The movement of people is by-products of spatial and temporal correlations. People go to a place at a certain time with a purpose and they meet because they are in the same place at the same time. Extracting and representing the statistical features of spatio-temporal correlations inherent in human mobility is the goal of this paper. Most of the existing human mobility models focus on representing only the spatial features of human mobility (e.g., where and how they visit) and devote less attention to representing the temporal features (when they visit). This paper shows through GPS experiments simultaneously tracking the movement of about 200 students in two university campuses that many existing models cannot capture the temporal features and their correlations with the spatial features, and proposes a new mobility model called spatio-temporal mobility model (STEP) that aims to remedy this deficiency. The paper reports a work-in-progress for evaluating the performance of STEP and the other mobility models in representing inherent spatio-temporal features of human mobility such as the inter-contact times and diffusion speeds which are captured in the GPS experiments.
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