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As life expectancy increases around the world, it also grows the number of people with reduced mobility (older adults and disabled individuals), leading to a need to rethink transport planning in urban areas to include these individuals. To accomplish this, city planners must understand the key features that most influence the travel behaviour among people with reduced mobility to provide independent and healthy lifestyles and promote the use of healthy active transport modes among them.

In this study, a set of machine learning models was trained to predict the travel behaviour of people with reduced mobility in Medellín, and the most appropriate model was used to examine the underlying key features that most influence the travel behaviour among these individuals. Additionally, a specific systemic analysis was carried out for people with reduced mobility who choose active transport modes to …