Interactive Relationship Between Light Environment and Crowd Flow in Metro Station Concourses

Abstract

This study takes Chongqing Nanping Metro Station as the research object, focusing on the collaborative optimization of light environment and crowd flow in metro station concourses. It aims to reveal the two-way coupling interaction mechanism between light environment and crowd flow, solve the mismatch between traditional static lighting design and the spatiotemporal heterogeneity of dynamic passenger flow, and achieve the dual goals of improving light environment quality and optimizing crowd flow efficiency. By integrating high-precision spectral measurement, AI video analysis, physiological signal monitoring and multi-agent simulation technology, a coupling database containing 2400 light environment parameters and 2600 dynamic passenger flow data is constructed. Random forest algorithm is used to identify illuminance, lighting uniformity and color temperature as key influencing factors. A quantitative model relating these factors to passenger flow speed, dwell time and path deviation rate is established based on partial least squares regression. The social force model is innovatively improved by introducing a visual perception correction coefficient, and a multi-agent coupling model is developed for verification. The results show that the optimal parameter combination is illuminance of 150–250 lx, color temperature of 4000–4500 K, and uniformity U₀ ≥ 0.6, which can achieve a passenger comfort score of 4.1, a 15% increase in crowd flow speed, and a 25% reduction in lighting energy consumption. This study reveals the quantitative relationship between the two, providing important theoretical and methodological support for the refined design of metro spaces.