Abstract
The environmental quality of rail transit spaces has increasingly attracted attention, as factors such as train noise and visual disturbances from elevated lines can impact pedestrians’ psychological perception through the audiovisual environment in these spaces. This study first collects audiovisual materials from rail transit spaces and pedestrian perception data through on-site surveys, measurements, VR environment simulations, and custom Deep Learning (DL) models. Using cluster analysis, the environments are categorized based on visual and auditory perceptions and evaluations of rail transit stations, delineating and classifying the spaces into different zones. The study further explores the interactive effects of audiovisual environmental factors on psychological perception within these zones. The results indicate that, based on audiovisual perception, the space within 300 m of a rail transit station can be divided into three zones and four distinct types of audiovisual perception spaces. The effect of the type of auditory environment on visual indicators was smaller than the effect of the visual environment on auditory indicators, and the category of vision had the greatest effect on the subjective indicators of hearing within Zones 1 and 2. This study not only provides a scientific basis for improving the environmental quality of rail transit station areas but also offers new perspectives and practical approaches for urban transportation planning and design.
| Original language | English |
|---|---|
| Article number | 1400 |
| Journal | Buildings |
| Volume | 15 |
| Issue number | 9 |
| DOIs | |
| State | Published - May 2025 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Keywords
- audiovisual environment
- soundscape
- transit spaces
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