Individual Mobility Profiles: Methods and Application on Vehicle Sharing

In this paper we present a methodology for extracting mobility profiles of individuals from raw digital traces (in particular, GPS traces), and study criteria to match individuals based on profiles. We instantiate the profile matching problem to a specific application context, namely proactive car pooling services, and therefore develop a matching criterion that satisfies various basic constraints obtained from the background knowledge of the application domain. In order to evaluate the impact and robustness of the methods introduced we present an experiment which is performed on a massive dataset containing GPS traces of private cars.