No abstract

The automatic generalization of urban street networks is a constant and important aspect of geographical information science. Previous studies show that the dual graph for street–street relationships more accurately reflects the overall morphological properties and importance of streets than do other methods. In this study, we construct a dual graph to represent street–street relationship and propose an approach to generalize street networks based on gravitational field theory. We retain the global structural properties and topological connectivity of an original street network and borrow from gravitational field theory to define the gravitational force between nodes. The concept of multi-order neighbors is introduced and the gravitational force is taken as the measure of the importance contribution between nodes. The importance of a node is defined as the result of the interaction between a given node and its multi-order neighbors. Degree distribution is used to evaluate the level of maintaining the global structure and topological characteristics of a street network and to illustrate the efficiency of the suggested method. Experimental results indicate that the proposed approach can be used in generalizing street networks and retaining their density characteristics, connectivity and global structure.

Using the theories of complex networks and gravitational field, we study the dynamic routing process under the framework of node gravitational field, define the equation of gravitation of travel path to data package and introduce two parameters α and γ for adjusting the dependences of transmission data on the unblocked degree of node, the transmission capacity of node and the path length. Based on the path's attraction, a gravitational field routing strategy under node connection ability constraint is proposed with considering the affect of node aggregation ability to transport process, and a parameter is used to adjust the control strength of routing process to node aggregation ability. In order to clarify the efficiency of suggested method, we introduce an order parameter η to measure the throughput of the network by the critical value of phase transition from free state to congestion state, and analyze the distribution of betweenness centrality and traffic jam. Simulation results show that, compared with the traditional shortest path routing strategy, our method greatly improve the throughput of a network, balance the network traffic load and most of the network nodes are used efficiently. Moreover, the network throughput is maximized under μ = -1, and the transmission performance of the algorithm is independent of the values of α and γ, which indicate the routing strategy is stable and reliable.