A grouping approach based on non‐uniform binary grid partitioning for crowd evacuation simulation

Abstract

Summary Small social groups based on kinship or friendships are ubiquitous in human crowds. Therefore, the effect of social groups on crowd evacuations and that of crowd evacuations on social groups must be investigated. To simulate the group phenomenon when an emergency occurs, we propose an improved social force model that takes into account the social group relationship among the population, and based on our proposed model, a novel grouping algorithm predicated on non‐uniform binary grid partitioning is put forward. The approach initially maps the individuals into the plane space, and then it adopts top‐down binary grid partitioning iteratively until the divided grid contains only the individuals with relations; then, the values of the relation and density of the non‐empty grid cells are calculated, and the grids are sorted according to these values. After sorting, selecting, merging, and forming the core grids, the other grids are merged to the core grids. We have compared the algorithm with the hierarchical classification algorithm and the grid‐based algorithm. The results show that the accuracy, speed, and scalability are all advantages. We also establish a simulation platform to illustrate the proposed grouping algorithm and the improved social force model for crowd evacuation simulation.

Special issue: 2016 International Conference on Information Technology in Medicine and Education (ITME2016)

“…The work of Liu et al proposes an improved social force model that takes into account the social group relationship among the population, and based on the proposed model, a novel grouping algorithm predicated on non‐uniform binary grid partitioning is put forward. The results show that the accuracy, speed, and scalability are all advantages.…”