A gradient induced flow (GIF) network or simply gradient network is defined as the collection of all directed links within a traffic network. GIF entities are of great practical importance in the fields of transport and urban planning as they offer far more efficient and robust transportation systems. In this paper, we study the topological characteristics and functional properties of gradient networks. We define centrality measure in order to characterize GIF entities. We also develop a superstatistical model of urban traffic. We discuss the dynamical route toward global synchronization of our transport systems. For clarity, we distinguish between the phase signal of traffic light (signal phase) and structural phase-state transitions (topological phase state). We refer to synchronizability as dynamical relationship between the nodes and not to some external dynamics. (a) For the covering entry of this conference, please see ITRD abstract no. E214666.
Samenvatting