2023 Journal article Open Access

Mobility constraints in segregation models
Gambetta D., Mauro G., Pappalardo L.
Since the development of the original Schelling model of urban segregation, several enhancements have been proposed, but none have considered the impact of mobility constraints on model dynamics. Recent studies have shown that human mobility follows specific patterns, such as a preference for short distances and dense locations. This paper proposes a segregation model incorporating mobility constraints to make agents select their location based on distance and location relevance. Our findings indicate that the mobility-constrained model produces lower segregation levels but takes longer to converge than the original Schelling model. We identified a few persistently unhappy agents from the minority group who cause this prolonged convergence time and lower segregation level as they move around the grid centre. Our study presents a more realistic representation of how agents move in urban areas and provides a novel and insightful approach to analyzing the impact of mobility constraints on segregation models. We highlight the significance of incorporating mobility constraints when policymakers design interventions to address urban segregation.Source: Scientific reports (Nature Publishing Group) 13 (2023). doi:10.1038/s41598-023-38519-6
DOI: 10.1038/s41598-023-38519-6
DOI: 10.48550/arxiv.2305.10170
Project(s): HumanE-AI-Net , SoBigData-PlusPlus
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