A personalized traffic simulation integrating emotion using a driving simulator

Since driver’s behavior is affected by driving environment and driver’s individual characteristics, it is important to understand driver’s behavior from these viewpoints. We present a novel driver’s behavior simulation that considers both the stable personality of individuals and the changes in driving behavior when the environment changed. In this study, driving styles are classified as aggressive, careful, and anxious. The driving styles are analyzed from the perspectives of personality traits and emotion, and the driving parameters of each driving style are learned through simulator experiments. Given individual personality, traffic conditions, and driving environment as input, our approach can generate traffic flow that reflects driver’s personalized driving behavior.