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A Study on User Satisfaction Evaluation of Acceleration-Based Automated Driving Patterns

가속도 기반 자율주행 패턴에 대한 이용자 만족도 평가 연구

  • Sooncheon Hwang (Dept. of Smart cities., Univ. of Seoul) ;
  • Dongmin Lee (Dept. of Transportation Eng & Smart cities., Univ. of Seoul)
  • 황순천 (서울시립대학교 스마트시티학과) ;
  • 이동민 (서울시립대학교 교통공학과 & 스마트시티학과)
  • Received : 2023.11.21
  • Accepted : 2023.12.04
  • Published : 2023.12.31

Abstract

With the rapid advances in automated driving technology, opportunities to experience automated driving directly or indirectly are being provided to the public. On the other hand, research on the preferred automated driving patterns from the user's perspective has not been conducted in Korea. This study used a driving simulator and an experimental vehicle capable of automated driving to evaluate the user satisfaction regarding longitudinal and lateral accelerations. Automated driving patterns were implemented in a virtual environment simulation using five values of longitudinal and lateral accelerations derived from driving experiments. Among these values, three were implemented through experimental vehicle-based automated driving to evaluate satisfaction and anxiety. The participants evaluated lateral acceleration more sensitively than longitudinal acceleration and showed higher levels of anxiety. Based on these results, the necessity of user-oriented evaluation research for automated driving patterns and the suitability of simulator-based evaluation methods were presented.

자율주행 기술이 빠르게 발전함에 따라 자율주행 기술을 직·간접적으로 체험할 수 있는 기회가 대중에게 제공되고 있지만, 이용자 관점에서 편안한 승차감을 기대할 수 있는 선호하는 자율주행 패턴에 대해서는 연구가 미비하다. 본 연구에서는 주행 시뮬레이터와 자율주행이 가능한 실험차를 활용하여 종·횡방향 가속도에 대한 이용자 측면 만족도 평가를 수행하였다. 주행 실험을 통하여 도출한 5가지 종·횡방향 가속도 값을 활용하여 자율주행 패턴을 가상환경 시뮬레이션으로 구현하였으며, 그 중 3가지 값에 대해서는 실차 기반 자율주행으로 구현하여 만족도 및 불안감 수준 평가실험을 추가 진행하였다. 연구 결과, 실험 참가자들은 종방향 가속도에 비하여 횡방향 가속도에 더 민감한 평가를 하였으며, 불안감 수준도 높게 나타나는 것을 확인할 수 있었다. 이러한 결과를 바탕으로 이용자 측면 자율주행 패턴 평가연구 필요성과, 시뮬레이터 기반 평가방법의 적정성을 제시하였다.

Keywords

Acknowledgement

본 연구는 2021년도 정부(경찰청)의 재원으로 과학치안진흥센터의 지원을 받아 수행된 연구입니다 (No.092021C26S02000, Lv.4 자율협력주행 대응 교통객체 인지고도화 및 악조건 해소기술 개발).

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