Journal of Korean Institute of Industrial Engineers (대한산업공학회지)

Korean Institute of Industrial Engineers (대한산업공학회)
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Development of an Evaluation Method for a Driver's Cognitive Workload Using ECG Signal

ECG 기반의 운전자별 인지 부하 평가 방법 개발

  • Hong, Wongi (Integrated Logistics Support R&D Lab, LIG Nex1) ;
  • Lee, Wonsup (Department of Industrial and Management Engineering, Pohang University of Science and Technology) ;
  • Jung, Kihyo (School of Industrial Engineering, University of Ulsan) ;
  • Lee, Baekhee (Department of Industrial and Management Engineering, Pohang University of Science and Technology) ;
  • Park, Jangwoon (Department of Industrial and Management Engineering, Pohang University of Science and Technology) ;
  • Park, Suwan (Public and Original Technology Research Center, DGIST) ;
  • Park, Yunsuk (Public and Original Technology Research Center, DGIST) ;
  • Son, Joonwoo (Public and Original Technology Research Center, DGIST) ;
  • Park, Seikwon (Department of Industrial Engineering, Air Force Academy) ;
  • You, Heecheon (Department of Industrial and Management Engineering, Pohang University of Science and Technology)
  • 홍원기 (LIG넥스원 ILS연구센터) ;
  • 이원섭 (포항공과대학교 산업경영공학과) ;
  • 정기효 (울산대학교 산업경영공학부) ;
  • 이백희 (포항공과대학교 산업경영공학과) ;
  • 박장운 (포항공과대학교 산업경영공학과) ;
  • 박수완 (대구경북과학기술원 공공원천기술연구센터) ;
  • 박윤숙 (대구경북과학기술원 공공원천기술연구센터) ;
  • 손준우 (대구경북과학기술원 공공원천기술연구센터) ;
  • 박세권 (공군사관학교 산업공학과) ;
  • 유희천 (포항공과대학교 산업경영공학과)
  • Received : 2013.02.19
  • Accepted : 2013.12.31
  • Published : 2014.06.15
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Abstract

High cognitive workload decreases a driver's ability of judgement and response in traffic situation and could result in a traffic accident. Electrocardiography (ECG) has been used for evaluation of drivers' cognitive workload; however, individual differences in ECG response corresponding to cognitive workload have not been fully considered. The present study developed an evaluation method of individual driver's cognitive workload based on ECG data, and evaluated its usefulness through an experiment in a driving simulator. The evaluation method developed by the present study determined the optimal ECG evaluation condition for individual participant by analysis of area under the receiver operating characteristic curve (AUC) for various conditions (total number of conditions = 144) in terms of four aspects (ECG measure, window span, update rate, and workload level). AUC analysis on the various conditions showed that the optimal ECG evaluation condition for each participant was significantly different. In addition, the optimal ECG evaluation condition could accurately detect changes in cognitive workload for 47% of the total participants (n = 15). The evaluation method proposed in the present study can be utilized in the evaluation of individual driver's cognitive workload for an intelligent vehicle.

Keywords

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