Navigation in large subway networks: An informational approach

The structural properties of the subway network are crucial in effective transportation in cities. This paper presents an information perspective of navigation in four different subway networks: New York City, Paris, Barcelona and Moscow. We addressed our study to investigate what is that makes it complicated to navigate in these kinds of networks and we carried out a comparison between them and their intrinsic constraints. Our methodological approach is based on a set of cost/efficiency indicators which are defined in the complex networks literature. We find that the overall complexity in finding stations measured by the average search information SS linearly increases as a function of the network size NN. The direct implication of this finding is that from these basic levels of required information, the average value H(k)H(k) can be represented as a function of the node degree kk. Finally, through analyzing subway networks in space PP, we reveal the existing service modularity among subway routes using a rescaled expression of SS.