建筑火灾中基于人群行为特征的智能疏散诱导

提出人员逃生从众度、疏散路径选择度等基本概念，通过建立“黑屋”实验平台，用多组人群进行多次疏散实验，研究人群疏散行为参数对疏散时间的影响。把建筑结构参数、火灾中的烟气、温度等参变量通过数据融合处理形成统一的知识表征。用人群密度、人员逃生从众度、疏散路径选择度等参数来表征火灾中人群的行为特征。首次构建智能疏散诱导的机理模型，形成基于人群特征的智能疏散诱导系统。通过智能疏散诱导系统对疏散指示灯的PWM控制，实现疏散路径的动态调整与优化，给出人群疏散的动态标识路径。实验结果表明该系统能够缩短疏散时间，提高疏散效率。

Intelligent Evacuation Guidance System Based on Behavior Characteristics of Crowds in Building Fire Hazards

Basic conceptions such as personnel escape conformity and evacuation route selectivity are proposed. A “Dark House” experimental platform is established and multiple groups of crowds are organized to carry out several evacuation experiments and to study the impact of evacuation parameters of people on the evacuation time. Structural parameters, as well as smoke and temperature parameters in the fire, are integrated via data integration to form a uniform knowledge representation. The parameters such as the crowd density, the personnel escape conformity and the evacuation route selectivity are configured to represent the behavior characteristics of the crowds in fire. A mechanism model for intelligent evacuation guidance is initially established to form an intelligent evacuation guidance system based on behavior characteristics of crowds. In presence of the PWM control on evacuation indicators by the intelligent evacuation guidance system, dynamic regulation and optimization for the evacuation route are realized, and a dynamically identified evacuation route is provided for the crowds. Experimental results show that the system can shorten the evacuation time and increase the evacuation efficiency.