대한교통학회지 (Journal of Korean Society of Transportation)

  • 제34권6호
  • /
  • Pages.560-569
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  • 2016
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  • 1229-1366(pISSN)
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  • 2234-4217(eISSN)
대한교통학회 (Korean Society of Transportation)
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고속도로 커브구간에서 운전자의 운전부하와 감마파 특성분석에 관한 연구

The Analysis of Driving Workload and Gamma Waves on Curved Sections in Expressway

  • 강학건 (원광대학교 토목환경공학과) ;
  • 남궁문 (원광대학교 토목환경공학과) ;
  • 김원철 (충남연구원 지역도시연구부) ;
  • 왕위걸 (남경대학교 교통과학공학과)
  • KANG, Xuejian (Department of Civil & Environmental Engineering, Wonkwong University) ;
  • NAMGUNG, Moon (Department of Civil & Environmental Engineering, Wonkwong University) ;
  • KIM, Won Chul (Department of Regional & Urban Research, Chungnam Institute, Chungnam Institute) ;
  • WANG, Weijie (Colleng of Transportation Science & Engineering, Nanjing Tech University)
  • 투고 : 2016.10.20
  • 심사 : 2016.12.14
  • 발행 : 2016.12.30
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초록

운전자의 정신부하는 교통사고를 감소하는데 중요한 역할을 하는 것으로 선행연구에서 나타나고 있다. 본 연구에서는 도로 및 환경요소 뿐만 아니라 운전자의 알파파, 베타파, 감마파를 측정할 수 있는 운전시뮬레이터를 활용하여 분석자료를 확보하였다. 운전자의 운전부하와 감마파의 연관성을 분석하기 위한 방법으로 로지스틱모형을 적용하였다. 분석결과, 도로의 커브가 많을수록 운전자의 베타 영역은 증가하는 반면 알파와 감마 영역은 감소되는 것으로 나타났다. 그리고, 운전부하는 감마영역과 음의 상관관계를 지닌 것으로 나타났다. 결론적으로, 직선구간에서의 도로주행이 운전자의 스트레스를 줄이고 행복감을 높일 수 있을 것으로 판단된다.

Previous studies show that driver mental workload plays a significant role in the occurrence of traffic accidents. This study also analyzes driving workload under different road conditions especially with the brain wave data collected by a driving simulator. We use a logistic regression model to explain the relationship between driving workload and gamma brain waves. The results show that beta band of brain waves becomes broader with more curved sections while alpha band and gamma band become narrower. Since driving workload is negatively correlated with gamma band, it can be concluded that driving condition with less curved section is beneficial for reducing driving stress and increasing driving comfort.

키워드

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피인용 문헌

  1. An Evaluation on the Length of Guidance Lane Marking on Expressways Using Virtual Driving Simulator vol.16, pp.5, 2017, https://doi.org/10.12815/kits.2017.16.5.01