목적 : 본 연구는 20대 건강한 초보운전자를 대상으로 음주운전이 운전에 미치는 영향을 알아보고자 하였다. 또한 초보운 전자의 음주운전에 대한 인식을 높이기 위한 근거를 제공하는 것을 목적으로 하였다. 연구방법 : 단면적 연구 수행으로 22명이 연구에 참여하였으며 연구 참여자는 음주 운전을 시뮬레이션하기 위해 3가지 음 주 안경(Fatal Vision Gogles, FVG)을 번갈아 착용하고 운전 시뮬레이터(GDS-300, Gridspace, 서울, 한국)를 사용하 였다. (1) 위약 고글, (2) 저용량 알코올 고글, (3) 고용량 알코올 고글의 세 가지 실험 조건에서 UFOV 평가(처리 속도, 분리 집중력, 선택적 집중력), 인지 평가, 점수 차감 및 결격을 사용하여 운전 능력을 측정하였다. 결과 : 연구 참여자의 평균 연령과 운전 경력은 각각 21.6±2.3세와 23.6±16.2개월이었다. 수집한 자료를 분석한 결과, 처리 속도, 분리 집중력, 선택적 집중력은 세 가지 조건에서 유의한 차이가 있었다. 반면에 인지 평가 점수, 운전점수 감 점 및 결격은 세 가지 조건에서 유의한 차이가 없었다. 결론 : 본 연구의 결과는 20대 초보운전자의 음주운전이 인지 기능, 운전점수 감점, 운전 결격에 영향을 미치지 않았으나 처리 속도, 분리 집중력, 선택적 집중력에 영향을 미친다는 것을 보여주었다. 본 연구의 결과를 바탕으로 실제 운전 중 음주 운전자에게 예측할 수 없는 돌발 상황이 발생할 때 상당한 위험을 초래할 수 있음을 제언하는 바이다.

PURPOSES : This study analyzed explanatory variables, such as dangerous driving behaviors, in a negative binomial regression model, using the Digital Tachograph data of commercial vehicles, to assess the factors associated with freeway accidents. METHODS : Fixed parameter and random parameter negative binomial regression models were constructed using freeway accident data of commercial vehicles from January 2007 to July 2018 on the Gyeongbu Expressway from West Ulsan Interchange to Gimcheon Junction. RESULTS : Six explanatory variables (logarithm of average annual daily traffic, sunny, rainy, and snowy weather conditions, road curvature, and driving behaviors that included sudden stops) were found to impact the occurrence of freeway accidents significantly. Two of these variables (snowy weather conditions and sudden stops among dangerous driving behaviors) were analyzed as random parameters. These variables were shown as probabilistic variables that do not have a fixed impact on traffic accidents CONCLUSIONS : The variables analyzed as random parameters should be carefully considered when the freeway operating authorities plan an improvement project for highway safety.

PURPOSES: This study aims to analyze how the installation of advanced warning devices affects individual drivers’driving behaviors with operating record data collected from 100 vehicles. METHODS: With collected data, the changes in individual drivers’driving behaviors, such as Forward Collision Warning (FCW) and Lane Departure Warning (LDW), were investigated with respect to the cumulative distance traveled and driving time. For the analysis, operating record data collected from 100 vehicles for seven months were used. RESULTS: The results showed that individual drivers’driving behaviors could be categorized into six different types. In addition, most of the drivers showed unstable warning patterns in the initial stage after installation of an advanced warning device. Approximately 40% of vehicles equipped with advanced warning systems were found to have positive effects, indicating that the frequencies of both FCW and LDW had been continuously decreasing after installation of the system. CONCLUSIONS : The warning device might be helpful for making drivers’driving behaviors safer. Driving behaviors during the initial stage of the system installation, which might be regarded as an adaptation phase, were found to be very unstable compared with normal situations, indicating that adequate education and training should be provided to all the drivers to prevent operator disruption at the initial installation of the system.

The Manchester Driver Behavior Questionnaire (DBQ) is the most commonly used frameworks for investigating the relationship between self-reported driving behavior and accident involvement. After Reason et al. introduced DBQ, there were many studies replicating the research of Reason et al. in many countries. There was, however, no study replication of the Reason's research in Korea. The aim of this study is to replicate the distinction among errors, lapses and violations, and to evaluate the relationship of these behaviors with road traffic accidents on Korean drivers. 223 Korean drivers completed the Korean version of original DBQ with questions regarding background information, such as age, gender, annual mileage and accident involvement. Participants answered self-assessment questions, also. Factor analysis revealed three factors like Reason et al. The three factors were dangerous errors, violations and relatively harmless errors.