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

The Korea Institute of Intelligent Transport Systems (한국ITS학회)
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Estimation of Driving Behavior Characteristics through Self-Reported-Based Driving Propensity

자기보고 기반 운전성향을 통한 주행행태 특성 추정 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 : 2023.12.05
  • Accepted : 2023.12.18
  • Published : 2024.02.28
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Abstract

To ensure safer road conditions, understanding the human factors influencing driving behavior is crucial. However, there are many difficulties in deriving the characteristics of individual human factors that affect actual driving behaviors. Therefore, this study analyzes self-reported dangerous-driving propensities in order to explore potential correlations with drivers' behaviors. The goal is to propose a method for assessing driving tendencies based on varying traffic scenarios. The study employed a questionnaire to gauge participants' propensity to drive dangerously, utilizing a simulator to analyze their driving behaviors. The aim is to determine any notable connections between dangerous-driving propensity and specific driving behaviors. Results indicate that individuals exhibiting a high propensity for reckless driving, as identified by the Korean DBQ, tend to drive at higher speeds and display more aggressive acceleration patterns. These findings contribute to a potential method for assessing reckless driving drivers.

안전한 도로교통 환경 조성을 위하여 운전행동에 영향을 미치는 인적요인에 관한 연구가 필요하지만, 실제 주행행태에 영향을 미치는 개인별 인적요인 특성을 도출하기에는 많은 어려움이 있다. 이에, 개별 운전자의 자기 보고를 통하여 도출되는 위험운전성향을 분석하여 주행 행태 특성과 상관성이 있는지 확인하고, 교통상황에 따른 주행행태에 영향을 미치는 운전성향을 추정하는 방법을 제시하고자 하였다. 본 연구에서는 기존에 고안된 설문 기법을 활용하여 실험 참가자들의 위험운전성향을 여러 방법으로 도출하고, 가상환경 기반의 주행 시뮬레이터 실험을 통하여 도출된 주행행태 특성을 분석하여 위험운전성향과 주행행태 특성 간 유의미한 상관관계가 있는지 확인하였다. 실험 결과, 한국형 DBQ를 통하여 도출되는 난폭운전성향이 높은 사람들이 상대적으로 빠른 주행속도와 가속도 행태를 보이는 것을 확인할 수 있었다. 이를 통하여 상대적으로 위험운전행동을 보이는 운전자를 추정할 수 있는 평가 방법을 확인할 수 있었다.

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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