Abstract
Human mobility is a multidisciplinary field of physics and computer science and has drawn a lot of attentions in recent years. Some representative models and prediction approaches have been proposed for modeling and predicting human mobility. However, multi-source heterogeneous data from handheld terminals, GPS, and social media, provides a new driving force for exploring urban human mobility patterns from a quantitative and microscopic perspective. The studies of human mobility modeling and prediction play a vital role in a series of applications such as urban planning, epidemic control, location-based services, and intelligent transportation management. In this survey, we review human mobility models based on a human-centric angle in a datadriven context. Specifically, we characterize human mobility patterns from individual, collective, and hybrid levels. Meanwhile, we survey human mobility prediction methods from four aspects and then describe recent development respectively. Finally, we discuss some open issues that provide a helpful reference for researchers' future direction. This review not only lays a solid foundation for beginners who want to acquire a quick understanding of human mobility but also provides helpful information for researchers on how to develop a unified human mobility model.
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- Urban Human Mobility: Data-Driven Modeling and Prediction
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Link prediction in human mobility networks
ASONAM '13: Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and MiningThe understanding of how humans move is a longstanding challenge in the natural science. An important question is, to what degree is human behavior predictable? The ability to foresee the mobility of humans is crucial from predicting the spread of human ...
Human Mobility Modeling on Metropolitan Scale Based on Multiple Cellphone Networks: Poster Abstract
IoTDI '17: Proceedings of the Second International Conference on Internet-of-Things Design and ImplementationModeling human mobility patterns from CDR(Call Detail Record) data is an efficient way to understand the effects of human movements on transportation, society and the environment. Previous human mobility models are focused on single cellphone network ...
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