Cascading Walks Model for Human Mobility Patterns

TL;DR

This paper introduces a cascading walks model that explains human mobility patterns, capturing key statistical features and anomalies observed in empirical data through a simple dynamical process.

Contribution

The paper presents a novel cascading process-based model that reproduces multiple statistical properties of human mobility, linking micro and macro movement patterns.

Findings

Model reproduces empirical scaling laws

Captures ultraslow diffusion in human mobility

Bridges individual and aggregated mobility patterns

Abstract

Uncovering the mechanism behind the scaling law in human trajectories is of fundamental significance in understanding many spatio-temporal phenomena. In combination of the exploration and the preferential returns, we propose a simple dynamical model mainly based on the cascading processes to capture the human mobility patterns. By the numerical simulations and analytical studies, we show more than five statistical characters that are well consistent with the empirical observations, including several type of scaling anomalies, and the ultraslow diffusion property, implying the cascading processes associated with the other two mechanisms are indeed a key in the understanding of human mobility activities. Moreover, both of the diverse individual mobility and aggregated scaling move-lengths, bridging the micro and macro patterns in human mobility. Our model provides deeper understandings on the emergence of human mobility patterns.