Abstract
졸음 운전 등 운전자의 상태 변화에 따른 자동차 사고가 급증하고 있으며 이를 방지하기 위한 시스템 구축 및 운전자의 상태를 판단하는 알고리즘 개발이 요구되어 지고 있다. 본 논문에서는 모의 주행 시스템을 통한 운전자의 심박변이도, 산호 포화도 (SPO2), 체온을 측정하여 운전자의 상태를 알려 주는 실험을 수행하였다. 즉, 심박변이도 (Heart rate variability, HRV) 분석을 위해 운전자의 심전도(Electrocardiogram, ECG) 신호를 획득 한 후 심전도 P,QRS, T 파형 중 R peak 을 자동으로 검출하였고 이를 통해 구한 R-R interval을 이용하여 HRV의 주요 파라메타를 시간영역(time domain)으로 해석하여 작업 환경에 따른 운전자의 상태를 비교 분석하였다. The accidents caused by drivers while driving are considered as the major causes along with other causes such as conditions of roads, weather and cars. In this study, we investigated the driver's workloads under three different driving conditions (Weather, Driving time zone, and Traffic density) through analyzing biological signals obtained from a car driving simulator system. The proposed method is able to detect R waves and R-R interval calculation in the ECG. Heart rate variability (HRV) was investigated for the time domain to determine the changes in driver's conditions.
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