Abstract

Obtaining insights into human mobility patterns and being able to reproduce them accurately is of the utmost importance in a wide range of applications from public health, to transport and urban planning. Still the relationship between the effort individuals will invest in a trip and the importance of its purpose is not taken into account in individual mobility models that can be found in the recent literature. Here, we address this issue by introducing a model hypothesizing a relation between the importance of a trip and the distance travelled. In most practical cases, quantifying such importance is undoable. We overcome this difficulty by focusing on shopping trips (for which we have empirical data) and by taking the price of items as a proxy. Our model is able to reproduce the long-tailed distribution in travel distances empirically observed and to explain the scaling relationship between distance travelled and item value found in the data.

Highlights

  • IntroductionIndividual human mobility is a complex phenomenon, involving various mechanisms interacting at different spatial and temporal scales

  • Individual human mobility is a complex phenomenon, involving various mechanisms interacting at different spatial and temporal scales. These dynamics are the product of individual behaviours, governed by decisions that may depend on multiple contextual factors such as economic resources, geography, culture, norms, habits or life experiences

  • We introduced a model of individual human mobility patterns able to reproduce and explain the relationship between the travel cost associated with a trip and the importance given to its destination observed in credit card data recorded in the provinces of Barcelona and Madrid in 2011

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Summary

Introduction

Individual human mobility is a complex phenomenon, involving various mechanisms interacting at different spatial and temporal scales. These dynamics are the product of individual behaviours, governed by decisions that may depend on multiple contextual factors such as economic resources, geography, culture, norms, habits or life experiences. Beneath this apparent complexity lies remarkable temporal and spatial regularities in the way people travel and interact with their environment [1]. Individual human mobility patterns are strongly influenced by geographical constraints [12] and by individuals’ socio-economic status [13,14,15] and social network [16,17,18,19]

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