Modeling Pedestrian Group Behavior in Crowd Evacuations

In the process of evacuation, individuals will group according to the close relationship, so grouping behavior is a factor that cannot be ignored in crowd evacuation simulation. At present, the method for crowd simulation is considered grouping only based on distance, without considering the relationship between individuals. Because of the above shortcomings, this paper considers the influence of location similarity, velocity similarity, and motion direction similarity on evacuation, and proposes an improved K-Medoids algorithm, which considers three different eigenvalues. After the crowd is clustered, the intra-group attraction is added to improve the social force model. In order to verify the effectiveness of the proposed method, multiple sets of experiments are designed. The results illustrate that the proposed method can improve evacuation efficiency. It is more in line with the crowd evacuation behavior in the real environment.