Crowd Management Through Optimal Layout of Fences: An Ant Colony Approach Based on Crowd Simulation

The increasing population density in public places necessitates urgent attention to address safety concerns via effective crowd management. In many congested scenarios such as peak-hour subway stations, the utilization of fences to guide crowd movement has become a widely adopted approach to alleviate congestion. This work presents a method that combines crowd simulation and management, focusing on the optimization of the fence layout for efficient crowd guidance. First, a congestion probability social force model (CP-SFM) is introduced to simulate the irrational pedestrians and to evaluate the efficacy of different fence layouts. Second, based on CP-SFM, we are the first to formulate the fence layout problem as an optimization problem with the objective to minimize the congestion of pedestrians in public places. Third, we further propose an ant colony crowd intervention algorithm (ACCI) to optimize the layout of fences. Lastly, we illustrate the performance of proposed ACCI on 18 scenarios including two real-world subway stations. Compared with other optimization methods, ACCI demonstrates promising performance in avoiding crowd congestion.