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Abstract In the past decade, various aspects of human mobility, from individual to population levels in both spatial and time scales, have been studied. However, existing human mobility models still fail to describe activities in all spatial ranges, while in particular, local activities like self-loop fluxes are generally ignored. Moreover, the regional attractiveness, a basic but useful concept in mobility model design, remains difficult to be quantified due to its intricacies. To resolve these two fundamental issues, we introduce a trip competition mechanism to empower a mobility model to estimate population fluxes in all spatial ranges. The model includes attraction scores of regions in concern, obtained via optimizing the working population distributions. Its capability of predicting a variety of mobility patterns is verified by empirical data from three different countries, and its accuracy outperforms those of existing models. The quantified attractiveness is also found to be highly correlated with common socioeconomic indicators, and is able to act as a distinct metric to characterize a region.
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