Perceptions of Women’s Safety in Transient Environments and the Potential Role of AI in Enhancing Safety: An Inclusive Mobility Study in India

Guilhermina Torrao (), Amal Htait and Shun Ha Sylvia Wong
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Guilhermina Torrao: College of Engineering and Physical Sciences, Aston University, Birmingham B4 7E, UK
Amal Htait: College of Engineering and Physical Sciences, Aston University, Birmingham B4 7E, UK
Shun Ha Sylvia Wong: College of Engineering and Physical Sciences, Aston University, Birmingham B4 7E, UK

Sustainability, 2024, vol. 16, issue 19, 1-23

Abstract: Travel safety for women is a concern, particularly in India, where gender-based violence and harassment are significant issues. This study examines how the perception of safety influences women’s travel behaviour and assesses the potential of technology solutions to ensure their safety. Additionally, it explores how AI and machine learning techniques may be leveraged to enhance women’s travel safety. A comprehensive mobility survey was designed to uncover the complex relationship between travel behaviour, reasons for mode choice, built environment, feelings, future mobility, and technological solutions. The responses revealed that security and safety are the most critical factors affecting women’s travel mode choices, with 54% and 41%, respectively. Moreover, over 80% of women indicated a willingness to change their travel behaviour after experiencing fear, anxiety, or danger during their everyday journeys. Participants were 24% less willing to use ride-sharing services than ride-hailing services, which could affect the transition towards more sustainable transportation options. Furthermore, AI-based sentiment analysis revealed that 46% of the respondents exhibited signs of ‘anger’ regarding what could help women feel safer in transient environments. The practical implications of this study’s findings are discussed, highlighting the potential of AI to enhance travel safety and optimise future sustainable transport planning.

Keywords: AI; future mobility; safety; sentiment analysis; sustainability; technology solutions; transient environments; travel behaviour; women (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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