Journal of Auto-vehicle Safety Association (자동차안전학회지)

Korean Auto-vehicle Safety Association (한국자동차안전학회)
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Traffic Accident Type Classification and Characteristic Analysis Research to Develop Autonomous Vehicle Accident Investigation Guidelines Using the National Forensic Service Data Base

국과수 데이터베이스를 활용하여 자율주행차 사고조사 가이드라인 개발을 위한 교통사고 유형 분류 및 특성 분석 연구

  • 인병덕 (서울과학수사연구소 이공학과) ;
  • 박다영 (연세대학교 통계데이터사이언스학과) ;
  • 박종진 (서울과학수사연구소 이공학과)
  • Received : 2023.10.30
  • Accepted : 2024.02.12
  • Published : 2024.03.31
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Abstract

In order to verify autonomous driving scenarios and safety, a lot of driving and accident data is needed, so various organizations are conducting classification and analysis of traffic accident types. In this study, it was determined that accident recording devices such as EDR (Event Data Recorder) and DSSAD (Data Storage System for Automated Driving) would become an objective standard for analyzing the causes of autonomous vehicle accidents, and traffic accidents that occurred from 2015 to 2020 were analyzed. Using the database system of IGLAD (Initiative for the Global Harmonization of Accident Data), approximately 360 accident data of EDR-equipped vehicles were classified and their characteristics were analyzed by comparing them with accident types of ADAS (Advanced Driver Assistance System)-equipped vehicles. It will be used to develop autonomous vehicle accident investigation guidelines in the future.

Keywords

Acknowledgement

본 연구는 국토교통부/국토교통과학기술진흥원의 지원으로 수행되었음(과제번호 RS-2021-KA162419).

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