Grounded theory-based analysis of factors influencing driving behavior.

Objective: This study aims to systematically explore the factors influencing driving behavior by analyzing the dynamic interactions among individual characteristics, external environmental conditions, and social influences, ultimately uncovering the complex relationships and coupling mechanisms behind these factors to support the development of intelligent driving systems and the optimization of traffic policies.

Methods: The research employed grounded theory as a qualitative analytical approach, combining in-depth interviews and simulated driving experiments with 28 participants. A three-level coding process integrated with the SOR (Stimulus-Organism-Response) framework was utilized to dissect the interplay between drivers' internal states, environmental stimuli, and behavioral responses.

Results: The findings revealed that driving experience, physiological conditions, and safety awareness directly shape decision-making processes, while environmental factors such as complex traffic scenarios and adverse weather conditions dynamically prompt drivers to adjust their strategies. Social norms were observed to exert indirect behavioral effects through situational interactions, and a significant positive correlation emerged between individual factors and environmental stimuli. Notably, the study highlighted complex relationships between drivers' experiential knowledge and their adaptability to real-time scenarios.

Conclusions: This research underscores the complexity of driving behavior as a product of dynamically coupled individual, environmental, and social factors. By emphasizing the interdependence of human experience and situational adaptation, the outcomes provide a theoretical foundation for designing human-centric intelligent driving technologies and formulating traffic management policies that account for multidimensional behavioral influences.