Complex Network Analysis of U.S. Bike Sharing Programs

The understanding of network patterns in terms of their scale-invariant properties and common ontogenetic drivers is critically important for designing optimal transportation networks. Here, network features of bike sharing networks in selected U.S. cities are considered. Namely, the degree distribution, average path length and clustering coefficient are considered over time. We compare networks between cities as well as over time allowing us to build a generalized picture of the structure and evolution of bike sharing networks. We propose a model for an efficient network-based sharing economy of mobility.