Can Betweenness Centrality Explain Traffic Flow?

Centrality measures describe structural properties of nodes (and edges) in a network. Betweenness centrality (Freeman 1977) is one of them, characterizing on how many shortest paths a node is. So far, network analysis concentrates on structural, i.e., topological properties of networks, and on static formulations of centrality. Although travel networks can be studied this way, they deviate from other networks in two significant ways: their embeddedness in geographic space is relevant, and their dynamic properties can not be neglected. For example, a physical urban street network constrains travel behavior in a way that people seek to satisfy their demands from physically near, not topologically near resources. Also, a physical street can have significant temporal constraints, such as night time closures, dynamic lane allocation, or current traffic volume, besides of slow rates of change in the network itself. This means, it is not appropriate to compare traffic flow on street networks with traditional betweenness centrality.