| Abstract |
Accessibility for wheelchair-users is a major problem in Ireland, limiting independence and inclusion. This project assessed the wheelchair accessibility of various urban environments to examine how physical inaccessibility - including Whole-Body Vibration exposure from uneven surfaces - affects the wellbeing of wheelchair-users.
A survey measured the social, emotional, financial and physical impacts of inaccessibility on wheelchair-users’ lives. Also, real-world vibration data was collected using a wheelchair-mounted accelerometer. From this, I created a supervised Python Random Forest classifier, to extract statistical features and conduct a Fast Fourier Transform to distinguish and identify various obstacles such as cobblestones and dished kerbs. Finally, spatial autocorrelation analysis quantified how inaccessible areas cluster geographically, while calculus-based diffusion models examined how inaccessibility spreads through urban systems.
Results showed a strong positive correlation (r = 0.98) between distances travelled by wheelchair-users and inaccessibility. The supervised Python Random Forest classifier achieved an accuracy of 82% in identifying specific obstacles encountered from vibration data. Survey analysis revealed that inaccessibility has substantial negative impacts on wheelchair-users’ quality of life, particularly in social participation, finances and emotional wellbeing.
In conclusion, inaccessibility remains a significant problem, extending beyond mobility limitations to impact wheelchair-users’ quality of life. The vibration-based classifier and machine learning methods proved to be effective in assessing and analysing accessibility, providing objective, data-driven insights into the challenges wheelchair-users face. Investigations also revealed how urban design patterns and infrastructure impede accessibility. Overall, combining quantitative modelling with real-world data offers a powerful approach to identifying, understanding, and ultimately addressing the systemic nature of urban inaccessibility.
|