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Study of Emergency Evacuation Model of Louvre Museum Based on A* Algorithm

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DOI: 10.23977/icmee.2019.2746


Xudong Cai

Corresponding Author

Xudong Cai


In this paper, we have built a complete model to provide the Louvre’s optimal crowd evacuation plan in most kinds of possible situations. Firstly, by analyzing the structure of the Louvre and the distribution of the exhibition halls, we refer to the principle of cellular automata to discretize the space of Louvre. Then we transform the 3D model into a 2D model and we use the Modified A* Algorithm to obtain the initial set of evacuation paths. The path self-learning algorithm and path self-optimization algorithm further optimize the evacuation path set. Finally, a gain evaluation algorithm evaluates the entire evacuation paths set, and obtain the optimal evacuation paths set.


Crowd evacuation plan, cellular automata, Modified A* algorithm, path self-learning algorithm

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