An Evolutionary Guardrail Layout Design Framework for Crowd Control in Subway Stations

Abstract

Deploying guardrails near elevator entrances is an effective way to alleviate congestion and improve the flow rate in subway stations. How to properly design the guardrail layout is a complex black-box optimization problem. Existing methods are mainly based on manual design, which are highly dependent on the empirical experience of the designers and may not get satisfactory results in complicated scenarios. To address the above issues, this article proposes an evolutionary framework to automatically optimize guardrail layouts in subway stations. In the proposed framework, a novel guardrail layout encoding method is proposed, which can facilitate the algorithm to generate regular guardrail layout design solutions. Furthermore, a new fitness evaluation function is proposed to effectively measure the quality of a given guardrail layout design strategy. To validate its effectiveness, the proposed framework is applied to two scenarios with different characteristics. Simulation results have demonstrated that the proposed framework can provide promising guardrail layout designs, which can alleviate the congestion of subway stations effectively.