PURPOSES : In this study, a virtual driving simulator was used to analyze the effects of implementing appropriate highway driving criteria on the attentiveness of motorists on Korean highways. METHODS : The study includes three scenarios. Scenario 1 was purposed to investigate the relationships between driver focus, the brain waves associated with drowsiness, and the speed of motorists driving along the straight 5-km section of Saemangeum South-North Road, which is the same as a car-only road. Scenarios 2 and 3 were designed to have shorter straight sections to enable comparison of the occurrence of drowsiness-related brain waves and velocity changes at 3 km and 2 km, respectively. RESULTS : Driver focus was found to decrease and result in speeding after driving 2.5 km of the straight section. Past this point, driver focus continued to decrease, and drivers continued to accelerate. However, upon reaching a curved section, driver focus increased according to the linear change; furthermore, drivers showed a tendency to reduce their speed to a value near the speed limit. CONCLUSIONS : According to the analysis of highway traffic accidents that occurred between 2013 and 2015, approximately 50% of total traffic accidents are due to speeding, drowsiness, and negligence. Therefore, if appropriately long straight sections, i.e., sections that are not associated with a reduced ability to focus, are calculated and implemented in road planning and operation, it is possible to prevent accidents caused by lack of driver focus.

목적 : 본 연구는 다양한 운전상황에서의어려움 정도를 평가하는 안전운전행동 체크리스트를 개발할 때 수집된 데이터를 라쉬분석을 활용하여 부적절한 문항을 확인하고 타당도를 검증하고자 하였다. 연구방법 : 안전운전행동체크리스트는 37문항으로 개발되었고 이 연구 참여한 대상자는 60세 이상 노인 운전자 의명21의1 원데이터를 활용하였다. 안전운전행동 체크리스트(자가보고식 노인 안전운전 측정도구)의 타당도 검증을 위해 라쉬분석을 사용하였고 Winsteps 프로그램을 통해 문항 적합성, 문항의 난이도, 평정척도의적합성을 검증하였다. 결과 : 탐색적 요인분석 결과 운전상황, 외부환경과 날씨, 주차, 일반적 운전상황 4개 요인으로 추출되었다. 라쉬 분석을 통해 1문항이 삭제되어 36문항이 적절하다고 분석되었다. 또한 문항의 난이도를 파악할 수 있었는데 문항 난이도 분석결과 가장 어려운 문항은 “눈길이나 빙판길에서 운전하기’, 가장 쉬운 문항은 “신호등 지키기”로 문항이었다. 결론 : 본 연구에서는 라쉬분석과 요인분석을 이용하여 안전운전행동 체크리스트의 타당도를 입증하였고 운전요인으로 4가지 요인을 확인하였다. 또 최종 문항의 난이도를 파악할 수 있었다. 향후 국내 상황에 적합한 운전 수행능력을 검증할 수 있는 다양한 평가와 중재가 개발되어 작업치료 임상현장에서 운전재활 기초자료로 활용되기를 기대한다.

Even though cars have a good effect on modern society, traffic accidents do not. There are traffic laws that define the regulations and aim to reduce accidents from happening; nevertheless, it is hard to determine all accident causes such as road and traffic conditions, and human related factors. If a traffic accident occurs, the traffic law classifies it as ‘Negligence of Safe Driving’ for cases that are not defined by specific regulations. Meanwhile, as Korea is already growing rapidly elderly population with more than 65 years, so are the number of traffic accidents caused by this group. Therefore, we studied predictive and comparative analysis of the number of traffic accidents caused by ‘Negligence of Safe Driving’ by dividing it into two groups : All-ages and Elderly. In this paper, we used empirical monthly data from 2007 to 2015 collected by TAAS (Traffic Accident Analysis System), identified the most suitable ARIMA forecasting model by using the four steps of the Box-Jenkins method : Identification, Estimation, Diagnostics, Forecasting. The results of this study indicate that ARIMA (1, 1, 0)(0, 1, 1)12 is the most suitable forecasting model in the group of All-ages; and ARIMA (0, 1, 1)(0, 1, 1)12 is the most suitable in the group of Elderly. Then, with this fitted model, we forecasted the number of traffic accidents for 2 years of both groups. There is no large fluctuation in the group of All-ages, but the group of Elderly shows a gradual increase trend. Finally, we compared two groups in terms of the forecast, suggested a countermeasure plan to reduce traffic accidents for both groups