A comparative analysis of perceptions of insecurity in Milan and Beijing metro stations

Metro stations, as essential public spaces, not only serve as vital transportation hubs but also form part of the broader built environment that shapes people's perceptions of insecurity. An important concern for passengers in these environments is safety, particularly in underground public spa...

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Main Authors: Jiaxin Liu, Hongming Yan, Marcus White, Xiaoran Huang
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2025-08-01
Series:Frontiers of Architectural Research
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Online Access:http://www.sciencedirect.com/science/article/pii/S2095263524001870
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author Jiaxin Liu
Hongming Yan
Marcus White
Xiaoran Huang
author_facet Jiaxin Liu
Hongming Yan
Marcus White
Xiaoran Huang
author_sort Jiaxin Liu
collection DOAJ
description Metro stations, as essential public spaces, not only serve as vital transportation hubs but also form part of the broader built environment that shapes people's perceptions of insecurity. An important concern for passengers in these environments is safety, particularly in underground public space where the design and organization of the physical surroundings play a crucial role. Despite various modern renovations in older metro stations, newer stations are generally perceived as safer. To understand this discrepancy, this research compares how visual factors in the built environments of old and new metro stations influence people's perceptions of insecurity. By examining two cities—Milan and Beijing, which follow distinct urban development models—this research also explores how differences in urbanization processes affect the contrast between old and new stations. This research introduces a novel methodology for analyzing underground public space by integrating 360-degree image capture, an enhanced semantic segmentation process, and predictive modeling using XGBoost and SHAP to reveal the complex relationships between these visual factors and safety perceptions. The results indicate that while factors like artificial light, floor, and the presence of people are significant across all stations, certain factors are particularly influential in specific contexts—for example, exposed pipes are more negatively associated with safety perception in Beijing's old stations, and platform doors have a strongly positive effect in Milan's new stations. The findings provide valuable insights for guiding the modernization of metro stations in the future, and offering an innovative approach to studying underground public space.
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spelling doaj-art-3fb2b0d3e58d45d0b82e12966815699a2025-08-20T02:57:46ZengKeAi Communications Co., Ltd.Frontiers of Architectural Research2095-26352025-08-0114486388410.1016/j.foar.2024.12.003A comparative analysis of perceptions of insecurity in Milan and Beijing metro stationsJiaxin Liu0Hongming Yan1Marcus White2Xiaoran Huang3School of Architecture and Art, North China University of Technology, Beijing 100144, China; School of Architecture, Urban Planning & Construction Engineering, Politecnico di Milano, Milano, ItalyFaculty of Design, Architecture and Building, University of Technology Sydney, Sydney, AustraliaCentre for Design Innovation, Swinburne University of Technology, Hawthorn, VIC 3122, AustraliaSchool of Architecture and Art, North China University of Technology, Beijing 100144, China; Corresponding author.Metro stations, as essential public spaces, not only serve as vital transportation hubs but also form part of the broader built environment that shapes people's perceptions of insecurity. An important concern for passengers in these environments is safety, particularly in underground public space where the design and organization of the physical surroundings play a crucial role. Despite various modern renovations in older metro stations, newer stations are generally perceived as safer. To understand this discrepancy, this research compares how visual factors in the built environments of old and new metro stations influence people's perceptions of insecurity. By examining two cities—Milan and Beijing, which follow distinct urban development models—this research also explores how differences in urbanization processes affect the contrast between old and new stations. This research introduces a novel methodology for analyzing underground public space by integrating 360-degree image capture, an enhanced semantic segmentation process, and predictive modeling using XGBoost and SHAP to reveal the complex relationships between these visual factors and safety perceptions. The results indicate that while factors like artificial light, floor, and the presence of people are significant across all stations, certain factors are particularly influential in specific contexts—for example, exposed pipes are more negatively associated with safety perception in Beijing's old stations, and platform doors have a strongly positive effect in Milan's new stations. The findings provide valuable insights for guiding the modernization of metro stations in the future, and offering an innovative approach to studying underground public space.http://www.sciencedirect.com/science/article/pii/S2095263524001870Metro stationUnderground public spacePerceptions of insecurityVisual factorsMachine learning modelsXGBoost
spellingShingle Jiaxin Liu
Hongming Yan
Marcus White
Xiaoran Huang
A comparative analysis of perceptions of insecurity in Milan and Beijing metro stations
Frontiers of Architectural Research
Metro station
Underground public space
Perceptions of insecurity
Visual factors
Machine learning models
XGBoost
title A comparative analysis of perceptions of insecurity in Milan and Beijing metro stations
title_full A comparative analysis of perceptions of insecurity in Milan and Beijing metro stations
title_fullStr A comparative analysis of perceptions of insecurity in Milan and Beijing metro stations
title_full_unstemmed A comparative analysis of perceptions of insecurity in Milan and Beijing metro stations
title_short A comparative analysis of perceptions of insecurity in Milan and Beijing metro stations
title_sort comparative analysis of perceptions of insecurity in milan and beijing metro stations
topic Metro station
Underground public space
Perceptions of insecurity
Visual factors
Machine learning models
XGBoost
url http://www.sciencedirect.com/science/article/pii/S2095263524001870
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