Investigating Urban Mobility Behavior and User Profiles Through Cluster Analysis

As cities persist in their growth and infrastructure evolves, the transportation demands become increasingly varied and are shaped by a multifaceted array of elements that include socio-demographic characteristics, features of the built environment, and cultural conventions, among others. Consequently, acquiring a thorough comprehension of the mobility patterns associated with various demographic profiles is essential for policymakers and urban planners in order to implement more customized transportation initiatives and strategies. This study aims to investigate the travel behaviors within the Tunisian Sahel region and seeks to delineate distinct mobility profiles through the utilization of a cluster analysis approach. Using a dataset comprising 2,021 observations of individuals aged fifteen and older, collected during a travel survey in 2019, a k-means cluster analysis was performed employing the elbow method and inertia variation to determine the optimal number of clusters. Our analysis encompasses a combination of categorical and numerical variables that represent the socio-demographic characteristics of our sample, their mobility attributes, and the developmental status of their residential delegations. The results reveal four distinct clusters, indicating that travel behaviors in the Sahel region are not monolithic but rather influenced by a blend of individual, contextual, and mobility-related factors. They also highlight varying lifestyles characterized by dynamic, regular, and even sedentary mobility. This research adds to the existing literature on travel behaviors in developing nations and offers significant insights for fostering more targeted transportation initiatives that are in harmony with the needs and challenges encountered by the Sahelian populace.