PURPOSES : The primary purpose of this study is to establish a crash probability model based on a statistical method that explains the relationship between regressor and explanatory variables using both fixed and random effects to control the heterogeneous characteristics of the observed data. In addition, an attempt was made to discover the leading cause of crashes by vehicle type, including passenger car, bus, truck, and trailer.
METHODS : The levels of each route and day of the week are grouped using raw expressway crash data for 10 years from 2012 to 2021, and a multilevel mixed-effect logit model is constructed for each vehicle type assuming that the error terms are derived from the hierarchical structure of the group to which they belong.
RESULTS : Speeding and obstacles on the road are significant factors that increase the probability of passenger car crashes, and bus crashes have a high rate at toll gates on weekdays.
CONCLUSIONS : The multilevel mixed-effect logit model derived in the study has higher accuracy than the general logit model, confirming that mixed-effect analysis is plausible.
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.
유류를 포함한 HNS의 물동량이 증가 추세에 있음에도 불구하고, 우리나라에서는 HNS 해상운송 중에 발생한 사고의 분석과 위험에 관한 연구가 미진하다. HNS는 형태와 종류가 다양하고 사고발생시 피해가 심각하게 나타난다. 액체화물운반선(유조선, 케미컬탱커선, 액화가스탱커선 등)의 사고에 대한 원인을 분석하고 위험성에 대한 연구가 필요하다.
최근 우리나라 연안해역은 선박교통량의 증가로 인해 해상교통이 폭주하고 있다. 이러한 교통폭주는 연안해역에 대해 인명, 재산, 환경오염 등의 심각한 해양사고를 야기할 수 있다. 본 연구에서는 우리나라 연안의 해양사고를 확률적으로 분석한다. 본 연구의 수행을 위해 해상교통량과 기상조건, 해양사고 등의 다양한 연관성을 기반으로 원인을 분석하였다. 그리고 해양사고의 형태를 선박의 크기, 선령, 선종 등 다양한 관점에서 분류하고 세부적으로 분석하였다.