A study on the correlation between MBTI dimensions and driving behavior characteristics

With the rapid global increase in motor vehicle usage, road traffic injuries have emerged as the leading cause of injury-related deaths worldwide. Within the complex traffic system, although factors such as vehicle performance and road conditions significantly influence driving safety, the driver's personality traits remain a critical determinant of traffic accidents. Consequently, exploring the intricate relationship between driving behavior patterns and personality traits is essential for understanding the underlying causes of traffic injuries and developing effective intervention strategies. Grounded in the theoretical framework of the Myers-Briggs Type Indicator (MBTI), this study systematically examines the interaction between personality traits and driving behavior. Through an empirical analysis of driving behavior data, this research makes several notable contributions. First, it introduces the "Six Driving Behavioral Facets," a multidimensional framework for analyzing the relationship between personality traits and driving behavior. Second, the study employs the "inverse chi-square test" to uncover latent patterns in otherwise non-significant results. Using the K-modes clustering algorithm, this study identified significant imbalances in the distribution of MBTI personality dimensions across eight clusters, particularly in the Thinking-Feeling (T-F) dimension. For example, in Cluster 1, Thinking (T) individuals accounted for 10.84% of the total population, compared to 15.09% for Feeling (F) individuals, while in Cluster 5, T individuals represented 17.48%, compared to 10.53% for F individuals. Such pronounced differences in personality distributions across clusters highlight the relevance of MBTI traits in shaping driving behavior patterns. These findings provide theoretical support for personalized traffic management strategies and the optimization of autonomous driving systems.