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The Journal of The Korea Institute of Intelligent Transport Systems Vol.24 No.5 pp.1-51
고령 화물차 운전자의 고속도로 사고 주요 위험요인 분석 : 베이지안 다수준 혼합효과 로짓모형의 적용
Identifying Key Risk Factors for Elderly Truck Drivers’ Accidents on Highways Using Bayesian Multilevel Mixed-Effect Logit Model
Abstract
This study applied a Bayesian Multilevel Mixed-Effect Logit Model to quantitatively analyze the risk factors influencing highway accidents involving elderly truck drivers. Unlike previous studies that primarily focused on elderly passenger car drivers, this research investigates the accident risk factors affecting elderly professional truck drivers. The analysis revealed that elderly truck drivers exhibited a higher likelihood of accidents in toll gate areas due to deceleration and acceleration, fatigue, and drowsiness. In contrast, they showed a lower accident risk on mainline highways, during nighttime driving, and in high-speed conditions. Additionally, the heterogeneity among highway routes significantly influenced accident probability, and the Bayesian multilevel model demonstrated superior predictive accuracy compared to traditional logit models. This study provides insights into the accident mechanisms of elderly professional drivers and highlights the necessity of customized traffic safety measures considering road environments and driver conditions. Future research should integrate vehicle dynamics and physiological and psychological factors to enhance accident prediction and prevention strategies.
