Mining GPS data for mobility patterns: A survey

With the help of various positioning tools, individuals' mobility behaviors are being continuously captured from mobile phones, wireless networking devices and GPS appliances. These mobility data serve as an important foundation for understanding individuals' mobility behaviors. For instance, recent studies show that, despite the dissimilarity in the mobility areas covered by individuals, there is high regularity in the human mobility behaviors, suggesting that most individuals follow a simple and reproducible pattern. This survey paper reviews relevant results on uncovering mobility patterns from GPS datasets. Specially, it covers the results about inferring locations of significance for prediction of future moves, detecting modes of transport, mining trajectory patterns and recognizing location-based activities. The survey provides a general perspective for studies on the issues of individuals' mobility by reviewing the methods and algorithms in detail and comparing the existing results on the same issues. Several new and emergent issues concerning individuals' mobility are proposed for further research.