An Improved Potential Field Based Method For Crowd Simulation

Crowd simulation explores crowd behavior in virtual environments, which has been extensively studied in many areas, such as safety and civil engineering, transportation, social science, and entertainment industry. In this paper, an improved potential field method is proposed to achieve the real-time crowd simulation, which is composed of the global navigation with Dijkstra's algorithm and the potential field based local navigation. First, a region separation is performed to divide the environment into a set of triangles, and thus a topological graph can be built with the triangles as vertices. Then a velocity-density model is introduced for improving the speed controlling mechanism and solving the "maximum speed dilemma" which means the velocity of an individual derived by potential field will be stuck into the maximum due to the ill speed control. Since the movement of an individual in the crowd is influenced by the socio-psychological forces, the individuals' actions express the group attributes. In order to represent the group attributes in the crowd, the repulsive potential function is improved in this paper. Experiments have been carried out and the results show that the improved potential field based method can simulate the crowd in real time and avoid the "maximum speed dilemma".