Construction and Empirical Study of Dynamic Optimal Evolution Model for
Urban Rail Transit Hyper Networks Based on Allometric Growth
Relationship
Abstract
The development of an urban rail transit network conforms to the
characteristics of logistic dynamic equations. Studying the evolution
laws of urban rail transit networks and accurately reproducing the
entire process of evolution can provide targeted guidance for rail
transit network planning and phased construction. This article studies
the structure and evolution laws of urban rail transit networks and
finds that the evolution and development of urban rail transit networks
are based on the evolution of lines, which aligns with the evolution
characteristics of hyperedge-driven hyper networks. At the same time,
the links between lines have the evolutionary characteristics of
combining randomness and prioritization. On this basis, a hyper network
model of urban rail transit was established with stations as nodes and
lines as hyperedges. Based on the allometry growth relationship between
transfer nodes and common nodes in urban rail transit networks, this
paper proposes a hyper network evolution model of rail transit that can
simulate the evolution process and generate a network similar to the
existing network. Finally, a comparative analysis was conducted between
the network generated by the model and four different levels of urban
rail transit networks, including Beijing, Shanghai, Guangzhou, and
Tianjin. The evolutionary network generated by the new model is highly
consistent with the leading critical indicators of the existing network
and has a high degree of similarity. A comparative verification was
conducted with the evolution data of the Beijing Rail Transit Network
(1984-2020) over a total of 45 years. Both network evolution processes
were found to conform to the dynamic logistic equation, proving that the
evolution model can reproduce the evolution process of the urban rail
transit network, which has practical guiding significance for the study
of rail transit network evolution.