Background Uncovering the mechanism behind the scaling laws and series of anomalies in human trajectories is of fundamental significance in understanding many spatio-temporal phenomena. Recently, several models, e.g. the explorations-returns model (Song et al., 2010) and the radiation model for intercity travels (Simini et al., 2012), have been proposed to study the origin of these anomalies and the prediction of human movements. However, an agent-based model that could reproduce most of empirical observations without priori is still lacking. Methodology/Principal Findings In this paper, considering the empirical findings on the correlations of move-lengths and staying time in human trips, we propose a simple model which is mainly based on the cascading processes to capture the human mobility patterns. In this model, each long-range movement activates series of shorter movements that are organized by the law of localized explorations and preferential returns in prescribed region. Conclusions/Significance Based on the numerical simulations and analytical studies, we show more than five statistical characters that are well consistent with the empirical observations, including several types of scaling anomalies and the ultraslow diffusion properties, implying the cascading processes associated with the localized exploration and preferential returns are indeed a key in the understanding of human mobility activities. Moreover, the model shows both of the diverse individual mobility and aggregated scaling displacements, bridging the micro and macro patterns in human mobility. In summary, our model successfully explains most of empirical findings and provides deeper understandings on the emergence of human mobility patterns.
Institute of Information Economy, Hangzhou Normal University, Hangzhou 311121, China;Alibaba Research Center for Complexity Sciences, Hangzhou Normal University, Hangzhou 311121, China;Department of Physics, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061-0435, USA;Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China;Alibaba Research Center for Complexity Sciences, Hangzhou Normal University, Hangzhou 311121, China;School of Systems Science, Beijing Normal University, Beijing 100875, China;Department of Transportation Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, P. R. China;Web Sciences Center, University of Electronic Science and Technology of China, Chengdu 610051, China;Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China
Recommended Citation:
Xiao-Pu Han,Xiang-Wen Wang,Xiao-Yong Yan,et al. Cascading Walks Model for Human Mobility Patterns[J]. PLOS ONE,2015-01-01,10(4)