Route design is a critical consideration in the compilation of rail operating schedules.This study analyzed the arrangement structure and attributes of signaling system equipment,and expressed the findings in the form of static configuration data.A graph model for rail route selection was established using graph machine learning methods.Applying the PageRank algorithm to the graph model,the importance of nodes was analyzed,yielding a ranked list of node significance.Based on node importance and route structure,a route classification was achieved,leading to the formulation of a route selection algorithm.This offers a reference solution for route selection.Then one line was taken as an example to validate the proposed algorithm,demonstrating its effectiveness in enhancing route selection efficiency.
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