关键词: 地铁车站, 改造阶段, 行人仿真评估, 仿真优化

Abstract: To address the engineering challenge of complex large passenger flows and the difficulty in precisely coupling and optimizing design schemes during the transformation of urban rail transit stations from single-track stations to multi-track transfer stations, a micro-pedestrian simulation and evaluation method suitable for the station renovation stage is proposed. The core innovation of this method lies in the construction of a systematic closed-loop analysis process of “Data input-simulation modeling-assessment-feedback optimization” based on the Legion simulation platform. By integrating building information models, passenger flow prediction data, and pedestrian behavior parameters, a high-precision three-dimensional simulation environment for the station is established to achieve quantitative analysis of the adaptability between the station renovation plan and the dynamic passenger flow status. Theses enable identification of passenger flow congestion points, thus supporting the refined design of station plans and operational decisions. The model was applied in a case study on the renovation of a metro station in south China, and the results show the following: (1) The transfer passage of Lines Ⅰ and Ⅱ is the main congestion bottleneck of the station due to interweaving of flow lines, and the peak passenger flow density reaches 1.3 per m². (2) An optimization suggestion of adding physical isolation is proposed. After the optimization, the maximum density of simulated passenger flow at the station is reduced by 23%, effectively alleviating congestion. The case study successfully verified the effectiveness of the proposed micro-pedestrian simulation assessment method. It can proactively predict risks during the station renovation stage and provide quantitative decision support for scheme design and optimization, thereby offering a scalable auxiliary analysis tool for similar station renovation projects.

Key words: metro station, renovation stage, pedestrian simulation assessment, simulation optimization