Deep Learning Improved Social Force Model to Simulate Crowd in Varying Scenes

Traditional social force models are capable of simulating various types of crowds, but due to their reliance on a single formula and simplified parameter control, they often lack realism when applied to crowd scenes. The integration of deep learning with social force models has already achieved success in pedestrian simulation tasks in specific scenarios, yet research in more generalized scenes is still lacking. Therefore, we have used deep learning in conjunction with social force models to construct crowd simulations in various scenarios. This model is based on the dynamics of crowd trajectories and refines key parameters of the social force model using deep learning methods. Experimental results prove that this model can effectively adapt to diverse environments different from the scenes on which the training data is based.