Ride Sharing: A Network Perspective

Ride sharing’s potential to improve traffic congestion as well as assist in reducing CO2 emission and fuel consumption was recently demonstrated by works such as [1]. Furthermore, it was shown that ride sharing can be implemented within a sound economic regime, providing values for all participants (e.g., Uber). Better understanding the utilization of ride sharing can help policy makers and urban planners in modifying existing urban transportation systems to increase their “ride sharing friendliness” as well as in designing new ride sharing oriented ones. In this paper, we study systematically the relationship between properties of the dynamic transportation network (implied by the aggregated rides) and the potential benefit of ride sharing. By analyzing a dataset of over 14 Million taxi trips taken in New York City during January 2013, we predict the potential benefit of ride sharing using topological properties of the rides network only. Such prediction can ease the analysis of urban areas, with respect to the potential efficiency of ride sharing for their inhabitants, without the need to carry out expensive and time consuming surveys, data collection and analysis operations.