基于熵度量的人群模型评估方法

人群模型评估是虚拟人群仿真研究的关键问题,现有的研究多通过个体仿真轨迹与真实轨迹之间的误差来评估人群模型.然而人群行为本质上是复杂的随机系统,简单的轨迹对比并不能有效反映模型能力.本文应用熵度量的模型评估方法,通过估计真实人群状态与仿真人群状态的误差分布实现了精确的人群仿真定量评估.同时引入失真情况的判断和处理规则,使得评估方法在仿真失真情况下能够保持准确性.实验结果表明,本文提出的算法及规则能有效地实现人群仿真模型的定量评估并给出模型参数选择的指导.

Evaluation Method of Crowd Model Based on Entropy Metric

Crowd model evaluation is a key issue in virtual crowd simulation. Most studies use the error between the individual simulation trajectory and the real trajectory to evaluate the crowd model. However, crowd behavior is essentially a complex random system, and simple trajectory comparison cannot adequately reflect model capabilities. In this study, the model evaluation method based on entropy metric is used to achieve the accurate quantitative evaluation of crowd simulation by estimating the error distribution between the real crowd state and the simulated crowd state. In addition, the judgment and processing rules for distortion are introduced so that the evaluation method can be accurate under the simulated distortion. The experimental results show that the algorithm and rules proposed in this study can fully realize the quantitative evaluation of the crowd simulation model and provide guidance for the selection of model parameters.