中文摘要：

用马尔可夫链模型研究非可视环境下的行人逃生路径。运用马尔可夫链转移概率矩阵和附带随机数的运算法则，结合空间网格的应用，得出有限非可视空间中步行者的逃生轨迹。用6个步法状态（停滞、爬行、步行、跳跃、慢跑、奔跑）来描述行人的行进特性，并用8个方向的选择来描述行人状态转移过程，同时从步态和方向两个视角来分析行人逃生路径的特点。研究表明，对行人逃生路径的研究手段而言，马尔克夫链模型更符合实际。

英文摘要：

This paper is aimed to introduce its authors＇ research on the escaping route for the pedestrians in the pitch dark conditions in an accident based on the Markov chain probability transition matrix. The so-called Markov chain probability transition matrix is by nature an algorithm with random-chosen number and the spatial-grid, by which an escaping route can be found from the initial position to the exit in a limited invisible space. It is a primary experimental study for us to use the chain for such a purpose. As is known, according to Markov chain model, the escaping manners can be divided into six ones, namely, standing, crawling, walking, leaping, jogging, and running. The applications of the model can be used in a case study of the escaping manners while defining the difference between this model and the biased random walking model. From the study on such differences, we can find two advantages in this model： （1） using the Markov chain cumulative probability and random number in describing the pedestrian escaping manners so as to define the 8 directions on studying the evacuation pattern, and （2） for setting up the 6 pedestrian escaping manners. Then, the 6 pace manners can be adopted to define the characteristics of pedestrian behaviors while the eight main direction changes are used to describe the transition characteristic of a pedestrian. At the same time, this paper has made an analysis of the escaping route from the two spots of view, i.e. the pedestrians＇ escaping manners and their escaping directions. In addition, the paper has also demonstrated the pedestrian direction changes. The results of our experiments show that Markov chain model is more realistic as a means of studying the pedestrian escaping route.