Towards an Extensive Map-oriented Trace Basis for Human Mobility Modeling


Human mobility analysis and modeling is a very interdisciplinary field of research. Mobility models play an important role particularly in assessing the simulative performance of mobile and opportunistic networks. The mobility traces, which most of these models are based on, however, mostly suffer from several shortcomings. In this paper, we use the extensive Lausanne Data Collection Campaign (LDCC) mobility trace as basis for further map-oriented processing. Map-matching and sensible addition of optimal routes between points mitigate problems like GPS spatial noise, anonymization, and data gaps. Moreover, stay point extraction is performed as a preparation for the analysis of elemental statistical mobility characteristics. An exemplary impact evaluation of contact statistics shows that the resulting map-oriented trace basis is indeed suited for large-scale mobility analysis and simulation.

In Proc. of the 35th Int. Performance Computing and Communications Conference (IPCCC ‘16), IEEE.