Abstract

Studies on the age and generation characteristics of traffic accidents primarily focus on the tendency of deaths and severe injuries, whereas the faults or drivers who caused the accidents are not considered. Using license holders as a parameter for measuring accident risk when evaluating the number of primary-party accidents is challenging because it includes those who possess licenses but do not drive. In previous studies, the age characteristics in traffic accidents were evaluated based on different age groups and generational characteristics. Therefore, a Bayesian age–period–cohort analysis was performed in this study to isolate the effects of age, period, and generation on the number of traffic crashes. This approach can identify the gender/age of the driver, who may be the primary contributor to an accident, as well as the risk of traffic accidents in younger and older drivers. The results show that 1) age imposes a more significant effect than the duration and cohort. In the case of single-vehicle accidents, 2) the effect of age was significantly more prominent for males over 80 years old and females over 70 years old.

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