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Machine Learning to Enhance Road and Traffic Safety for Senior and Disabled Citizens
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Author(s): Soorya Sathish (Heriot-Watt University, Dubai, UAE)and Cristina Turcanu (Heriot-Watt University, Dubai, UAE)
Copyright: 2026
Pages: 36
Source title:
Improving Quality of Life for People with Disabilities Through Smart Technologies
Source Author(s)/Editor(s): Ikram Ur Rehman (University of West London, UK), Moustafa Nasralla (Prince Sultan University, Saudi Arabia), Drishty Sobnath (Heriot Watt University, UAE), Muazzam Ali Khan Khattak (Quaid-i-Azam University, Pakistan)and Sundus Ali (NED University of Engineering and Technology, Pakistan)
DOI: 10.4018/979-8-3373-2033-5.ch005
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Abstract
Machine learning (ML) models have the potential to improve road safety by predicting and preventing accidents. Building on this idea, this study examines how ML can enhance safe transportation for the elderly and people with disabilities, who often face significant mobility challenges. Traditional transport safety strategies tend to react to accidents rather than proactively address risks, further disadvantaging these vulnerable road users. This chapter explores how predictions based on specific ML models can analyse accident patterns and inform specific safety measures. By integrating AI-based accident prediction with intelligent traffic systems, adaptive signals, and accessibility-focused solutions, this research explores solutions and recommendations to guide urban planning and create safer and more inclusive transport networks tailored to those who need them most.
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