一种基于空间划分的人群仿真混合模型

A Space-Division Based Hybrid Model for Crowd Simulation

为了在同一个模型中同时利用宏观模型和微观模型的优点并应用于人群仿真中,开展了基于混合模型的建模方法研究,提出了一种基于空间划分的人群仿真混合模型、该模型通过将仿真环境划分为互斥、完备的仿真空间,在其上分别采用微观或宏观模型,并通过模型间交互机制使得两种模型生成的仿真结果能互为输入,以保证人群从一个仿真空间向与其相邻的仿真空间迁移时人群信息的一致性。实验结果表明,该仿真模型能够有效克服微观模型适应性不强的弱点,并具有仿真效率高的特点。这种基于空间划分的人群仿真混合模型能够有效克服宏观模型的仿真结果的准确性,同时高效的仿真效率使得模型能够适用于对大规模人群的实时仿真。

Macroscopic and microscopic models are the two main modelling methods for crowd simulation.Whereas macroscopic is able to hold an efficient model execution but course-grain simulation results,fine-grain simulation results can be generated by microscopic model with the cost of low model execution efficiency.In addition,macroscopic model cannot be applied to diverse simulation environments.In order to take the advantages of both microscopic and macroscopic model,a space-division based hybrid model for crowd simulation is proposed for crowd simulation.Through dividing simulation environment into exclusive and complete subspaces,microscopic/macroscopic model were applied into each subspace.Hence different types of simulation models can be co-existed and executed simultaneously in the proposed model.Simulation results indicate that the proposed model is able to generate a fine grain simulation result and can be applied to incompatible simulation environment for macroscopic model.In the meanwhile,the proposed method also hold higher simulation efficiency compared with microscopic model.The proposed space-division based hybrid model can not only improve the simulation result accuracy,but also ensure the model can be applied into real-time simulation process of crowd simulation.