Robust Design Optimization for Egressing Pedestrians in Unknown Environments
For evacuation planners, this provides a method to design robust layouts that improve egress efficiency despite uncertainty in crowd size.
This paper optimizes obstacle placement and shape to reduce pedestrian egress time in unknown environments, achieving robust performance against varying group sizes using Particle Swarm Optimization.
In this paper, we deal with a size-variable group of pedestrians moving in a unknown confined environment and searching for an exit. Pedestrian dynamics are simulated by means of a recently introduced microscopic (agent-based) model, characterized by an exploration phase and an egress phase. First, we study the model to reveal the role of its main parameters and its qualitative properties. Second, we tackle a robust optimization problem by means of the Particle Swarm Optimization method, aiming at reducing the time-to-target by adding in the walking area multiple obstacles optimally placed and shaped. Robustness is sought against the number of people in the group, which is an uncertain quantity described by a random variable with given probability density distribution.