Che He
ABSTRACT
This paper presents the Macro Bi-level Optimal Transport model (MBOT model) based on optimal transport theory applied to large aggregated places for crowd evacuation. Optimal transport theory bridges geometry and probability, providing a new way to model probability distributions and measure the distance between probability distributions using a geometric approach. Our approach treats the evacuated population as a set of discrete particles with probability distributions while abstracting the evacuation space into a simple geometric structure, establishing the corresponding mathematical model, and using optimal transport theory to determine the optimal evacuation plan for these particles from the initial location to a specified safe area. We introduce an evacuation cost that maximizes evacuation efficiency by optimizing that cost in two levels. We apply the proposed model to a subway station, compare our plan with the randomized evacuation plans and study the effects of evacuation crowd density, distribution and number of exits on evacuation time. The results show that our model converges to an optimal evacuation solution within an acceptable number of iterations, which can significantly improve evacuation efficiency and reduce potential risks in emergencies. The results of this paper can provide a scientific basis for planning and implementing evacuation plans for large venues and promote scientific and standardized safety management in emergencies.
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Index Terms
- Crowd Evacuation Approach Based on Optimal Transport
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