Evidence map›Paper›PMID 25860140›Full record

ArticlePloS one2015

Cascading walks model for human mobility patterns.

Xiao-Pu Han, Xiang-Wen Wang, Xiao-Yong Yan, Bing-Hong Wang

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Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Xiao-Pu HanInstitute of Information Economy, Hangzhou Normal University, Hangzhou 311121, China; Alibaba Research Center for Complexity Sciences, Hangzhou Normal University, Hangzhou 311121, China.
Xiang-Wen WangDepartment 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.
Xiao-Yong YanAlibaba 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.
Bing-Hong WangDepartment of Modern Physics, University of Science and Technology of China, Hefei 230026, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUncovering 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

findingsIn 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.

Indexed as

Models, BiologicalMovementWalkingAlgorithmsComputer SimulationHuman ActivitiesHumansModels, StatisticalTravel

Identifiers

PMID25860140
PMCPMC4393089

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.