A personalized and emotion based virtual simulation model for pedestrian‐vehicle collision avoidance

Abstract

Since the differences of individual pedestrians and the diversity of pedestrian-vehicle avoidance behaviors in real life, it is important to consider the behavioral heterogeneity of pedestrians and vehicles in simulation. Most existing simulation models cannot generate personalized pedestrian-vehicle avoidance scenarios. Taking personality and emotional factors into account, we proposed a simulation method to realize various pedestrian-vehicle collision avoidance scenarios by adjusting the parameter of personality trait. In this study, drivers' yielding strategies were classified as careful and aggressive based on their different personality traits. For pedestrians, in addition to personality traits, emotional factors were also introduced to achieve more realistic speed control. The experimental results showed that the proposed method could generate personalized pedestrian-vehicle collision avoidance scenarios in multiple traffic scenarios.