Modelling the Selection of Waiting Areas on Subway Platforms Based on the Bacterial Chemotaxis Algorithm

Abstract

Based on the bacterial chemotaxis algorithm, a new waiting-area selection model (WASM) is proposed that predicts well the pedestrian distribution in subway waiting areas. WASM regards passengers waiting on a subway platform as two-dimensional points and adopts an essential rejection factor to determine the target waiting area. Based on WASM, three experiments were carried out to explore how passenger volume, waiting-area capacity, and staircase position affect the number and distribution of waiting passengers. The experimental results show the following. 1) Regardless of the passenger flow, passengers prefer waiting areas that are between the stairs. 2) Setting proper capacity limits on waiting areas can help to improve subway transportation efficiency when passenger flow is relatively high. 3) The experimental results show that the closer the staircases, the more passengers are left stranded on the platform

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