Abstract
Smart phones and social networking tools allow to collect large-scale data about mobility habits of people. These data can support advanced forms of sharing, coordination and cooperation possibly able to reduce the overall demand for mobility. Our goal is to develop a recommender system–to be integrated in smart phones, tablets, and in-vehicle platforms–capable of identifying opportunities for sharing cars and rides. We present a methodology, based on the extraction of suitable information from mobility traces, to identify rides along the same trajectories that are amenable for ride sharing. We provide experimental results showing the impact of this technology and we illustrate a Web-based platform implementing the key concepts presented.
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