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| The Guided Crowd Evacuation Based on Gaussian Mixture Model |
| LIU Tianyu1, YANG Xiaoxia2, ZHANG Jihui1, ZHAO Yiqun1, ZHOU Meiqi1
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1. Institute of Complexity Science, College of Automation, Qingdao University, Qingdao 266071, China;
2. School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266525, China |
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Abstract In this paper, the guided crowd evacuation dynamics model based on cellular automata is proposed, this model combines Gaussian mixture methodand fuzzy logic theory to study the influence of guides on pedestrian evacuation behaviors. Bayesian Information Criterion (BIC)determines the optimal number of guides and EM algorithmdetermines the optimal positions of the guides. The cellular automata model is used as the driven model of pedestrian motion, and fuzzy logic theory is adopted to simulate the pedestrians' selection behaviors for the guides. The influences of guide quantity, guide speed and exit width on the evacuation are explored, and it is concluded that the guides can improve the evacuation efficiency to a certain extent. However, the number of guides is not the more the better. Increasing the width of the exit within a certain range can increase the capacity of the exit and effectively reduce the evacuation time. When the speed of the guide is 75% of the pedestrian speed, the evacuation efficiency could be the highest. The model in this paper combines the advantages of small computation of cellular automata model and high clustering accuracy of Gaussian mixture model, which provides a new idea for pedestrian dynamics modeling and puts forward effective suggestions for pedestrian evacuation behaviors.
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Received: 01 June 2020
Published: 23 September 2020
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