Individual human trajectories are characterized by fat-tailed distributions of jump sizes and waiting times, suggesting the relevance of continuous-time random-walk (CTRW) models for human mobility. However, human traces are barely random. Given the importance of human mobility, from epidemic modelling to traffic prediction and urban planning, we need quantitative models that can account for the statistical characteristics of individual human trajectories. Here we use empirical data on human mobility, captured by mobile-phone traces, to show that the predictions of the CTRW models are in systematic conflict with the empirical results. We introduce two principles that govern human trajectories, allowing us to build a statistically self-consistent microscopic model for individual human mobility. The model accounts for the empirically observed scaling laws, but also allows us to analytically predict most of the pertinent scaling exponents.
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We thank M. Gonzales, D. Wang, J. Bagrow and Z. Qu for discussions and comments on the manuscript. This work was supported by the James S. McDonnell Foundation 21st Century Initiative in Studying Complex Systems; NSF within the Information Technology Research (DMR-0426737), and IIS-0513650 programmes; the Defense Threat Reduction Agency Award HDTRA1-08-1-0027 and the Network Science Collaborative Technology Alliance sponsored by the US Army Research Laboratory under Agreement Number W911NF-09-2-0053.
The authors declare no competing financial interests.
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Song, C., Koren, T., Wang, P. et al. Modelling the scaling properties of human mobility. Nature Phys 6, 818–823 (2010). https://doi.org/10.1038/nphys1760
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