期刊
COMPUTERS ENVIRONMENT AND URBAN SYSTEMS
卷 64, 期 -, 页码 332-343出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.compenvurbsys.2017.04.004
关键词
Human mobility; Scaling laws; Urban dynamic; Transport prediction; Built environment
类别
资金
- Natural Science Foundation of China [41522104, 41271166]
- Fundamental Research Funds for the Central Universities of China [15lgjc24]
- China Scholarship Council [201306380083]
The relationship of the built environment to human travel is one of the mainstream themes in urban studies. It provides a foundation for transport prediction. The existing literature is limited in accuracy when predicting spatial temporal travels from built environment. Understanding the scaling laws of spatial visitation frequency sheds new light on the issue. The scaling laws connect travel and the built environment by ordered-rankings, which make it possible to predict the number of arrivals from environmental variables. This research analyses the scaling laws of dynamic spatial visitation frequency using taxis' global positioning system (GPS) records, and proposes a model to predict spatial temporal arrivals from points of interest (POIs). The results show that: (i) the scaling law of spatial visitation frequency is exponential; (ii) the exponential scaling law is explained by the linear preferential attachment effect and a logarithmic travel growth process; (iii) the exponential scaling law is not sensitive to time; (iv) the proposed model predicts spatial temporal arrivals with high accuracy (R-2>0.6). (C) 2017 Elsevier Ltd. All rights reserved.
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