AI Article Synopsis
- Understanding human mobility patterns is crucial for fields like public health and urban planning, but current models often overlook the connection between trip purpose and effort.
- Researchers propose a new model that links the importance of a trip to the distance traveled, using shopping trips and item prices as a measurable proxy for this importance.
- The developed model successfully mirrors observed travel distance distributions and clarifies the relationship between how far people travel and the value of the items they purchase.
Article 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.
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Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7653376 | PMC |
| http://dx.doi.org/10.1098/rsif.2020.0673 | DOI Listing |
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