율주행자동차 교통사고 분석 및 자율주행자동차 개발시 활용될 수 있을 것으로 기대된다.

Keywords

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