Optimal Control of Pedestrian Flows by Congestion Forecasts Satisfying User Equilibrium Conditions

Reducing congestion is one of the most important issues in theme park management. Optimization algorithms for reducing congestion in theme parks using simulation optimization methods have been proposed. In many existing methods, theme park managers directly regulate the movement of visitors. However, restricting the freedom to wander considerably reduces the visitor satisfaction. Thus, when controlling congestion in theme parks, we must consider the trade-off between reducing congestion and restricting freedom. In this paper, we propose an indirect control method for pedestrian flows using congestion forecasts and information distribution. Specifically, we propose a simulation-based heuristic algorithm for the problem of finding an optimal information distribution policy for congestion forecasts satisfying user equilibrium conditions.