Traffic network: A cascade fault-oriented flow allocation method

In the field of complex networks, cascade failure has been widely studied due to its ubiquity and profound impact. The urban rail transit network is designed such that failures at one station or part would propagate throughout the network, affecting train operations at nearby stations or sections as well as disrupting passenger flow throughout the network. A sensible passenger flow assignment plan can enhance a network operation's emergency reaction capability and significantly lessen the impact of a network cascade failure in the event of a failure. However, current passenger assignment models aimed at reducing the phenomenon of cascading failures are not comprehensive and do not fully consider the impact of the overall network centrality and path flow capacity on network cascading failures. This study defines the term "path flow capacity" and proposes a traffic network pass-passenger assignment model (New_CC) with Tsallis entropy, based on the concept of system load balancing. The model gives weight to the connecting edges of the traffic network, integrates the betweenness centrality with the theory of structural holes, and enhances the initial passenger flow assignment technique. The distribution results can improve the path flow capacity of the network to a certain extent, and the overall distribution of liquidity is relatively average. Then we define a new cascading failure model, this model is used to determine the path flow capacity at various nodes and investigate the traffic network's resistance to cascading failure under various load distribution methods, using the path flow capacity at nodes as the initial load. The findings indicate that compared to the traditional model, the New_CC model makes more sense. There is almost no overloading between neighboring nodes, and some of the central node traffic is dispersed to the outer nodes of the network. There is no phenomenon that the loads of consecutive nodes on a road are too large at the same time, which causes the transportation network to be blocked at multiple nodes at the same time. In addition, the improved passenger flow assignment model can enhance the path flow capacity of the network to a certain extent, and all the effective paths take up as much as possible the passenger flow between the OD pairs corresponding to the paths in the network.The traffic network's cascade fault model is more robust and can withstand intentional attacks at a lower cost when used in a cascade fault simulation where the path flow capacity serves as the initial load. The improvement of robustness will be further strengthened with the increase of the propagation rate threshold and the decrease of the average degree. From a transportation network perspective, protecting nodes with greater path flow capacity is also a better way to prevent cascading failures, reduce maintenance costs, and give decision makers more options.