Abstract
When there are too many people in large shopping malls, crowd congestion accidents are likely to occur. To ensure the rapid and safe evacuation of indoor crowds, this paper uses crowd density maps to determine the location of crowded areas and uses an improved ant colony algorithm to optimize the evacuation route from this location to the exit. First, a crowd density map is generated from the collected image data by the improved multiscale convolutional neural network algorithm, and the location of the high-density crowd is determined as the initial location. Then, the pheromone volatility coefficient $\rho $ is measured through adaptive adjustment by using the exponential decline method and the introduction of elite ants to optimize and update the ant colony pheromone to improve the ant colony algorithm, and the optimal evacuation route from the location of the crowded area to the exit is obtained. The research in this paper uses Beijing Xidan Joy City as an example. The results show that the method in this paper can optimize evacuation routes and reduce the turning points of the evacuation route by 25% and reduce the route length by 10%. Therefore, it can be seen that the proposed method can achieve the optimal evacuation path with the shortest distance and the least turning points, which has feasibility and practicability.
Highlights
In recent years, with the acceleration of the urbanization process, the population of cities has grown rapidly, and various activities in public places have increased
The processed data are processed by an improved multiscale convolutional neural network algorithm, which replaces the whole network layer with a full convolutional layer, so the crowd density map of the area is obtained
To optimize the defects of the ant colony algorithm, this paper proposes an improved evacuation route determination method based on an improved ant colony algorithm
Summary
With the acceleration of the urbanization process, the population of cities has grown rapidly, and various activities in public places have increased. These places have the characteristics of high mobility and a high concentration of people. If there are uncertain emergencies in public places during an event, such as people falling down and fires, it causes crowds congestion in the rapid evacuation process. The design of optimal evacuation route in public places includes two problems. The first is to determine the location of high-density crowds. The other is to design safe evacuation routes for high-density crowds
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