A paper titled Investigating the impact of in-vehicle warning information complexity on drivers: The role of working memory capacity and cognitive load authored by Kunchen Li, Wei Yuan, George Yannis, Fuwei Wu and Chang Wang has been published in Accident Analysis & Prevention. This Paper investigates the impact of the complexity of the warning messages on the behavior and physiological states of the driver, taking into account individual differences in working memory capacity and cognitive load levels. A total of 37 participants were recruited to conduct a mixed design driving simulation experiment, with working memory capacity treated as a between-subjects factor. The analysis included correlation as well as a Generalized Linear Mixed-effects Model (GLMM). The findings suggest that visually rich warnings lead to increased braking reaction times, especially between drivers having low working memory capacity and under high cognitive load. These findings offer theoretical insights to assist manufacturers in designing human-centered, personalized, and adaptive in-vehicle warning systems.