Abstract

As large passenger flow commonly arises in metropolitan metro stations during peak hours, most of bottleneck congestion appears in the entrance halls of metro stations. Previous research work on mitigating metro congestion mostly focus on optimizing single facility and lack a comprehensive analysis on how congestion arises. We propose a system dynamics based framework for optimizing the aisle length and mitigating bottleneck congestion in the entrance halls. We first define the key bottleneck region (KBR) of metro stations consisting of security check area, automatic fare gate area, and the area between them. Then we propose a system dynamics model for simulating passenger flows in KBR by determining the boundary and using a causal analysis of a KBR system. Finally we conduct a case study on the optimization of aisle length, based on the field observation data from three metro stations of Beijing, China. The results reveal that the minimum aisle length of commuter metro stations for acceptable system’s passing efficiency is 6m, and suggest the optimized aisle length for three different commuter metro stations. Our study provides a feasible and effective approach to alleviate passenger flow bottleneck without changing the number of facilities, and can improve the efficiency of metro stations effectively.

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