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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。
Using Markov Chains to Study Pedestrian Escape Paths in Non - visual Environment. By using Markov chain transfer probability matrix and arithmetic with random numbers, the escape trajectory of pedestrians in finite non-visible space is obtained by using the application of space grid. Describe the characteristics of pedestrians in six steps (stagnation, crawling, walking, jumping, jogging, running) and describe the pedestrian transition with eight directions, and analyze the gait and direction from two perspectives Pedestrian escape path characteristics. The research shows that the Markov chain model is more realistic in terms of the means of pedestrian escape.