A unified driving behavior model based on psychological safety space

Almost all traffic phenomena are influenced by driving behavior, making the understanding and description of driving behavior a key aspect of traffic research. Traditional driving behavior models, such as car-following and lane-changing models, are often confined to specific scenarios, thus limiting their applicability across diverse driving conditions. This study aims to analyze the underlying mechanisms of human drivers’ decision-making in diverse driving contexts and develop a unified driving behavior model suitable for a wide range of situations. By integrating situational awareness theory with personal space theory, the concept of Psychological Safety Space (PSS) is defined and its boundaries are quantified using risk field theory. A unified driving behavior model is then developed based on psychological safety space, incorporating a spatial trajectory planning algorithm and a speed regulation algorithm. The proposed model is evaluated against classical models, including the intelligent driver model, desired risk model, and desired safety margin model, as well as empirical data. The results demonstrate that the driving behavior model based on psychological safety space achieves high accuracy and effectiveness in scenarios such as car-following, lane-changing, and intersection navigation. This study offers new perspectives and methods for understanding and simulating driver behavior and contributes to the advancement of driving behavior model development.