基于非对称高斯函数的个人/群组动态舒适空间建模

Modeling of Personal/Group Dynamic Comfort Space Based on Asymmetric Gaussian Function

设计了一种基于非对称高斯函数的动态舒适空间模型.首先利用人的运动状态信息来确定不同速度下的个人舒适空间的形状.然后考虑到性别、年龄等个人社会属性特征的差异性,提出一个可扩展的模糊推理框架来定义个性化的舒适空间大小.在对单人的舒适空间建模的基础上,提出了共同关注区域的概念并通过最小覆盖圆算法对行人群组进行分析,构建群组的舒适空间.在实验部分对所提出动态舒适空间模型进行了定性与定量的分析与评价,验证了该模型的合理性.

A dynamic comfort space model based on asymmetric Gaussian function is designed.Firstly,the shapes of comfort spaces at different speeds are determined according to the motion state information of a human.Then a scalable fuzzy reasoning framework is proposed to define the size of personalized comfort space by considering the differences of individual social attributes such as gender and age.Based on the comfort space model of an individual person,the concept of common concern area is proposed,and the case of human group is analyzed through the minimum covering circle algorithm,so as to construct the comfort space for the group.Qualitative as well as quantitative experiments are carried out to analyze and evaluate the effectiveness of the proposed dynamic comfort space model,and the rationality of the model is verified.